TWI720956B - Behavior-focused active demand management system - Google Patents

Abstract

Systems and methods for providing incentives for the public to travel during time windows and routes that help alleviate traffic congestion. The systems described herein include at least five components: a computer server software system that includes various algorithms and database sub-systems; a mobile device application, an agency-oriented software to help manage the traffic, an enterprise-oriented software to help manage the employee travel, and a merchant-oriented software to help attract customers and increase sales. Generally, a user may enter an origin, destination, and preferred time of travel for an intended trip into the mobile device application, which transmits the information to a remote server. The server computes recommended departure times and routes for the trip and provides the user with available incentives for traveling the route at one or more departure time windows. The user's mobile device transmits GPS data to the server, which allows the server to verify whether the user has traveled the route during the specified time window. If so, the server then provides the incentive to the user via the user's mobile device or through

Description

Method and system for active traffic demand management and behavior induction

The present invention relates to a system and method for active traffic management, in particular, it uses historical traffic information, real-time traffic conditions, traffic service information and user-selected departure time, travel route, alternative destination and travel mode to actively manage , Coordinate the traffic demand, and finally achieve the system and method to reduce the degree of traffic congestion.

The following description will be useful for understanding the present invention, but the prior art or any reference information related to public documents provided below is not meant to protect the present invention.

Vehicle traffic congestion refers to a situation that occurs when traffic networks such as highways increase usage. It is characterized by low speed driving, longer driving time, increased vehicle waiting in line, and reduced vehicle fuel efficiency. The more common traffic congestion refers to when the traffic demand is quite large, the number of vehicles exceeds the load of the road, and the mutual influence of the vehicles will cause the traffic flow through the satin of the road to decrease per unit time, which causes traffic congestion. . When the demand exceeds the carrying capacity of the road, traffic congestion will occur, and when there is a situation where the vehicle stops completely for a period of time Time is the so-called traffic jam.

Generally speaking, when a traffic jam occurs, the space demand generated by passengers/passengers is greater than the traffic capacity of the road, that is, the saturation of the road is higher. In the current experience, a large proportion of traffic congestion is caused by purely increasing demand for transportation, and the rest are caused by factors such as traffic accidents, road works and weather changes.

There are also many attempts to solve traffic congestion, including adding more roads, widening roads, increasing traffic control, providing employees with flexible working hours, encouraging shared rides, providing instant traffic monitoring services and toll highways. However, these solutions have one or more shortcomings, including their effectiveness, feasibility, sustainability and cost issues.

According to the above requirements, the present invention provides a system and method, and provides incentives to enable passengers to select the departure time, travel route, destination, and travel mode recommended by the system in the itinerary, so as to effectively alleviate congested traffic conditions.

The present invention proposes an active traffic demand management system, including mobile application software, computer software server system, a traffic management software for government departments (government software), an enterprise-oriented information management software (enterprise software), and a business-oriented management software Information management software (merchant software). These modules together constitute the active traffic management method and system solution protected by this patent. Among them, the mobile application software system is executed on the user's mobile device. The computer software server system is used to communicate with mobile applications and includes travel time Prediction module, path calculation module, reward providing module, verification module, destination recommendation and prediction module, travel chain planning module, active traffic early warning module, and special event management module. The travel time prediction module dynamically predicts the travel time of the road traffic network in the next period of time based on the laws in historical traffic information, combined with real-time traffic conditions and event information that have an impact on road traffic. The route calculation module calculates the route between the departure place and the destination based on multiple departure times close to the priority departure time selected by the user. When the user departs from the departure place to the destination, Each departure time corresponds to the time interval from departure to arrival of the user. The reward providing module is used to determine the rewards that can be provided to the user at each departure time. The verification module receives location information from the mobile application software, and confirms that the user has departed from the place of departure within the selected departure time based on the location information, and at least part of the journey after departure is carried out along the route. Destination recommendation and forecasting module refers to that the destination selected by the user is a popular attraction (such as tourist attractions, theme parks, etc.), and its passenger flow demand is close to saturation, thereby reducing the experience of this trip, or When the user actively requests to browse the selectable destinations, based on the passenger flow of the destination, the traffic conditions on the road, the discounts and rewards of each destination, the user's travel history and lifestyle, etc., intelligently recommend better Destination options to enhance the system function module of the travel experience. The travel chain planning module allows users to make unified plans for the next multiple trips on the mobile device. The active traffic early warning module can actively and intelligently extract emergencies that may be related to the user's travel, and send early warning information to the user in time. The special event management module can receive special events that affect the traffic input by the system operator, and perform Traffic modeling analyzes the impact of this event on road traffic conditions. In addition, government users can monitor dynamic traffic conditions, hot spots, and traffic impacts of emergencies in real-time on their traffic management software. At the same time, the traffic information resources owned by the government, including municipal construction, emergencies, sports competitions, group activities and other information can also be shared back to the system through this platform. Enterprise users can view information about employee registration, use of this mobile terminal application, etc. through their information management software. Through the report automatically generated by the system, managers can see data such as how many employees use mobile terminal applications, change departure time, flexibly commute to and from get off work, how much time they have saved, and how much carbon dioxide they emit during a certain period of time. In addition, through this system, companies can invest in rewards and specify that this reward can only be redeemed by employees of the company. Companies can also promote mobile terminal applications to employees through this platform. Business users can see how many potential users pass by the business area and their distribution in time and space on their information management software. Merchant users can use this software to attract users to spend through a series of promotional activities, such as the distribution of discount coupons and vouchers. Merchant software will also automatically generate reports, allowing operators to intuitively see user consumption and the effects of promotional activities in the past period of time.

According to an embodiment of the present invention, the driving time prediction module in the active traffic demand management system is used to analyze historical data and real-time traffic data, and the reward providing module is based on the minimum impact on the route or the traffic system caused by the departure time To select rewards, and the reward providing module dynamically adjusts the distribution of rewards based on historical data, real-time data, and the departure time selected by other users. The user’s preferences and the user’s lifestyle information are taken into consideration.

According to an embodiment of the present invention, the verification module in the active traffic demand management system receives location information from the global positioning system of the mobile application, and analyzes the location information received from the global positioning system to confirm that the user is selected Enter the location close to the departure place for the departure time, and confirm that the user has successfully completed the selected part of the scheduled route.

According to an embodiment of the present invention, the route determination module in the active traffic demand management system calculates one or more optimal driving routes between the departure place and the destination during multiple departure times, and when When there is additional traffic volume on the route, each departure time takes into account the additional travel time caused by the additional traffic volume on the route.

According to an embodiment of the present invention, the active traffic demand management system further includes a load balancing module, a road condition monitoring and warning module, and a user behavior analysis module. The load balancing module is used to measure the route and departure journey time pre-selected by other users. The road condition monitoring and warning module is used to confirm accidents on the route and send messages to notify users of the accidents. The user behavior analysis module receives the user’s behavior information from the mobile application and analyzes it based on the behavior information. The reward providing module adjusts and provides it to the user based on the behavior information analyzed by the user behavior analysis module. Rewards.

The present invention also proposes a calculation method for monitoring traffic flow, which includes receiving the departure place and destination and priority travel time from the user; at least one route is calculated between the departure place and the destination, and the user is based on the mobile device’s cross Communication information, when the system is scheduled to travel along a certain route at a certain time, that is, when there is additional traffic volume on the route, the additional travel time caused by the additional traffic volume is taken into account; the calculation is close to the priority travel time Multiple departure times, when the user wants to start from the place of departure and follow the route to the destination, recommend the best route corresponding to each departure time; calculate the reward provided to the user according to each departure time; send and display The route, each departure time and the rewards related to the route and each departure time; a selected route and a selected departure time and corresponding rewards are received from the user; at least part of the user’s itinerary is driving along the route, And receive location information from the user; confirm that the user has arrived at the destination within the selected departure time, and at least part of the itinerary is from the departure place to the destination along the route; and send the reward to the user.

According to an embodiment of the present invention, the calculation method for monitoring traffic flow further includes calculating a preset travel time from the place of departure to the destination according to each departure time, wherein the preset travel time includes analyzing historical data of the route and real-time route data. Traffic data; confirm accidents on the route, and send messages to notify users of the accident; and provide users with alternate routes, and receive the alternate route selected by the user from the user.

According to an embodiment of the present invention, the steps of calculating at least one route between the departure place and the destination and calculating a plurality of departure times close to the priority travel time in the calculation method for monitoring traffic flow further include The departure time of at least one route and itinerary previously selected by other users is taken into consideration.

According to an embodiment of the present invention, the step of calculating the reward provided to the user according to each departure time in the calculation method of monitoring traffic flow includes predicting the minimum impact of the departure time on the degree of congestion of the route; The time difference between the priority travel time and the priority travel time is taken into consideration; the user’s preference or life style information is taken into consideration; the reward is dynamically adjusted based on historical data, real-time traffic data and the departure time selected by other users; Receive behavioral information, and adjust the rewards provided to users based on the analysis results of the behavioral information.

According to an embodiment of the present invention, in the step of receiving location information from the user in the calculation method for monitoring traffic flow, the location information is received from the global positioning system of the user’s mobile device, and the user is confirmed to be selected The departure time is from the place of departure, and it is confirmed that the user has arrived at the destination within the selected departure time, and at least part of the itinerary is from the place of departure along the route to the destination. The steps are analyzed from the world The location information received by the positioning system confirms that the user enters the location close to the departure place at the selected departure time, and confirms that the user has successfully completed the selected part of the scheduled route.

According to an embodiment of the present invention, the destination recommendation and prediction module combines the destination recommendation function with the prediction function, eradicating the user’s mobile device use record and the user’s travel history, and predicting the user’s potential Travel destinations, or receive the destination input by the user and intelligently analyze and recommend similar alternative destinations, and combine the traffic, passenger flow, rewards and other information around the destination to actively and orderly guide the user’s travel .

According to an embodiment of the present invention, the recommendation function in the destination recommendation and prediction module refers to that the destination selected by the user is a popular scenic spot (such as a tourist attraction, a theme park, etc.) and its passenger flow demand is approaching Saturation, or when the user actively requests to browse alternative destinations, comprehensively analyze and compare the crowdedness of the destination, the degree of congestion of the traffic arteries leading to the destination, other alternative modes of travel except self-driving, and alternative modes of travel The above information and the comprehensive recommendation level of the system for each destination are displayed to users, so as to provide positive and reasonable guidance to the demand for passenger flow. Avoid the situation where everyone flocks to the same popular destination due to information asymmetry or uncoordinated users, and ultimately improve road traffic conditions, destination passenger flow management, and enhance user travel experience .

According to an embodiment of the present invention, the prediction function in the destination recommendation and prediction module means that the system can mine the user behavior data stored in the system according to the record of the user's use of the mobile terminal application, and take the initiative as an example. Users provide various services and actively guide users to relieve traffic congestion. Based on the user's travel records, the system will actively predict where the user is most likely to go at a certain moment based on the user's location and other information, and display these predicted addresses on the mobile terminal application. The user only needs to click on the icon on the mobile terminal application to conveniently plan the path.

According to an embodiment of the present invention, a user can plan a travel chain through a mobile terminal application. That is: the user can enter multiple destinations that they want to reach, and the mobile terminal application will automatically create multiple travel plans in sequence to form a A travel chain. The destination of the previous travel plan will automatically become the starting point of the next travel plan, and the departure time of the next travel plan will also depend on the arrival time of the previous travel plan. This allows the user to conveniently enter multiple destinations at once and plan travel.

According to an embodiment of the present invention, the active traffic early warning module refers to the results of data mining. The system will not only actively predict where the user may go next, and which destinations the user will recommend, but also predict the user Possible paths and areas to go through. If some incidents including severe weather, traffic emergencies, serious congestion, etc. occur in this route or related area, the system will actively push warning information to users to remind them to change their travel plans or prepare in advance. In other words, even if the user is not using a mobile terminal application, the system can still actively calculate information that may be relevant to the user, and push the information that may be of interest to the user.

According to an embodiment of the present invention, the system's special event management system allows multiple types of users, including system users, government departments, and ordinary users, to report and input various traffic-related emergencies in the system. Once the system administrator confirms this information, the system's traffic event prediction system will be triggered. The built-in traffic model and algorithm of the system will predict the impact of the event on the road traffic network, the duration, and the spatial range of the impact, so as to be more accurate Provide technical support for users’ travel planning.

100‧‧‧Active Traffic Demand Management System

104‧‧‧Booking process

108‧‧‧Verification Process

112‧‧‧Send transaction mechanism

120‧‧‧Data Search Engine

122‧‧‧Real-time data

124‧‧‧Historical travel time data

130‧‧‧Online user transaction execution engine

132‧‧‧Event travel time prediction algorithm

136‧‧‧The path algorithm of the least marginal cost related to time

140‧‧‧Reward providing algorithm

144‧‧‧Time and space load averaging algorithm

148‧‧‧Reward generation and accounting algorithm

150‧‧‧Online road condition monitoring and user alarm module

152‧‧‧Online verification engine

156‧‧‧Update engine for driving time of link section

160‧‧‧Vendor transaction engine and accounting database

164‧‧‧User Behavior Analysis Engine

170‧‧‧Marketing Intelligence Engine

172‧‧‧Preferences or lifestyle information

176‧‧‧Create Account

180‧‧‧Estimated event travel time

Route 184‧‧‧

188‧‧‧Reward

190‧‧‧Enter the departure place and destination and browse the departure time

192‧‧‧Select departure time

193‧‧‧Browse the destinations recommended by the system

194‧‧‧General computer

195‧‧‧Web Application

196‧‧‧Mobile device

197‧‧‧Mobile App

198‧‧‧Global Positioning System Satellite

250‧‧‧Departure time option display function

252‧‧‧Departure time

254‧‧‧Estimated driving time

256‧‧‧Reward

270‧‧‧Departure time selection window

272‧‧‧Departure time

274‧‧‧Estimated driving time

280‧‧‧Route selection display window

Route 284A‧‧‧

Route 284B‧‧‧

Route 284C‧‧‧

286‧‧‧window

290‧‧‧Destination location

292‧‧‧Departure location

300‧‧‧Reward selection window

304‧‧‧Voucher

308‧‧‧Coupon

12‧‧‧Computer device

21‧‧‧Processing unit

22‧‧‧System memory

23‧‧‧System bus

24‧‧‧Read Only Memory

25‧‧‧Random access memory

26‧‧‧Basic Input/Output System

27‧‧‧Hard Disk Drive

28‧‧‧Disk Drive

29‧‧‧Removable Disk

30‧‧‧Optical Drive

31‧‧‧CD

32‧‧‧Hard Disk Drive Interface

33‧‧‧Disk Drive Interface

34‧‧‧Optical Disk Drive Interface

35‧‧‧Operating System

36‧‧‧Application

37‧‧‧Other program modules

38‧‧‧Program data

40‧‧‧Keyboard

42‧‧‧Pointing device

46‧‧‧Serial port interface

47‧‧‧Display

48‧‧‧Video Adapter

49‧‧‧Remote Computing Device

50‧‧‧Storage device

51‧‧‧Local Area Network

52‧‧‧Wide Area Network

53‧‧‧Adapter

54‧‧‧Modem

Figure 1A is a schematic diagram of the upper part of the module of the active traffic demand management system of the present invention.

Figure 1B is a schematic diagram of the lower part of the module of the active traffic demand management system of the present invention.

Figure 2A is a schematic diagram of the departure time option display function of the present invention.

Figure 2B is a schematic diagram of the departure time selection window of the present invention.

Figure 2C is a schematic diagram of the route selection window of the present invention.

Figure 2D is a schematic diagram of the reward selection window of the present invention.

Figure 3 is a flow chart of the implementation steps of the active traffic demand management system described in Figures 1A and 1B according to the present invention.

Fig. 4 is a flow chart of the execution steps of the active traffic demand management system described in Fig. 1A and Fig. 1B according to the present invention.

Figure 5 is a schematic diagram of the hardware equipment and operating environment of the present invention to realize the active traffic demand management system.

The present invention relates to a system and method that provides incentives for people to choose the departure time, travel route, alternative destination and other travel modes recommended by the system to effectively relieve congested traffic conditions.

This disclosure provides an active traffic demand management system, including mobile application software, computer software server system, and a government agency-oriented transaction system. Communication management software, an information management software for enterprises, and an information management software for businesses.

The mobile application software is installed on a mobile device of a user.

The computer software servo system includes a path calculation module, a travel time prediction module, a reward providing module, a verification module, an emergency traffic impact analysis module, a load balancing module, a road condition monitoring and warning module, and user behavior analysis Modules, a travel chain planning module, a destination prediction and recommendation module, and an active warning module.

The emergency traffic impact analysis module includes systems that allow system operators, ordinary users, government traffic management departments, and other users to report and enter various traffic-related emergencies, group activities, traffic congestion and other information. The functional module dynamically estimates their impact on the road traffic network based on the various input events, including the traffic algorithm module of the impact range, duration, and degree of impact, and screens out the users affected by the traffic event.

The travel chain planning module includes a method module that allows the user to enter a series of destinations on the smart mobile terminal and automatically combine them into a dynamic travel chain. According to the multiple travel destinations input by the user, the system calculates the starting and ending points of each pair The method module for the optimal travel path between the two and the travel chain planning module and automatic travel chain planning module that automatically uses the user's last travel destination as the starting point of the next travel, and determines the start time of the next travel according to the arrival time of the previous travel. The destination of the user's last trip is taken as the starting point of the next trip, and the starting time of the next trip is determined according to the arrival time of the last trip.

The destination prediction and recommendation module includes one when the destination selected by the user is a popular attraction, and its passenger flow demand is close to saturation, which reduces the experience of this trip, or the user actively requests to browse alternative destinations , Take the initiative to recommend modules for other destinations, a display of passenger flow to other destinations, traffic conditions on the road, discounts and rewards for each destination, user travel records and lifestyle information, and intelligently recommend comparisons Good destination options to enhance the travel experience of the system function module, an algorithm module based on user usage records, travel trajectory and other information, for active data mining, prediction of the user’s possible travel destination and departure time, the system Recommend and predict the user’s travel destination, the possible departure time and the emergencies monitored by the system, actively determine the traffic information that may be related to the user’s travel, and take the initiative to identify the traffic information that may be related to the user’s travel. The method of traffic information is pushed to the user and presented through the smart mobile terminal, and the method module that receives the user's feedback on the pushed message and sends it back to the remote server.

Traffic management for government users (that is, the traffic management software of government departments) includes a software module that supports government departments to share historical traffic data, real-time traffic data, emergencies and other information with the system, and a support system Have historical traffic data, real-time traffic data, emergencies and other information shared back to the functional module of the government department, a function module that allows the government to view the traffic flow on the road traffic network in real time, and monitor the changes in the traffic flow in the future Functional modules, functional modules that allow government departments to implement a series of active traffic management strategies, including closed roads, closed lanes, and no turning, etc., and the system is based on these new management policies. Slightly, a functional module that updates traffic flow prediction results and a functional module that pushes these traffic management strategies and the resulting changes in traffic flow to system users.

The information management system for enterprise users (ie, enterprise-oriented information management software) includes a software that supports companies to encourage and manage employees to participate in this active transportation system management system, a software that allows companies to invest in incentives to encourage employees to take measures to reduce departure time, and A functional module that restricts only employees of the company from being able to redeem enterprise investment rewards, a functional module that encourages employees to travel during peak hours and supports flexible commuting system management, and a functional module that encourages employees to travel during peak hours and coordinate their departure time To support the functional modules of traffic management at the entrance and exit of the enterprise park.

The information management system for merchant users (ie, information management software for merchants) includes a software that supports merchants to analyze the number of potential customers and their distribution in time and space through data mining based on active traffic management systems. Support merchants to carry out various promotions for potential customers and existing customers, and push these promotional information to the user's functional module and a functional module that accepts the user's use, redeem the rewards distributed by the system, and consumes at the merchant.

The present invention relates to a system and method that provides incentives for people to choose the departure time, travel route, alternative destination and other travel modes recommended by the system to effectively relieve congested traffic conditions. Here, the flow mentioned in the present invention refers to the flow of vehicles or pedestrians on the road, the flow of commercial transportation and cargo exchange, or the movement of passengers and people, and so on. The system of the present invention includes at least five parts: one includes various algorithms or modules Computer (computer) server software systems of modules and database sub-systems, mobile applications running on users' mobile devices (such as smart phones), a traffic oriented to government departments Management software (government software), a business-oriented information management software (enterprise software), and a business-oriented information management software (business software). Generally speaking, the user can input the origin, destination and preferred time of the scheduled itinerary into the mobile application, and the mobile application will send this information to the remote server System (remote server system, hereinafter referred to as "system"). The server will estimate one or more routes of this itinerary, and provide applicable incentives (available incentives) corresponding to each route at one or more departure times. The system can also recommend other travel destinations and modes of transportation to the user based on information such as traffic jams, or when the user actively requests it. For example, each time window or time frame is 15 to 30 minutes apart. In one embodiment, suppose the system wants to suggest the user to start at the time that can reduce the degree of traffic congestion, and the system will provide the user with the best reward corresponding to this time. For a predetermined itinerary, the user's mobile device can retrieve multiple time windows, and each time window has a reward from the system, and a preset route and time window created by the user later.

When the user actually creates the selected itinerary, the global positioning system (GPS) in the user’s mobile device will start to activate. At this time, the mobile device’s application will compare the received GPS location information ( GPS location information) and reserved route information (route information) to confirm whether the user has passed the selected path, or has traveled at least part of the selected path in a specific time window. Although the above comparison procedure can generally be performed by a mobile application, users can still selectively allow the application to send GPS location information to a remote server to receive additional real-time warnings and unexpected network outages. For example, route navigation in the event of an accident. After the itinerary is verified, the server will import the user's previously booked rewards into the user's account, and the system will notify the user through the user's mobile device or via email.

The algorithm included in the system is used to analyze one or more routes and the historical and real-time traffic data of each route, in order to predict a route that can cause the least impact on the selected route. Affected departure time. It is understandable that if the departure time is unreasonable from the perspective of traffic congestion management, driving this specific route during these departure times can only get less rewards or even no rewards.

The algorithm included in the system is used to analyze one or more routes and the historical and real-time traffic data of each route, in order to predict a route that can cause the least impact on the selected route. Affected departure time. It is understandable that if the departure time is unreasonable from the perspective of traffic congestion management, driving this specific route during these departure times can only get less rewards or even no rewards.

For each route, the calculation method in the system is to dynamically adjust the reward based on historical data, real-time data, and the currently reserved departure time. distribution. When the number of users using this system is increasing, the above-mentioned dynamic adjustment mechanism will be particularly advantageous, which helps to ensure that there will be no independent scheduled departure time and scheduled route overloaded during these departure times. , Thereby increasing the degree of traffic congestion.

Figures 1A and 1B show block diagrams of an active traffic and demand management system 100 (active traffic and demand management system, or "system 100" for short) in an embodiment of the present invention. Figure 1A is the upper half of the block diagram, which shows the predetermined process 104 of the system 100, and Figure 1B is the bottom half of the block diagram, which shows the verification process 108 and the post transaction process of the system 100. ) 112. In addition, the hardware environment and operating environment of the system 100 according to an embodiment of the present invention are shown in FIG. 5 and described below.

As mentioned above, the system 100 includes a mobile device application 197 (for example, an application for a smart phone). The mobile application 197 is operated on a user's mobile device, such as an iPhone® mobile phone, Android® Mobile phones or Windows Phone® phones, tablet phones, etc., and various calculation methods and software modules are executed on one or more remote server systems. In addition, although it is not shown in the drawings for the sake of clarity, it is understandable that the software module and other components of the system 100 can be communicatively connected with each other, as described below. The system 100 may also include a general web application 195 to allow users to log in through a conventional computer 194, such as a notebook computer, a desktop computer, or a tablet computer. System 100.

During operation, the mobile application 197 of the system 100 allows the user to select a departure time (departure time window) and route between the departure place and the destination designated by the user. This procedure first requires the user to input the desired departure place, destination, and desired time of travel (preferred time of travel) to the mobile application 197. The mobile application 197 can send this information to the system 100. Based on this information and historical information, the system 100 predicts the required driving distance between a specific departure place and a destination in multiple future departure time intervals. The system 100 returns the predicted travel time to the mobile application 197, and each time interval can be 15 minutes, 30 minutes, or other time intervals.

In the process of operation, the system can also display related information about alternative destinations and alternative travel modes when certain implementation logic is satisfied, or when the user sends an active request through a mobile device (193). For example, when the user tells the system that he wants to travel to Yilan, and the system has detected that Yilan is overcrowded during the holidays, and the road to Yilan has been abnormally blocked, the system can collect information about other tourist attractions around the user. Display, supplemented by corresponding rewards or discounts, to encourage some users to turn to destinations with relatively better traffic conditions, so as to achieve the purpose of balancing passenger flow and reducing traffic jams.

For each departure time, the system 100 provides one or more (for example: one to three, or even more) different routes through different expressways or major arterial roads. For each provided route, the system 100 can provide a set of applicable rewards and the rewards will be different due to different choices of the route and the departure time. One Generally speaking, the rewards provided can be provided by an entity (entity) to provide discounts or discounts (entity units such as retailers (retailers), service providers (service providers), manufacturers (manufactures) or municipal units (municipalities) )). When the user uses his mobile device 196, the user can first view the route provided by the system 100, the predicted travel time, and the rewards provided by the system 100 through the mobile device 196, and establish the rewards for departure at a specific departure time by agreeing to and Take the route with the reward. Then, in order for the system 100 to give the user the previously agreed reward, the user must complete the agreed driving choice and route (or a partial route sufficient for verification).

The system 100 confirms that the user has completed the journey in a two-step method. As described further below, the mobile application 197 is executed on the user's mobile device 196 at the previously preset departure time to start communication with the GPS satellite 198 Communication connection. When the user is in the middle of the journey, the mobile device 196 will confirm whether the user has entered the preset route at the preset departure time in two ways. In one embodiment, the mobile application 197 compares the GPS data and route information stored in the mobile device 196 in a preset process. In addition, based on the agreement with the user, the mobile application 197 can send GPS data to the system 100. If the user enters the agreed route within the agreed time, the first step of the confirmation process is completed, and the mobile application 197 will continue to perform internal checking (perform internal checking) or communicate with the system 100. When the user follows Drive along the designated route. Once the system 100 confirms that the user has completed the specified route or at least part of it can be verified as being in the specified route (but Not necessarily all), then confirm that the second step of the procedure has been completed.

The user must successfully go through the first step and the second step in the aforementioned confirmation procedure in order for the system 100 to fully verify that the user has completed his previous preset. After the system 100 confirms that the user has completed the preset route, the system 100 will send the agreed reward to the user’s account through the mobile device program 197 via the email address set by the user, and the reward can be based on The instructions provided to the user at the beginning to exchange. More details are discussed below.

Please continue to refer to FIG. 1A and FIG. 1B. The system 100 includes multiple algorithms or multiple sub-modules to realize its functionality. Each sub-module is detailed below. It is understandable that these one or more sub-modules can be logically or physically connected in at least one or more ways, and their modules and other components can be connected to each other in communication to perform this The function described at the place. In addition, some embodiments will include all sub-modules or a subset of these sub-modules.

The system 100 includes a data-mining engine 120, which is used to receive and analyze historical traffic data, and prepare the data into a format suitable for real-time query, data processing, and route planning. In one embodiment, for each historical period (such as the past year or the past five years, etc.), the historical traffic data is based on a road with an average speed of 15 minutes as each connected section (such as a highway). Between the points defined above). This data can include the traffic volume on a specific highway. The original historical data is used to capture the statistical data of time-varying driving time (such as average value or standard Accuracy). Because it may be affected by seasonal factors, in order to improve the accuracy of the forecast, the noise of the preset driving time on a known day (such as the fifth Friday in September or a specific holiday) data) filter. In addition, when in order to improve the accuracy of path calculation, a variable temporal discretization scheme can be used to reduce the requirements for data storage, as described below.

The data search engine 120 further includes a capacity discovery algorithm, which uses sequential vehicle speed data to calculate the capacity of the road section. The carrying capacity exploratory calculation method uses connected sections and time to estimate the sequential speed data of each road. The available capacity index (ACI) is used to define and calculate the current traffic flow status of each connected section (using real-time data) and estimate the residual capacity between the theoretical capacity in the connected section (residual capacity) capacity). The loadable index is stored in each link section and can be used by algorithms.

The system 100 further includes an online user transaction execution engine (TEE) 130, which has several sub-modules or several algorithms, including an experienced travel time prediction algorithm 132, and time Related M-time-dependent minimal marginal cost path algorithm 136 (or route determination module), incentive offering algorithm 140, time and space Spatio-temporal load balancing algorithm 144 and reward generation and accounting Algorithm (incentive generation and bookkeeping algorithm)148. The following describes the sub-modules of each online user transaction execution engine.

When the user inputs the departure place and destination through the mobile device 196, the mobile application 197 transmits the departure place and destination information to the online user transaction execution engine 130 and the block 90. Then, for multiple future departure times that exceed one or more routes, the online user transaction execution engine 130 uses the event travel time prediction algorithm 132 to return the estimated event travel time between the departure place and the destination. experienced travel time) 180. The event travel time 180 refers to the estimated time that the user travels on one of the routes during a specific departure time. Therefore, the future conditions must be considered for each departure time. For this module, the event travel time estimation algorithm 132 uses historical travel time data 124 and real-time data 122 as input values, and for each historical travel time The weights of the data 124 and the real-time data 122 are changed according to one or more factors. For example, the amount of time is entered into the future event travel time estimation algorithm 132 to estimate the travel time. For example, the real-time data 122 may be related to the travel time expected by the user, and when the prediction is generated, it will become closer in time to the travel time expected by the user. In one embodiment, the real-time data 122 and/or the historical driving time data 124 may be provided by a third-party provider, such as INRIX, Inc., TomTom, Intl or Traffic.com, and so on.

In addition to the way the user manually enters the destination, the system will also actively combine the user's historical travel records, intelligently analyze the user's activity patterns and recommend the destination they may want to go to. The user sees these items on the mobile device You can easily plan your journey with just one click. On the other hand, when the destination selected by the user is a popular scenic spot (such as tourist attractions, theme parks, etc.), and its passenger flow demand is close to saturation, which reduces the experience of this trip, or the user actively requests to browse and choose At destinations, the system will also combine destination passenger flow, traffic conditions on the road, discounts and rewards for each destination, user travel records and lifestyle, etc., intelligently recommend better destination options Improve the travel experience. This destination recommendation and prediction function of the system not only frees users from the trouble of entering addresses in the user experience, but more importantly, it can balance traffic demand on the road traffic network, and remove some travelers from the most crowded destinations. Guide to places where the passenger flow density is relatively low, thereby reducing the degree of traffic congestion, and also improving user satisfaction when traveling.

When the user browses and or selects an expected departure time, the time-related minimum marginal cost roadshow algorithm 136 will generate one or more routes (hereinafter referred to as “M routes”) 184 and display them in the user’s actions装置196. The path algorithm 136 of the time-related minimum marginal cost calculates the M route and the departure time of each pair of departure and destination. The departure time is the total value of the minimum marginal cost route. The concept of marginal cost is that when additional traffic units are added to the incoming line, the unit travel time will increase. Therefore, for the route with the smallest marginal cost, that is, once the user specifies the route, the cost of the existing user traveling the route is minimized. This calculation method can ensure that users can achieve the least cost by choosing this route. The best least marginal cost route is calculated by the time-related least marginal cost path algorithm 136, where M is the system Set parameters. For example, if M can be 3, more than three routes will confuse the user. In another embodiment, M can be set to 3, and there may be more than 3 routes for the user to choose. Of course, in other embodiments, the number of routes is not limited to 3, which is also It can be a parameter less than 3 or greater than 3.

The reward providing algorithm 140 is used to select a set of appropriate rewards 188, and present the rewards 188 to the user through the mobile application 197. Each reward 188 will be linked to the known departure time and route. In other words, after the user selects the departure time and route, the block 192 shows "Select Departure Time". If the user chooses a different departure time and/or a different route, the user will be rewarded as well. Will be different. If the departure time and route selected by the user are conducive to achieving the goal of managing traffic congestion, the reward providing module 140 will provide a higher-value reward to the user. In addition, the reward providing module 140 can also be referred to as the time-space carrying capacity average algorithm 144, which is described in detail below. The description is that the user's previously selected departure time is reserved, and the user of the system 100 can adjust it accordingly. The load level of the traffic flow to avoid overloading the traffic network.

In another embodiment, the reward provided by the reward providing module 140 can be linked to the preferences or life style information 172 of the user stored in the system 100. The user’s preferences or lifestyle information 172 can be obtained by (1) asking the user about the user’s lifestyle information during the registration process, such as block 176 and or (2) cooperating with other vendors (e.g. Amazon , Amazon®) to know the user’s preferences or purchase wish list (wish lists), and provide rewards or coupons with clear goals and attractiveness.

Please refer to FIG. 2A. FIG. 2A shows the departure time selection screen display 250 of the mobile application 197 running on the mobile device 196. As shown in the figure, the system 100 provides the user with a list of departure time (departure time windows) 252 to estimate the estimated travel times 254 of each departure time 252 in the previously selected route and provide rewards for each departure time. 256. The estimated travel time 254 may include average values, minimum values corresponding to multiple routes (for example, 3 routes), or other statistical measurement values of multiple routes. In this embodiment, the longest driving time (for example, the most congested time) occurs when the departure time 252 is 7:45-8:00 in the morning and 8:00-8:15 in the morning. At these departure times 252 will not provide any rewards. Furthermore, when the estimated travel time 254 is reduced (for example: no congestion time), a better reward 256 can be provided to attract users to choose to start when the route is least congested, so as to avoid overloading the capacity. Traffic flow occurs on the selected route. It is understandable that, in some embodiments, the user may have various combinations of departure time, route, and rewards to choose from.

Please refer to Figure 2B, Figure 2C and Figure 2D. Figures 2B, 2C, and 2D respectively illustrate the continuous screen displays 270, 280, and 300 of the mobile application 197 running on the mobile device 196, which are illustrated in another embodiment and allow the user to select the departure time , Routes and rewards. Figure 2B illustrates the departure time selection screen 270, which provides The department (departure time windows) 272 lists and the estimated travel times (estimated travel times) 274. As described above, the estimated travel times 274 may include the average value, the minimum value, or other statistical measurement values of multiple routes.

Once the user selects a departure time, a route selection display screen 280 will be provided to the user, as shown in Figure 2C. In this embodiment, the route selection display window 280 includes three routes 284A-284C for the user to travel through the starting position 292 and the destination position 290. When the user touches or activates one of the other routes 284A-284C, a window 286 pops up to allow the user to select the activated route or the marked route. In this embodiment, the user has selected the third route 284C (or route 284C).

After the user selects a specific route, an incentive selection screen 300 is displayed, as shown in FIG. 2D. The reward selection window 300 may provide the user with one or more options to select coupons 304, coupons 308, or other rewards, such as different products, services, and the function of adding a personal account (account enhancement features) and so on.

Please refer to Figure 2E. When the destination selected by the user is a popular scenic spot (such as a tourist attraction, a theme park, etc.), the destination recommendation module window will be displayed. The destination recommendation window will comprehensively analyze and compare the crowdedness of the destination's passenger flow, the degree of congestion of the traffic arteries leading to the destination, other alternative modes of travel other than self-driving, the time cost of alternative modes of travel, the destination manager or surrounding businesses Provide information such as rewards or discounts, and display the above information together with the system's comprehensive recommendation level for each destination to the user, so as to provide a positive and reasonable guide to the demand for passenger flow. Avoid the situation where everyone flocks to the same popular destination due to information asymmetry or uncoordinated users, and ultimately improve road traffic conditions, destination passenger flow management, and enhance user travel experience . For example, in Figure 2E, starting from the user’s city, destination B has become a popular tourist destination due to its moderate distance and beautiful scenery, especially on holidays, the main traffic route from the starting city to destination B It will become abnormally clogged. Relatively speaking, the passenger flow density of the other destinations is low, and the park management or the merchants provide corresponding discounts or incentives to attract users to come to spend, the travel time to these destinations or alternative travel methods Travel time is also within the acceptable range. Therefore, the system will recommend destination D, destinations A and B to varying degrees. The system hopes to influence the user's travel destination and travel mode selection through this information display and application rewards, so as to reduce the degree of road traffic congestion and objectively help users improve the travel experience.

The purpose of the time-space carrying capacity averaging algorithm 144 is to avoid the traffic flow being so large that it is allocated to the same departure time and/or the same route, so that the specific departure time/route will not be overloaded. Because for different future departure times and rewards for each user at different times, the user needs to consider that the previously set default departure time is earlier than the current departure time considered by the current user in the known time . This is because using the same route at an earlier departure time may affect the later departure time. Similarly, the current user may affect the earlier scheduled departure time. In this case, the time-space bearing average algorithm 144 can calculate and track the estimated travel time to ensure The previously preset departure time will not seriously affect the preset departure time of subsequent users.

Next, the reward generation and accounting algorithm 148 in the online user transaction execution engine 130 will be introduced. The user agrees to select a certain route at a specified departure time, such as block 192, "this default value will be stored in the online user transaction execution engine 130 and it will be marked as "active". When the user completes the previously agreed route, this default value can be changed to other status such as "completed" (completed), or the user did not actually complete the preset itinerary and changed to "failed". Transaction status The data will be stored and analyzed to learn the behaviors and preferences of each user. The reward generation and accounting algorithm 148 also needs to ensure the validity of the reward provided by the contract with the reward provider.

As shown in FIG. 1B, the system 100 further includes an online roadway condition monitoring and user alert module 150. When an unplanned or unexpected accident occurs in the transportation network, and the event is not known by the system 100 when the user makes a reservation through the system 100, if the system 100 determines (1) the accident will be Seriously affect the driving time of the user on the selected route and/or (2) The user has settings in the user's preferences or life style information 172 and wants to receive real-time alerts of accidents that may affect him or her , The system 100 will alert the user with the alarm module 150.

In this embodiment, the online road condition monitoring and user alarm module 150 will periodically inquire the real-time network condition data providing module 122 for real-time road condition data, and new accidents may occur. The online road condition monitoring and user alarm module 150 can then call and regularly scan existing appointments, And update the travel time of each route with the existing preset. If the increased driving time exceeds a certain threshold, the online road condition monitoring and user warning module 150 will start a warning program to allow the user (1) to re-evaluate whether to drive at the same departure time The same route, or (2) Re-evaluate one or more new departure times and routes. The user can choose whether to keep the originally agreed-upon reward, route and departure time, or choose a new reward according to the newly selected departure time and route.

The system 100 further includes an online validation engine (VLE) 152. It can be known that a scheduled itinerary needs to be verified before the system 100 can give the corresponding reward to the user. In order to achieve the above effects, a two-step verification mechanism (validation process) will be necessary. Before the departure time arranged by the user, the mobile application 197 starts to communicate with the GPS 198. When the user is driving on the route, the mobile device 196 will use two steps to confirm that the user enters the predetermined route at the designated departure time. As described above, in one embodiment, the mobile application 197 compares the satellite positioning data received from the global positioning system 198 with the route information stored in the mobile device 196 in the process. In addition, according to the agreement with the user, the mobile application software 197 will transmit global satellite positioning data to the system 100. When the user enters the designated departure time and the corresponding route, the first step of the verification mechanism is completed. Then, the mobile application software 197 will continue to perform internal inspections or communicate with the system 100 to confirm whether the user has a route. Travel along the journey, when the system 100 confirms that the user successfully has enough part to drive on the predetermined route (not All needs to be completed), then the second step of the verification mechanism is considered complete. In other words, if the user does not drive a sufficient part of the predetermined route, the online verification engine 152 will mark the final status of the reservation as "invalidated".

After the first step of the verification mechanism is completed, the user must continue to drive along the pre-planned route to allow the online verification engine 152 to analyze the received GPS location data. When the user successfully completes the pre-planned route on the predetermined route, the online verification engine 152 will confirm that the second step of the above-mentioned verification mechanism has been completed. It should be noted that the online verification engine 152 will only confirm that the scheduled itinerary has been completed only after the two steps in the above-mentioned verification mechanism have been completed.

Another advantage of using the data of the online verification engine 152 is to accurately verify the estimated travel time by recording the actual travel time and comparing this travel time with the previously calculated estimated travel time. These information can be used as an input value of the link segment travel time update engine 156.

The mobile application 197 displays the user's driving route during the verification process: in one embodiment, the mobile application 197 is used to provide a turn-by-turn voice navigation or visual guidance method To help guide the user to drive along the selected route between the departure place and the destination.

In order to update the estimated link travel time, the link section travel time update engine (STU) 156 is used to record and merge the experienced link section travel time with the historical link section journey time data. In one embodiment, the above action is performed by A Bayesian updating method. In another embodiment, the current experienced travel time information can also be used as part of the historical travel time data 124 to provide the system 100 for calculating future estimates.

The system 100 further includes a vendor transaction engine and accounting database (VTE) 160. The vendor transaction engine and accounting database 160 is used to track how many types and amounts of coupons are generated by the system 100. Each coupon should have its own attributes and be stored in the vendor transaction engine and accounting database 160 in the form of database records. During each transaction reconciliation period, the vendor transaction engine and the accounting database 160 will verify the transaction database of the vendor with the recorded coupon. For the contract manufacturer, the coupon transaction can be automatically executed and recorded in the account system of the contract manufacturer. The records of this account system can be reconciled with the vendor's transaction engine and the accounting database 160, and the used or expired coupons will become invalid. Because the income of used coupons will be processed in the form of accounts receivable information. For ordinary merchants, there is no pre-existing coupon transaction account mechanism, so when the coupon is redeemed, the system 100 will also provide a website for the merchant to enter the serial number of the redeemed coupon and its transaction account. This mechanism The used coupons can be invalidated, and the transaction amount can be sent to the vendor transaction engine and accounting database 160 and recorded. The above processing method is only an example of an operating mechanism of the vendor transaction engine and the accounting database 160 for the use of retailer's coupons, that is, the vendor transaction engine and the accounting database 160 can be applied to other different types of rewards. Configuration.

The system 100 further includes a user behavior analysis engine (user behavior analysis engine). analysis engine, UBA)164. Each reservation status will be recorded and analyzed by the user behavior analysis engine 164. The analysis is mainly to understand how often registered members make appointments, how often they complete the verification of the appointment, and how often they try to complete the verification of the appointment but fail in the end while driving. The reason for the failure may be that the designated route is too congested or because of unknown reasons, the originally planned route needs to be diverted. The user behavior analysis engine 164 can also send questionnaires to the user regularly, and collect and understand the user's experience based on the user's feedback.

The analysis on the coupon transaction mainly lies in the frequency with which the user may use the predetermined coupon, as well as the average transaction amount and classification, such as social demographic attributes. The user behavior analysis engine 164 can also try to understand and analyze which types of coupons different users choose based on their different preferences and lifestyle information 172. With these preferences and lifestyle information 172, the marketers in the system 100 will have a better idea because they know which types of rewards these users prefer. Therefore, it is possible to design rewards corresponding to the activities or choices corresponding to these preferences and life style information 172.

User experience feedback can be an important unit in collecting preferences and lifestyle information 172 to serve as a basis for improving the function of the system 100. Preference and lifestyle information 172 can be collected in the website application 195 and the mobile application 197 of the system 100, and collected through the "send feedback" function in each platform.

As shown in FIG. 1A, the system 100 further includes a marketing intelligence engine (MIE) 170. The marketing intelligence engine 170 is used to allow marketers to inquire and receive the results analyzed by the user behavior analysis engine 164. Result, in order to help the marketing unit design and implementation. Generally speaking, the questions that marketers may ask include: for the relevant personal characteristics, time, place of departure and destination or city type, the user’s favorite coupon/reward type; for the relevant city, road, place of departure, The frequency of travel reservations at destination or departure time; the characteristics of coupons for relevant factors such as cities, roads, departure places, destinations and/or personal characteristics; and any use collected through website application 195 or mobile application 197 Feedback from the person.

Fig. 3 illustrates a flow chart for implementing the steps 200 of the active traffic demand management system 100 as described in Figs. 1A and 1B. The specific embodiment of each step in the execution program 200 is as described above. Step 200 is performed to obtain the best travel time by receiving departure and destination data from the user and executing the mobile application 197 on the mobile device 196 by the user, as in step 204. Then the system 100 calculates the estimated travel time of one or more routes in a plurality of departure times, as in step 206. The system 100 also decides to provide rewards to the user in one or more routes and multiple departure times, as in step 208. Then, in step 210, the system 100 sends a menu list of the departure time and estimated travel time to the user's mobile application 197, and displays it on the user's mobile device 196.

The system then receives the time window selected by the user, as in step 212, and provides rewards related to one or more routes to the user, as in step 214. As mentioned above, the departure time, route and rewards given to the user can be in order, simultaneously or any combination thereof. The system 100 then receives the route selected by the user and the corresponding reward, as in step 216. When approaching the selected departure time, the user's mobile device 196 monitors the user's actual location through route information and GPS location information. Additionally or alternatively, with the user’s consent, the system 100 can receive the GPS location from the user’s mobile device 196 to monitor the user’s location to confirm that the user enters the route of his choice during the selected departure time. The starting point, such as step 218 and step 220. When the user travels along the route, the mobile application 197 (or the system 100) confirms that the user has completed at least part of the selected route, as in step 222. For example, the mobile application 197 or the system 100 can confirm that the user has passed through this part of the route and has the most congested road section (for example, tunnel, bridge, or city, etc.) before completing the route. Once the user completes the specific road section, the system 100 can provide the user with the reward agreed by the previous user, as in step 224.

In addition to the travel reservation, verification, transfer and other links described in Figures 3 and 4, it is worth mentioning that there are several different ways to initiate these actions. In addition to the user's active input of the start and end points on the mobile terminal application, the background system can also conduct active data mining based on the user's usage record, travel trajectory and other information, predict the user's possible travel destination and departure time, and prompt The user is ready to travel. Another way of active traffic management is that the active early warning module predicts the user’s possible travel destination, departure time, and travel route, analyzes unexpected events, traffic congestion and other abnormal situations that may be related to the user’s travel, and takes the initiative Push warning information to users. These two data mining-based active traffic demand management methods minimize the manual intervention required between users and the system. Even if the user forgets to use the mobile terminal application, it can ensure that the system can actively provide high-quality services for the user's travel.

Fig. 4 is a flowchart of the execution step 230 of the active traffic demand management system 100 as described in Figs. 1A and 1B. Figure 5 is a schematic diagram of the hardware equipment and operating environment of the present invention to realize the active traffic demand management system. At the beginning, as in step 232, the user will use the mobile application 197 to select the departure place and destination of the planned itinerary. The user can actively enter information such as the start and end points through the mobile terminal application, and can also start the itinerary planning according to various travel prompts that the system actively pushes to the mobile terminal client. Then, in step 234, the user views the list of itinerary options received by the system 100, which provides various routes, departure time, estimated journey time, and rewards. Next, in step 236, the user can select a specific itinerary option, and the reward combined with the specific itinerary option is determined according to the parameters in the specific itinerary option.

The user can then depart from the selected departure place at the selected departure time and follow the selected route to the selected destination, such as step 238 and step 240. When the user arrives at the selected destination (or a route with a driving part on the selected route) according to the selected itinerary option, the user will receive the reward from the system 100 and can redeem the reward later , Such as step 242 and step 244.

Generally speaking, companies are based on employee welfare, employee care, environmental protection, For the purpose of alleviating traffic congestion in corporate office parks, there is a need and motivation to participate in an active traffic demand management system. Enterprises can use information management software for enterprise users to implement and manage the flexible commuting system for employees, implement active traffic management in the park, and provide special rewards for employees of the enterprise to encourage employees to use the active traffic demand management system and plan rationally. Travel and reduce the departure time. And employees can not only reduce the travel time spent on the road, but also get additional rewards sponsored by the employer, so they are more willing to contribute to alleviating traffic congestion. In the end, the automatically generated report will make statistics on the company's employee welfare, environmental protection, and corporate image.

Through this business information management software, using data mining technology based on geographic location information, the system can statistically analyze how many potential users pass through the area where the business is located within a certain period of time. Merchants can use this software to initiate and manage market promotions and distribute discount coupons, vouchers, free products, etc. to attract users to the merchants for consumption. In the end, the automatically generated report will make statistics for the business on the development of new users, the growth of operating income, and the cultivation of member user loyalty.

Through this government traffic management software, the government can not only share its historical, real-time traffic data, emergencies, group activities and other information with the active traffic demand management system to better serve citizens’ traffic travel, but also Obtain data feedback on citizen travel behavior, GPS trajectory data, traffic demand, etc. from the active traffic demand management system, and provide technical support and data for traffic management departments in real-time monitoring of traffic, implementing traffic management strategies, and calibrating traffic model parameters. basis. In addition, the government can also use the resources at its disposal, such as parking agency Golden coupons, free highway passes, etc., provide incentives to citizens to encourage citizens to travel rationally and ease traffic congestion. This also eased the government's expensive financial pressure on new construction and maintenance of road infrastructure from the side. In the end, the report automatically generated by the software will make quantitative statistics on the government's achievements in traffic congestion alleviation, information system construction, service level improvement, and government image.

Although the application scope of the above embodiment is vehicle traffic management on the road, it is understandable that the concept of the present invention can be applied to a variety of execution procedures and used to manage traffic flow that may be congested (such as pedestrian traffic or other vehicles). Of traffic). For example, the present invention can be used to manage a congested parking lot, or to manage multiple parking lots by rewarding users to enter or exit one of the parking lots within a time agreed by the user. Similarly, the system 100 defined in the present invention can be applied to manage pedestrian traffic flow in various places, such as sports events, carnivals, concerts, or public events like parades. In these locations, the participants of an event may arrive at a selected location or leave from a location at certain times due to rewards, so as to reduce congestion in this location. Of course, those skilled in the art can know that the system of the present invention can be used in other applications.

Therefore, it can be understood that the advantage provided by the present invention is that by reducing the degree of congestion on overcrowded roads, the system and method of the present invention can not only increase the fuel consumption efficiency of vehicles, but also effectively reduce traffic. Exhaust emissions from the tool. In addition, during peak traffic hours, the embodiment of the present invention An extremely rewarding mechanism to encourage users to choose other departure times outside the peak hours, instead of restricting users from driving peak sections through punishments, and it is well known that the departure time of the itinerary is actually very flexible, so the present invention The reward mechanism can be used to attract users to choose other alternative departure times to relieve traffic congestion during peak hours. It is not only beneficial to the users but also to the society as a whole. It is a win-win strategy model.

In addition, because the system of the present invention is implemented based on the concept of rewarding good behaviors, it can be beneficial to users, manufacturers, public institutions, and politics. Among them, the cost of government departments will be the smallest because of the cost. The system of the invention can also be operated by the private sector, which can also provide positive effects for the general public. Of course, those skilled in the art should be aware of other features of the embodiments of the present invention.

Please refer to Figure 5. Figure 5 is a schematic diagram of the hardware equipment and operating environment of the active traffic demand management system 100. The purpose of Figure 5 is mainly to provide a short and common description to provide an appropriate The computing hardware equipment and operating environment are not necessary, but the instruction modules that can be executed by the computing system, or the hardware equipment similar to personal computers that can be used in computing systems, will be described in this article. Generally speaking, program modules include routines, programs, objects, components, data structures, etc., which will perform specific tasks or implementations. Specific data types.

In addition, those skilled in the art should know that the present invention The described embodiments can also be implemented using other computing system configurations, including hand-held devices, multiprocessor systems, microprocessor-based, and programmable Consumer electronics (programmable consumer electronics), network PCs, minicomputers, mainframe computers or cloud computing architectures, etc. Of course, the present invention can also be executed in a distributed computing environment through one or more network connections to allow remote devices to execute programs. It should be noted that, in a distributed computing environment, each program module can be configured in the storage unit of the local device and the remote device.

As shown in FIG. 5, the hardware equipment and operating environment in this embodiment includes a general-purpose computing device, that is, the computer device 12. The computer device 12 includes a system memory 22, a processing unit 21, and a system bus 23, and is coupled to different system components, including the system memory 22 coupled to the processing unit 21. The system component may include one or more processing units 21, so that the computer device 12 has a single central processing unit 21 or multiple processing units, which is generally regarded as a parallel processing environment. In addition, the computer device 12 may be a conventional computer, a distributed computer, a mobile computing device, or any other type of computing device.

The system bus 23 can be any type of bus structure, including a memory bus or a memory controller, a peripheral bus, and can be used in a variety of bus structures. The local bus. The system memory 22 can be generally referred to as a memory, which includes a read only memory (ROM) 24 and a random access memory (RAM) 25. Among them, during the startup process of the computer device 12, a basic input/output system (BIOS) 26 can be stored in the read-only memory 24, and the basic input/output system 26 carries applications in the components. The basic routine of sending messages between. In addition, the computer device 12 may further include a hard disk drive 27 for reading or writing a hard disk (not shown), and a removable magnetic disk (removable magnetic disk) for reading or writing. A magnetic disk drive 28 with a disk 29 and an optical disk drive 30 for reading or writing CDs, DVDs, or other optical media. Of course, the computer device 12 may also include one or more other types Storage devices (for example: flash memory storage devices, etc.).

The hard disk drive 27, the magnetic disk drive 28, and the optical disk drive 30 are respectively composed of a hard disk drive interface 32, a magnetic disk drive interface 33, and an optical disk drive interface (optical disk drive interface). ) 34 are respectively connected to the system bus 23. For the computer device 12, its driver and its computer-readable media provide non-volatile storage of computer-readable instructions, data structures, program modules, and other data. In addition, those skilled in the art can understand that any other types of computer-readable media can also be used to store data by entering the computer, such as magnetic cassettes, flash memory cards, USB devices, digital audio and video disks, Bernoulli cartridges, random access memory (RAM) Or read-only memory (ROM) and so on, the data they store can be used in the operating environment. Furthermore, those skilled in the art should be able to clearly see that the hard disk drive 27 and other forms of computer readable media (for example: removable disk 29, removable optical disk 31, flash drive Memory cards, USB drives, etc.) can all be regarded as part of the system memory 22, and can be read and written by the processing unit 21.

Multiple program modules can be stored in the hard disk drive 27, disk drive 29, optical drive 31, read-only memory 24 or random access memory 25, and include an operating system 35, one or more application programs 36. Other program modules 37 (such as one or more modules and application programs mentioned above) and program data 38. The user can input commands and messages to the computer device 12 through input devices such as the keyboard 40 and the pointing device 42. Other input devices (not shown in the figures) include microphones, joysticks, game pads, satellite dishes, or scanners for input. In addition, these and other input devices are usually coupled to the processing unit 21 through the serial port interface 46 of the system bus 23, but they can also be coupled from other ports, such as parallel ports. (parallel port), game port (game port), universal serial bus (USB), etc. Furthermore, the display 47 or other types of display devices may also be connected to the system bus 23 through a video adapter 48, for example. In addition to displays, computer devices generally include other peripheral output devices (not shown in the figure), such as speakers or printers.

The computer device 12 may be implemented in a network operating environment by being logically connected to one or more remote computers, for example, remote computers (remote computers). computer 49, and these logical connections can be achieved by connecting to the computer device 12 (local computer) or a communication device connected to the computer device 12. Of course, it is not limited to a specific type of communication device. The remote computing device 49 can be another computer, a server, a router, a network PC, a client, a memory storage device, and an interconnection device. Compared with the above-mentioned computer device 12, the remote computing device 49 usually has many parts or even all components. The remote computer 49 can be connected to the storage device 50. As shown in Figure 5, the logical connection includes a local-area network (LAN) 51 and a wide-area network (WAN) 52. This kind of network connection environment should be common in office and enterprise-wide computer networks, intranets, and Internet roads.

When used in a local network environment, the computer device 12 is connected to the local network 51 through a network interface or a kind of adapter 53 in a communication device. In the operating environment of a wide area network, the computer device 12 usually has a modem 54, a communication device, or any other type of communication device applied to the wide area network 52 (such as the Internet). The modem 54 is coupled to the system bus 23 through the serial port interface 46 and can be installed inside or outside the computer device 12. In a network environment, the program modules described in the personal computing device 12 or a part of the program modules can be stored in the remote computing device 49 and/or the remote storage device 50. It can be understood that the network connection or other connection means described in the present invention can also be applied to the communication equipment for establishing the communication network between the computing devices. Prepared.

The computer device 12 and its related components are represented here by specific embodiments and conceptualized high-level schematic diagrams. The actual technical design and implementation methods may change based on the realization of a specific purpose, but they will still maintain the same overall characteristics as the disclosed concept.

However, the above are only preferred embodiments of the present invention, and should not be used to limit the scope of the present invention. Any changes and modifications that can be obviously made by those skilled in the field of this case should be regarded as not. It deviates from the essence of the present invention.

100‧‧‧Active Traffic Demand Management System

104‧‧‧Booking process

120‧‧‧Data Search Engine

122‧‧‧Real-time data

124‧‧‧Historical travel time data

130‧‧‧Online user transaction execution engine

132‧‧‧Event travel time prediction algorithm

136‧‧‧The path algorithm of the least marginal cost related to time

140‧‧‧Reward providing algorithm

144‧‧‧Time and Space Carrying Average Algorithm

148‧‧‧Reward generation and accounting algorithm

170‧‧‧Marketing Intelligence Engine

172‧‧‧Preferences or lifestyle information

176‧‧‧Create Account

180‧‧‧Estimated event travel time

Route 184‧‧‧

188‧‧‧Reward

190‧‧‧Enter the departure place and destination and browse the departure time

192‧‧‧Select departure time

193‧‧‧Browse the destinations recommended by the system

194‧‧‧General computer

195‧‧‧Web Application

196‧‧‧Mobile device

197‧‧‧Mobile App

Claims (16)

An active traffic demand management and behavior induction system, including: i) a mobile application software, which is executed on a mobile device of a user; ii) a computer software server system, which is used to communicate with the mobile application software , The computer software servo system includes: (1) a path calculation module, based on a plurality of departure times close to a priority departure time selected by the user, calculates a departure place and the corresponding departure place A route between a destination, wherein when the user departs from the departure place to the destination, each departure time corresponds to a time interval from departure to arrival of the user; (2) a The travel time prediction module is used to calculate a preset travel time from the departure place to the destination paired with the departure place at each departure time; (3) a reward providing module for Determine the rewards that can be provided to the user at each departure time; (4) A verification module receives a location information from the mobile application software, and confirms that the user is in the selected departure time based on the location information Depart from the place of departure in time, and at least part of the itinerary after departure is carried out along the route; (5) An emergency traffic impact analysis module to calculate the impact range and duration of traffic accidents , Severity; (6) A travel chain planning module that allows users to plan a travel chain and arrange a series of trips accordingly; (7) A destination prediction module, which predicts the user’s possible travel destination and departure time; and (8) an active warning module, which analyzes the possibility of the user’s travel destination and departure time based on the predicted travel destination and departure time. Travel-related emergencies, traffic congestion and abnormal situations, and actively push warning information to users; iii) A traffic management software for government departments, supporting traffic data sharing, emergency management, and providing incentives to alleviate traffic congestion Iv) A business-oriented information management software that supports corporate park traffic management, flexible commuting, and corporate incentives to alleviate traffic congestion; and v) a business-oriented information management software that supports potential users to analyze and carry out various promotions , Attract users to consume. The system for active traffic demand management and behavior guidance according to claim 1, wherein the travel time prediction module is used to analyze a historical data and a real-time traffic data, and the reward providing module is based on the departure time for the The route or traffic system causes the least impact to select the reward, and the reward providing module dynamically adjusts the distribution of the reward based on the historical data, the real-time data, and the departure time selected by other users, and uses the reward. The preferences of the user and the life style information of the user are taken into consideration. The active traffic demand management and behavior induction system according to claim 1, wherein the verification module receives the location information from a global positioning system of the mobile application software, and analyzes the received from the global positioning system Location information to confirm the user’s input at the selected departure time is close to the departure To a location in the city and confirm that the user has successfully completed the selected part of the predetermined route. The system for active traffic demand management and behavior guidance according to claim 1, wherein the route determination module calculates one or more between the departure place and the destination in a plurality of departure times Route, and when there is additional traffic on the route, each departure time is taken into consideration for the extra journey time caused by the additional traffic on the route. The active traffic demand management and behavior induction system as described in claim 1, further comprising: i) a load balancing module for measuring a route and a departure journey time pre-selected by other users Ii) A road condition monitoring and warning module is used to confirm an accident on the route and send a message to notify the user of the accident; and iii) a user behavior analysis module, which is from The mobile application software receives a behavior message from the user and analyzes it based on the behavior message. The reward providing module adjusts and provides it to the user according to the behavior information analyzed by the user behavior analysis module. Of the reward. The proactive traffic demand management and behavior induction system described in claim 1, wherein the modules for traffic incident handling include: i) A functional module that allows system operators, ordinary users, and various users of government traffic management departments to report and input various traffic-related emergencies, group activities, and traffic congestion; ii) According to Enter various events, dynamically estimate their impact on the road traffic network, including the scope of impact, duration, and degree of impact of the traffic algorithm module; and iii) screen out the users affected by the traffic event and push warning information Functional modules for users. The system for active traffic demand management and behavior induction as described in claim 1, wherein the modules that support users to carry out travel chain planning include: i) Allow users to input a series of destinations on smart mobile terminals and automatically It is combined into a dynamic travel chain method; ii) Based on the multiple travel destinations entered by the user, the system calculates the optimal travel path between each pair of departure and destination points; and iii) Automatically send the user the last time The destination of the trip is used as the starting point of the next trip, and it is a functional module that determines the start time of the next trip according to the arrival time of the last trip. The system for active traffic demand management and behavior induction as described in claim 1, wherein the destination prediction and recommendation module intelligently recommends the user’s travel destination, including: i) A destination selected by the user is a certain A popular attraction, and its passenger flow demand is close to saturation, thus reducing the experience of this trip, or use When users actively request to browse alternative destinations, they actively recommend other destinations; ii) A module that displays the passenger flow of other destinations, the traffic conditions on the road, the discounts and rewards of each destination, and the user travel Records and lifestyle information, and intelligently recommends better destination options to enhance the travel experience of the system function module; iii) Based on user usage records, travel trajectory information, active data mining, predict the user's possible The algorithm module of travel destination and departure time; iv) Firstly, the system recommends and predicts the user’s travel destination, the possible departure time, and the emergencies monitored by the system, and actively judges the possible related to the user’s travel Traffic information method module; v) a method module that actively pushes traffic information that may be related to the user’s travel to the user through a smart mobile terminal and presents it; and vi) a method module that receives the user’s push The feedback of the message and send it back to the functional module of the remote server. The proactive traffic demand management and behavior induction system described in claim 1, in which the traffic management system for government users includes: i) A support government department will have historical traffic data, real-time traffic data, and emergency traffic data. Event information is shared with the software module of the system; ii) A functional module that supports the sharing of historical traffic data, real-time traffic data, and emergency information owned by the system back to government departments; iii) A functional module that allows the government to view the traffic flow on the road traffic network in real time and monitor the changes in the traffic flow in the future; iv) Allow government departments to implement road closures, lane closures, and no turning A series of functional modules for active traffic management strategies; v) A system that updates the functional modules of traffic flow prediction results based on these new management strategies; and vi) Pushes these traffic management strategies and the resulting changes in traffic flow Function modules for system users. The system of active traffic demand management and behavior induction as described in claim 1, wherein the information management system for enterprise users includes: i) a software that supports enterprises to encourage and manage employees to participate in this active traffic system management system; ii ) A functional module that allows companies to invest in rewards to encourage employees to take measures to reduce the departure time, and restricts that only employees of the company can redeem corporate investment rewards; iii) A functional module that encourages employees to travel during peak hours and supports flexible commuting system management Functional module; and iv) A functional module that supports traffic management at the entrance and exit of the enterprise park by encouraging employees to travel during peak hours and coordinating their departure time. The proactive traffic demand management and behavior induction system described in claim 1, wherein the information management system for merchant users includes: i) A software that supports merchants to analyze the number of potential customers and their distribution in time and space through data mining based on active traffic management systems; ii) A software that supports merchants to carry out various promotions for potential customers and existing customers , And push these promotional information to the user's functional module; and iii) a functional module that accepts the user's use, redeem the rewards distributed by the system, and consumes at the merchant. A method for active traffic demand management and behavior induction includes: i) receiving a departure place and a destination corresponding to the departure place and a priority travel time from a user; ii) at the departure place and the destination At least one route is calculated between, and when the route has additional traffic, the additional travel time caused by the additional traffic is taken into consideration; iii) multiple departure times close to the priority travel time are calculated, When the user wants to depart from the departure place and go to the destination along the route, each departure time corresponds to a time interval from departure to arrival of the user; iv) calculated according to each departure time A reward provided to the user; v) sending and displaying the route, each of the departure time and the reward related to the route and each of the departure time; vi) receiving a selected route and a selected route from the user The selected departure time and the corresponding reward; vii) At least part of the user travels along the route and receives a position information from the user; vii) confirms that the user has reached the destination within the selected departure time And at least part of the itinerary is from the departure place to the destination along the route; and ix) sending the reward to the user. The method for active traffic demand management and behavior induction as described in claim 12 further includes: i) calculating a preset travel time from the departure place to the destination according to each departure time, wherein the preset travel time The travel time includes analyzing a historical data of the route and a real-time traffic data of the route; ii) confirming an accident on the route and sending a message to notify the user of the accident; and iii) providing the use One is a backup route, and the backup route selected by the user is received from the user. The method for active traffic demand management and behavior guidance according to claim 12, wherein at least one route is calculated between the departure place and the destination, and one of a plurality of departure times close to the priority travel time is calculated The steps further include: i) taking into consideration at least one route and a departure time of a trip previously selected by other users. The method for active traffic demand management and behavior induction according to claim 12, wherein the step of calculating a reward provided to the user according to each departure time includes: i) predicting the departure time relative to the route The minimum impact caused by the degree of congestion; ii) the time difference between each departure time and the priority travel time is taken into consideration; iii) the user’s preference or life style information is taken into consideration; iv) based on a historical data, A real-time traffic data and the departure time selected by other users are used to dynamically adjust the reward; and v) analyze a behavior message received from the user, and adjust and provide to the user according to an analysis result of the behavior message The reward for the person. The method for active traffic demand management and behavior induction according to claim 12, wherein the calculation method is in a global positioning system of a mobile device of the user in the step of receiving a location information from the user Receive the location information, and confirm that the user departs from the departure place at the selected departure time, and confirm that the user has arrived at the destination within the selected departure time, and has at least Part of the step from the departure place along the route to the destination is to analyze the location information received from the global positioning system to confirm that the user enters a location close to the departure place at the selected departure time. A location and confirm that the user has successfully completed the selected part of the predetermined route.

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