CN114550443A - Road network data processing method, equipment and readable medium - Google Patents
Road network data processing method, equipment and readable medium Download PDFInfo
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- CN114550443A CN114550443A CN202210072734.5A CN202210072734A CN114550443A CN 114550443 A CN114550443 A CN 114550443A CN 202210072734 A CN202210072734 A CN 202210072734A CN 114550443 A CN114550443 A CN 114550443A
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Abstract
The embodiment of the application provides a road network data processing method, road network data processing equipment and a readable medium, wherein the road network data processing method comprises the following steps: acquiring sensor data and road network data related to a road network; determining traffic flow data according to the sensor data and the road network data; performing road network analysis according to the traffic flow data, and determining corresponding path data and key point control data; and performing cooperative control on road network traffic according to the path data and the key point control data. The analysis of the path of the global vehicle and the local single-point control can cooperatively execute the global control and the single-point control, more accurately control the road network and improve the processing efficiency of road network data.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a road network data processing method, a terminal device, and a machine-readable medium.
Background
With the development of information technology, more and more transactions in life begin to introduce information technology for management. Taking the road as an example, the user can navigate based on the information technology, so that the user can go to the destination more conveniently. And as well as to manage roads so as to manage urban roads, etc.
At present, the application of active management and control technology for roads at home and abroad is in the primary stage, and many academic researches are in local management and control optimization. The local technologies are optimized to control the upstream and downstream traffic flows of the event points, however, the urban road networks are communicated, so that the problems of other associated local areas are often brought, and the processing efficiency is low.
Disclosure of Invention
The embodiment of the application provides a road network data processing method, so that the road network data processing efficiency is improved.
Correspondingly, the embodiment of the application also provides electronic equipment and a machine readable medium, which are used for ensuring the realization and the application of the method.
In order to solve the above problem, an embodiment of the present application discloses a road network data processing method, where the method includes:
acquiring sensor data and road network data related to a road network;
determining traffic flow data according to the sensor data and the road network data;
performing road network analysis according to the traffic flow data, and determining corresponding path data and key point control data;
and performing cooperative control on road network traffic according to the path data and the key point control data.
Optionally, the determining traffic flow data according to the sensor data and the road network data includes:
time alignment is carried out on the sensor data and the road network data;
and mapping the aligned sensor data and the aligned road network data into a road network to determine traffic flow data.
Optionally, the mapping the aligned sensor data and the aligned road network data into a road network to determine traffic flow data includes:
mapping the aligned sensor data and the aligned road network data to corresponding road sections of the road network according to the position information;
analyzing the data mapped by each road segment, and determining corresponding traffic flow data, wherein the traffic flow data comprises: traffic flow data, vehicle speed data, and/or event data.
Optionally, the performing road network analysis according to the traffic flow data to determine corresponding path data and key point control data includes:
determining a driving track of a vehicle according to identification information of the vehicle, and determining path data according to the driving track;
and determining position information according to the event data, and determining key point control data according to the position information.
Optionally, the determining the driving track of the vehicle according to the identification information of the vehicle and determining the path data according to the driving track include:
acquiring positioning data of the vehicle according to the identification information of the vehicle, and determining a running track of the vehicle according to the positioning data;
and determining the starting position and the terminal position of the vehicle according to the running track, and determining the path data according to the starting position and the terminal position of the vehicle.
Optionally, the determining the location information according to the event data, and determining the key point control data according to the location information include:
determining corresponding position information according to the event data, and determining key points of corresponding road sections according to the position information;
and generating key point control data corresponding to the key points.
Optionally, the performing cooperative control on road traffic according to the path data and the key point control data includes:
performing global path planning according to the path data, and determining corresponding path guiding information;
and executing control operation on the key points according to the key point control data.
Optionally, the method further includes performing at least one of the following control operations on the keypoints according to the keypoint control data:
determining speed limit information corresponding to the key points according to the key point control data;
controlling the ramp corresponding to the key point according to the key point control data;
opening a hard road shoulder corresponding to the key point according to the key point control data;
sending prompt information corresponding to the key points according to the key point control data;
and opening or closing the toll station corresponding to the key point according to the key point control data.
The embodiment of the application also discloses an electronic device, which comprises: a processor; and a memory having executable code stored thereon that, when executed, causes the processor to perform a method as described in embodiments of the present application.
One or more machine-readable media having stored thereon executable code that, when executed, causes a processor to perform a method as described in embodiments of the present application are also disclosed.
Compared with the prior art, the embodiment of the application has the following advantages:
in the embodiment of the application, sensor data and road network data related to a road network can be acquired, traffic flow data is determined according to the sensor data and the road network data, road network analysis is performed according to the traffic flow data, corresponding path data and key point control data are determined, a path of a global vehicle and local single-point control are analyzed, road network traffic is cooperatively controlled according to the path data and the key point control data, global control and single-point control can be cooperatively executed, the road network is controlled more accurately, and the processing efficiency of the road network data is improved.
Drawings
FIG. 1 is a flowchart illustrating steps of an embodiment of a road network data processing method according to the present application;
fig. 2 is a schematic processing diagram of a road network management and control system according to an embodiment of the present application;
FIG. 3 is a flow chart illustrating steps of another road network data processing method according to an embodiment of the present application;
FIG. 4 is a flowchart illustrating steps of an embodiment of a road network data processing apparatus according to the present application;
fig. 5 is a schematic structural diagram of an apparatus according to an embodiment of the present application.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.
The embodiment of the application can be applied to the management scene of road data, such as the management and control of road data in cities, and the management and control of roads between cities. Active Traffic Management (ATM) can be performed on roads, and the ATM comprises a series of complete and coherent traffic management europe formulas, and can perform historical management on frequent and accidental traffic jams, so that benefits of traffic equipment are brought into play. The road network in the embodiment of the application refers to a road network in the traffic field, and is a road system which is formed by connecting and interweaving various roads and various levels of roads into a net distribution in a certain area. The system comprises a road network consisting of various levels of roads, an urban road network consisting of various roads in an urban area, and the like.
Referring to fig. 1, a flowchart illustrating steps of an embodiment of a road network data processing method according to the present application is shown.
Various types of sensors can be arranged in the road network, including a gate, a road test unit rsu (road Side unit), a camera, a radar, a weather device, and the like, and also including sensors for the road network in a vehicle and a user device, such as a radar of the vehicle, a positioning sensor of the user device, and the like. The acquisition of the data of the various sensors needs to be allowed by the corresponding data sources and is acquired on the basis of authorization. The road network data refers to multi-source event stream data in the road network, such as highway facility equipment data, event data reported by user equipment, processing rule data of some time and the like.
Wherein, the acquiring of road-related sensor data and road network data comprises: the sensor based on the road association acquires at least one of the following sensor data: traffic flow data, construction data, traffic accident data, meteorological data, speed data, positioning data and the like; acquiring at least one of the following road network data: device data corresponding to road facilities, event data reported by user equipment, processing rule data and the like. The system comprises a plurality of sensor data and road network data, wherein each sensor data and each road network data are correspondingly associated with position information, the position information can be latitude and longitude information, the position information can also comprise information such as names of roads and highways, and the sensor data and the road network data are also associated with time information so as to determine the time for producing the data. For example, the traffic data may be traffic data for a certain road segment at a certain time.
The gate can be understood as a road and a highway entrance, image data and system data of the gate can be collected at the gate, and a Road Side Unit (RSU) can be used for measuring road speed, traffic flow and the like. And then, based on the data, analysis is performed to determine current traffic data and the like. The road and the highway can be provided with image acquisition equipment such as cameras and the like, can acquire road network images, and can determine traffic flow data, construction data, traffic accident data and the like of the road and the highway by analyzing the road network images. The traffic data is traffic flow data on roads and roads, such as the number of vehicles running per second, and the like, so that whether the roads are congested or not and whether the roads are smooth or not can be determined. The construction data refers to data of construction events occurring on roads and highways, which may cause the roads and the highways to be narrow or not to pass through. The traffic accident data refers to data of traffic accident incidents occurring on roads and highways, which may cause the roads and the highways to be narrowed down or to be impassable. In other examples, vehicle identification data, such as license plate number, may also be obtained from the image data and used upon demand with authorization. The traffic volume (traffic volume) data is the number of vehicles passing through a certain link per unit time, and the traffic volume (traffic volume) is expressed by a formula, i.e., the number of passing vehicles/time.
The radar can comprise a radar arranged on a road or a highway, and can also comprise a radar on a vehicle, and the radar can sense the speed of the traffic flow in the current time slice in real time and acquire the speed data. In addition, the user equipment can also acquire the speed data, and whether the road is congested or not, whether the traffic is smooth or not can be analyzed based on the speed data.
The weather device may include various weather sensors that sense current weather conditions, such as temperature, humidity, barometric pressure, wind speed, rain, wind direction, and other weather data.
Therefore, sensor data can be obtained through sensors arranged on road networks, vehicles and the like, the road network data can be reported through road network equipment, vehicle-mounted equipment, user equipment and the like, and road network control is carried out based on the sensor data and the road network data.
And 104, determining traffic flow data according to the sensor data and the road network data.
The sensor data and the road network data may be analyzed to determine traffic flow data for roads and highways in the road network. After the sensor data and the road network data are obtained, the sensor data and the road network data can be respectively subjected to data cleaning, and abnormal data can be deleted. Abnormal data in the sensor data and the road network data can be determined through analysis, for example, data with too high or too low data values, such as vehicle speed data exceeding 400 kilometers per hour (km/h), and flow data exceeding a flow threshold value. Also, the vehicle speed is too low or 0.
After the data cleaning is completed, the sensor data and road network data may be analyzed to determine traffic flow data. In an optional embodiment, the determining traffic flow data according to the sensor data and the road network data includes: and performing time alignment on the sensor data and the road network data, mapping the aligned sensor data and the aligned road network data into a road network, and determining traffic flow data. The sensor data and the road network data can be aligned according to time, and traffic flow data, construction data, traffic accident data, meteorological data, vehicle speed data, positioning data and the like at the same time, equipment data corresponding to road facilities, event data reported by user equipment, processing rule data and the like are determined. And then mapping the data to corresponding road sections of the road network, thereby determining the traffic flow, construction events, traffic accident time, meteorological time, processing rules and the like of each road section.
Wherein the mapping the aligned sensor data and the aligned road network data into a road network to determine traffic flow data comprises: mapping the aligned sensor data and the aligned road network data to corresponding road sections of a road network according to the position information, analyzing the data mapped by each road section, and determining corresponding traffic flow data, wherein the traffic flow data comprises: traffic flow data, vehicle speed data, and/or event data. The aligned sensor data and the aligned road network data can be mapped to corresponding road sections of the road network according to the position information to obtain the sensor data and the road network data on the specified road section at the specified time, and then the data are analyzed to determine the traffic flow data on the specified road section at the specified time, which can include the traffic flow data and the vehicle speed data on the specified road section at the specified time, and can also include event data of the occurrence of the traffic flow data and the vehicle speed data, such as meteorological data of meteorological events, traffic accident data of traffic accident time, construction data of construction events and the like, and processing rule data aiming at the corresponding events.
And 106, performing road network analysis according to the traffic flow data, and determining corresponding path data and key point control data.
After the traffic flow data is determined, road network analysis can be carried out according to the traffic flow data to determine the passing of corresponding roads, path planning can be carried out based on the road passing condition, and key points of some roads can be controlled.
The road network analysis is carried out according to the traffic flow data, and the corresponding path data and the corresponding key point control data are determined, wherein the method comprises the following steps: determining a driving track of a vehicle according to identification information of the vehicle, and determining path data according to the driving track; and determining position information according to the event data, and determining key point control data according to the position information. The running track of each vehicle can be determined according to the identification information of the vehicle, such as the positioning data fed back by positioning systems such as a GPS (global positioning system) and a Beidou of the vehicle, and the running track is determined according to the positioning data. Based on the travel path, route data of the vehicle may be determined, which may describe communication information between a start point and an end point of the vehicle, and the route data includes a start point position, an end point position, vehicle speed information, and the like. Therefore, the start point and the end point of the global traffic can be analyzed based on the path data so as to carry out comprehensive scheduling of traffic resources. Event data in traffic flow data, such as events like congestion, road repair, traffic accidents and the like, or events such as congestion and the like are analyzed based on traffic flow data, speed data and the like, the events like congestion are determined, position information corresponding to the event data, such as position information corresponding to a map and the like of positioning data, related key points, such as key points like ramps, toll stations and the like, are further determined based on the position information, and corresponding key point data are determined, so that single-point optimization can be performed on roads, highways and the like.
Wherein, the determining the driving track of the vehicle according to the identification information of the vehicle and the determining the path data according to the driving track comprise: acquiring positioning data of the vehicle according to the identification information of the vehicle, and determining a running track of the vehicle according to the positioning data; and determining the starting position and the terminal position of the vehicle according to the running track, and determining the path data according to the starting position and the terminal position of the vehicle. The method comprises the steps of obtaining positioning data of a vehicle based on identification information of the vehicle, determining a running track of the vehicle based on the positioning data, analyzing the running track, determining a starting point position and an end point position of the vehicle, and determining running paths of the vehicle at the starting point position and the end point position based on the starting point position, the end point position and the running track which can be matched with a map to obtain corresponding path data. And determining data such as vehicle speed and the like corresponding to each road section in the path data by combining the traffic flow data. The data of the path corresponding to the average vehicle speed, the passing time and the like in different periods can be analyzed, and the subsequent scheduling and use are facilitated. In the embodiment of the application, positioning data and the like can be polled periodically, and then the path data of each vehicle can be analyzed, wherein the path data can be the path data of a section of road section in the driving process of the vehicle, for example, the current position is taken as a starting point, or a starting point is taken as a starting point, and an intersection of the road section is taken as a terminal point and the like.
The determining location information according to the event data and determining the key point control data according to the location information includes: and determining corresponding position information according to the event data, determining key points of corresponding road sections according to the position information, and generating key point control data corresponding to the key points. The time data and the corresponding positioning data can be acquired, the position information is determined based on the positioning data, and the road section corresponding to the time can be determined according to the position information and the map. In other examples, event data includes an event identifier, location information, time information, description information, and the like, and the location information may be obtained based on the event data, so as to determine the location information to determine the key point of the corresponding road segment. The key point can be understood as a key node for processing the event, and can be road facilities and the like, such as intersection signal lamps, ramps, toll stations and the like corresponding to the event. Based on the key point, key point control data of event processing can be determined, such as adjusting and controlling intersection signal lamps, closing toll stations and the like.
And step 108, performing cooperative control on road traffic according to the path data and the key point control data.
After the path data and the key point control data are acquired, road traffic can be cooperatively controlled based on the path data and the key point control data. The global path planning can be carried out based on the path data, and the global path planning can regulate and control the path by combining with historical data. And the single-point optimization can be carried out on the key points based on the key point control data, and upstream and downstream traffic is planned.
The cooperative control of the road traffic according to the path data and the key point control data comprises the following steps: performing global path planning according to the path data, and determining corresponding path guiding information; and controlling the key points according to the key point control data. In the embodiment of the present application, the route data may be route data currently traveled by vehicles, and the global distribution and traveling condition of the vehicles in the road network may be determined according to the route data of each vehicle. The condition of the road network can be determined by combining historical data and event data, for example, the congestion condition of the road network in a current time interval and a specified time interval later can be determined based on the historical data and accident event data, and for example, a certain road section is determined to be narrowed down and a vehicle runs slowly or is congested based on the accident event data and construction event data, global path planning can be performed based on the running slowly or congestion condition, and the running path of the vehicle can be guided based on the global path planning to determine corresponding path guiding information. The method comprises the steps that a congested road section and predicted traffic vehicle data can be determined based on path data, historical road data, event data and the like, when the congested road section and the predicted traffic vehicle data reach guiding conditions, such as congestion of the road section, the predicted traffic vehicle data exceed a congestion threshold value and the like, the adjustable path information of the vehicles can be analyzed, shunting guidance is carried out on the vehicles, and the path guiding information is obtained. The route guidance information can be distributed in various forms such as navigation, broadcast, information display equipment (or called guidance screen) on the road, short message, push information and the like.
And executing control operation on the key points according to the key point control data, wherein the control operation comprises at least one of the following control operations: determining speed limit information corresponding to the key points according to the key point control data; controlling the ramp corresponding to the key point according to the key point control data; opening a hard road shoulder corresponding to the key point according to the key point control data; sending prompt information corresponding to the key points according to the key point control data; and opening or closing the toll station corresponding to the key point according to the key point control data. The key points are determined to be related to historical data, event data and the like, the key points can be correspondingly related to the global path planning, planning events related to the key points are determined based on the global path planning, and local scheduling can be correspondingly carried out through the key points. The method comprises the steps of determining key point control data corresponding to key points, determining speed limit information and road section information based on the key point control data, and issuing the speed limit information on corresponding road sections, so that the speed limit of a vehicle is dynamically adjusted. The associated ramp can be determined based on the key point control data, so that ramp control is performed, such as ramp opening and ramp closing, and the determination is specifically performed according to the condition of the road. HARD road SHOULDERs corresponding to the key points can be opened based on the key point control data, wherein the HARD road SHOULDERs (HARD short) refer to road SHOULDER parts (including the curb belts) which are adjacent to the roadway and paved with a pavement structure with certain strength. The device has the functions of protecting and supporting a road surface structure, and is used for the vehicles to bypass and the vehicles with faults to temporarily park. For example, non-motor vehicles and pedestrians are convenient to pass on a road with mixed traffic. And if an emergency lane marked by yellow lines on the right side of the highway is used, the emergency lane is mainly used for temporarily stopping a fault vehicle, and emergency vehicles can conveniently pass through the emergency lane in emergency. For example, a hard shoulder can be opened for rapid traffic in case of an emergency. Sending prompt information corresponding to the key points according to the key point control data, such as the path guide information, for example, XXXX road congestion, XX road section recommendation and the like; the key points are associated with event data of the road sections, such as accident events, construction events and the like, so that road conditions can be known conveniently, such as prompting of front accidents, attention to avoidance and the like. The toll station corresponding to the key point can be opened or closed according to the key point control data, the associated toll station and the like can be determined based on the key point control data, and then the corresponding toll station can be opened or closed based on the corresponding control situation. Such as opening toll booths based on emergency events, in case of closed highways, etc.
The local scheduling is carried out through single-point control, and traffic passing optimization can be realized through control scheduling measures which can be taken under a certain specific event. For example, after a traffic accident occurs, on an expressway, an accident upstream can remind passing vehicles to avoid accident risks in real time, and measures such as opening emergency lanes at accident points can improve passing speed and reduce travel time.
In summary, sensor data and road network data related to a road network can be acquired, traffic flow data is determined according to the sensor data and the road network data, road network analysis is performed according to the traffic flow data, corresponding path data and key point control data are determined, a path of a global vehicle and local single-point control are analyzed, road network traffic is cooperatively controlled according to the path data and the key point control data, global control and single-point control can be cooperatively executed, the road network is controlled more accurately, and processing efficiency is improved.
On the basis of the embodiment, the multi-source data can be acquired by combining the internet of things equipment, the vehicle-mounted equipment, the user equipment and the like of a road network, global planning and single-point optimization are carried out, and management and control processing of multiple dimensions is carried out. Fig. 2 is a schematic processing diagram of a road network management and control system.
The sensor data can be acquired through road network associated equipment, including Internet of things equipment, vehicle-mounted equipment, user equipment and the like, and can be used as an edge node of a distributed system to sense corresponding edge data. The internet of things equipment of the road network can comprise various edge equipment such as bayonet equipment, image acquisition equipment, meteorological equipment, charging equipment and radar. Sensor data may be acquired based on these devices. And multi-source road network data can be obtained from other multiple data sources. The method comprises the steps that road network data can be reported through road network equipment, vehicle-mounted equipment, user equipment and the like, such as highway facility equipment data, event data reported by users, event processing rules, such as emergency response schemes and the like.
And based on the sensor data and the road network data, data cleaning can be carried out, and then time alignment and other processing are carried out to obtain traffic flow data of the whole network and generate a traffic model of the whole network. And then the management and control of road network traffic can be carried out based on the traffic flow data. The OD analysis polling triggering can be carried out regularly, wherein the OD analysis refers to the analysis of the starting point and the ending point of the global traffic trip, is used for comprehensively scheduling resources, triggers the traffic OD analysis in a timed polling mode, and determines the target of the global scheduling. The path data may be acquired as the OD analysis result in the manner of the above-described embodiment. The control of the key points can be triggered by event triggering, early warning triggering and the like, wherein various events such as congestion, construction and the like can be determined through traffic flow data, and events needing early warning such as possible congestion, traffic guidance and the like can be determined, so that the control of the key points is triggered.
The OD analysis based path data can be used for carrying out congestion analysis on a road network, then global path planning on the road network is carried out, and vehicles and users which are issued in various modes and are used for guiding the paths of the vehicles are achieved. And the single-point control of the key points can be carried out based on the key point control data, so that the single-point optimization processing of dynamic speed limit, ramp control, open hard road shoulders, information prompt, open/close toll stations and the like can be realized, and the global and single-point control is carried out by combining an induction screen (namely display equipment) in a road network, intersection control equipment such as toll stations, traffic lights and the like, a road test unit (RSU), navigation equipment and the like.
For example, after a traffic accident occurs, on an expressway, the accident upstream can remind passing vehicles to avoid accident risks in real time, and measures such as opening emergency lanes at accident points can be taken to improve passing speed and reduce travel time. As another example, historical data is used to analyze which road segments are frequently congested, and route guidance is used to correct the driving route of the vehicle in combination with route data. An independent optimization method can be adopted based on specific events, such as severe weather events, speed limitation of all road sections on the expressway can be realized, such as traffic accident events, and information reminding and avoidance can be carried out at the upstream; the upstream lane controller performs stepped speed limiting, and the stepped speed limiting is performed from 100 to 40 in sequence; if the upstream flow is larger than a certain amount, controlling the flow by switching on and off the toll station; an emergency lane is opened near the accident point position, and the traffic is promoted.
Therefore, the management and control information generated by the global and single-point optimization engines can be displayed on the guidance screen in real time. And dynamically switching on and off the toll station ramps based on the calculation of the global and single-point optimization engines. And (4) based on the management and control information generated by the global and single-point optimization engines, sending and receiving the information to the passing vehicles at the RSU. And issuing the control information through a navigation Application (APP), realizing in-vehicle information reminding, and finishing a control closed loop.
On the basis of the above embodiments, the present application further provides a road network data processing method, which can implement global + single-point optimization and improve traffic processing efficiency of a road network.
Referring to fig. 3, a flowchart illustrating steps of another road network data processing method according to an embodiment of the present application is shown.
Various types of sensors can be arranged in the road network, including a gate, a road test unit RSU, a camera, a radar, weather equipment, etc., and also sensors used in vehicles and user equipment for the road network, such as a radar of a vehicle, a positioning sensor of user equipment, etc. The acquisition of the data of the various sensors needs to be allowed by the corresponding data sources and is acquired on the basis of authorization. The road network data refers to multi-source event stream data in the road network, such as highway facility equipment data, event data reported by user equipment, processing rule data of some time and the like.
The sensor data and the road network data may be analyzed to determine traffic flow data for roads and highways in the road network. After the sensor data and the road network data are obtained, the sensor data and the road network data can be respectively subjected to data cleaning, and abnormal data can be deleted. Abnormal data in the sensor data and the road network data can be determined through analysis, for example, data with too high or too low data values, such as vehicle speed data exceeding 400 kilometers per hour (km/h), and flow data exceeding a flow threshold value. Also, the vehicle speed is too low or 0. Then, the sensor data and the road network data can be aligned according to time, and traffic flow data, construction data, traffic accident data, meteorological data, vehicle speed data, positioning data and the like at the same time, equipment data corresponding to road facilities, event data reported by user equipment, processing rule data and the like are determined. And then mapping the data to corresponding road sections of the road network, thereby determining the traffic flow, construction events, traffic accident time, meteorological time, processing rules and the like of each road section.
Wherein the mapping the aligned sensor data and the aligned road network data into a road network to determine traffic flow data comprises: mapping the aligned sensor data and the aligned road network data to corresponding road sections of the road network according to the position information; analyzing the data mapped by each road segment, and determining corresponding traffic flow data, wherein the traffic flow data comprises: traffic flow data, vehicle speed data, and/or event data.
And 308, determining the running track of the vehicle according to the identification information of the vehicle, and determining path data according to the running track.
Wherein, the determining the driving track of the vehicle according to the identification information of the vehicle and the determining the path data according to the driving track comprise: acquiring positioning data of the vehicle according to the identification information of the vehicle, and determining a running track of the vehicle according to the positioning data; and determining the starting position and the terminal position of the vehicle according to the running track, and determining the path data according to the starting position and the terminal position of the vehicle.
The aligned sensor data and the aligned road network data can be mapped to the corresponding road sections of the road network according to the position information to obtain the sensor data and the road network data on the specified road sections at the specified time, and then the data are analyzed to determine the traffic flow data on the specified road sections at the specified time, which can include the traffic flow data and the vehicle speed data on the specified road sections at the specified time, and can also include the event data of the occurrence of the traffic flow data and the vehicle speed data, such as the meteorological data of meteorological events, the traffic accident data at the traffic accident time, the construction data of construction events and the like, and the processing rule data aiming at the corresponding events.
The aligned sensor data and the aligned road network data can be mapped to corresponding road sections of the road network according to the position information to obtain the sensor data and the road network data on the specified road section at the specified time, and then the data are analyzed to determine the traffic flow data on the specified road section at the specified time, which can include the traffic flow data and the vehicle speed data on the specified road section at the specified time, and can also include event data of the occurrence of the traffic flow data and the vehicle speed data, such as meteorological data of meteorological events, traffic accident data of traffic accident time, construction data of construction events and the like, and processing rule data aiming at the corresponding events.
Wherein, the determining the position information according to the event data and the determining the key point control data according to the position information comprises: determining corresponding position information according to the event data, and determining key points of corresponding road sections according to the position information; and generating key point control data corresponding to the key points.
Event data in traffic flow data, such as events like congestion, road repair, traffic accidents and the like, or events such as congestion and the like are analyzed based on traffic flow data, speed data and the like, the events like congestion are determined, position information corresponding to the event data, such as position information corresponding to a map and the like of positioning data, related key points, such as key points like ramps, toll stations and the like, are further determined based on the position information, and corresponding key point data are determined, so that single-point optimization can be performed on roads, highways and the like.
And step 312, performing global path planning according to the path data, and determining corresponding path guidance information.
And step 314, executing control operation on the key points according to the key point control data.
Wherein the execution of at least one of the following control operations on the keypoints in accordance with the keypoint control data: determining speed limit information corresponding to the key points according to the key point control data; controlling the ramp corresponding to the key point according to the key point control data; opening a hard road shoulder corresponding to the key point according to the key point control data; sending prompt information corresponding to the key points according to the key point control data; and opening or closing the toll station corresponding to the key point according to the key point control data.
After the path data and the key point control data are acquired, road traffic can be cooperatively controlled based on the path data and the key point control data. The global path planning can be carried out based on the path data, and the global path planning can regulate and control the path by combining with historical data. And the single-point optimization can be carried out on the key points based on the key point control data, and upstream and downstream traffic is planned.
For example, after a traffic accident occurs, on an expressway, the accident upstream can remind passing vehicles to avoid accident risks in real time, and measures such as opening emergency lanes at accident points can be taken to improve passing speed and reduce travel time. As another example, historical data is used to analyze which road segments are frequently congested, and route guidance is used to correct the driving route of the vehicle in combination with route data. An independent optimization method can be adopted based on specific events, such as severe weather events, speed limitation of all road sections on the expressway can be realized, such as traffic accident events, and information reminding and avoidance can be carried out at the upstream; the upstream lane controller performs stepped speed limiting, and the stepped speed limiting is performed from 100 to 40 in sequence; if the upstream flow is larger than a certain amount, controlling the flow by switching on and off the toll station; an emergency lane is opened near the accident point position, and the traffic is promoted.
Therefore, the management and control information generated by the global and single-point optimization engines can be displayed on the induction screen in real time. And dynamically switching on and off the toll station ramps based on the calculation of the global and single-point optimization engines. And (4) based on the management and control information generated by the global and single-point optimization engines, sending and receiving the information to the passing vehicles at the RSU. And issuing the control information through a navigation Application (APP), realizing in-vehicle information reminding, and finishing a control closed loop.
It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the embodiments are not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the embodiments. Further, those skilled in the art will also appreciate that the embodiments described in the specification are presently preferred and that no particular act is required of the embodiments of the application.
On the basis of the foregoing embodiments, this embodiment further provides a road network data processing apparatus, which is applied to an electronic device of a server device (cluster), as shown in fig. 4.
An obtaining module 402 is configured to obtain road network related sensor data and road network data.
And a traffic flow analysis module 404, configured to determine traffic flow data according to the sensor data and the road network data.
And a road network analysis module 406, configured to perform road network analysis according to the traffic flow data, and determine corresponding path data and key point control data.
And the cooperative control module 408 is configured to perform cooperative control on road network traffic according to the path data and the key point control data.
In summary, sensor data and road network data related to a road network can be acquired, traffic flow data is determined according to the sensor data and the road network data, road network analysis is performed according to the traffic flow data, corresponding path data and key point control data are determined, a path of a global vehicle and local single-point control are analyzed, road network traffic is cooperatively controlled according to the path data and the key point control data, global control and single-point control can be cooperatively executed, the road network is controlled more accurately, and processing efficiency is improved.
Optionally, the traffic flow analysis module is configured to perform time alignment on the sensor data and the road network data; and mapping the aligned sensor data and the aligned road network data into a road network to determine traffic flow data.
Further, the traffic flow analysis module is configured to map the aligned sensor data and the aligned road network data to corresponding road segments of a road network according to the position information; analyzing the data mapped by each road segment, and determining corresponding traffic flow data, wherein the traffic flow data comprises: traffic flow data, vehicle speed data, and/or event data.
Optionally, the road network analysis module includes:
and the path analysis submodule is used for determining the driving track of the vehicle according to the identification information of the vehicle and determining path data according to the driving track.
And the single-point analysis submodule is used for determining position information according to the event data and determining key point control data according to the position information.
The path analysis submodule is used for acquiring positioning data of the vehicle according to the identification information of the vehicle and determining a running track of the vehicle according to the positioning data; and determining the starting position and the terminal position of the vehicle according to the running track, and determining the path data according to the starting position and the terminal position of the vehicle.
The single-point analysis submodule is used for determining corresponding position information according to the event data and determining key points of corresponding road sections according to the position information; and generating key point control data corresponding to the key points.
The cooperative control module is used for carrying out global path planning according to the path data and determining corresponding path guiding information; and executing control operation on the key points according to the key point control data.
The cooperative control module is configured to perform at least one of the following control operations on a key point according to the key point control data: determining speed limit information corresponding to the key points according to the key point control data; controlling the ramp corresponding to the key point according to the key point control data; opening a hard road shoulder corresponding to the key point according to the key point control data; sending prompt information corresponding to the key points according to the key point control data; and opening or closing the toll station corresponding to the key point according to the key point control data.
Therefore, the management and control information generated by the global and single-point optimization engines can be displayed on the induction screen in real time. And dynamically switching on and off the toll station ramps based on the calculation of the global and single-point optimization engines. And (4) based on the management and control information generated by the global and single-point optimization engines, sending and receiving the information to the passing vehicles at the RSU. And issuing the control information through a navigation Application (APP), realizing in-vehicle information reminding, and finishing a control closed loop.
The present application further provides a non-transitory, readable storage medium, where one or more modules (programs) are stored, and when the one or more modules are applied to a device, the device may execute instructions (instructions) of method steps in this application.
Embodiments of the present application provide one or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause an electronic device to perform a method as described in one or more of the above embodiments. In the embodiment of the present application, the electronic device includes various types of devices such as a terminal device and a server (cluster).
Embodiments of the present disclosure may be implemented as an apparatus, which may include electronic devices such as a terminal device, a server (cluster), etc. within a data center, using any suitable hardware, firmware, software, or any combination thereof, in a desired configuration. Fig. 5 schematically illustrates an example apparatus 500 that may be used to implement various embodiments described herein.
For one embodiment, fig. 5 illustrates an exemplary apparatus 500 having one or more processors 502, a control module (chipset) 504 coupled to at least one of the processor(s) 502, a memory 506 coupled to the control module 504, a non-volatile memory (NVM)/storage 508 coupled to the control module 504, one or more input/output devices 510 coupled to the control module 504, and a network interface 512 coupled to the control module 504.
The processor 502 may include one or more single-core or multi-core processors, and the processor 502 may include any combination of general-purpose or special-purpose processors (e.g., graphics processors, application processors, baseband processors, etc.). In some embodiments, the apparatus 500 can be used as a terminal device, a server (cluster), or the like in the embodiments of the present application.
In some embodiments, apparatus 500 may include one or more computer-readable media (e.g., memory 506 or NVM/storage 508) having instructions 514 and one or more processors 502 in combination with the one or more computer-readable media and configured to execute instructions 514 to implement modules to perform the actions described in this disclosure.
For one embodiment, control module 504 may include any suitable interface controllers to provide any suitable interface to at least one of the processor(s) 502 and/or any suitable device or component in communication with control module 504.
The memory 506 may be used, for example, to load and store data and/or instructions 514 for the apparatus 500. For one embodiment, memory 506 may comprise any suitable volatile memory, such as suitable DRAM. In some embodiments, the memory 506 may comprise a double data rate type four synchronous dynamic random access memory (DDR4 SDRAM).
For one embodiment, control module 504 may include one or more input/output controllers to provide an interface to NVM/storage 508 and input/output device(s) 510.
For example, NVM/storage 508 may be used to store data and/or instructions 514. NVM/storage 508 may include any suitable non-volatile memory (e.g., flash memory) and/or may include any suitable non-volatile storage device(s) (e.g., one or more Hard Disk Drives (HDDs), one or more Compact Disc (CD) drives, and/or one or more Digital Versatile Disc (DVD) drives).
NVM/storage 508 may include storage resources that are physically part of the device on which apparatus 500 is installed, or it may be accessible by the device and need not be part of the device. For example, NVM/storage 508 may be accessed over a network via input/output device(s) 510.
Input/output device(s) 510 may provide an interface for apparatus 500 to communicate with any other suitable device, input/output devices 510 may include communication components, audio components, sensor components, and so forth. The network interface 512 may provide an interface for the apparatus 500 to communicate over one or more networks, and the apparatus 500 may wirelessly communicate with one or more components of a wireless network according to any of one or more wireless network standards and/or protocols, such as access to a communication standard-based wireless network, such as WiFi, 2G, 3G, 4G, 5G, etc., or a combination thereof.
For one embodiment, at least one of the processor(s) 502 may be packaged together with logic for one or more controller(s) (e.g., memory controller module) of the control module 504. For one embodiment, at least one of the processor(s) 502 may be packaged together with logic for one or more controller(s) of the control module 504 to form a System In Package (SiP). For one embodiment, at least one of the processor(s) 502 may be integrated on the same die with logic for one or more controller(s) of the control module 504. For one embodiment, at least one of the processor(s) 502 may be integrated on the same die with logic for one or more controller(s) of the control module 504 to form a system on chip (SoC).
In various embodiments, the apparatus 500 may be, but is not limited to: a server, a desktop computing device, or a mobile computing device (e.g., a laptop computing device, a handheld computing device, a tablet, a netbook, etc.) among other terminal devices. In various embodiments, the apparatus 500 may have more or fewer components and/or different architectures. For example, in some embodiments, device 500 includes one or more cameras, a keyboard, a Liquid Crystal Display (LCD) screen (including a touch screen display), a non-volatile memory port, multiple antennas, a graphics chip, an Application Specific Integrated Circuit (ASIC), and speakers.
The detection device can adopt a main control chip as a processor or a control module, sensor data, position information and the like are stored in a memory or an NVM/storage device, a sensor group can be used as an input/output device, and a communication interface can comprise a network interface.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the true scope of the embodiments of the application.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The method and the device for processing power consumption of the IDC, the terminal device and the machine-readable medium provided by the application are introduced in detail, and specific examples are applied in the description to explain the principle and the implementation of the application, and the description of the above embodiments is only used for helping to understand the method and the core idea of the application; meanwhile, for a person skilled in the art, according to the idea of the present application, the specific implementation manner and the application scope may be changed, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. A road network data processing method, characterized in that the method comprises:
acquiring sensor data and road network data related to a road network;
determining traffic flow data according to the sensor data and the road network data;
performing road network analysis according to the traffic flow data, and determining corresponding path data and key point control data;
and performing cooperative control on road network traffic according to the path data and the key point control data.
2. The method of claim 1, wherein said determining traffic flow data from said sensor data and road network data comprises:
time alignment is carried out on the sensor data and the road network data;
and mapping the aligned sensor data and the aligned road network data into a road network to determine traffic flow data.
3. The method of claim 2, wherein mapping the aligned sensor data and the aligned road network data into a road network, determining traffic flow data, comprises:
mapping the aligned sensor data and the aligned road network data to corresponding road sections of the road network according to the position information;
analyzing the data mapped by each road segment, and determining corresponding traffic flow data, wherein the traffic flow data comprises: traffic flow data, vehicle speed data, and/or event data.
4. The method of claim 1, wherein said analyzing the road network based on the traffic flow data to determine corresponding path data and key point control data comprises:
determining a driving track of a vehicle according to identification information of the vehicle, and determining path data according to the driving track;
and determining position information according to the event data, and determining key point control data according to the position information.
5. The method of claim 4, wherein determining the travel track of the vehicle from the identification information of the vehicle and determining the path data from the travel track comprises:
acquiring positioning data of the vehicle according to the identification information of the vehicle, and determining a running track of the vehicle according to the positioning data;
and determining the starting position and the terminal position of the vehicle according to the running track, and determining the path data according to the starting position and the terminal position of the vehicle.
6. The method of claim 4, wherein determining location information from the event data and determining keypoint control data from the location information comprises:
determining corresponding position information according to the event data, and determining key points of corresponding road sections according to the position information;
and generating key point control data corresponding to the key points.
7. The method of claim 1, wherein the cooperative control of road traffic based on the path data and the key point control data comprises:
performing global path planning according to the path data, and determining corresponding path guiding information;
and executing control operation on the key points according to the key point control data.
8. The method of claim 7, wherein the performing of at least one of the following control operations on keypoints in accordance with the keypoint control data:
determining speed limit information corresponding to the key points according to the key point control data;
controlling the ramp corresponding to the key point according to the key point control data;
opening a hard road shoulder corresponding to the key point according to the key point control data;
sending prompt information corresponding to the key points according to the key point control data;
and opening or closing the toll station corresponding to the key point according to the key point control data.
9. An electronic device, comprising: a processor; and
a memory having executable code stored thereon that, when executed, causes the processor to perform the method of any of claims 1-8.
10. One or more machine-readable media having executable code stored thereon that, when executed, causes a processor to perform the method of any of claims 1-8.
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