WO2018001444A1 - System and method for creation and delivery of personalized traffic and route information - Google Patents

System and method for creation and delivery of personalized traffic and route information Download PDF

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Publication number
WO2018001444A1
WO2018001444A1 PCT/EP2016/025068 EP2016025068W WO2018001444A1 WO 2018001444 A1 WO2018001444 A1 WO 2018001444A1 EP 2016025068 W EP2016025068 W EP 2016025068W WO 2018001444 A1 WO2018001444 A1 WO 2018001444A1
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WO
WIPO (PCT)
Prior art keywords
traffic
vehicle
information
parameters
road network
Prior art date
Application number
PCT/EP2016/025068
Other languages
French (fr)
Other versions
WO2018001444A9 (en
Inventor
Predrag BALENTOVIC
Original Assignee
Atto D.O.O.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Atto D.O.O. filed Critical Atto D.O.O.
Priority to PCT/EP2016/025068 priority Critical patent/WO2018001444A1/en
Publication of WO2018001444A1 publication Critical patent/WO2018001444A1/en
Publication of WO2018001444A9 publication Critical patent/WO2018001444A9/en

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Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34Route searching; Route guidance
    • G01C21/36Input/output arrangements for on-board computers
    • G01C21/3626Details of the output of route guidance instructions
    • G01C21/3641Personalized guidance, e.g. limited guidance on previously travelled routes
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/0104Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/0112Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/0104Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/0116Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/0104Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/012Measuring and analyzing of parameters relative to traffic conditions based on the source of data from other sources than vehicle or roadside beacons, e.g. mobile networks
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/0104Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125Traffic data processing
    • G08G1/0129Traffic data processing for creating historical data or processing based on historical data
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/0104Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125Traffic data processing
    • G08G1/0133Traffic data processing for classifying traffic situation
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/0104Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0137Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • G08G1/0141Measuring and analyzing of parameters relative to traffic conditions for specific applications for traffic information dissemination
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/015Detecting movement of traffic to be counted or controlled with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/052Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/065Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • G08G1/0962Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0967Systems involving transmission of highway information, e.g. weather, speed limits
    • G08G1/096708Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
    • G08G1/096716Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control where the received information does not generate an automatic action on the vehicle control
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • G08G1/0962Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0967Systems involving transmission of highway information, e.g. weather, speed limits
    • G08G1/096733Systems involving transmission of highway information, e.g. weather, speed limits where a selection of the information might take place
    • G08G1/096741Systems involving transmission of highway information, e.g. weather, speed limits where a selection of the information might take place where the source of the transmitted information selects which information to transmit to each vehicle
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • G08G1/0962Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0967Systems involving transmission of highway information, e.g. weather, speed limits
    • G08G1/096766Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission
    • G08G1/096775Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission where the origin of the information is a central station
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • G08G1/0962Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968Systems involving transmission of navigation instructions to the vehicle
    • G08G1/096805Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
    • G08G1/096811Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed offboard
    • G08G1/096816Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed offboard where the complete route is transmitted to the vehicle at once
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • G08G1/0962Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968Systems involving transmission of navigation instructions to the vehicle
    • G08G1/096833Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route
    • G08G1/096838Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route where the user preferences are taken into account or the user selects one route out of a plurality
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • G08G1/0962Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968Systems involving transmission of navigation instructions to the vehicle
    • G08G1/096833Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route
    • G08G1/096844Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route where the complete route is dynamically recomputed based on new data
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34Route searching; Route guidance
    • G01C21/36Input/output arrangements for on-board computers
    • G01C21/3691Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34Route searching; Route guidance
    • G01C21/36Input/output arrangements for on-board computers
    • G01C21/3697Output of additional, non-guidance related information, e.g. low fuel level

Definitions

  • This invention is generally related to the field of navigation and route guidance. Particularly present invention is related to the field of traffic related information collecting, processing and delivery to traffic participants, where said information is personalized with respect to each vehicle.
  • Traffic information displayed in such systems can be collected in multitude of ways, including manual entry by the operators of such services, receiving data directly from various roadside sensors or indirectly from other traffic services, traffic monitoring centers, and government agencies.
  • Some systems enable the services users to provide traffic data to the system. This can be done directly by the user by entering the information on the computer or mobile device, or automatically by collecting and transmitting the information from the user's mobile device running an application provided by the service provider.
  • a number of systems and devices are presently capable of calculating the route for navigating the vehicle to selected destination.
  • Such systems include web map based routing services, "on board” vehicle navigation devices and mobile device applications capable of route calculation and guidance.
  • Many such systems are equipped with GPS location sensor and are capable of displaying the present vehicle location along with calculated route on the graphical map, providing textual, graphical or voice based route guidance messages while driving, such as "turn right”.
  • the present invention relates to a system and a method for calculation and delivery of personalized traffic and route information, wherein said information is dynamically configured depending on a traffic related data in real-time and current road network traffic optimization parameters.
  • present invention provides the system and the method of personalization of a traffic related route data and personalization of delivered information for each vehicle in real-time.
  • the method includes collecting traffic related data from available traffic related information sources, analyzing and processing the collected data and delivering a subset of collected and processed information to user devices in a personalized manner.
  • personalized manner refers to the ability of the system to select, modify and deliver the information to user devices in a way where each user device may receive a different subset of information, modified or different information or the same information in different time, as decided by the system and required to realize the present invention and methods described herein.
  • User device may be any of: mobile phone or smartphone, tablet, personal data assistant (PDA), personal computer (PC), mobile navigation device, in- vehicle navigation device, on board vehicle navigation or display device, or any other device comprising of a communication interface capable of exchanging traffic related data and a user interface capable of presenting said data.
  • User devices may be equipped with the location sensor enabling the device to communicate its current location to the system.
  • the term “device” is used as the synonym to "user device”
  • vehicle is used as a synonym for the user device that is located in the vehicle
  • driver is used as a synonym for the driver of said vehicle who is able to see, hear and interact with the user device within the vehicle.
  • the user device may be an integrated part of the vehicle and is able to access vehicle sensors such as vehicle speedometer, rain detection sensors, traction control sensors (ABS) and other available sensors.
  • vehicle sensors such as vehicle speedometer, rain detection sensors, traction control sensors (ABS) and other available sensors.
  • collected data may include present (real-time), inferred, scheduled, historical and predicted traffic related data and events such as traffic density and speed, travel times, traffic jams, slowdowns, collisions, incidents and works; information, warnings and limitations from static and dynamic road signs, state of traffic lights, camera video streams, incidents detected based on analysis of camera video streams, weather information, manually created events by the system administrators or vehicle drivers and any other traffic related or traffic affecting information.
  • collected information may include start and end time of said events.
  • sources of said information may include user devices themselves, various roadside sensors, road equipment, traffic monitoring and control centers, government agencies, traffic prediction systems, weather forecasting systems, historical information databases, traffic models and other traffic related or traffic affecting information providing services.
  • the system has a direct connection with the traffic operation control and monitoring center and is able to retrieve real-time data from said center. Said data comprises only a part of collected traffic related information.
  • system operation and system behavior defining parameters can be operated from the traffic operation control and monitoring center through the said connection.
  • Collected information may be directly sent to user devices, optionally being analyzed and processed before sending (e.g. converted or combined with other information) or stored as historical information used for future traffic analysis.
  • User devices may be able to present received information to drivers in any format, including textual, picture, map and audio formats.
  • messages entered directly by the operators of traffic operation control and monitoring center may be delivered and displayed to drivers.
  • meteorological data from weather stations may be retrieved and generate a warning displayed to the driver in the event of decreased travel safety, including ice formation, wet road, reduced visibility and other road safety affecting meteorological situations.
  • the system may retrieve the status of changeable traffic signs and display an image of their displayed content on the device.
  • a sign content may also be converted to textual or audio message based on its meaning and sent to device.
  • the system may detect the allowed speed limit for the road section based on the contents of the changeable traffic signs, assuming they are displaying the message denoting a speed limit or other content that implies a speed limit, and display said speed limit on the device.
  • the system may analyze and process all of the said collected information and display to drivers a calculated safe driving speed.
  • Maximum legal speed for the road segment on which the vehicle is travelling on can be taken in account so the suggested speed never exceeds the legal speed.
  • the system may display to drivers the duration of the current phase of the upstream (in direction of traffic flow) traffic lights to approaching drivers.
  • collected information may be forwarded to other systems, including traffic monitoring and control centers, government agencies, historical information databases, and other traffic related data-consuming services.
  • the present invention relates to a method comprising delivery of a personalized traffic information to user devices in a way in which each user device receives in real-time only a calculated subset of the traffic related information.
  • the relevant set of traffic related information may be determined by the combination of any number of user device parameters: device current location, heading, speed, acceleration, sensor readings, stored historical movements, type and characteristics of the vehicle currently containing the device, manually entered device settings and other device, vehicle or driver parameters associated with the device.
  • information from static and dynamic road signs may be delivered to vehicles in a personalized manner, depending on said user device parameters.
  • variable road sign containing the picture prohibiting truck traffic may be delivered and displayed only to user devices currently contained within truck vehicles.
  • the method may include delivering and displaying personalized messages to drivers by delivering the same traffic related information, but modifying the delivery or display times.
  • the method may include sending an early warning to a subset of user devices about an upstream traffic conditions allowing them to change their route in time, and a delayed warning to other user devices, increasing their safety, but decreasing their chances from changing direction.
  • the method may include delivering and displaying different personalized subsets of traffic related information to different vehicles, even when the vehicles have the same or nearly same set and values of the device parameters.
  • the method may include delivering and displaying different personalized subsets of traffic related information to different vehicles, even when the vehicles have approximately the same location.
  • the method may include sending a warning to a subset of user devices about an upstream traffic flow disturbance with an alternative route suggestion, but only a warning without an alternative route suggestion to other user devices.
  • the method includes optimizing network traffic, with the goal of achieving network traffic as close as possible to the desired road network traffic parameters, where road network traffic parameters comprise of parameters relating to traffic flow, traffic distribution within the road network, traffic speed, travel times, levels of pollution and travel safety in general, or any combination or thereof, by sending personalized messages to the drivers, affecting their driving behavior relating to driving speed and route taken.
  • said personalized messages contain a suggested driving speed, the suggested driving speed taking into account current speed limits, contents of traffic signs, traffic light phase periods and traffic distribution within the road network of the selected route.
  • the personalized messages further contain weather warnings, suggested turns and routes to take, warning of upstream traffic incidents and flow reductions and any other driving related messages, warnings and suggestions.
  • the desired road network traffic parameters may be determined from the maximum traffic flow capacity of the road networks segments, or as a percentage of the said value.
  • the desired road network traffic parameters are changeable and dynamically determined by a goal oriented optimization process, where the goals include any combination of minimizing traffic slowdowns, congestions and jams, maximizing traffic speed, minimizing travel times, reducing pollution and optimization of any other combination of any other travel related parameters.
  • the desired road network traffic parameters or desired optimization goals may be set manually from the system's user/administrator interface, programmatically through an application-programming interface (API) or by schedule.
  • API application-programming interface
  • the system may include route guidance function (navigation), enabling the user device users to enter the desired location and receive guidance information in the form of suggested routes from the current location to the specified destination.
  • the system may take into account collected traffic affecting information (present, inferred, scheduled, historical and predicted traffic related data) when calculating suggested route with the goal of optimizing route quality, including travel distance and travel time.
  • the system may also monitor the said collected information for change, periodically recalculating the route, and suggesting new route or automatically replacing the previous route suggestion with a new route.
  • the method includes optimizing network traffic and achieving the desired road network traffic parameters by sending different personalized navigation routes to drivers traveling within the road network, thus controlling their future locations in time.
  • the method includes optimizing network traffic by detecting reductions in the traffic flow capacity of a part of the road network (e.g. caused by the lane closure) and sending an alternative personalized route which does not include the affected road network segments with the reduced capacity, only to a subset of vehicles which would otherwise be guided to the affected segments, thus decreasing the influx of new vehicles to the affected road segment and better achieving the desired road network traffic parameters.
  • the method of optimizing network traffic by delivering personalized routes may also take into account the benefits to the driver, including travel time and travel distance. Said benefits to the driver may be considered as part of desired road network traffic parameters.
  • the method may include fair distribution of calculated personalized traffic routes so that no personalized route sent to any one vehicle is substantially worse than other possible routes, considering the distance or time traveled, by any combination of:
  • the effects of the travel of currently guided vehicles through the road network are also taken into account and form a part of the collected traffic affecting information. This includes both current and predicted locations of the vehicles and their influence on the road network traffic parameters along their routes.
  • the system may take into account the current lane the driver is driving on and modify the guidance directions to avoid negatively affecting driving safety.
  • the system may avoid delivering information to drivers that may cause them to cross multiple lanes within a small distance during high-density traffic.
  • the system may react to the detected reductions in the traffic flow on a road segment by informing the driver about said flow reduction or offering to the driver a personalized navigation route bypassing the affected road segments, even if the driver was not actively using the navigation function of the device at the time.
  • the system may determine, with the degree of certainty, the current route the vehicle is traveling on and the road segments it will travel on in the near future, determine that the vehicle will be affected by travel flow reductions detected or predicted on said road segments, and, if the degree of certainty is greater than a preset threshold value, inform the driver of said flow reduction or offer to the driver a personalized navigation route even if the driver was not actively using the navigation function of the device at the time.
  • the system may skip informing a subset of drivers in order to keep them on the same route if by doing this the system will better achieve the desired road network traffic parameters.
  • the current vehicle route and road segments the vehicle will travel in the near future may be determined with a degree of certainty by the combination of any of: number of possible detours from the assumed route the driver can take, percentage of drivers that generally take the possible detours relative to those that remain on the assumed route and specifically the percentage of times the driver of said vehicle had stayed on the assumed route relative to the possible detours, currently occupied lane relative to the number of lanes the vehicle should take in order to make the turn relative to the distance to the turn.
  • the system may advise the driver on speed that is required to safely pass through or stop before the traffic lights. If the red light is displayed and the driver is not slowing down within the set distance, a warning will be displayed on the device. If the green traffic light is displayed, but the driver is not able to pass safely through the intersection, because the light will change to red before the vehicle reaches the intersection, a warning will be displayed on the device. If the driver can safely pass through the intersection if he increases the vehicle speed, and the increased speed is within the legal and safe boundaries, a notice will be displayed on the device suggesting the driver to increase speed to a recommended value.
  • the system may use the route guidance information to select a single traffic light related to the driver's direction and optionally the driver's next turn based on driver's location and route. If the route guidance information is not available (e.g. the driver is not using the navigation function) the system may infer the direction and next intended turn of the driver by the lane they are driving in, the road network structure and turn restrictions and readings from the acceleration sensor in the event the location sensor is not sufficiently precise.
  • the method includes automatically detecting traffic flow reductions, congestion, traffic jam, blocked lane by monitoring the plurality of locations the vehicle has travelled in time and calculating vehicle speeds.
  • Traffic flow reduction, congestion and traffic jams are detected by a decrease of traffic flow and travel speeds on the monitored road segments compared to recent and historical typical values.
  • Blocked lane may be detected by a combination of any of: movement of vehicles to other parallel lanes and subsequent return of some vehicles to the assumed blocked lane, reduced speed of travel in the neighboring lanes, and greatly reduced speed of travel directly before the lane blockage in the same lane as the blockage.
  • the method includes detecting stopped vehicles in designated locations by monitoring the vehicle's location and speed. If the vehicle speed reaches zero and the vehicle is currently within a predestined location such as tunnel or emergency lane vehicle stop will be detected.
  • the method includes monitoring the plurality of vehicles and their movement through intersections, detecting their stops in front of intersections, measuring the duration of said stops, detecting subsequent movement through the intersection, storing and analyzing said information and calculating the sequence and duration of the phases of the traffic lights.
  • FIG. A illustrates a schematic exemplary of a system according to embodiments of the present invention
  • FIG. B illustrates flow-chart of a method of personalization of traffic related route guidance and personalization of an information for each vehicle in real-time according to embodiments of the present invention
  • FIG. C illustrates a schematic flow-chart of a method of calculation of personalized route guidance for a vehicle, according to embodiments of the present invention.
  • FIG. D illustrates a schematic illustration of an exemplary fragment of a traffic road network, used hereinafter for demonstrating the method of creation and personalization of traffic related route guidance and personalization of an information for each vehicle in real-time according to embodiments of the present invention.
  • a system 200 is comprises of a central Traffic Information and Routing server (TIRS) 350, a plurality of user devices 260 and a plurality of traffic related information sources 400 available within a road network.
  • TIRS Traffic Information and Routing server
  • the system 200 is configured to collect a traffic related data in real-time, to analyze and process the traffic related data, to receive parameters of each vehicle in real-time, and retrieve current road network traffic optimization parameters. Under control of the traffic information and route server 350, the system 200 is configured to personalize information for each vehicle depending on the current traffic related data, current parameters of each vehicle and current road network traffic optimization parameters, and to send a personalized information to each vehicle. The personalized information sent to each vehicle is dynamically changed depending on the change of traffic related data, parameters of each vehicle and road network traffic optimization parameters in real-time. Further, the system is configured to carry out the computer program running on the TIRS 350.
  • the TIRS 350 is running a computer program, comprising of multiple modules and submodules 304 to 315, with the purpose of collecting traffic related information from available traffic related information sources 400, analyzing and processing said information and delivering a relevant subset of collected and processed information, including route guidance information, to the each of user devices 250 in a personalized manner for further use by the user devices 260. Additionally, said traffic related information comprises calculated navigation routes.
  • An information collecting module 306 coordinates the process of collecting the traffic related data in real-time from the plurality of traffic related information sources 400.
  • the information collecting module 306 performs monitoring, predicting, analyzing and processing traffic relevant data, providing said data for use to other modules.
  • the information collecting module 306 is divided into multiple submodules, the submodules comprising of a traffic center data exchange module 307, a real-time information collector 308, an information predictor 309, a historical information storage 310 and an information change monitor 311.
  • the traffic center data exchange module 307 may be used to collect real-time traffic data from existing traffic operation control centers.
  • Real-time information collector 308 may be used to collect real time information from roadside sensors and equipment directly or from other external real-time traffic related information providing sources indirectly.
  • Information processing module 306 may store all of the collected and processed information to Historical information storage 310 for future use by other system modules.
  • Information predictor module 309 may use already collected information by the Information processing module 306 and its submodules, predicting future parameters and providing them for further use to other system modules through the Information processing module 306.
  • a device communication module 315 on the TIRS 350 and a communication module 203 on each of the device 250 may be used to exchange information between the TIRS 350 and devices 260 by a cellular, wireless or radio network, or any other wireless or wired type of communication. Data exchange may be achieved by any standard or custom communication protocol, such as TCP, UDP, HTTP, WebSocket, custom protocols or any other suitable protocol.
  • Devices 250 may be equipped with a variety of sensors, including a location sensor 205, enabling the device 250 to communicate periodically its current location, heading and speed to the TIRS 350. All information collected from the devices 260 may be used by the information processing module 306. In some embodiments, Information processing module 306 may determine the speed and heading of a device by analyzing the plurality of recent device 260 locations retrieved from the historical information storage 310.
  • the driver may send an event from his personal device 250 to the TIRS 350, describing the current traffic-affecting situation by using the available user input module 204 available on the device. For example, the driver may report a traffic jam at its current location.
  • Information sent to user devices 260 by the TIRS 350, through the device communication module 315, may be presented to drivers by using a Display 201, an Audio speaker 202 or any other means of communication provided by the device.
  • devices may display information and routes on a map, where said map was received from the traffic network map database 305 or stored on the device 250 itself.
  • modules and submodules may have different names, organization or responsibilities of modules and submodules than described herein and in the Fig. A, without affecting the functionality of the system.
  • some modules or submodules along with their functionality may be partially or completely implemented on the user devices themselves, including, for example, Routing module 312, Route calculator 313, Route deduction submodule 314 and Traffic network map database 305. All modules, within TIRS 350 or user device 250, may be implemented in software, hardware, and any combination of thereof.
  • FIG. D is a schematic illustration of an exemplary fragment of a traffic road network 100, used hereinafter for demonstrating the method of personalization of traffic related and route information and the method of calculation of a personalized route guidance information, according to embodiments of the present invention.
  • the present invention is in no way limited to the exemplary road fragment 100 and can be applied to any traffic road network.
  • the exemplary road fragment 100 is comprised of intersections 1 tough 6 and vehicles A through T. Each vehicle may have a location sensor and transmit its location to the Traffic information and route server (TIRS) 350.
  • TIRS Traffic information and route server
  • TIRS 350 may receive the information from vehicles A through T and store and process them along with other information collected from other traffic related information sources available within the road network. TIRS 350 may exchange data with vehicles and send personalized messages to vehicles traveling on the road network. Said messages may be presented to the vehicle's drivers through the user device, where said messages may be presented in any format, including textual, picture, map and audio formats.
  • the vehicle D has suffered a problem that has caused it to stop in the right traffic lane between the intersections 1 and 2, partially reducing available traffic flow, causing a traffic congestion and a formation of traffic queue of vehicles E through I.
  • the stopped vehicle D is used only as one example of a possible traffic disturbance.
  • the present invention is in no way limited to reacting only to stopped vehicles and may react to any traffic disturbance, including those affecting the current or future traffic flow, changes to traffic capacity, traffic speed, travel times and other changes to traffic-affecting parameters.
  • the traffic disturbance caused by the vehicle D may be detected by the TIRS 350 in various ways, including based on information by roadside equipment, combining and comparing readings from multiple roadside equipment, from information collected from external systems or traffic operation and control centers, or based on collected information or direct notification from any other traffic related information source.
  • the traffic disturbance caused by the vehicle D can be detected based on manual notifications sent by any of user devices to TIRS 350, including manual notification by the driver of vehicle D or by any of the nearby drivers of vehicles E through I.
  • the traffic disturbance caused by the vehicle D can be detected by the TIRS 350 by analyzing the movement patterns of the vehicle D and of nearby vehicles E through I having the user device, including their currently assigned routes and speeds, by detecting any combination of: slowdown or stop of vehicle D, slowdown of other said vehicles or their shift from the right lane to the left lane passing the location of the stopped vehicle.
  • the TIRS 350 may react to the traffic flow reduction caused by vehicle D by attempting to optimize traffic. In some embodiments, the TIRS 350 may determine the remaining traffic capacity of the link between intersections 1 and 2, and attempt to optimize the influx of new vehicles to achieve said set road network optimization parameters. In some embodiments, the TIRS may optimize traffic and achieve currently set road network optimization parameters by sending different personalized messages to vehicles A through C affecting their driving behavior, including driving speed and route. In the remainder of this example, it is assumed that the currently set road network optimization parameters include optimizing traffic flow and time through the whole traffic network example. Note that in other embodiments said parameter may include achieving network traffic as close as possible to the desired road network traffic values, including traffic flow, traffic distribution within the road network, traffic speed, travel times and travel safety in general, or any combination or thereof.
  • the TIRS 350 may determine the remaining traffic capacity of the link between intersections 1 and 2, and attempt to optimize the influx of new vehicles so that the travel time, travel distance or both, through the affected link remains as close to equal to those on other alternative routes, for example, route passing through the intersection 4.
  • the TIRS 350 may respond to said traffic flow reduction by sending different personalized traffic information messages to vehicles A through C, influencing their driving speed and route taken, even though they are located nearly at the same location at intersection 1.
  • TIRS 350 may alert vehicle B about the congestion ahead and offered a preferred detour through the intersection 4, therefore increasing the chance that the vehicle B will take the route through the intersection 4.
  • TIRS 350 may offer only a warning to vehicle C, without offering to the vehicle an alternative route, enabling the vehicle to take an alternative route through intersection 4 but with the lesser possibility compared to the vehicle B.
  • TIRS 350 may offer no advance warning to the vehicle A increasing the chance the vehicle will traveling straight through the intersection 1 towards the vehicle D.
  • TIRS 350 may delay warning for some of vehicles and warn them about an upstream congestion only after it is no longer possible for vehicles to alter their route, e.g. vehicle R.
  • TIRS 350 when attempting to influence driving behavior, to achieve the maximum effect TIRS 350 may attempt to further increase the probability of drivers making the desired driving decisions by analyzing the baseline probability of driver making said decision in the event when not influenced by the system, and further positively influencing the decision rather than attempting to overturn it.
  • TIRS 350 may take into account the current lane the vehicle is occupying and the turn restrictions of the intersections the vehicle is likely to pass and avoid sending personalized messages to the driver that would promote illegal or unlsafe driving decisions.
  • TIRS 350 may offer a different personalized route to each vehicle to achieve the road network optimization parameters. For example, assuming the vehicles S and T are guided to the same location at the intersection 6 along the same route passing through the intersection 2, upon detecting the reduced traffic capacity at the link between the intersections 1 and 2 TIRS 350 may reroute the driver of the vehicle T through the intersection 4, while leaving the vehicle S on the original route passing through the intersection 2.
  • the system may offer to the driver a recommended route, even if the driver was not currently using the navigation function. For example, assuming that for the exemplary road network TIRS 350 will determine with a great degree of probability that the vehicles A and Q will travel to or through the intersection 6, TIRS 350 may offer to the vehicles a temporary route guidance avoiding the link between intersections 1 and 2 with the decreased traffic capacity.
  • information from static and changeable road signs may be delivered to vehicles in a personalized manner, depending on said user device parameters.
  • TIRS 350 may forward this information in the form of a warning to an approaching truck M, but not to an approaching personal vehicle O.
  • TIRS will detect that the truck L is passing in the opposite direction and will not forward this warning to a said vehicle L.
  • TIRS 350 may detect that the truck P has joined the traffic after the location of the sign T, was not able to see the sign, and forward the warning to the vehicle.
  • FIG B is a schematic flow-chart illustrating a method of delivery of personalized traffic related route guidance and personalization of an information for each vehicle in real-time, according to preferred embodiments of the present invention.
  • the method may include, for example, collecting traffic related data as illustrated in block 500, analyzing and processing traffic related data as illustrated in block 501, determining each vehicles parameters (location, speed, heading, route, etc.) as illustrated in block 502, personalizing the collected information for each vehicle taking into account the relevance of information to said vehicle as illustrated in block 503, fetching current road network optimization parameters as illustrated in block 504, personalizing the collected information for each vehicle so the road network optimization parameters are achieved as illustrated in block 505, sending personalized information to vehicle as illustrated in block 506 and monitoring the traffic information, vehicle information and optimization parameters for changes as illustrated in block 507.
  • the illustrated process steps are repeated once the change in any relevant information or parameter is detected, periodically or nearly continuously.
  • the step 500 of Collecting a traffic related data comprises collecting the traffic related data in real-time from the plurality of traffic related data sources 400, through the Information processing module 306 and its submodules, Traffic center exchange module 307 and Real-time information collector 308, and collecting vehicle data through the Device communication module 315 communicating with the Communication module 203 on the device 250, where said data is comprised of the device 250 status, settings and sensor readings, including the readings derived from the Location sensor 205, the Acceleration sensor 206 and other available sensors.
  • the step 501 of Analyzing and processing data is realized within the Information processing module 306, using the traffic related data collected by the Collecting traffic data in step 500, by analyzing and processing data based on system configuration resulting in a further expanded set of information, where said information comprises information which can be presented to drivers in textual, audio, map and picture format, but is not yet personalized, and linking said information to segments of the traffic network 100.
  • the Analyzing and processing the traffic related data in step 501 comprises of any combination of steps including:
  • the collected traffic related data may contain recorded vehicle passing's with license plate data - by comparing the collected data with the previously collected data for separate nearby locations, retrieved from the Historical information storage 310, the system may infer the time it took the vehicles to cover the distance between said locations and determine the vehicle speed;
  • - aggregating data including, for example aggregating the plurality of speeds of collected data of individual vehicles, nearby to each other and traveling on the same road segment in the same direction, may be converted to a single average speed of the said road segment;
  • the Information processing module 306 may evaluate said data and parameters, where by applying further transformations or logical comparisons new data for use within the system are generated.
  • Determining the current road network traffic parameters or numeric influence on value and rate of change of said parameters is comprised of any combination of: directly using the collected traffic related data, where said collected data comprises information of said road network traffic parameters, using the accuracy of measurement as the probability of each parameter, and inferring or calculating the parameters based on other available data; or inferring or calculating the parameters based on other available data.
  • Inferring or calculating the parameters based on other available data includes any combination of:
  • traffic related events e.g. traffic works, traffic accident or any other traffic affecting event
  • said influence may be set in advance depending on the type of the event or determined by consulting the Historical information storage 310, by retrieving or calculating the influence of said event in past, optionally giving greater weight to situations where other gathered data was most similar to the currently gathered data;
  • meteorological data e.g. rain, snow, fog or other visibility drop, or any other traffic affecting meteorological situation
  • influence may be set in advance depending on the type of the event or determined by consulting the Historical information storage 310, by retrieving or calculating the influence of said event in past, optionally giving greater weight to situations where other gathered data was most similar to the currently gathered data;
  • current road network traffic parameters or numeric influence on value and rate of change may be fed into the Information predictor 309, along with the information about schedules traffic related events, and, based on road network configuration from Traffic network map database 305 and Historical information from Historical information storage 310, expanded in space to other neighboring road segments and time into the future.
  • the step 502 of Determining each vehicles parameters comprises of determining each vehicles location based on information from the Location sensor 205, and determining the speed and heading of each vehicle, either by using the optional function of the Location sensor 205, where said sensor function can also report speed or heading, or by calculating speed or heading through measuring the difference between several sequential Location sensor 205 readings indicating the location and time of the vehicle, where said calculation can be done on the user device 250 itself, or on the server 350 within the Information processing module 306 using previously recorded vehicle data stored in the Historical information storage 310.
  • the step 502 further comprises storing the vehicle parameters in the Historical information storage 310 for further use.
  • the step 503 of Personalizing the gathered information for each vehicle is realized within the Information processing module 306 and comprises a series of steps, including selecting and modifying the information in a way where each user device may receive a different subset of information, modified or different information or the same information in different time, where said selection and modification of information is done through a rule based evaluation process depending on the user set preferences or parameters of user's device, values of user device sensors and the remembered behavior and previous actions of the user, including, for example, deemphasizing information to which the user has not responded in the past, including, for example information not viewed, hidden of deleted by the user.
  • Remembered previous behavior and user actions may be stored in the Historical information storage 310.
  • the step 504 of Retrieving the current road network optimization parameters is realized within the Routing module 312, and includes calculating the desired road network parameters for the segments of the road traffic network 100, where said parameters include traffic flow, traffic density, traffic speed, travel time and level of pollution.
  • the calculation of said parameters may comprise of any combination of:
  • Calculating the desired parameters through execution of a configured function based on collected and calculated information, including current and predicted values of road network parameters and the theoretical or measured limits for the parameters of the road network values. Calculating of the desired parameters includes for example, setting the desired parameters to a percentage of available traffic capacity of the road network, and/or setting the desired parameters to percentage of the peak or average value of traffic density or speed which has historically caused traffic congestion, where said value may be retrieved from the Historical information storage 310.
  • the results of the execution of a goal oriented optimization process where said goals may include even distribution of traffic through the road network (minimization of flow differences), maximization of travel speed, minimization of travel times, maximization of traffic flow, minimization of pollution (based on maximizing constraint traffic flow and minimizing vehicle stops), minimization of occurrence of traffic parameters leading to congestions and any combination of thereof.
  • Said optimization process is executed by the Routing module 312 and may be based on any appropriate optimization method which may be realized as a computer program running on the TIRS 350, including mathematical optimization algorithms, iterative methods, heuristics, goal based programming, genetic algorithms, neural network based optimization, other known optimization techniques or the combination of thereof.
  • Said methods of desired parameters calculation may apply to the whole traffic network, or to subset of the traffic network. Additionally, each subset of the traffic network may have different values of the desired parameters set independently.
  • the step 505 of Personalizing information for each vehicle to achieve the desired road network parameters is executed by the Routing module 312 based on the results of previous steps, receiving as input the processed traffic related information and desired road network parameters and calculating as output the further personalized messages through a series of steps, including selecting and modifying the information in a way where each user device may receive a different subset of information, modified or different information or the same information in different time, as to achieve the road network parameters close to those defined by the desired road network parameters.
  • the step 505 of Personalizing information for each vehicle to achieve the desired road network parameters comprises:
  • Routing module 312 Selecting a set of personalized information to send to the drivers, where the calculated effect minimizes the difference between the current and desired values of the road network parameters.
  • Said optimization process is executed by the Routing module 312 and may be based on any appropriate optimization method which may be realized as a computer program running on the TIRS 350, including mathematical optimization algorithms, iterative methods, heuristics, goal based programming, genetic algorithms, neural network based optimization, other known optimization techniques or the combination of thereof.
  • the personalized traffic related information from step 503 may directly advance to step 506 and sent to user devices.
  • FIG. C is a schematic flow-chart illustrating a method of calculation of personalized route guidance information for a vehicle, according to some embodiments of the present invention. As shown, the method may include, for example,
  • a routing request from vehicle including desired destination, as illustrated in block 600, fetching/determining vehicle's current location as illustrated in block 601, collecting/determining traffic related data in real time as illustrated in block 602, analyzing and processing traffic related data as illustrated in block 603, retrieving current road network optimization parameters or goals as illustrated in block 604, calculating a set of routes, taking into account real-time and predicted traffic information, as illustrated in block 605, personalizing a route for vehicle, by evaluating the calculated set of routes, selecting the best route taking into account the impact to desired road network traffic parameters or optimization goals, travel parameters of nearby vehicles, routes of other vehicles and fairness as illustrated in block 606, sending personalized route to vehicle as illustrated in block 607, and monitoring traffic information, vehicle information and optimization parameters for changes as illustrated in block 608.
  • the method of calculation of personalized route guidance information for the vehicle selects a new personalized route from the set of calculated allowed routes depending on the change of the real-time traffic data, the vehicle's current location and the road network traffic optimization parameters, and sending the new personalized route data to the vehicle. Determining in step (604) of the road network traffic optimization parameters in real-time for each of the set of allowed routes, wherein the road network traffic optimization parameters are determined as a function of inferred, scheduled, historical and predicted traffic related data on traffic flow, traffic distribution within the road network, average traffic speed, and travel times, or any combination or thereof.
  • the real-time traffic related data are dependent on events such as traffic density and speed, travel times, traffic jams, slowdowns, collisions, incidents and road work information, warnings and limitations from static and dynamic road signs, state of traffic lights, camera video streams, incidents detected based on analysis of camera video streams, weather information, manually created events by the system administrators or vehicle drivers and any other traffic related or traffic affecting data.
  • events such as traffic density and speed, travel times, traffic jams, slowdowns, collisions, incidents and road work information, warnings and limitations from static and dynamic road signs, state of traffic lights, camera video streams, incidents detected based on analysis of camera video streams, weather information, manually created events by the system administrators or vehicle drivers and any other traffic related or traffic affecting data.
  • Step 601 of Determining vehicle's parameters is equivalent to the step 502
  • Step 602 of Collecting traffic related data is equivalent to the step 500
  • Step 603 of Analyzing and processing traffic related data is equivalent to the step 501
  • Step 604 of Retrieving current road network optimization goals is equivalent to the step 503
  • calculation and delivery of the personalized traffic information and route guidance implementation may share the implementation of equivalent steps as to eliminate the redundant calculations.
  • Step 605 of Calculating a set of possible routes is executed by the Route calculator submodule 313 and comprises:
  • the routing algorithm may be realized by a weight based routing algorithm, where a weight is assigned to each segment of the road network, whereby the routing algorithm will find the path through the traffic network with the smallest weight, from the starting location to the desired destination.
  • Said weight assigned to each segment of the traffic network is calculated as a sum of individual weights proportional to the traffic -reducing factors and inversely proportional to the traffic increasing factors, where each weight is additionally modified to take into account the desired traffic network parameters by increasing the weights of those weights that increase the probability of reaching the desired traffic network parameters.
  • Each individual weight may comprise of any combination of: weights derived from the current and predicted values of the traffic network parameters, including positive weight proportional to traffic reducing traffic network parameters (such as traffic density, travel time, etc.) and positive weight reversely proportional to positively influencing parameters (such as traffic speed); weights derived from the current and predicted locations of other vehicles based on the plurality of other calculated routes, including positive weight proportional to the count of vehicles detected; weights derived from the historical or typical road network characteristics derived from data retrieved from the Historical information storage 310, including positive weight proportional to the historical or typical values of traffic flow, traffic density or travel time and reversely proportional to the historical or typical value of traffic speed.
  • weights derived from the current and predicted values of the traffic network parameters including positive weight proportional to traffic reducing traffic network parameters (such as traffic density, travel time, etc.) and positive weight reversely proportional to positively influencing parameters (such as traffic speed); weights derived from the current and predicted locations of other vehicles based on the plurality of other calculated routes, including positive weight proportional to
  • Said weighted routing algorithm is executed by the Route calculator 313 and may be based on any appropriate routing or pathfinding algorithm or method which may be realized as a computerized process running on TIRS 350, including dijkstra's algorithm or any variation of thereof, A*, B*, SMA*, D* algorithms or any variation of thereof, sample algorithm, equal-cost multi-path cost algorithms, path planning algorithms, Yen's algorithm, K shortest path routing, any other mathematical procedures of finding the shortest route or routes in a weighed graph, iterative methods, methods based on analyzing deviations of the previously found paths, heuristics, genetic algorithms, neural network based routing algorithms, other known routing or pathfinding techniques of any combination of thereof.
  • any appropriate routing or pathfinding algorithm or method which may be realized as a computerized process running on TIRS 350, including dijkstra's algorithm or any variation of thereof, A*, B*, SMA*, D* algorithms or any variation of thereof, sample algorithm, equal-cost multi-path cost algorithms, path planning
  • Step 606 of Personalizing a route for a vehicle is executed by the Routing module 312 and comprises evaluating the calculated set of routes, selecting the best route, where the selection of the route is done by taking into account any combination of:
  • steps 605 and 606 may by joined and executed in a single step.
  • selection criteria described of the step 606 may be represented as weights and the final route determined by the routing process of the step 605.

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Abstract

The present invention relates to a system and a method of a traffic related route data and personalization of an information for each vehicle in real-time. The system comprises a traffic information and route server TIRS (350), a user device (250) at each vehicle, the user device (250) is able to exchange information with the TIRS (350) and a plurality of traffic related data sources (400) available within a road network (100). The system is configured to collect and analyze a traffic related data in real-time, to receive parameters of each vehicle in real-time, and retrieve current road network traffic optimization parameters, where the system is configured to personalize information for each vehicle and send a personalized information to each vehicle in real-time. The method according to the present invention comprises the steps of collecting (500) a traffic related data in real-time from the plurality of traffic related data sources (400), analyzing and processing (501) the traffic related data by an information processing module (306) resulting in determining of current road network traffic parameters, determining parameters (502) of each vehicle, wherein said parameters are each vehicle's route, speed and heading, wherein the route of each vehicle runs from a current location of each vehicle to a target position of each vehicle, personalizing the traffic related data for each vehicle (503) depending on user set parameters of the user's device (250), values of the user device (250) sensors (205; 206), and remembered traffic behavior of the user, retrieving current road network traffic optimization parameters (504) by the routing module (312) where said road network traffic optimization parameters are calculated from the desired road network parameters for the whole traffic network, or the segments of the road traffic network, performing personalizing of an information (505) by the routing module (312) for each vehicle depending on the current road network traffic optimization parameters from step (504) and the current road network traffic parameters from step (501), and selecting a set of personalized information and sending (506) said set to each vehicle.

Description

SYSTEM AND METHOD FOR CREATION AND DELIVERY OF PERSONALIZED TRAFFIC
AND ROUTE INFORMATION
FIELD OF THE INVENTION
[0001] This invention is generally related to the field of navigation and route guidance. Particularly present invention is related to the field of traffic related information collecting, processing and delivery to traffic participants, where said information is personalized with respect to each vehicle.
BACKGROUND OF THE INVENTION
[0002] A number of services that present traffic information already exists. Such services include radio broadcasts containing traffic information, web sites with textual information or maps displaying the traffic information such as traffic density, and mobile device applications presenting such data in textual format, picture format or on the map.
[0003] Traffic information displayed in such systems can be collected in multitude of ways, including manual entry by the operators of such services, receiving data directly from various roadside sensors or indirectly from other traffic services, traffic monitoring centers, and government agencies.
[0004] Some systems enable the services users to provide traffic data to the system. This can be done directly by the user by entering the information on the computer or mobile device, or automatically by collecting and transmitting the information from the user's mobile device running an application provided by the service provider.
[0005] A number of systems and devices are presently capable of calculating the route for navigating the vehicle to selected destination. Such systems include web map based routing services, "on board" vehicle navigation devices and mobile device applications capable of route calculation and guidance.
[0006] Many such systems are equipped with GPS location sensor and are capable of displaying the present vehicle location along with calculated route on the graphical map, providing textual, graphical or voice based route guidance messages while driving, such as "turn right".
SUMMARY OF THE INVENTION
[0007] The present invention relates to a system and a method for calculation and delivery of personalized traffic and route information, wherein said information is dynamically configured depending on a traffic related data in real-time and current road network traffic optimization parameters. Particularly, present invention provides the system and the method of personalization of a traffic related route data and personalization of delivered information for each vehicle in real-time.
[0008] In brief, the method includes collecting traffic related data from available traffic related information sources, analyzing and processing the collected data and delivering a subset of collected and processed information to user devices in a personalized manner. The term "personalized manner" refers to the ability of the system to select, modify and deliver the information to user devices in a way where each user device may receive a different subset of information, modified or different information or the same information in different time, as decided by the system and required to realize the present invention and methods described herein.
[0009] User device may be any of: mobile phone or smartphone, tablet, personal data assistant (PDA), personal computer (PC), mobile navigation device, in- vehicle navigation device, on board vehicle navigation or display device, or any other device comprising of a communication interface capable of exchanging traffic related data and a user interface capable of presenting said data. User devices may be equipped with the location sensor enabling the device to communicate its current location to the system. In the remainder of this document, the term "device" is used as the synonym to "user device", the term "vehicle" is used as a synonym for the user device that is located in the vehicle, the term "driver" is used as a synonym for the driver of said vehicle who is able to see, hear and interact with the user device within the vehicle. Terms "displayed in vehicle" and "displayed to driver" should be interpreted as meaning "displayed on user device located in the vehicle" and "displayed to the driver of vehicle through the user device located in the said vehicle" respectively. Other uses of the terms "vehicle" and "driver" should be interpreted accordingly. In some embodiments, the user device may be an integrated part of the vehicle and is able to access vehicle sensors such as vehicle speedometer, rain detection sensors, traction control sensors (ABS) and other available sensors.
[0010] In some embodiments, collected data may include present (real-time), inferred, scheduled, historical and predicted traffic related data and events such as traffic density and speed, travel times, traffic jams, slowdowns, collisions, incidents and works; information, warnings and limitations from static and dynamic road signs, state of traffic lights, camera video streams, incidents detected based on analysis of camera video streams, weather information, manually created events by the system administrators or vehicle drivers and any other traffic related or traffic affecting information. In some embodiments, collected information may include start and end time of said events. In some embodiments, sources of said information may include user devices themselves, various roadside sensors, road equipment, traffic monitoring and control centers, government agencies, traffic prediction systems, weather forecasting systems, historical information databases, traffic models and other traffic related or traffic affecting information providing services.
[0011] In some embodiments, the system has a direct connection with the traffic operation control and monitoring center and is able to retrieve real-time data from said center. Said data comprises only a part of collected traffic related information. In some embodiments, system operation and system behavior defining parameters can be operated from the traffic operation control and monitoring center through the said connection. [0012] Collected information may be directly sent to user devices, optionally being analyzed and processed before sending (e.g. converted or combined with other information) or stored as historical information used for future traffic analysis.
[0013] User devices may be able to present received information to drivers in any format, including textual, picture, map and audio formats.
[0014] In some embodiments, messages entered directly by the operators of traffic operation control and monitoring center may be delivered and displayed to drivers.
[0015] In some embodiments, meteorological data from weather stations may be retrieved and generate a warning displayed to the driver in the event of decreased travel safety, including ice formation, wet road, reduced visibility and other road safety affecting meteorological situations.
[0016] In some embodiments, the system may retrieve the status of changeable traffic signs and display an image of their displayed content on the device. A sign content may also be converted to textual or audio message based on its meaning and sent to device.
[0017] In some embodiments, the system may detect the allowed speed limit for the road section based on the contents of the changeable traffic signs, assuming they are displaying the message denoting a speed limit or other content that implies a speed limit, and display said speed limit on the device.
[0018] In some embodiments, the system may analyze and process all of the said collected information and display to drivers a calculated safe driving speed. Maximum legal speed for the road segment on which the vehicle is travelling on can be taken in account so the suggested speed never exceeds the legal speed.
[0019] In some embodiments, the system may display to drivers the duration of the current phase of the upstream (in direction of traffic flow) traffic lights to approaching drivers.
[0020] In some embodiments, collected information may be forwarded to other systems, including traffic monitoring and control centers, government agencies, historical information databases, and other traffic related data-consuming services.
[0021] The present invention relates to a method comprising delivery of a personalized traffic information to user devices in a way in which each user device receives in real-time only a calculated subset of the traffic related information.
[0022] In some embodiments, the relevant set of traffic related information may be determined by the combination of any number of user device parameters: device current location, heading, speed, acceleration, sensor readings, stored historical movements, type and characteristics of the vehicle currently containing the device, manually entered device settings and other device, vehicle or driver parameters associated with the device.
[0023] In some embodiments, information from static and dynamic road signs (including Variable Message Signs, Dynamic Message Signs, Textual Displays, Pictograms, Prismatic Changeable Signs and other signs where the displayed image is changeable) may be delivered to vehicles in a personalized manner, depending on said user device parameters. E.g. variable road sign containing the picture prohibiting truck traffic may be delivered and displayed only to user devices currently contained within truck vehicles.
[0024] In some embodiments, the method may include delivering and displaying personalized messages to drivers by delivering the same traffic related information, but modifying the delivery or display times. In some embodiments, the method may include sending an early warning to a subset of user devices about an upstream traffic conditions allowing them to change their route in time, and a delayed warning to other user devices, increasing their safety, but decreasing their chances from changing direction.
[0025] In some embodiments, the method may include delivering and displaying different personalized subsets of traffic related information to different vehicles, even when the vehicles have the same or nearly same set and values of the device parameters.
[0026] In some embodiments, the method may include delivering and displaying different personalized subsets of traffic related information to different vehicles, even when the vehicles have approximately the same location.
[0027] In some embodiments, the method may include sending a warning to a subset of user devices about an upstream traffic flow disturbance with an alternative route suggestion, but only a warning without an alternative route suggestion to other user devices.
[0028] In some embodiments, the method includes optimizing network traffic, with the goal of achieving network traffic as close as possible to the desired road network traffic parameters, where road network traffic parameters comprise of parameters relating to traffic flow, traffic distribution within the road network, traffic speed, travel times, levels of pollution and travel safety in general, or any combination or thereof, by sending personalized messages to the drivers, affecting their driving behavior relating to driving speed and route taken. In some embodiments, said personalized messages contain a suggested driving speed, the suggested driving speed taking into account current speed limits, contents of traffic signs, traffic light phase periods and traffic distribution within the road network of the selected route. The personalized messages further contain weather warnings, suggested turns and routes to take, warning of upstream traffic incidents and flow reductions and any other driving related messages, warnings and suggestions.
[0029] In some embodiments, the desired road network traffic parameters may be determined from the maximum traffic flow capacity of the road networks segments, or as a percentage of the said value.
[0030] In some embodiments, the desired road network traffic parameters are changeable and dynamically determined by a goal oriented optimization process, where the goals include any combination of minimizing traffic slowdowns, congestions and jams, maximizing traffic speed, minimizing travel times, reducing pollution and optimization of any other combination of any other travel related parameters.
[0031] In some embodiments, the desired road network traffic parameters or desired optimization goals may be set manually from the system's user/administrator interface, programmatically through an application-programming interface (API) or by schedule.
[0032] In some embodiments, the system may include route guidance function (navigation), enabling the user device users to enter the desired location and receive guidance information in the form of suggested routes from the current location to the specified destination. The system may take into account collected traffic affecting information (present, inferred, scheduled, historical and predicted traffic related data) when calculating suggested route with the goal of optimizing route quality, including travel distance and travel time. The system may also monitor the said collected information for change, periodically recalculating the route, and suggesting new route or automatically replacing the previous route suggestion with a new route.
[0033] In some embodiments, the method includes optimizing network traffic and achieving the desired road network traffic parameters by sending different personalized navigation routes to drivers traveling within the road network, thus controlling their future locations in time.
[0034] In some embodiments, the method includes optimizing network traffic by detecting reductions in the traffic flow capacity of a part of the road network (e.g. caused by the lane closure) and sending an alternative personalized route which does not include the affected road network segments with the reduced capacity, only to a subset of vehicles which would otherwise be guided to the affected segments, thus decreasing the influx of new vehicles to the affected road segment and better achieving the desired road network traffic parameters.
[0035] In some embodiments, the method of optimizing network traffic by delivering personalized routes may also take into account the benefits to the driver, including travel time and travel distance. Said benefits to the driver may be considered as part of desired road network traffic parameters. In some embodiments, the method may include fair distribution of calculated personalized traffic routes so that no personalized route sent to any one vehicle is substantially worse than other possible routes, considering the distance or time traveled, by any combination of:
not using those calculated personalized routes which would cause the vehicle to travel the distance or time fd percent greater than any combination of other routes sent to others vehicles, shortest route or quickest route, fd being a system parameter, and replacing them with alternative routes; and calculating and storing the time and distance lost when compared with any combination of other routes sent to others vehicles, shortest route or quickest route, and in the future retrieving the lost total distance and time, if the retrieved lost total distance and time are found compensating the vehicle by assigning it a shorter and/or faster route, calculating the distance and time difference between the other routes, and finally subtracting the said difference from the stored values;
[0036] In some embodiments, the effects of the travel of currently guided vehicles through the road network are also taken into account and form a part of the collected traffic affecting information. This includes both current and predicted locations of the vehicles and their influence on the road network traffic parameters along their routes.
[0037] In some embodiments, the system may take into account the current lane the driver is driving on and modify the guidance directions to avoid negatively affecting driving safety. E.g., the system may avoid delivering information to drivers that may cause them to cross multiple lanes within a small distance during high-density traffic.
[0038] In some embodiments, the system may react to the detected reductions in the traffic flow on a road segment by informing the driver about said flow reduction or offering to the driver a personalized navigation route bypassing the affected road segments, even if the driver was not actively using the navigation function of the device at the time.
[0039] In some embodiments, the system may determine, with the degree of certainty, the current route the vehicle is traveling on and the road segments it will travel on in the near future, determine that the vehicle will be affected by travel flow reductions detected or predicted on said road segments, and, if the degree of certainty is greater than a preset threshold value, inform the driver of said flow reduction or offer to the driver a personalized navigation route even if the driver was not actively using the navigation function of the device at the time.
[0040] In some embodiments, the system may skip informing a subset of drivers in order to keep them on the same route if by doing this the system will better achieve the desired road network traffic parameters.
[0041] The current vehicle route and road segments the vehicle will travel in the near future may be determined with a degree of certainty by the combination of any of: number of possible detours from the assumed route the driver can take, percentage of drivers that generally take the possible detours relative to those that remain on the assumed route and specifically the percentage of times the driver of said vehicle had stayed on the assumed route relative to the possible detours, currently occupied lane relative to the number of lanes the vehicle should take in order to make the turn relative to the distance to the turn.
[0042] In some embodiments, the system may advise the driver on speed that is required to safely pass through or stop before the traffic lights. If the red light is displayed and the driver is not slowing down within the set distance, a warning will be displayed on the device. If the green traffic light is displayed, but the driver is not able to pass safely through the intersection, because the light will change to red before the vehicle reaches the intersection, a warning will be displayed on the device. If the driver can safely pass through the intersection if he increases the vehicle speed, and the increased speed is within the legal and safe boundaries, a notice will be displayed on the device suggesting the driver to increase speed to a recommended value.
[0043] The system may use the route guidance information to select a single traffic light related to the driver's direction and optionally the driver's next turn based on driver's location and route. If the route guidance information is not available (e.g. the driver is not using the navigation function) the system may infer the direction and next intended turn of the driver by the lane they are driving in, the road network structure and turn restrictions and readings from the acceleration sensor in the event the location sensor is not sufficiently precise.
[0044] In some embodiments, the method includes automatically detecting traffic flow reductions, congestion, traffic jam, blocked lane by monitoring the plurality of locations the vehicle has travelled in time and calculating vehicle speeds.
[0045] Traffic flow reduction, congestion and traffic jams are detected by a decrease of traffic flow and travel speeds on the monitored road segments compared to recent and historical typical values.
[0046] Blocked lane may be detected by a combination of any of: movement of vehicles to other parallel lanes and subsequent return of some vehicles to the assumed blocked lane, reduced speed of travel in the neighboring lanes, and greatly reduced speed of travel directly before the lane blockage in the same lane as the blockage.
[0047] In some embodiments, the method includes detecting stopped vehicles in designated locations by monitoring the vehicle's location and speed. If the vehicle speed reaches zero and the vehicle is currently within a predestined location such as tunnel or emergency lane vehicle stop will be detected.
[0048] In some embodiments, the method includes monitoring the plurality of vehicles and their movement through intersections, detecting their stops in front of intersections, measuring the duration of said stops, detecting subsequent movement through the intersection, storing and analyzing said information and calculating the sequence and duration of the phases of the traffic lights.
BRIEF DESCRIPTION OF THE DRAWINGS
[0049] In the text that follows, the present invention will be described in detail by means of disclosed embodiments with reference to following figures:
[0050] FIG. A illustrates a schematic exemplary of a system according to embodiments of the present invention;
[0051] FIG. B illustrates flow-chart of a method of personalization of traffic related route guidance and personalization of an information for each vehicle in real-time according to embodiments of the present invention; [0052] FIG. C illustrates a schematic flow-chart of a method of calculation of personalized route guidance for a vehicle, according to embodiments of the present invention; and
[0053] FIG. D illustrates a schematic illustration of an exemplary fragment of a traffic road network, used hereinafter for demonstrating the method of creation and personalization of traffic related route guidance and personalization of an information for each vehicle in real-time according to embodiments of the present invention.
DETAILED DESCRIPTION OF THE PRESENT INVENTION
[0054] According to present invention, as illustrated in FIG. A, a system 200 is comprises of a central Traffic Information and Routing server (TIRS) 350, a plurality of user devices 260 and a plurality of traffic related information sources 400 available within a road network.
[0055] The system 200 is configured to collect a traffic related data in real-time, to analyze and process the traffic related data, to receive parameters of each vehicle in real-time, and retrieve current road network traffic optimization parameters. Under control of the traffic information and route server 350, the system 200 is configured to personalize information for each vehicle depending on the current traffic related data, current parameters of each vehicle and current road network traffic optimization parameters, and to send a personalized information to each vehicle. The personalized information sent to each vehicle is dynamically changed depending on the change of traffic related data, parameters of each vehicle and road network traffic optimization parameters in real-time. Further, the system is configured to carry out the computer program running on the TIRS 350.
[0056] The TIRS 350 is running a computer program, comprising of multiple modules and submodules 304 to 315, with the purpose of collecting traffic related information from available traffic related information sources 400, analyzing and processing said information and delivering a relevant subset of collected and processed information, including route guidance information, to the each of user devices 250 in a personalized manner for further use by the user devices 260. Additionally, said traffic related information comprises calculated navigation routes.
[0057] An information collecting module 306 coordinates the process of collecting the traffic related data in real-time from the plurality of traffic related information sources 400. The information collecting module 306 performs monitoring, predicting, analyzing and processing traffic relevant data, providing said data for use to other modules. To enable greater understanding, the information collecting module 306 is divided into multiple submodules, the submodules comprising of a traffic center data exchange module 307, a real-time information collector 308, an information predictor 309, a historical information storage 310 and an information change monitor 311. The traffic center data exchange module 307 may be used to collect real-time traffic data from existing traffic operation control centers. Real-time information collector 308 may be used to collect real time information from roadside sensors and equipment directly or from other external real-time traffic related information providing sources indirectly. Information processing module 306 may store all of the collected and processed information to Historical information storage 310 for future use by other system modules. Information predictor module 309 may use already collected information by the Information processing module 306 and its submodules, predicting future parameters and providing them for further use to other system modules through the Information processing module 306.
[0058] A device communication module 315 on the TIRS 350 and a communication module 203 on each of the device 250 may be used to exchange information between the TIRS 350 and devices 260 by a cellular, wireless or radio network, or any other wireless or wired type of communication. Data exchange may be achieved by any standard or custom communication protocol, such as TCP, UDP, HTTP, WebSocket, custom protocols or any other suitable protocol. Devices 250 may be equipped with a variety of sensors, including a location sensor 205, enabling the device 250 to communicate periodically its current location, heading and speed to the TIRS 350. All information collected from the devices 260 may be used by the information processing module 306. In some embodiments, Information processing module 306 may determine the speed and heading of a device by analyzing the plurality of recent device 260 locations retrieved from the historical information storage 310.
[0059] In some embodiments, the driver may send an event from his personal device 250 to the TIRS 350, describing the current traffic-affecting situation by using the available user input module 204 available on the device. For example, the driver may report a traffic jam at its current location.
[0060] Information sent to user devices 260 by the TIRS 350, through the device communication module 315, may be presented to drivers by using a Display 201, an Audio speaker 202 or any other means of communication provided by the device. In some embodiments, devices may display information and routes on a map, where said map was received from the traffic network map database 305 or stored on the device 250 itself.
[0061] It is understood that some embodiments may have different names, organization or responsibilities of modules and submodules than described herein and in the Fig. A, without affecting the functionality of the system. In some embodiments, some modules or submodules along with their functionality may be partially or completely implemented on the user devices themselves, including, for example, Routing module 312, Route calculator 313, Route deduction submodule 314 and Traffic network map database 305. All modules, within TIRS 350 or user device 250, may be implemented in software, hardware, and any combination of thereof.
[0062] Referring now to FIG. D., which is a schematic illustration of an exemplary fragment of a traffic road network 100, used hereinafter for demonstrating the method of personalization of traffic related and route information and the method of calculation of a personalized route guidance information, according to embodiments of the present invention. The present invention is in no way limited to the exemplary road fragment 100 and can be applied to any traffic road network. [0063] The exemplary road fragment 100 is comprised of intersections 1 tough 6 and vehicles A through T. Each vehicle may have a location sensor and transmit its location to the Traffic information and route server (TIRS) 350. To achieve a greater clarity of explanation it is assumed that all of the vehicles depicted within the exemplary road network have a user device and are able to exchange information with the TIRS 350, however, the method and system described herein are not limited in this respect and can be used at any road network, even where only a subset of vehicles contain a user device.
[0064] TIRS 350 may receive the information from vehicles A through T and store and process them along with other information collected from other traffic related information sources available within the road network. TIRS 350 may exchange data with vehicles and send personalized messages to vehicles traveling on the road network. Said messages may be presented to the vehicle's drivers through the user device, where said messages may be presented in any format, including textual, picture, map and audio formats.
[0065] For demonstrating some embodiments of the present invention, it is assumed that the vehicle D has suffered a problem that has caused it to stop in the right traffic lane between the intersections 1 and 2, partially reducing available traffic flow, causing a traffic congestion and a formation of traffic queue of vehicles E through I. The stopped vehicle D is used only as one example of a possible traffic disturbance. The present invention is in no way limited to reacting only to stopped vehicles and may react to any traffic disturbance, including those affecting the current or future traffic flow, changes to traffic capacity, traffic speed, travel times and other changes to traffic-affecting parameters.
[0066] The traffic disturbance caused by the vehicle D may be detected by the TIRS 350 in various ways, including based on information by roadside equipment, combining and comparing readings from multiple roadside equipment, from information collected from external systems or traffic operation and control centers, or based on collected information or direct notification from any other traffic related information source.
[0067] In some embodiments, the traffic disturbance caused by the vehicle D can be detected based on manual notifications sent by any of user devices to TIRS 350, including manual notification by the driver of vehicle D or by any of the nearby drivers of vehicles E through I.
[0068] In some embodiments, the traffic disturbance caused by the vehicle D can be detected by the TIRS 350 by analyzing the movement patterns of the vehicle D and of nearby vehicles E through I having the user device, including their currently assigned routes and speeds, by detecting any combination of: slowdown or stop of vehicle D, slowdown of other said vehicles or their shift from the right lane to the left lane passing the location of the stopped vehicle.
[0069] In some embodiments, the TIRS 350 may react to the traffic flow reduction caused by vehicle D by attempting to optimize traffic. In some embodiments, the TIRS 350 may determine the remaining traffic capacity of the link between intersections 1 and 2, and attempt to optimize the influx of new vehicles to achieve said set road network optimization parameters. In some embodiments, the TIRS may optimize traffic and achieve currently set road network optimization parameters by sending different personalized messages to vehicles A through C affecting their driving behavior, including driving speed and route. In the remainder of this example, it is assumed that the currently set road network optimization parameters include optimizing traffic flow and time through the whole traffic network example. Note that in other embodiments said parameter may include achieving network traffic as close as possible to the desired road network traffic values, including traffic flow, traffic distribution within the road network, traffic speed, travel times and travel safety in general, or any combination or thereof.
[0070] In some embodiments, the TIRS 350 may determine the remaining traffic capacity of the link between intersections 1 and 2, and attempt to optimize the influx of new vehicles so that the travel time, travel distance or both, through the affected link remains as close to equal to those on other alternative routes, for example, route passing through the intersection 4.
[0071] In some embodiments, for example, the TIRS 350 may respond to said traffic flow reduction by sending different personalized traffic information messages to vehicles A through C, influencing their driving speed and route taken, even though they are located nearly at the same location at intersection 1. In some embodiments, for example, TIRS 350 may alert vehicle B about the congestion ahead and offered a preferred detour through the intersection 4, therefore increasing the chance that the vehicle B will take the route through the intersection 4. Additionally, TIRS 350 may offer only a warning to vehicle C, without offering to the vehicle an alternative route, enabling the vehicle to take an alternative route through intersection 4 but with the lesser possibility compared to the vehicle B. Additionally, TIRS 350 may offer no advance warning to the vehicle A increasing the chance the vehicle will traveling straight through the intersection 1 towards the vehicle D. Additionally, TIRS 350 may delay warning for some of vehicles and warn them about an upstream congestion only after it is no longer possible for vehicles to alter their route, e.g. vehicle R.
[0072] In some embodiments, when attempting to influence driving behavior, to achieve the maximum effect TIRS 350 may attempt to further increase the probability of drivers making the desired driving decisions by analyzing the baseline probability of driver making said decision in the event when not influenced by the system, and further positively influencing the decision rather than attempting to overturn it.
[0073] In some embodiments, when attempting to influence driving behavior, TIRS 350 may take into account the current lane the vehicle is occupying and the turn restrictions of the intersections the vehicle is likely to pass and avoid sending personalized messages to the driver that would promote illegal or unlsafe driving decisions.
[0074] In some embodiments, when vehicles are using the navigation function, TIRS 350 may offer a different personalized route to each vehicle to achieve the road network optimization parameters. For example, assuming the vehicles S and T are guided to the same location at the intersection 6 along the same route passing through the intersection 2, upon detecting the reduced traffic capacity at the link between the intersections 1 and 2 TIRS 350 may reroute the driver of the vehicle T through the intersection 4, while leaving the vehicle S on the original route passing through the intersection 2.
[0075] In some embodiments, the system may offer to the driver a recommended route, even if the driver was not currently using the navigation function. For example, assuming that for the exemplary road network TIRS 350 will determine with a great degree of probability that the vehicles A and Q will travel to or through the intersection 6, TIRS 350 may offer to the vehicles a temporary route guidance avoiding the link between intersections 1 and 2 with the decreased traffic capacity.
[0076] In some embodiments, information from static and changeable road signs may be delivered to vehicles in a personalized manner, depending on said user device parameters. E.g. , assuming the variable road sign X contains the picture prohibiting truck traffic between the intersection 4 in the direction of intersection 5; TIRS 350 may forward this information in the form of a warning to an approaching truck M, but not to an approaching personal vehicle O. TIRS will detect that the truck L is passing in the opposite direction and will not forward this warning to a said vehicle L. Additionally, TIRS 350 may detect that the truck P has joined the traffic after the location of the sign T, was not able to see the sign, and forward the warning to the vehicle.
[0077] Reference is now made to figure B, which is a schematic flow-chart illustrating a method of delivery of personalized traffic related route guidance and personalization of an information for each vehicle in real-time, according to preferred embodiments of the present invention. As shown, the method may include, for example, collecting traffic related data as illustrated in block 500, analyzing and processing traffic related data as illustrated in block 501, determining each vehicles parameters (location, speed, heading, route, etc.) as illustrated in block 502, personalizing the collected information for each vehicle taking into account the relevance of information to said vehicle as illustrated in block 503, fetching current road network optimization parameters as illustrated in block 504, personalizing the collected information for each vehicle so the road network optimization parameters are achieved as illustrated in block 505, sending personalized information to vehicle as illustrated in block 506 and monitoring the traffic information, vehicle information and optimization parameters for changes as illustrated in block 507. The illustrated process steps are repeated once the change in any relevant information or parameter is detected, periodically or nearly continuously.
[0078] The step 500 of Collecting a traffic related data comprises collecting the traffic related data in real-time from the plurality of traffic related data sources 400, through the Information processing module 306 and its submodules, Traffic center exchange module 307 and Real-time information collector 308, and collecting vehicle data through the Device communication module 315 communicating with the Communication module 203 on the device 250, where said data is comprised of the device 250 status, settings and sensor readings, including the readings derived from the Location sensor 205, the Acceleration sensor 206 and other available sensors. The step 501 of Analyzing and processing data is realized within the Information processing module 306, using the traffic related data collected by the Collecting traffic data in step 500, by analyzing and processing data based on system configuration resulting in a further expanded set of information, where said information comprises information which can be presented to drivers in textual, audio, map and picture format, but is not yet personalized, and linking said information to segments of the traffic network 100.
[0079] The Analyzing and processing the traffic related data in step 501 comprises of any combination of steps including:
- converting all data to a standard set of measurement units;
- linking of data to other data forming new data including, for example the collected traffic related data may contain recorded vehicle passing's with license plate data - by comparing the collected data with the previously collected data for separate nearby locations, retrieved from the Historical information storage 310, the system may infer the time it took the vehicles to cover the distance between said locations and determine the vehicle speed;
- aggregating data including, for example aggregating the plurality of speeds of collected data of individual vehicles, nearby to each other and traveling on the same road segment in the same direction, may be converted to a single average speed of the said road segment; and
- determining from the data the current road network traffic parameters or the numeric influence on the value (delta) or rate of change of said parameters, including traffic flow, traffic density, traffic speed, travel time and level of pollution, and assigning a probability to each, where said assigned possibility determines the certainty that the given value is correct;
- analyzing the plurality of collected and calculated data and parameters, the Information processing module 306 may evaluate said data and parameters, where by applying further transformations or logical comparisons new data for use within the system are generated.
- converting collected and calculated data and parameters to presentable information, forming information which can be displayed to driver on user devices in textual, audio, map and picture format.
- assigning collected and calculated information to the traffic road network segments stored in the Traffic network map database 305, where said information relates to the said segment.
Determining the current road network traffic parameters or numeric influence on value and rate of change of said parameters is comprised of any combination of: directly using the collected traffic related data, where said collected data comprises information of said road network traffic parameters, using the accuracy of measurement as the probability of each parameter, and inferring or calculating the parameters based on other available data; or inferring or calculating the parameters based on other available data.
Inferring or calculating the parameters based on other available data includes any combination of:
- typical or most likely historical values from the Historical information storage 310;
- determining the impact of traffic related events (e.g. traffic works, traffic accident or any other traffic affecting event), where said influence may be set in advance depending on the type of the event or determined by consulting the Historical information storage 310, by retrieving or calculating the influence of said event in past, optionally giving greater weight to situations where other gathered data was most similar to the currently gathered data;
- determining the impact of meteorological data (e.g. rain, snow, fog or other visibility drop, or any other traffic affecting meteorological situation), and determining the influence to the parameters, where said influence may be set in advance depending on the type of the event or determined by consulting the Historical information storage 310, by retrieving or calculating the influence of said event in past, optionally giving greater weight to situations where other gathered data was most similar to the currently gathered data;
- interpreting the current images of the dynamic traffic signs, by converting the displayed picture, picture code, message text or message metadata to an event related to the road network segment past the sign (e.g. traffic works, traffic accident or any other traffic affecting event), and determining the influence to the parameters, where said influence may be set in advance depending on the type of the event or determined by consulting the Historical information storage 310, by retrieving or calculating the influence of said event in past, optionally giving greater weight to situations where other gathered data was most similar to the currently gathered data.
In some embodiments, current road network traffic parameters or numeric influence on value and rate of change may be fed into the Information predictor 309, along with the information about schedules traffic related events, and, based on road network configuration from Traffic network map database 305 and Historical information from Historical information storage 310, expanded in space to other neighboring road segments and time into the future.
[0080] The step 502 of Determining each vehicles parameters comprises of determining each vehicles location based on information from the Location sensor 205, and determining the speed and heading of each vehicle, either by using the optional function of the Location sensor 205, where said sensor function can also report speed or heading, or by calculating speed or heading through measuring the difference between several sequential Location sensor 205 readings indicating the location and time of the vehicle, where said calculation can be done on the user device 250 itself, or on the server 350 within the Information processing module 306 using previously recorded vehicle data stored in the Historical information storage 310. The step 502 further comprises storing the vehicle parameters in the Historical information storage 310 for further use.
[0081] The step 503 of Personalizing the gathered information for each vehicle is realized within the Information processing module 306 and comprises a series of steps, including selecting and modifying the information in a way where each user device may receive a different subset of information, modified or different information or the same information in different time, where said selection and modification of information is done through a rule based evaluation process depending on the user set preferences or parameters of user's device, values of user device sensors and the remembered behavior and previous actions of the user, including, for example, deemphasizing information to which the user has not responded in the past, including, for example information not viewed, hidden of deleted by the user. Remembered previous behavior and user actions may be stored in the Historical information storage 310.
[0082] The step 504 of Retrieving the current road network optimization parameters is realized within the Routing module 312, and includes calculating the desired road network parameters for the segments of the road traffic network 100, where said parameters include traffic flow, traffic density, traffic speed, travel time and level of pollution. The calculation of said parameters may comprise of any combination of:
- Directly retrieving the manually or externally set values of desired parameters,
- Setting the desired parameters through configured schedule, and
- Calculating the desired parameters through execution of a configured function based on collected and calculated information, including current and predicted values of road network parameters and the theoretical or measured limits for the parameters of the road network values. Calculating of the desired parameters includes for example, setting the desired parameters to a percentage of available traffic capacity of the road network, and/or setting the desired parameters to percentage of the peak or average value of traffic density or speed which has historically caused traffic congestion, where said value may be retrieved from the Historical information storage 310. The results of the execution of a goal oriented optimization process, where said goals may include even distribution of traffic through the road network (minimization of flow differences), maximization of travel speed, minimization of travel times, maximization of traffic flow, minimization of pollution (based on maximizing constraint traffic flow and minimizing vehicle stops), minimization of occurrence of traffic parameters leading to congestions and any combination of thereof. Said optimization process is executed by the Routing module 312 and may be based on any appropriate optimization method which may be realized as a computer program running on the TIRS 350, including mathematical optimization algorithms, iterative methods, heuristics, goal based programming, genetic algorithms, neural network based optimization, other known optimization techniques or the combination of thereof.
[0083] Said methods of desired parameters calculation may apply to the whole traffic network, or to subset of the traffic network. Additionally, each subset of the traffic network may have different values of the desired parameters set independently.
[0084] The step 505 of Personalizing information for each vehicle to achieve the desired road network parameters is executed by the Routing module 312 based on the results of previous steps, receiving as input the processed traffic related information and desired road network parameters and calculating as output the further personalized messages through a series of steps, including selecting and modifying the information in a way where each user device may receive a different subset of information, modified or different information or the same information in different time, as to achieve the road network parameters close to those defined by the desired road network parameters.
The step 505 of Personalizing information for each vehicle to achieve the desired road network parameters comprises:
- Retrieving the current and predicted values of the road network parameters created by the execution of the step 501,
- Retrieving the desired values of the road network parameters created by the execution of step 504,
- Calculating the required change of the current and predicted parameters required to achieve the desired parameters of the road network,
- Fetching the collected and calculated information created initially by the step 501 and further personalized by the step 503,
- Forming further personalized information by selecting and modifying collected and calculated personalized information, where information for each vehicle may be personalized in multiple combination or in multiple ways, said forming comprising omission of some information, where said information will not be sent to the driver; modification of delivery or display time of some information, and modification of information, including giving or omitting explicit instructions of expected driver actions (e.g. alternative route suggestions), modifying the priority of information, modifying the method of display of information to the drivers and other modification which may have an effect on the driver behavior,
- Calculating the effect of presenting said personalized information to the driver on the current and future road network parameters,
- Selecting a set of personalized information to send to the drivers, where the calculated effect minimizes the difference between the current and desired values of the road network parameters. Said optimization process is executed by the Routing module 312 and may be based on any appropriate optimization method which may be realized as a computer program running on the TIRS 350, including mathematical optimization algorithms, iterative methods, heuristics, goal based programming, genetic algorithms, neural network based optimization, other known optimization techniques or the combination of thereof.
[0085] In the case of information not affecting driver behavior or the optimization function of the system being disabled the personalized traffic related information from step 503 may directly advance to step 506 and sent to user devices.
[0086] Reference is now made to figure C, which is a schematic flow-chart illustrating a method of calculation of personalized route guidance information for a vehicle, according to some embodiments of the present invention. As shown, the method may include, for example,
receiving a routing request from vehicle, including desired destination, as illustrated in block 600, fetching/determining vehicle's current location as illustrated in block 601, collecting/determining traffic related data in real time as illustrated in block 602, analyzing and processing traffic related data as illustrated in block 603, retrieving current road network optimization parameters or goals as illustrated in block 604, calculating a set of routes, taking into account real-time and predicted traffic information, as illustrated in block 605, personalizing a route for vehicle, by evaluating the calculated set of routes, selecting the best route taking into account the impact to desired road network traffic parameters or optimization goals, travel parameters of nearby vehicles, routes of other vehicles and fairness as illustrated in block 606, sending personalized route to vehicle as illustrated in block 607, and monitoring traffic information, vehicle information and optimization parameters for changes as illustrated in block 608. The illustrated process may be repeated once the change in any relevant information or parameter is detected, periodically or nearly continuously. Accordingly, the method of calculation of personalized route guidance information for the vehicle selects a new personalized route from the set of calculated allowed routes depending on the change of the real-time traffic data, the vehicle's current location and the road network traffic optimization parameters, and sending the new personalized route data to the vehicle. Determining in step (604) of the road network traffic optimization parameters in real-time for each of the set of allowed routes, wherein the road network traffic optimization parameters are determined as a function of inferred, scheduled, historical and predicted traffic related data on traffic flow, traffic distribution within the road network, average traffic speed, and travel times, or any combination or thereof. The real-time traffic related data are dependent on events such as traffic density and speed, travel times, traffic jams, slowdowns, collisions, incidents and road work information, warnings and limitations from static and dynamic road signs, state of traffic lights, camera video streams, incidents detected based on analysis of camera video streams, weather information, manually created events by the system administrators or vehicle drivers and any other traffic related or traffic affecting data. [0087] A detailed description of the method described in figure C with references to system described in figure A is given hereinafter.
[0088] Since the calculation and delivery of personalized route guidance information may be viewed as a specialized case of the calculation and delivery of personalized traffic information many of the steps of the said methods may be viewed as equivalent, with the only difference being that the scope of the route guidance method may be optimized to take into account only the vicinity of the possible routes. Said equivalent steps include:
Step 601 of Determining vehicle's parameters is equivalent to the step 502
Step 602 of Collecting traffic related data is equivalent to the step 500
Step 603 of Analyzing and processing traffic related data is equivalent to the step 501
Step 604 of Retrieving current road network optimization goals is equivalent to the step 503 In some embodiments, calculation and delivery of the personalized traffic information and route guidance implementation may share the implementation of equivalent steps as to eliminate the redundant calculations.
[0089] Step 605 of Calculating a set of possible routes is executed by the Route calculator submodule 313 and comprises:
Retrieving the current and predicted values of the traffic information, including current and predicted road network parameters, created by the execution of the step 603
Retrieving the desired values of the road network parameters created by the execution of step
604
Calculating a set of possible routes for the vehicle by using a routing algorithm.
In some embodiments the routing algorithm may be realized by a weight based routing algorithm, where a weight is assigned to each segment of the road network, whereby the routing algorithm will find the path through the traffic network with the smallest weight, from the starting location to the desired destination.
Said weight assigned to each segment of the traffic network is calculated as a sum of individual weights proportional to the traffic -reducing factors and inversely proportional to the traffic increasing factors, where each weight is additionally modified to take into account the desired traffic network parameters by increasing the weights of those weights that increase the probability of reaching the desired traffic network parameters.
Each individual weight may comprise of any combination of: weights derived from the current and predicted values of the traffic network parameters, including positive weight proportional to traffic reducing traffic network parameters (such as traffic density, travel time, etc.) and positive weight reversely proportional to positively influencing parameters (such as traffic speed); weights derived from the current and predicted locations of other vehicles based on the plurality of other calculated routes, including positive weight proportional to the count of vehicles detected; weights derived from the historical or typical road network characteristics derived from data retrieved from the Historical information storage 310, including positive weight proportional to the historical or typical values of traffic flow, traffic density or travel time and reversely proportional to the historical or typical value of traffic speed.
Said weighted routing algorithm is executed by the Route calculator 313 and may be based on any appropriate routing or pathfinding algorithm or method which may be realized as a computerized process running on TIRS 350, including dijkstra's algorithm or any variation of thereof, A*, B*, SMA*, D* algorithms or any variation of thereof, sample algorithm, equal-cost multi-path cost algorithms, path planning algorithms, Yen's algorithm, K shortest path routing, any other mathematical procedures of finding the shortest route or routes in a weighed graph, iterative methods, methods based on analyzing deviations of the previously found paths, heuristics, genetic algorithms, neural network based routing algorithms, other known routing or pathfinding techniques of any combination of thereof.
[0090] Step 606 of Personalizing a route for a vehicle is executed by the Routing module 312 and comprises evaluating the calculated set of routes, selecting the best route, where the selection of the route is done by taking into account any combination of:
Analyzing the impact on other vehicles and impact on the desired values of the traffic network parameters, favoring the routes with less negative impact on other vehicles and desired traffic network goals
Analyzing the routes of other guided vehicles in the vicinity of the vehicle or routes of other vehicles the said vehicle will be in the vicinity of in the future, and favoring the routes which will more evenly distribute the vehicles if said distribution better achieves the desired traffic network parameters
Analyzing the length and travel time of the route, along with fairness (difference in length and travel time) when compared to other routed vehicles, and favoring the shorter routes, those with smaller travel times and fairer routes
[0091] In some embodiments, steps 605 and 606 may by joined and executed in a single step. In some embodiments selection criteria described of the step 606 may be represented as weights and the final route determined by the routing process of the step 605.
[0092] It should be noted that in some embodiments, the order of some activities illustrated in the flowcharts C and B might be changed while other activities run in parallel or in other order than pictured, without changing the functionality of the system.
[0093] The foregoing descriptions of specific embodiments of the present invention have been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the invention to the precise forms disclosed, and obviously many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and its practical application, to thereby enable others skilled in the art to best utilize the invention and various embodiments with various modifications as are suited to the particular use contemplated. It is understood that various omissions, substitutions of equivalents are contemplated as circumstance may suggest or render expedient, but is intended to cover the application or implementation without departing from the spirit or scope of the claims of the present invention.

Claims

1. A Method of personalization of a traffic related route guidance and personalization of an information for each vehicle in real-time, the method comprising:
- collecting (500) a traffic related data in real-time from the plurality of traffic related data sources (400),
- analyzing and processing (501) the traffic related data by an information processing module (306) resulting in determining of current and predicted road network traffic parameters,
- determining parameters (502) of each vehicle, wherein said parameters are each vehicle's route, speed and heading, wherein the route of each vehicle runs from a current location of each vehicle to a target position of each vehicle,
- personalizing the traffic related data for each vehicle (503) depending on user set parameters of the user's device (250), values of the user device (250) sensors (205; 206), and remembered traffic behavior of the user,
- retrieving current road network traffic optimization parameters (504) by the routing module (312) where said road network traffic optimization parameters are calculated from the desired road network parameters for the whole traffic network (100), or the segments of the road traffic network (100),
- performing personalizing of an information (505) by the routing module (312) for each vehicle depending on the current road network traffic optimization parameters from step (504) and the current road network traffic parameters from step (501),
- selecting a set of personalized information and sending (506) said set to each vehicle, and
- continuously monitoring the traffic related data, parameters of each vehicle and current road network traffic parameters, wherein depending on a change of any of said data and parameters, the set of personalized information is changed and resented to all, or to some of said vehicles.
2. The method according to claim 1, wherein analyzing and processing (501) the traffic related data comprises of any combination of steps including converting said data to a standard set of measurement units, linking of said data to other traffic related data or aggregating said data received from the plurality of traffic related data sources (400) and forming additional traffic related data, aggregating the plurality of sensor data of individual vehicles, nearby to each other and traveling on the same road segment in the same direction and determining from said data the current road network traffic parameters or the numeric influence on the rate of change of said parameters.
3. The method according to claim 2, wherein determining the current road network traffic parameters or numeric influence on rate of change of said parameters comprises directly using the collected traffic related data from step (500) and inferring or calculating said parameters based on the traffic related data.
4. The method according to claim 3, wherein converting the collected and calculated traffic related data to presentable information is performed, forming the personalized information which can be displayed to driver on user devices (250) in textual, audio, map and picture format and assigning collected and calculated information to the traffic road network segments stored in the traffic network map database (305), where said information relates to the said segment.
5. The method according to claims 1 to 4, wherein personalizing of information for each vehicle to achieve the desired road network parameters further comprises calculating the change of the current and predicted traffic parameters required to achieve the road network traffic optimization parameters, retrieving calculated information created initially by the step (501) and further personalized by the step (503) and selecting the set of the personalized information by selecting and modifying collected and calculated personalized data.
6. The method according to claim 5, wherein the selected set of personalized information for each single vehicle is further personalized by omission of some information from the selected set of said information, modification of delivery or display time of some information from the selected set of personalized information and modification of the set of personalized information, including giving or omitting explicit instructions of expected driver actions, modifying the priority of information, modifying the method of display of information to the drivers and other modification which may have an effect on the driver behavior.
7. The method according to preceding claims, wherein calculating an effect of sending said personalized information to the driver on the current and future road network parameters is performed, where the calculated effect minimizes the difference between the current and desired values of the road network parameters.
8. A method of calculation of a personalized route guidance for a vehicle, the method comprising:
- receiving (600) a routing request from the vehicle, wherein the route runs from a current location of the vehicle to a target position of the vehicle,
- determining (601) the current location of the vehicle, collecting the traffic related data in real time (602) from the plurality of traffic related data sources (400), analyzing said locations and data (603), retrieving current road network traffic optimization parameters (604) by the routing module (312),
- calculating (605) a set of routes for the vehicle depending on the real-time traffic related data resulting from the steps (602, 603), - evaluating (606) the set of calculated routes and selecting among said set a personalized route, where the personalized route is affected by the road network traffic optimization parameters from the step (604) and the current vehicle's distance and travel time to the target destination,
- sending (607) the personalized route data to the vehicle,
- monitoring (608) the real-time traffic data, the vehicle's current location and the road network traffic optimization parameters, and
- selecting a new personalized route from the set of calculated routes, or repeating the steps (601) to (606) resulting in a new personalized route, depending on the change of the realtime traffic data, the vehicle's current location and the road network traffic optimization parameters, and sending the new personalized route data to the vehicle.
9. The method according to claim 8, wherein determining (604) road network traffic optimization parameters in real-time for each of the set of allowed routes, where the road network traffic optimization parameters are determined as a function of inferred, scheduled, historical and predicted traffic related data on traffic flow, traffic distribution within the road network, traffic speed, and travel times, or any combination or thereof.
10. The Method according to claim 8, wherein the real-time traffic related data are dependent on events such as traffic density and speed, travel times, traffic jams, slowdowns, collisions, incidents and road work information, warnings and limitations from static and dynamic road signs, state of traffic lights, camera video streams, incidents detected based on analysis of camera video streams, weather information, manually created events by the system administrators or vehicle drivers and any other traffic related or traffic affecting data.
11. A system for personalization of traffic related route guidance and personalization of an information for each vehicle in real-time, the system comprising a traffic information and route server TIRS (350), a user device (250) at each vehicle, the user device (250) is capable of sending values of the user device sensors to the TIRS (350) and to receive from the TIRS (350) a personalized information which can be displayed to the driver's user device (250), and a plurality of traffic related data sources (400) available within a road network (100), wherein the system is configured to collect a traffic related data in real-time, to analyze and process the traffic related data, to receive parameters of each vehicle in real-time, and retrieve current road network traffic optimization parameters, wherein the system, under control of the traffic information and route server TIRS (350), is configured to personalize information for each vehicle depending on the current traffic related data, current parameters of each vehicle and current road network traffic optimization parameters, wherein the system is configured to send the personalized information to each vehicle in realtime.
12. The system according to claim 11, wherein the personalized information sent to each vehicle is dynamically changed depending on the change of traffic related data, parameters of each vehicle and road network traffic optimization parameters in real-time.
13. The system according to claims 11 to 12, wherein the user device (250) sensors are at least location sensors (205) and acceleration sensors (206).
14. The system according to claims 11 and 13, wherein the system is configured to carry out the computer program running on the TIRS (350) for carrying out the method of claims 1 to 7.
15. The system according to claims 11 and 13, wherein the system is configured to carry out the computer program running on the TIRS (350) for carrying out the method of claims 8 to 10.
PCT/EP2016/025068 2016-06-30 2016-06-30 System and method for creation and delivery of personalized traffic and route information WO2018001444A1 (en)

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