WO2023142295A1 - 基于无过饱和状态的约定出行管控方法、装置及存储介质 - Google Patents
基于无过饱和状态的约定出行管控方法、装置及存储介质 Download PDFInfo
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- WO2023142295A1 WO2023142295A1 PCT/CN2022/090834 CN2022090834W WO2023142295A1 WO 2023142295 A1 WO2023142295 A1 WO 2023142295A1 CN 2022090834 W CN2022090834 W CN 2022090834W WO 2023142295 A1 WO2023142295 A1 WO 2023142295A1
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/081—Plural intersections under common control
Definitions
- the present invention relates to the technical field of intelligent transportation, and more specifically, it relates to a method, system and storage medium for managing and controlling scheduled trips based on a non-oversaturation state.
- Intersection control under oversaturated conditions has always been a recognized difficulty in the ITS field. This is because: 1) If the stranded fleet in the road section is too long, or even the phenomenon of queue backflow to the upstream occurs, the original point-queue traffic flow model will fail and cannot A simple model is used to describe the ongoing traffic flow changes in the road section; 2) It is difficult for the system to provide accurate departure time for each vehicle arriving at the intersection at the same time, and at most it can only provide an average delay in the case of a fixed timing, so that The traffic forecast of the vehicle loses its due meaning; 3) After the first vehicle enters an oversaturated state, the latter vehicle can find an alternate route, so that the first vehicle at the same origin and destination may leave the current area later than the latter vehicle, Destroying the proper travel order; 4) When oversaturation occurs frequently in the road network, the traveler's pursuit of the shortest individual travel time and the manager's pursuit of the best system performance will gradually deviate from the planning direction, eventually resulting in traffic congestion.
- the domestic patent CN103337167A proposes that motor vehicles should be reserved before traveling, it requires travelers to give the set of routes to be used when making reservations, and there is no countermeasures for travelers to plan again after departure.
- the system provides the traveler with the path planning result according to the starting and ending points of the trip, the path is completely calculated by the real-time detection weight value.
- the travel time is longer than the effective time of the real-time weight value, the planning result It is no longer valid; and the patent application CN108510091A also adopts a similar approach in the processing of the weight.
- Patent applications CN106203662A and CN108986459A proposed a method for controlling road network congestion based on path allocation and dynamic charging. Compared with the method of combining departure delay planning and intersection control, the charging strategy is limited by the sensitivity of travelers to changes in fees. Moreover, the plan does not propose how to accurately estimate the remaining travel time of the route in an oversaturated state. It is impossible to achieve precise control of road conditions, and it is impossible to achieve orderly and reliable travel. There are also patent applications that use congestion charging as a means of control. CN106504530A. Patent applications CN107730877A and CN108492558A that only mention reserved routes but do not give any trajectory control methods for vehicles that have already traveled include. The problem with this type of technical solutions is that the road network may still be oversaturated, and the performance during operation will be different from that expected. The performance achieved varies widely.
- the characteristics of this type of control scheme are: 1) The selected indicators are the average value of the traffic flow attributes of all road sections in the area, which can only represent the approximate degree of congestion in the area, but cannot be finely managed to any road section and intersection; 2) cannot Accurately estimate the moment when the threshold falls back, so it is impossible to provide accurate travel time predictions for vehicles that are about to enter the area, and can only communicate with travelers in a mandatory rather than guiding way. Therefore, the threshold control method is only suitable for the realization of extensive and stress-based traffic resource management and control rather than fine-grained and proactive anticipation.
- MFD research in 2016 constructed a planning model that considered traffic flow parameters and signal control parameters such as phase difference. But until the present invention puts forward the application, the MFD model still has the following limitations: 1) due to the limitation of its calculation method, the model has only been applied in the simple road network (based on a single arterial road), and the complex road network topology and The derivation work under regional signal control still needs to be improved; 2) The MFD model does not emphasize the orderliness of vehicle travel, that is, there is no measure to ensure that the vehicle FIFO (first-in, first-out) criterion is established in the area; 3) More importantly, The MFD model does not have any measures to ensure that the intersections through which the traffic flows are not oversaturated. Therefore, the current MFD-based modeling ideas cannot achieve a stable, orderly, and reliable vehicle-road coordination mechanism design.
- a reasonable design of the agreed travel mechanism and vehicle-road coordination system can not only meet the requirements of stability, order, and reliability for motor vehicle travel, but also will not sacrifice the system's ability to further control supply and demand. On the contrary, fine adjustment of traffic flow should be given. Provides new possibilities for expansion. In terms of fine-grained control of traffic flow, one of the applications most closely related to the state of the road network is crossing intersections without parking. Although foreign countries have proposed hardware products that pass through intersections without stopping according to signal parameters, they generally can only work when the green light is green and there is no stranded motorcade ahead of the road.
- patent CN108682168A passes through signalized intersections without stopping by reducing the speed of the vehicle, which can extend the application scenario to any signal condition, but these solutions, like existing hardware products, require Solve two common problems: 1) How to obtain an accurate estimate of the queue dissipation time if the intersection is already in an oversaturated state; 2) How to prevent other vehicles from jamming in front of the platoon when the platoon slows down, thus disturbing the platoon There are travel plans.
- the existing technical solutions can only be applied in relatively simple scenarios, such as the road network or intersection control timing parameters of a single main road (thus ensuring that conflicting traffic flow will be polite) does not occur dynamically Varying (thus ensuring that delay estimates are largely accurate) road network.
- the technical problem to be solved in the present invention is how to predict the traffic situation at each moment (that is, the "approximate” of "agreed travel") through traffic organization conditions and intelligent traffic interaction data, as a peak shift
- the management and control basis of travel so as to guide vehicles into the road network in an orderly manner, and arrive at the destination step by step (that is, the "fixed” of "agreed travel”).
- the first object of the present invention is to provide a method for managing and controlling scheduled trips based on the non-oversaturation state, so as to solve the periodic congestion on the road network caused by disorderly trips of motor vehicles.
- the second object of the present invention is to provide an agreed trip management and control device based on the non-oversaturation state, so as to solve the periodic congestion on the road network caused by the disorderly travel of motor vehicles.
- the third object of the present invention is to provide a computer-readable storage medium.
- the present invention provides a method for managing and controlling scheduled trips based on the non-oversaturation state, which includes the following steps:
- Step S1 predetermine the road network management and control area, and input the maximum carrying capacity, preset traffic organization, time quantification unit, and signal cycle length parameters of each road network section into the management and control center system, and calculate the static data of the road network;
- Step S2 after the management and control center system obtains the classification data of all travel traffic volumes divided by origin-destination OD and check-in time, combined with the road network static data in step S1, calculates the timing parameters for the traffic flow to reach the layout without oversaturation, and Send the timing parameters to the intersection control system and travel assistance system;
- Step S3 the intersection control system restricts the flow rate of the signal phase of the intersection to ensure that the number of vehicles passing through each cycle does not exceed the number of vehicles rated by the timing parameters;
- Step S4 all motor vehicles entering the road network management and control area travel according to the agreement of the travel assistance system.
- the complete travel steps include making an appointment, checking in and waiting, departing at the time arranged by the system, and following the traffic organization and intersection after departure. Control and complete the journey according to the global optimal steering selection;
- Step S5 if the set conditions are satisfied, the motor vehicle is allowed to adjust the driving speed, so as to realize travel without parking in the road section.
- step S1 includes the following steps:
- Step S11 inputting the topological structure of the road network management and control area into the management and control center system in the form of high-precision electronic map data, the management and control center system determines the static traffic organization information of the road network management and control area, static traffic organization
- the information includes the maximum carrying capacity and the maximum speed limit of each road section, and when using the fixed-period signal control mode, it also includes the sequence of vehicles moving in each phase when conflicts occur at each intersection, and the minimum movement that each phase of the intersection must pass through within a cycle traffic flow;
- Step S12 determining the dynamic standard time unit of the road network control area according to the static traffic organization information determined in step S11;
- Step S13 calculate the quantified road network static data according to the standard time unit determined in step S12, the road network static data includes the free travel time from the entrance of the road section to the next intersection, and the free travel time is the standard time unit Integer multiples, and the speed of the vehicle in the road section after quantification does not exceed the original maximum speed limit.
- step S2 the origin-destination OD data is obtained through the reservation mode or the self-adaptive mode, and the high-precision time data of the traveler’s multiple check-in actions are processed according to statistical rules to obtain the check-in time.
- the cycle and calculation rules are pre-determined by the system, and according to the set criteria, the departure time of the traffic flow balance layout, the dynamic path, and the planning of the intersection control collaborative optimization are calculated to calculate the timing parameters; preferably, the timing parameters include the time sequence parameters per unit time The flow rate of the decision point, the optimal travel time index value established by the decision point, the traffic volume that can depart in this cycle, the waiting time at the entrance, the virtual traffic flow rate, the acceptable traffic flow at the intersection, and the additional virtual traffic flow pool.
- step S3 measures to limit flow include traffic dynamic organization of urban road network, signal control mode, ramp control at expressway intersection, and travel assistance system control.
- the virtual traffic flow rate, The acceptable traffic flow at the intersection and the additional virtual traffic flow pool three parameters determine the proportion of passing and prohibiting time of each phase in each cycle.
- the carrier of the travel assistance system is a vehicle-mounted terminal or a smart phone, and the wireless communication method of the carrier is mobile communication or Internet of Vehicles communication; after the traveler completes the reservation action by connecting to the cloud server, the traveling vehicle completes the travel activity according to the following steps :
- Step S21 the vehicle indicates that it can leave at any time through the remote check-in method, and the travel assistance system records this check-in time as high-precision time data and uploads it to the management and control center system.
- Step S22 After receiving the departure delay value assigned by the management and control center system, the travel assistance system allows the vehicle to wait in the same place or in the virtual parking lot from the check-in time through exclusive signal control or travel itinerary prediction and guidance information, until the management and control center The optimal departure time planned by the system will enter the road network. In the reservation mode, if the vehicle has not reported before the assigned optimal departure time, it will be considered as giving up the current scheduled travel opportunity;
- Step S23 when the vehicle departs, the travel assistance system continuously provides the vehicle with updated dynamic route planning information services under the premise of following the static traffic organization arrangement and system intersection control, so that each time the vehicle enters a new decision point , the path can be re-planned to ensure that the vehicle always travels on the space-time path with the optimal global travel time;
- Step S24 optional, the travel assistance system generates a travel summary of the day after the traveler completes the itinerary, and shows the traveler the driving trajectory of the day, the reason for the non-periodic delay, and whether there is a better travel plan information.
- step S22 when the departure delay value is assigned, the order of the first-in-first-out FIFO in the road network control area is followed, and the vehicles with the same OD and the same level set off and enter the road network in the order of check-in, and also Arrive at the destination in the same sequence; at the same time, if there is no delay caused by accidental events in the road network, the vehicles after departure enjoy the passage time of free flow under the static traffic organization;
- the traffic volume that can depart in this period and the waiting time at the entrance determine the traffic flow that can depart in this period and the delay that vehicles staying at the entrance still need to wait.
- step S23 the path is re-planned by means of path switching or based on a dynamic steering mode, including the following steps:
- Step S31 when the vehicle enters the decision point, the travel assistance system allows the vehicle to reselect the space-time path with the shortest travel time at the decision point according to the updated road conditions of the road section and the traffic forecast behind each special item;
- Step S32 when driving in the road section from the decision point to the bottleneck point, the travel assistance system will limit the driving speed of the vehicle formation.
- the process of formation driving in addition to completing the lane-changing actions necessary for the planned steering in the selection step S31, it has been exercising within the allowable speed range, neither overtaking behaviors that are not authorized by the system are allowed, nor are normal vehicles Stuck in the space-time position where it should travel normally, forming a new bottleneck;
- the travel time index value established by the decision point and the additional virtual traffic flow pool to determine the optimal steering option and the upper limit of the vehicle that can be accommodated at each decision point in each unit time.
- step S32 if there is no possibility of non-periodic delay events in the road section, the management and control center system can further give a specific recommended speed, so that the formation vehicles can safely pass from the decision point to the bottleneck point at a constant speed In the area of the road section, the number of stops and acceleration and deceleration is reduced to improve driving comfort and reduce energy consumption and emissions required for travel.
- the present invention provides an agreed travel control device based on no oversaturation state
- the control device includes a processor and a memory; the memory is used to store program codes, and transmit the program codes to the processing The processor; the processor is configured to execute the above-mentioned method according to the instructions in the program code.
- the present invention provides a computer-readable storage medium, the computer-readable storage medium is used to store program code, and the program code is used to execute the above-mentioned method.
- the present invention has the advantages of:
- Travelers travel in an orderly manner. In the balanced distribution of traffic flow maintained by the system, as long as there is no emergency, the travel trajectory of travelers will follow the first-in-first-out FIFO rule. Sequentially leave the same road segment), path first-in-first-out (vehicles of the same class leave the same path in the order they entered the path), and OD first-in-first-out (vehicles of the same type leave the road network in the order they entered the road network).
- the same type of vehicle is the vehicle with the same user level and the same OD.
- the traffic forecast is accurate and reliable. By setting up the path planning index value at the decision point in the road network, it provides a rational decision-making basis for travelers. As long as travelers act according to the travel plan recommended by the system after departure, the time difference between the actual travel result and the recommended plan will be small. Will not exceed one signal cycle length.
- the present invention realizes stable, orderly, and reliable balanced distribution of traffic flow in road network planning, and then establishes a benign trust between traffic managers and travelers by means of stable, reliable, orderly, and orderly. cycle to further reduce the uncertainty of the system in the event-free state.
- traffic managers can still manually or regularly update the balanced distribution of traffic flow in response to mid-to-long-term changes in traffic travel demand, so that the balanced distribution design will not be too rigid due to changes in demand.
- the present invention guides the travel plan through the traffic forecast accurate to the period, which itself has the technical feature of off-peak travel.
- the present invention is based on the theoretical basis of three-layer fixed points, which not only conforms to the optimal interests of users but also considers the optimal criteria of the system, so that users can voluntarily follow the arrangement of the system, And in a specific way, the peak-staggered travel plan with the time accuracy as the unit period is realized, which has the basic characteristics of reasonableness and precision.
- the invention can help traffic managers to optimize the automatic driving scene in a targeted manner, reduce the difficulties caused by roadside perception and vehicle perception caused by road slowing or congestion, thereby improving the realizability of automatic driving, and is expected to be able to pass low-level management and control technology Realize high-level automatic driving business, and clarify the time-space ownership of the road network, make the responsibility for traffic incidents more clear, and further reduce the difficulty and processing time when emergencies occur.
- Fig. 1 is the flow chart of the state appointment travel method without supersaturation state among the present invention
- Fig. 2 is the position setting figure of decision point and bottleneck point in standard crossing scene among the present invention
- Fig. 3 is the incremental characteristic schematic diagram of Webster function among the present invention.
- Fig. 4 is a schematic diagram of expanding the starting point into a virtual parking lot in the present invention to recombine each OD component in the starting flow;
- Fig. 5 is a schematic diagram of traveling without parking in the present invention.
- the realization of road network traffic supply and demand balance can be divided into two stages, including the "approximate” stage of formulating road network traffic flow layout parameters based on travel demand deduction, and making decisions based on the results of these parameters.
- Guidance to maintain the "set" phase of the traffic flow layout In order to develop a stable, orderly and reliable road network traffic flow layout.
- Figure 1 shows the implementation steps of the agreed travel mechanism proposed by the present invention.
- the core of its system design idea is to combine reasonable mechanism design on the basis of maintaining no oversaturation state and FIFO rule, and then unify the route
- the network manager (that is, the optimal system) and the traveler (that is, the user balance) plan the travel activities of motor vehicles, thereby forming a stable, orderly, and reliable layout, and further realizing the non-parking formation driving under the satisfied conditions .
- the non-oversaturation state proposed in Figure 1 and below is derived from the extension of the concept of traffic signals, and its actual definition is that before the start of the next cycle, the traffic flow at any node position (such as the bottleneck point before the intersection) can be obtained Opportunity to leave the current node position.
- the so-called first-in-first-out FIFO criterion requires travelers of the same level to: 1) leave the road segment in the same order as they entered the road segment; 2) leave the road segment in the same order as they entered the road segment; 3) if With the same OD, they leave the road network in the same order as they entered the road network.
- the agreed travel control method based on the non-oversaturation state includes the following steps:
- Step S1 predetermine the road network management and control area, and input the maximum carrying capacity of each road section of the road network, preset traffic organization, time quantification unit, and signal cycle length parameters into the management and control center system, and calculate the static data of the road network;
- step S2 the management and control center system obtains the classification data of all travel traffic volumes divided by origin and destination OD and check-in time, and combines the static data of the road network in step S1 to calculate the timing parameters for the traffic flow to reach the non-oversaturation state layout, and compare the timing The parameters are sent to the intersection control system and travel assistance system;
- Step S3 the intersection control system performs flow limitation and steering guidance on the signal phase of the intersection to ensure that the number of vehicles passing through each cycle does not exceed the number of vehicles rated by the timing parameters;
- Step S4 all motor vehicles entering the road network management and control area travel according to the agreement of the travel assistance system.
- the complete travel steps include making an appointment, checking in and waiting, departing at the time arranged by the system, following the traffic organization and intersection control after departure, and always following the Global optimal steering selection to complete the journey;
- step S5 the motor vehicle is allowed to adjust the driving speed under the condition that the set conditions are satisfied, so as to realize travel without parking in the road section.
- Step S1 comprises the following steps:
- Step S11 input the topological structure of the road network control area into the control center system in the form of high-precision electronic map data, the control center system determines the static traffic organization information of the road network control area, the static traffic organization information includes the maximum speed limit of each road section, When each intersection conflicts, the sequence of vehicles moving in each phase, and the minimum mobile traffic flow that each phase of the intersection must pass through within a cycle.
- Step S12 determine the dynamic standard time unit and signal cycle length of the road network control area according to the static traffic organization information determined in step S11; specifically, after estimation, the control center system provides a reasonable parameter range, where the standard time Between the unit and the length of the signal cycle, there can be many ways to realize travel without oversaturation in the region, but the simplest and purest embodiment is to set the standard time unit and the unified signal cycle length of the whole road network to be the same Length, that is, the entire historical (or simulated) travel peak period [0, T C ] can be divided according to the length of the signal cycle:
- C 0 is the unified signal cycle length, which is pre-determined by the system; m is an integer time variable, and m C is defined as
- the operator [x] + represents the smallest positive integer not less than x.
- Step S13 calculate the quantified road network static data according to the standard time unit determined in step S12, the road network static data includes the free travel time from the entrance of the road section to the next intersection, and the free travel time is the standard time unit Integer multiples, and the speed of the vehicle in the road section after quantification does not exceed the original maximum speed limit.
- variable speed limit In order to realize the synchronization of traffic flow at the intersection, the free travel time of all road sections should be quantified as a multiple of the unified signal cycle length, that is, the following relationship is guaranteed by means such as variable speed limit
- the node a is the entry point of the steering ab, and it is also the location where the vehicle completes the dynamic steering selection decision, so it is called the decision point;
- the node a′ is the location where the steering enters the intersection, and it is also the location where the queue is formed in the point queue model, so Can be called the bottleneck point.
- the positions of decision points and bottleneck points at four-phase intersections are shown in Figure 2.
- d a'b (m) is the delay time experienced by the traffic flow when it arrives at the intersection at time m.
- the signal delay must be a function related to the traffic flow, that is, the greater the traffic flow to the intersection, the higher the delay time.
- the traffic flow arriving at the intersection must be automatically limited in the network allocation stage.
- the present invention proposes a design called projected supplementary delay to accomplish automatic flow limitation at intersections.
- the so-called estimated supplementary delay means that during traffic allocation, an additional punitive delay is designed at each intersection.
- the traffic estimate will inform the rear vehicles of a higher delay value to encourage The rear vehicle is temporarily delayed entering the intersection queue; if the rear vehicle still insists on entering the intersection through the turn, the phase red light will execute the punitive delay.
- the design or selection of supplementary functions is a relatively important pre-planning work. From the above design goals, we can see that the selection of the expected supplementary function has the following differences from the selection of the signal delay estimation function: (1) the estimated supplementary delay function can be slightly greater than the actual delay, but in any case must not be less than the actual delay; (2) the estimated supplementary The choice of delay function should reflect the principle that the larger the input traffic flow, the higher the penalty delay. On the basis of these two points, it is estimated that the supplementary delay function should be as close as possible to the actual delay in the non-oversaturated stage to reduce the consumption of road network capacity. In one embodiment, the Webster model is chosen as the estimated supplementary delay function, and its characteristics are shown in FIG. 3 . Although this function cannot accurately describe the intersection delay in the oversaturated state, it can be seen from Figure 3 that it can fully achieve the purpose of discouraging vehicles from flooding into the intersection at one time. Therefore, in the following embodiments, the signal delay estimation can be defined as:
- f(m) is the traffic flow arriving at the intersection at time m
- r(m) is the red signal ratio of steering/phase at that time.
- the so-called quasi-free flow state means that the traffic flows from each turning decision point to the bottleneck point in a free flow state, and then completely passes through the intersection from the bottleneck point after a unit time to reach the destination or the next decision point.
- the minimum travel time of quasi-free flow from decision point a to destination s is defined as Once the segment travel time quantification in step S1 is completed, it is obvious that this time is the shortest time for the vehicle to complete the desired trip.
- step S2 after the management and control center system obtains the classification data of all travel traffic volumes divided by origin-destination OD and check-in time, combined with the static data of the road network in step S1, it calculates the timing parameters for the traffic flow to reach the layout without oversaturation, and Send the timing parameters to the intersection control system and travel assistance system;
- the multi-layer fixed-point model is used to design the stable state of the road network in terms of dynamic route planning, signal coordination control and departure time planning.
- the dynamic optimization process of traffic flow equilibrium distribution can be expressed by six NCP inequalities, namely:
- ETA Estimation Time of Arrival, the fastest time to reach the destination
- RSA Red-Signal Anti-Stage, minimum red signal delay phase index value is the traffic prediction made by the system for route planning and signal optimization.
- Table 2 further shows the analogy relationship of the two index values.
- the computing system can optimize the original traffic flow layout to an equilibrium state. Combined with the setting of no supersaturation state and FIFO criterion, the above calculation can be simplified to a certain extent. Finally, the key parameter group at each moment in the equilibrium state can be obtained as
- This parameter group is the timing parameters, which represent the important parameters for maintaining a stable, orderly, and reliable road network during the peak travel period, which in turn includes the flow rate of the decision point per unit time, the ETA index value established at the decision point, and the current period.
- Departure traffic volume, waiting time at the entrance (departure delay), road section virtual traffic flow rate (ie red letter ratio multiplied by road section saturation flow rate), RSA index value established at each intersection, additional virtual traffic flow pool (ie The additional red letter ratio is multiplied by the section saturation flow rate).
- the traffic control center system sends these parameters to the intersection control system of each intersection (including the road network entrance) and the OBU of all users.
- the road network will adopt certain constraints and idleness to effectively control the traffic flow, that is, it has entered the "fixed" stage in the agreed travel mechanism.
- step S3 the intersection control system limits the flow rate of the signal phase of the intersection to ensure that the number of vehicles passing through each cycle does not exceed the number of vehicles rated by the timing parameters;
- the present invention proposes an intersection control method that faces the entire control road network area and completes step S3. Its implementation method can be the traffic signal control method of the urban road network, or the ramp control of the expressway intersection, or even rely on the travel assistance system Controlled guidance and control.
- the goal of the present invention is not to distribute the right of way of the intersection to as much traffic volume as possible, but to distribute the appropriate impedance to the traffic volume passing through the intersection, which meets the requirements of the control center system when the vehicle departs.
- the delay phase of the red signal and the length of the clearing phase of the intersection can be specifically determined by the r m , ⁇ m , r e m of the timing parameters of each phase, that is, the time ratio between the control passage and the prohibition time, Complete the functions of supporting route travel time in traffic forecasting and realizing automatic flow limitation.
- the carrier of the travel assistance system is a vehicle-mounted terminal or a smart phone, and the wireless communication mode of the carrier is mobile communication or Internet of Vehicles communication (DSRC dedicated to Internet of Vehicles); after the traveler completes the reservation action by connecting to the cloud server, the traveling vehicle Follow the steps below to complete your travel activity:
- DSRC Internet of Vehicles communication
- Step S21 the vehicle indicates that it can leave at any time through the remote check-in method, and the travel assistance system records this check-in time as high-precision time data and uploads it to the management and control center system.
- Step S22 After receiving the departure delay value assigned by the management and control center system, the travel assistance system allows the vehicle to wait in the same place or in the virtual parking lot from the check-in time through exclusive signal control or travel itinerary prediction and guidance information, until the management and control center
- the accuracy of the optimal departure time is the standard time unit. In the reservation mode, if the vehicle has not reported before the assigned optimal departure time, it will be considered as giving up the current reservation travel opportunities;
- Step S23 when the vehicle departs, the travel assistance system continuously provides the vehicle with updated dynamic route planning information services under the premise of following the static traffic organization arrangement and system intersection control, so that each time the vehicle enters a new decision point , the path can be re-planned to ensure that the vehicle always drives on the space-time path with the optimal travel time;
- Step S24 optional, the travel assistance system generates a travel summary of the day after the traveler completes the itinerary, and shows the traveler the driving trajectory of the day, the reason for the non-periodic delay, and whether there is a better travel plan information.
- step S22 when the departure delay value is assigned, the order of the first-in-first-out FIFO in the road network control area is followed, and the vehicles with the same OD and the same level set off and enter the road network in the order of check-in, and also follow the same order. Arrive at the destination sequentially; at the same time, if there is no delay caused by accidental events in the road network, the vehicles after departure enjoy free travel time under static traffic organization.
- the traffic flow of all entrances entering the road network at each moment can be determined through h m and w m of the timing parameters.
- the traffic entering the road network is reconstructed through the concept of virtual parking lot before entering the road network officially, so as to achieve the best effect of traffic control.
- the specific operation steps are as follows:
- step S23 the path is re-planned by means of path switching or based on a dynamic steering mode, including the following steps:
- Step S31 when the vehicle enters the decision point, the travel assistance system allows the vehicle to reselect the space-time path with the shortest travel time according to the updated road conditions of the road section and the traffic forecast behind each special item at the decision point. Road, switch to the required steering;
- Step S32 when driving in the road section from the decision point to the bottleneck point, the travel assistance system will limit the driving speed of the vehicle formation (for example, give the speed range), and the limitation follows the first-in-first-out order concept in the road section, so that During the process of driving in formation on the road section, the vehicles of the same level have been running within the allowable speed range except for completing the necessary lane change action planned by the selection step S31. It will not allow normal running vehicles to stay in the space-time position where they should travel normally, forming a new bottleneck;
- the flow induction and flow limitation in the road section are completed according to the timing parameters f m , ⁇ m , r e m , and the specific operation steps are as follows:
- the vehicle (user) will obtain the latest road segment travel time estimate at the decision point a at time m, and when it reaches the next decision point after passing through optional turns (such as going straight, turning right, turning left, and turning around, etc.),
- the ETA index value obtained by the new decision point, the sum of the two is used as the traffic forecast of the turn, and the turn a + with the smallest traffic forecast value is always selected until the journey is completed.
- the ETA index value will introduce the expected supplementary delay to correct the traffic forecast value, complete the persuasion of rushing vehicles, and achieve the effect of automatic flow limitation. In this way, the same OD traffic flow departing at the same time is always in the same dynamic and stable space-time envelope during the travel process, which facilitates the system to achieve orderly and reliable service goals.
- step S32 if there is no possibility of non-periodic delay events in the road section, the management and control center system can further give a specific recommended speed, so that the formation vehicles can safely pass through the road section from the decision point to the bottleneck point at a constant speed Areas, reducing the number of stops and accelerations and decelerations to improve driving comfort and reduce energy consumption and emissions required for travel.
- step S4 travel according to the agreement of the travel assistance system, and the vehicle-associated user needs to meet the following requirements during the travel process:
- step S5 due to the current limiting measures in steps S1 to S4, the traffic flow in each section of the road network has reached the state of no oversaturation, if the current section can exclude other non-periodic delay factors, then it can be passed
- the simple dynamic variable speed limit method adjusts the driving speed of motor vehicles, realizes non-stop travel between the decision point and the bottleneck point of the current road section, and eliminates the waiting action of the fleet at the bottleneck point.
- Figure 5 shows the schematic diagram of the principle of travel without parking. According to the settings in the figure, the dynamic speed limit between the decision point a and the bottleneck point a' can be set as
- ⁇ ja is the phase obtained by the traffic flow in the intersection entering the road section aa'
- ⁇ ja' is the phase difference when turning to aa' to enter the intersection.
- the control device includes a processor and a memory; the memory is used to store program codes and transmit the program codes to the processor; the processor is used to The instructions in the above program code execute the above method.
- a computer-readable storage medium the computer-readable storage medium is used to store program code, and the program code is used to execute the above method.
- the agreed travel mechanism in the present invention also has the characteristics of stability, order and reliability. For individual drivers, these characteristics include: 1) In the traffic flow layout of the road network realized by the system based on optimal parameters, if the road network is not affected by aperiodic factors, then the user can plan or summarize what he has learned afterwards. The dynamic optimal travel plan that can be found is still the original travel plan provided by the system; 2) The basic order of FIFO is established between the travel of users of the same level and the same OD, so as to ensure basic fairness; 3) As long as the travel provided by the system is executed Plan, the difference between the user's arrival time at the destination and the traffic forecast provided by the system will not exceed one uniform time unit.
- the above method ensures that the main delays of travel vehicles are formed before departure by realizing the traffic flow layout without oversaturation, and the delays at all intersections on the way do not exceed one signal cycle.
- the realization of no-stop travel can Reducing unnecessary vehicle acceleration and deceleration can minimize energy consumption and carbon emissions, and improve the comfort of drivers and passengers.
- the agreed travel mechanism allows the traveler to continuously examine the travel plan on the way, and choose the optimal steering according to the latest road conditions, rather than forcing them to always drive on a specific path. Therefore, although the methods mentioned in the above steps cannot be directly applied to road network traffic flow guidance under the influence of non-periodic events, because vehicles retain the ability to adapt to changes, by achieving no oversaturation and deploying ETA index values, agreed travel The mechanism still provides a relatively complete basis for traffic flow layout and available path information for the formulation of corresponding scenario guidance strategies. More specifically, if the impact of non-periodic events can be reasonably quantified, then by making corresponding corrections to the ETA index value and setting reasonable correction trigger conditions for different events, the corresponding traffic flow management can be quickly formulated Strategy.
- the present invention has deeper theoretical support for path allocation, and the behavior of motor vehicle users is more stable. Therefore, it can not only provide a basis for safety responsibility for automatic driving, but also take into account road safety. overall network efficiency.
- the no-oversaturation state mechanism can be applied to smart roads, and combined with the agreed trips of the urban road network to achieve high-precision and high-density off-peak trips during peak travel periods during holidays.
- the road network manager implements the above step 1, and through simulation, for example, assuming that all users start according to their intentions and enter the road network with the shortest distance, obtain the parameter m C of the end time of the travel simulation peak hour;
- the dispatching method in the above example can be further expanded and improved. For example, by dividing travel in lanes and using rest areas as buffer zones, the requirements for the agreed travel mechanism of road networks in surrounding cities can be reduced for off-peak travel during holidays. This extension should also belong to the protection scope of this patent.
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Abstract
基于无过饱和状态的约定出行管控方法，涉及智能交通技术领域，解决机动车无序出行给道路路网造成的周期性拥堵的技术问题，方法包含以下步骤：步骤S1，预先确定路网管控区域，并计算得到路网静态数据；步骤S2，管控中心系统根据起讫点、报到时刻、路网静态数据计算得到时序参数；步骤S3，交叉口控制系统根据时序参数进行流量限制；步骤S4，所有进入路网管控区域的机动车按照出行辅助系统的约定出行；步骤S5，在满足设定条件下，允许机动车对行车速度进行调节，实现路段内无停车出行。
Description
本发明涉及智能交通技术领域，更具体地说，它涉及基于无过饱和状态的约定出行管控方法、系统及存储介质。
在现实中，除了一部分由交通事故、恶劣天气等偶然因素引发的非周期性堵塞事件，路网出行高峰时段大部分拥堵问题的根本成因都是交通供给和需求之间的结构性失衡。这是由于经济的快速发展，城市机动车保有量的不断增加，使得路网中交通设施的建成速度和匹配程度已无法跟上机动车出行量的快速变化，造成周期性的拥堵现象不断地随机出现在道路路网的各个区域，导致了路网行驶速度降低、出行时间延长且不确定性增加、车辆燃料消耗增加以及空气污染、噪声污染增加等一系列社会经济影响。
要解决道路周期性拥堵问题，依靠大量的基建投入来提高交通供给固然不现实，而通过限购限行等政策，对机动车的消费和使用进行一刀切的遏制，这种做法既不能持续，也不利于车联网技术的未来发展。目前相关领域的共识是，基于智能交通系统ITS，一方面有序引导交通需求，另一方面对现有交通设施资源存量进行精细化与信息化管理，提高路道路网对出行需求动态变化的主动适应能力，从而为进一步的供需管控措施提供系统支撑与技术基础。
结合车联网与自动驾驶等信息领域的最新技术成果，各种基于车(如动态路径规划)路(如信号优化控制、匝道控制)协同的路网管控方案层出不穷，但是绝大部分方案中并没有针对路网交通态势施加出发延时这一处理方式，也就是允许出行者“抬腿就走”地进入路网。由于出行量和出发时刻本身具有不确定性，系统缺乏出发延时规划的直接后果，就是路网中将几乎不可避免地出现过交通流量饱和现象，即路网中已形成的滞留车队需要经两个周期及以上的时间才能分批次离开当前路口。过饱和状态下的路口控制向来是ITS领域公认 的难点，这是因为：1)如果路段中滞留车队过长，甚至发生队列倒灌至上游现象，会导致原有的点队列交通流模型失效，无法通过简单的模型描述路段中正在发生的交通流变化；2)系统很难向同时到达路口的每一辆车提供准确的离开时间，最多只能在固定配时的情况下提供一个平均延误，使车辆的交通预测失去了应有的意义；3)先发车辆进入过饱和状态后，后发车辆可以寻找备用路径，使得同一起讫点的先发车辆有可能比后发车辆更晚离开当前区域，破坏了应有的出行秩序；4)当路网中过饱和现象频发时，出行者追求个体总行程时间最短和管理者追求系统性能最优的规划方向就会逐渐偏离，最终造成车路两者在各自优化过程中互相抗衡，建模的复杂性迫使有些模型甚至同时放弃了系统最优和个体均衡两种目标，转而追求自动化控制的瞬态平稳，丧失了系统管控的实际意义。更糟的是，系统的不稳定、无序、不可预测等特性又会进一步激发出行者的焦虑，让车辆更加争先恐后地进入路网，造成一系列的恶性循环，放大了原本的不确定性，从而进一步加剧车路协同系统的建模困难、计算困难以及互通困难。
国内专利CN103337167A虽然提出了机动车在出行前应先预约，但要求出行者在预约时要给出拟采用的路径集合，而对出行者在出发后进行再规划没有任何应对引导措施。在国内专利CN1038224467A提出的方案中，虽然系统根据出行的起讫点向出行者提供了路径规划结果，但该路径完全通过即时检测权值算得，当行程时间长于即时权值的有效时间，该规划结果就不再有效；而专利申请CN108510091A在权值的处理上也采用了类似的做法。
专利申请CN106203662A和CN108986459A提出了一类基于路径分配和动态收费管控路网拥堵的方法，相对于出发延时规划与交叉口控制结合的做法，收费策略受限于出行者对费用的敏感度变化，且方案未提出过饱和状态下如何准确估计路径剩余的行程时间，无法做到对路况的精确管控，也就不可能实现出行的有序和可靠；同样采用拥挤收费作为管控手段的还有专利申请CN106504530A。仅仅提及预约路径而没有给出任何已出行车辆轨迹控制方法的 则包括专利申请CN107730877A和CN108492558A，这类技术方案的问题同样在于路网依旧可能出现过饱和状态，在运行中的表现会与预计达到的性能大相径庭。
国内专利CN102938210A和CN106529703A通过区域信号控制的方式实现了较为初步的车辆轨迹控制：当区域内交通流分布令某些指标(分别是路段交通强度平均值和平均车流量)超过阈值，系统就开始通过区域边缘交叉口的信号限制其他车辆再进入该区域，限行措施会一直持续到指标回落或高峰时段结束。这类控制方案的特点是：1)所选指标都是区域内所有路段交通流属性的平均值，只能代表区域大致的拥挤程度，却无法精细管理到任意的路段和交叉口；2)不能准确估计阈值回落的时刻，因而也无法向即将进入该区域车辆提供精准的行程时间预测，只能以强制性而非引导性的方式与出行者沟通。因此，阈值控制的方式只适合实现粗放化、应激型而非精细化、主动预判型的交通资源管控。
在交通理论方面，2016年MFD研究构造过一个将交通流参数与相位差等信号控制参数一起考虑的规划模型。但直至本发明提出申请为止，MFD模型仍存在以下限制：1)由于其计算方法的局限性，模型仅在简单路网(以单条主干道为主)中得到过应用，复杂路网拓扑结构和区域信号控制下的推导工作仍有待完善；2)MFD模型不强调车辆出行的有序性，即没有任何保证车辆FIFO(先进先出)准则在区域内成立的措施；3)更重要的是，MFD模型没有任何措施保障交通流所经过交叉口达到无过饱和状态。因此，基于目前MFD的建模思路也无法实现稳定、有序、可靠的车路协同机制设计。
设计合理的约定出行机制与车路协同系统，不仅能满足机动车车辆出行对稳定、有序、可靠方面的要求，还不会牺牲系统进一步进行供需管控的能力，相反应当给交通流的精细调节提供新的扩展可能。在交通流精细管控方面，与路网状态联系最紧密的一个应用就是无停车过交叉口。尽管国外已经提出了根据信号参数无停车通过交叉口的硬件产品，但一般只能工作在绿灯且道路前方 无滞留车队的情况下。一些与减少交叉口停车次数有关的技术专利——如专利CN108682168A通过降低车速以不停车方式通过信号交叉口，可以将应用场景推广到任何信号状况下，但这些方案与已有硬件产品一样，需要解决两个共通的问题：1)如果交叉口已经存在过饱和状态，如何获得准确的队列消散时间估计；2)如何在车队降低速度期间，防止有别的车辆加塞到车队前方，从而扰乱车队既有的行进计划。为了解决或回避上述两个问题，已有技术方案只能应用在较为简单的场景中，例如单条主干道(由此保证冲突交通流会礼让)的路网或交叉口控制配时参数不发生动态变化(由此保证延误估计基本准确)的路网。
显然，现有技术均不能很好地解决机动车无序出行给道路路网造成的周期性拥堵的问题，同时也无法在此基础上构建真正实用的无停车行驶机制。
发明内容
针对现有技术的上述不足，本发明要解决的技术问题是如何通过交通组织条件和智能交通交互数据，预测得出每个时刻交通态势(即“约定出行”的“约”)，作为错峰出行的管控基础，从而有序引导车辆进入路网，并按部就班地抵达目的地(即“约定出行”的“定”)。
更具体的，本发明的目的一是提供基于无过饱和状态的约定出行管控方法，以解决机动车无序出行给道路路网造成的周期性拥堵。
本发明的目的二是提供基于无过饱和状态的约定出行管控装置，以解决机动车无序出行给道路路网造成的周期性拥堵。
本发明的目的三是提供一种计算机可读存储介质。
为了实现上述目的一，本发明提供基于无过饱和状态的约定出行管控方法，包含以下步骤：
步骤S1，预先确定路网管控区域，并将路网各路段最大承载力、预置交通组织、时间量化单位、信号周期长度参数输入到管控中心系统，计算得到路网 静态数据；
步骤S2，所述管控中心系统获得所有出行交通量按起讫点OD及报到时刻划分的分类数据后，结合步骤S1的路网静态数据，计算出交通流达到无过饱和状态布局的时序参数，并将所述时序参数发送给交叉口控制系统和出行辅助系统；
步骤S3，所述交叉口控制系统对交叉口的信号相位进行流量限制，保证在每个周期内通过不超过所述时序参数所额定的车辆数；
步骤S4，所有进入所述路网管控区域的机动车按照所述出行辅助系统的约定出行，完整的出行步骤包括预约、报到并等候、按系统安排的时刻出发、出发后遵循交通组织与交叉口控制并一直按全局最优转向选择完成行程；
步骤S5，在满足设定条件下，允许所述机动车对行车速度进行调节，实现路段内无停车出行。
作为进一步的改进，步骤S1包含以下步骤：
步骤S11，将所述路网管控区域的拓扑结构以高精度电子地图数据的形式输入到所述管控中心系统，所述管控中心系统确定所述路网管控区域的静态交通组织信息，静态交通组织信息包括各个路段最大承载力、最高限速，在使用固定周期信号控制模式时还包括各个交叉口发生冲突时每个相位车辆移动的先后顺序、周期内交叉口的每个相位必须通过的最小移动交通流；
步骤S12，根据步骤S11中所确定的静态交通组织信息来确定所述路网管控区域动态的标准时间单元；
步骤S13，根据步骤S12中所确定的标准时间单元，计算出量化后的路网静态数据，路网静态数据包括从路段入口到达下一交叉口的自由行驶时间，自由行驶时间为标准时间单元的整数倍，且量化后车辆在路段内的行驶速度不超过 原本的最高限速。
进一步地，在步骤S2中，通过预约模式或自适应模式来获取所述起讫点OD数据，将出行者多次进行报到动作的高精度时刻数据按统计规则进行处理得到所述报到时刻，其采样周期与计算规则由系统预先确定，并根据设定的准则得到交通流均衡布局的出发时刻、动态路径、交叉口控制协同优化的规划计算出时序参数；优选地，所述时序参数包括单位时间的决策点通过流率、决策点建立的最优行程时间索引值、本周期可出发的交通量、入口处等待时间、虚拟交通流率、交叉口可承受的交通流量、额外虚拟交通流量池。
进一步地，在步骤S3中，进行流量限制的措施包括城市路网的交通动态组织、信号控制方式、高速路口的匝道控制、以及出行辅助系统控制，优选地，可通过所述虚拟交通流率、交叉口可承受的交通流量、额外虚拟交通流量池三项参量确定每个周期内每个相位的通行与禁行时间比例。
进一步地，所述出行辅助系统的载体为车载终端或智能手机，载体的无线通讯方式为移动通信或车联网通信；出行者通过连接云服务器完成预约动作后，出行的车辆按以下步骤完成出行活动：
步骤S21，车辆通过远程报到方式表示可以随时出发，出行辅助系统将这一报到时刻记录为高精度时刻数据并上传到管控中心系统，该数据可以作为自适应模式下的预约记录，并作为同一等级同一OD出行者先后次序的判断依据；
步骤S22，出行辅助系统在接收管控中心系统分配的出发延时值后，通过专属的信号控制或出行行程预测引导信息，让车辆从报到时刻开始就在原地或虚拟停车场轮候，直至管控中心系统规划的最优出发时刻才进入路网，在预约模式下，如果车辆在所分配的最优出发时刻前仍未报到，则被视为放弃当前预约出行机会；
步骤S23，当车辆出发后，出行辅助系统在遵循静态交通组织安排和系统交 叉口控制的前提下，不断地为车辆提供更新后的动态路径规划信息服务，使车辆每次进入一个新决策点时，便可对路径进行再规划，保证车辆始终行驶在行程全局时间最优的时空路径上；
步骤S24，可选的，出行辅助系统在出行者完成行程后生成当日出行总结，向出行者展示当日的行车轨迹，基于何种原因造成的非周期性延误，以及是否存在更优的出行方案的信息。
进一步地，在步骤S22中，在被分配出发延时值的时候，遵守路网管控区域先进先出FIFO的顺序，具有相同OD且为同一等级的车辆按报到的先后顺序出发进入路网，也按相同的先后顺序到达目的地；同时，在路网中没有发生偶然事件造成延误的情况下，出发后的车辆享有静态交通组织下自由流的通行时间；
可选的，根据所述本周期可出发的交通量、入口处等待时间确定可以在本周期内出发的交通流量以及滞留在入口车辆还需要等待的延时。
进一步地，在步骤S23中，通过路径切换方式或基于动态转向模式对路径进行再规划，包括以下步骤：
步骤S31，当车辆进入决策点时，出行辅助系统允许车辆在决策点根据更新后的路段路况以及各专项背后的交通预测，重新选择行程时间最短的时空路径；
步骤S32，在从决策点到瓶颈点的路段内行驶时，出行辅助系统会对车辆编队的行驶速度做出限定，该限定遵守路段内先进先出的顺序理念，使得同一等级的车辆在路段内编队行驶过程中，除了完成选择步骤S31所规划转向所必需的换道动作外，一直在允许的速度范围内行使，既不允许进行未经系统授权的超车行为，也不会让正常运行的车辆在应当正常行进的时空位置上滞留，形成新的瓶颈；
优选地，根据所述决策点通过流率、决策点建立的行程时间索引值、额外 虚拟交通流量池来确定每个单位时间内每个决策点的最优转向选择及其可容纳车辆上限。
进一步地，在步骤S32中，如果路段中不存在发生非周期性延误事件的可能，管控中心系统可以进一步给出具体的推荐速度，使编队车辆可以以恒定速度安全地通过从决策点到瓶颈点的路段内区域，减少停车和加减速次数，以提高驾乘舒适度，降低出行所需能耗和排放。
为了实现上述目的二，本发明提供基于无过饱和状态的约定出行管控装置，所述管控装置包括处理器以及存储器；所述存储器用于存储程序代码，并将所述程序代码传输给所述处理器；所述处理器用于根据所述程序代码中的指令执行上述的方法。
为了实现上述目的三，本发明提供一种计算机可读存储介质，所述计算机可读存储介质用于存储程序代码，所述程序代码用于执行上述的方法。
本发明与现有技术相比，具有的优点为：
1.在不发生(非周期性)突发事件的情况下，管控下的路网具备以下优点：
(1)交通流均衡分布的稳定。系统求得的交通预测与控制变量，路网交通流分布达到的是用户最优均衡状态——如果在系统辅助下，出行者的所有出行选择都采用理性决策，那么对于所有出行者而言，不存在比初始推荐方案更优的出行选择方案。在这种情况下，路网会因为每个出行者都得到了最优出行方案，而形成一种稳定的交通流均衡分布。
(2)出行者出行有序。在系统维持的交通流均衡分布中，只要不发生突发事件，出行者的出行轨迹就会遵循先进先出FIFO的准则，具体的准则包括路段先进先出(同等级的车辆以进入路段的先后顺序离开同一路段)，路径先进先出(同等级的车辆以进入路径的先后顺序离开同一路径)以及OD先进先出(同类型的车辆以进入路网的先后顺序离开路网)。这里的同类型车辆即处于相同用 户等级且具有相同OD的车辆。
(3)交通预测准确可靠。通过在路网中的决策点设立路径规划索引值，为出行者提供理性决策的依据，只要出行者在出发后按系统推荐的出行方案行动，实际的出行结果与推荐方案在时间上的差异就不会超过一个信号周期长度。
本发明在路网规划中实现稳定、有序、可靠的交通流均衡分布，进而以稳定实现可靠、可靠实现有序、有序实现稳定的方式，建立交通管理者与出行者之间信任的良性循环，进一步降低系统在无突发事件状态下的不确定性。当然，交通管理者还是可以因应交通出行需求的中长期变化，对交通流均衡分布进行手动或定期更新，使均衡分布设计不至于因脱离需求变化而过分僵化。
2.本发明通过无过饱和状态准则的引入，以及进一步实现的无停车出行，可以使系统具备以下优势：
(1)可形成合理精细的错峰出行计划。基于无过饱和状态准则，本发明通过精确到周期的交通预测，对出行计划进行引导，其本身就具备错峰出行的技术特征。与传统强制型和粗放型的错峰出行技术方案不同，本发明基于三层不动点的理论基础，既符合用户最优利益又考虑了系统最优准则，使用户能自愿遵循系统的安排，并以具体的方式实现了时间精度为单位周期的错峰出行计划，具有合理、精细的基本特征。
(2)降低机动车出行能源消耗。通过配置出发延时，将出行者出行中(在无突发事件时)的大部分延误都管控在出发之前，而在主要等待时间内车辆可以通过熄火节省能源，从而最大程度上地避免不必要的能源消耗。另外，如果路况中的非确定性因素进一步得到消除，那么本发明可减少不必要停车次数，甚至实现无停车出行，进一步提升能源使用效率和驾乘的舒适度。
(3)为突发事件管控提供良好的均衡分布基础。尽管约定出行机制设计的主要目的是降低周期性拥堵中的不确定性，但稳定的无过饱和状态交通流布局 形成后能为疏导非周期性拥堵提供一个良好的交通流管控背景，而且在不受突发事件影响的路网部分，原有的交通预测可部分地提供交通疏导的依据。
(4)提高无线通信信道、传输规律性。在无过饱和状态的约定出行场景中，交通流将以稳定的流量通过所有的RSU部署节点，因而对沿途各种基站或边缘计算单位的无线带宽和计算需求相对也较为平稳，这为实现各种车路协同无线通信的应用提供了良好的基础。
(5)为自动驾驶提供良好的实现基础。本发明可以帮助交通管理者有的放矢地对自动驾驶场景进行优化，降低路段缓行或拥堵状态对路侧感知、车载感知造成的困难，从而提高自动驾驶的可实现性，有望可以通过低等级的管控技术实现高等级的自动驾驶业务，并通过明晰路网的时空归属权，使得交通事件的责任归属更加明确化，进一步降低突发事件发生时的处置难度和处理时间。
通过以下附图所作的对非限制性实施例所作的详细描述，本发明的其它特征、目的和优点将会变得更明显。
图1为本发明中无过饱和状的态约定出行方法的流程图；
图2为本发明中标准路口场景中决策点与瓶颈点的位置设置图；
图3为本发明中Webster函数的递增特性示意图；
图4为本发明中出发点扩展为虚拟停车场，以重新组合出发流中各OD成分的示意图；
图5为本发明中无停车出行示意图。
下面结合附图中的具体实施例对本发明做进一步的说明。可以理解的是， 此处所描述的具体实施例仅用于解释相关发明，而非对该发明的限定。另外还需要说明的是，为了便于描述，附图中仅示出了与有关发明相关的部分。而且，在不冲突的情况下，本发明中的实施例及实施例中的特征可以相互组合，这些组合显然也属于本发明专利的保护范围。
参阅图1～5，在本发明中，路网交通供需平衡的实现可以分为两个阶段，包括根据出行需求推演制定路网交通流布局参数的“约”阶段，以及根据这些参数结果做出引导以维护交通流布局的“定”阶段。从而制定稳定、有序、可靠的路网交通流布局。
图1表示的是本发明所提出的基于约定出行机制的实现步骤，其系统设计思想的核心是在维持无过饱和状态和先进先出FIFO准则的基础上，结合合理的机制设计，进而统一路网管理者(即系统最优)与出行者(即用户均衡)双方对机动车出行活动的规划目标，由此形成稳定、有序、可靠的布局，并进一步实现满足条件下的无停车编队行驶。
图1中及下文所提出的无过饱和状态，源于交通信号概念的推广，其实际定义为在下一周期开始前，任一处节点位置(如交叉口前的瓶颈点)的车流都能得到离开当前节点位置的机会。而所谓的先进先出FIFO准则，则要求同一等级的出行者，在出行途中：1)将以进入路段时同样的次序离开路段；2)将以进入路径时同样的次序离开路径；3)如果具有相同的OD，则以进入路网时同样的次序离开路网。
基于无过饱和状态的约定出行管控方法，包含以下步骤：
步骤S1，预先确定路网管控区域，并将路网各路段最大承载力、预置交通组织、时间量化单位、信号周期长度参数输入到管控中心系统，计算得到路网静态数据；
步骤S2，管控中心系统获得所有出行交通量按起讫点OD及报到时刻划分 的分类数据后，结合步骤S1的路网静态数据，计算出交通流达到无过饱和状态布局的时序参数，并将时序参数发送给交叉口控制系统和出行辅助系统；
步骤S3，交叉口控制系统对交叉口的信号相位进行流量限制和转向引导，保证在每个周期内通过不超过时序参数所额定的车辆数；
步骤S4，所有进入路网管控区域的机动车按照出行辅助系统的约定出行，完整的出行步骤包括预约、报到并等候、按系统安排的时刻出发、出发后遵循交通组织与交叉口控制并一直按全局最优转向选择完成行程；
步骤S5，在满足设定条件下，允许机动车对行车速度进行调节，实现路段内无停车出行。
步骤S1包含以下步骤：
步骤S11，将路网管控区域的拓扑结构以高精度电子地图数据的形式输入到管控中心系统，管控中心系统确定路网管控区域的静态交通组织信息，静态交通组织信息包括各个路段最高限速、各个交叉口发生冲突时每个相位车辆移动的先后顺序、周期内交叉口的每个相位必须通过的最小移动交通流。
步骤S12，根据步骤S11中所确定的静态交通组织信息来确定路网管控区域动态的标准时间单元和信号周期长度；具体为，通过估算后，管控中心系统提供合理的参数范围，其中，标准时间单元和信号周期长度之间可以采用多种方式实现区域内的无过饱和状态出行，但最简单、单纯的一种实施例就是将标准时间单元与全路网的统一信号周期长度设为同样的长度，即整个历史(或仿真)出行高峰时期[0,T
C]可以按信号周期长度划分为：
0,C
0,2C
0,3C
0,…,(m-1)C
0,mC
0,(m+1)C
0,…,m
CC
0 (1)
其中C
0为统一信号周期长度，由系统预先确定；m为整数型时间变量，而m
C的定义为
其中运算符[x]
+表示的是不小于x的最小正整数。
步骤S13，根据步骤S12中所确定的标准时间单元，计算出量化后的路网静态数据，路网静态数据包括从路段入口到达下一交叉口的自由行驶时间，自由行驶时间为标准时间单元的整数倍，且量化后车辆在路段内的行驶速度不超过原本的最高限速。
尽管上述实施例并不是标准时间单元与统一周期长度唯一的定义方式，但为了阐述简便，以下若干个实施例会建立在定义式(1)的基础上。
为了实现交通流在路口的同步，所有路段的自由行驶时间都应量化为统一信号周期长度的倍数，即通过可变限速等手段保证以下关系
其中节点a为转向ab的进入点，同时也是车辆完成动态转向选择决策的位置，因此称为决策点；节点a′为转向进入交叉口的位置，在点队列模型中也是队列形成的位置，因此可称为瓶颈点。决策点和瓶颈点在四相路口的位置如图2所示。
故而在m时刻的决策点位置，转向ab的即时阻抗可按点队列模型表示为
其中d
a′b(m)为车流在时刻m到达交叉口感受到的延误时间。在实际中，信号延误必定是与交通流相关的函数，即到达交叉口的交通流越大，该延误时间越高。显然，要实现路网内所有交叉口在所有时刻的无过饱和状态，必须在网络分配阶段就对到达交叉口的交通流进行自动限流。
本发明提出一种名为预计补充延误的设计来完成交叉口的自动限流。所谓预计补充延误，即在交通分配时，每个交叉口设计一个额外的惩罚性延误，当 交叉口输入的交通流到达一定程度时，交通估计就会告知后方车辆一个较高的延误值，鼓励后方车辆暂缓进入交叉口队列；假如后方车辆依然执意要通过该转向进入交叉口，相位红灯就会执行该惩罚性延误。通过交通运行预测的警示和红灯的补充延误处罚，可以有效应对发生在具体交叉口的聚集现象。
因此，预计补充函数的设计或选择是一项较重要的前期规划工作。通过上述设计目标可知，选择预计补充函数与选择信号延误估计函数有以下不同：(1)预计补充延误函数可以略大于实际延误，但在任何情况下都绝不能小于实际延误；(2)预计补充延误函数的选择应当体现出输入交通流越大，惩罚性延误越高的原则。在这两点的基础上，预计补充延误函数应在非过饱和阶段尽量贴近实际延误，以降低对路网通行能力的消耗。在一个实施例中，Webster模型就被选为预计补充延误函数，其特性如图3所示。尽管这个函数无法准确描述过饱和状态下的路口延误，但从图3可以看出，它完全能很好地达到劝阻车辆一次性涌入交叉口的目的。于是，在接下来的实施例中，信号延误估计就可以被定义为：
d(m)＝d
W(f(m)，r(m)) (5)
其中f(m)是在时刻m到达交叉口的车流，r(m)是该时刻转向/相位的红信比。
进一步地，可以通过引入松弛变量——额外红信比r
e来考虑交叉口未到达饱和的交通动态。采用非线性互补问题(Nonlinear Complementarity Problem，NCP)理论对该约束关系进行描述，可得：
在满足式(6)所描述的约束条件时，转向ab最终的即时阻抗可以取到最小值为
如果路网中所有路段都能取得上述最小值，那么所有车辆在路网中就能以准自由流的状态通行。所谓准自由流状态，即车流以自由流状态从每个转向的决策点到达瓶颈点，再经过一个单位时间从该瓶颈点完全通过交叉口，到达目的地或下一个决策点。
进一步地，定义从决策点a前往目的地s的准自由流最小行程时间定义为
一旦完成步骤S1中的路段行程时间量化，那么显然该时间是车辆能完成期望行程的最短时间。
在步骤S2中，管控中心系统获得所有出行交通量按起讫点OD及报到时刻划分的分类数据后，结合步骤S1的路网静态数据，计算出交通流达到无过饱和状态布局的时序参数，并将所述时序参数发送给交叉口控制系统和出行辅助系统；
在一个实施例中，多层不动点模型被用于设计路网在动态路径规划、信号协同控制以及出发时刻规划三方面规划所到达的稳定状态。结合表达式(6)实现的无过饱和状态约束，交通流均衡分布的动态优化过程可以用六个NCP不等式表示，即：
其中交通出行动态不等式组(8)-(10)的参数变量定义如表1所示。
表1
其中，ETA(Estimation Time of Arrival，最快到达目的地时刻)、RSA(Red-Signal Anti-Stage，最小红信号延误相位)索引值分别是系统对路径规划、信号优化作出的交通预测。表2进一步显示了两种索引值的类比关系。
表2
这六个不等式分别描述了路网交通流布局计算中的几项准则，包括预测性动态用户最优路径规划(PDUO Route Choice)、交通流守恒(Flow Conservations)、通行延误时间分配(Red-time Allocations)、交叉口信号相位约束(Signal Control Constraint)、出行时刻优化(Departure-Time Choice)以及出行供需平衡(Supply-Demand Equilibrium)的动态关系。表3提供了各项准则的基本描述。
表3
基于NCP不等式组(8)-(10)和(6)进行迭代式的优化求解，计算系统可以将原始交通流布局优化到均衡状态。结合无过饱和状态和FIFO准则的设定，可以一定程度上简化上述计算。最终，可以获得在均衡状态下每个时刻的关键参数组为
X
m＝X(f
m,ψ
m,h
m,w
m,r
m,π
m,r
e
m) (11)
该参数组即为时序参数，表征的是出行高峰时段要维持路网稳定、有序、可靠的重要参数，依次包括单位时间的决策点通过流率、在决策点建立的ETA索引值、本周期可出发的交通量、入口处等待时间(出发延时)、路段虚拟交通流率(即红信比乘以路段饱和流率)，各交叉口建立的RSA索引值，额外虚拟交通流量池(即额外红信比乘以路段饱和流率)。
交通管控中心系统将这些参数下发给各个路口(包括路网入口)的交叉口管控系统和所有用户的OBU。从步骤S3开始，基于这些参数结果，路网将采取一定的约束与闲置，对交通流进行有效管控，即进入了约定出行机制中的“定”阶段。
在步骤S3中，所述交叉口控制系统对交叉口的信号相位进行流量限制，保证在每个周期内通过不超过所述时序参数所额定的车辆数；。
进一步地，本发明提出的是面向整个管控路网区域，完成步骤S3的交叉口控制方法，其实现方式可以为城市路网的交通信号控制方式，或高速路口的匝道控制，甚至依托出行辅助系统控制的引导管控。
由于本发明实施管控的目标不在于将交叉口的通行权最大程度地分配给尽量多的交通量，而是给通过交叉口的交通量分配合适的阻抗，符合在车辆出发时管控中心系统为其提供的交通预测，以实现交通流按约定运行，因此当某些交叉口在未饱和状态下时，会安排所有相位都处于禁行状态，具体表现包括信号交叉口的所有相位都显示成红信号，从而保证无论是当前交叉口，还是交通流即将前往的下一交叉口，都能够维持在无过饱和状态之下。
在一个实施例中，可以通过时序参数的r
m,π
m,r
e
m来具体确定每个路口各个相位的红信号延迟相位及路口清零相位的长度，即管控通行与禁行时间比例，完成佐证交通预测中路径行程时间和实现自动限流的功能。
所述的出行辅助系统的载体为车载终端或智能手机，载体的无线通讯方式为移动通信或车联网通信(车联网专用无线通讯DSRC)；出行者通过连接云服务器完成预约动作后，出行的车辆按以下步骤完成出行活动：
步骤S21，车辆通过远程报到方式表示可以随时出发，出行辅助系统将这一报到时刻记录为高精度时刻数据并上传到管控中心系统，该数据可以作为自适应模式下的预约记录，并作为同一等级同一OD出行者先后次序的判断依据；
步骤S22，出行辅助系统在接收管控中心系统分配的出发延时值后，通过专属的信号控制或出行行程预测引导信息，让车辆从报到时刻开始就在原地或虚拟停车场轮候，直至管控中心系统规划的最优出发时刻才进入路网，最优出发时刻的精度为标准时间单元，在预约模式下，如果车辆在所分配的最优出发时刻前仍未报到，则被视为放弃当前预约出行机会；
步骤S23，当车辆出发后，出行辅助系统在遵循静态交通组织安排和系统交 叉口控制的前提下，不断地为车辆提供更新后的动态路径规划信息服务，使车辆每次进入一个新决策点时，便可对路径进行再规划，保证车辆始终行驶在行程时间最优的时空路径上；
步骤S24，可选的，出行辅助系统在出行者完成行程后生成当日出行总结，向出行者展示当日的行车轨迹，基于何种原因造成的非周期性延误，以及是否存在更优的出行方案的信息。
在步骤S22中，在被分配出发延时值的时候，遵守路网管控区域先进先出FIFO的顺序，具有相同OD且为同一等级的车辆按报到的先后顺序出发进入路网，也按相同的先后顺序到达目的地；同时，在路网中没有发生偶然事件造成延误的情况下，出发后的车辆享有静态交通组织下自由行驶时间。
在一个实施例中，可以通过时序参数的h
m,w
m来确定所有入口在每个时刻进入路网的交通流量。进入路网的流量通过虚拟停车场的概念在正式进入路网前就进行流量重构，从而达到流量控制的最佳效果。具体操作步骤如下：
(1)所有的路网入口将扩展成一个虚拟路口，如图4所示。不同目的地的车辆将采用等比例的准则放行。
(2)相同目的地的车辆则根据车辆关联用户到达虚拟停车场待机的时刻进行排序，其出发延时的分配也遵循FIFO准则。
由此，通过在源头处就管控车辆的进入次序，达到将拥堵彻底排除在区域路网之外的目标。
在步骤S23中，通过路径切换方式或基于动态转向模式对路径进行再规划，包括以下步骤：
步骤S31，当车辆进入决策点时，出行辅助系统允许车辆在决策点根据更新后的路段路况以及各专项背后的交通预测，重新选择行程时间最短的时空路径，具体表现为通过决策点后进行换道，切换到所需要的转向；
步骤S32，在从决策点到瓶颈点的路段内行驶时，出行辅助系统会对车辆编队的行驶速度做出限定(如给出速度范围)，该限定遵守路段内先进先出的顺序理念，使得同一等级的车辆在路段内编队行驶过程中，除了完成选择步骤S31所规划转向所必需的换道动作外，一直在允许的速度范围内行使，既不允许进行未经系统授权的超车行为，也不会让正常运行的车辆在应当正常行进的时空位置上滞留，形成新的瓶颈；
在一个实施例中，根据时序参数的f
m,ψ
m，r
e
m来完成路段内流量的诱导与限流，具体操作步骤如下：
(1)车辆(用户)在时刻m的决策点a会获取最新的路段行程时间估计，加上通过可选转向(如直行、右转、左转以及调头等)后到达下一个决策点时在新决策点获取的ETA索引值，将两者之和作为转向的交通预测，始终选择该交通预测值最小的转向a
+直至完成行程。
(2)一旦流量超过限定的上限，ETA索引值就会引入预计补充延误对交通预测值进行修正，完成对抢行车辆的劝退，达到自动限流的效果。这样相同时刻出发相同OD交通流在出行的过程中始终处于同一个动态而稳定的时空包络中，便于系统进而完成有序、可靠等服务目标。
在步骤S32中，如果路段中不存在发生非周期性延误事件的可能，管控中心系统可以进一步给出具体的推荐速度，使编队车辆可以以恒定速度安全地通过从决策点到瓶颈点的路段内区域，减少停车和加减速次数，以提高驾乘舒适度，降低出行所需能耗和排放。
在步骤S4中，按照出行辅助系统的约定出行，车辆关联用户需要在出行过程中满足以下要求：
(1)按约定的时刻出发，如果未能按时出发，那么将在出发地虚拟停车场等待管控中心系统重新分配出发时刻；
(2)在路段内尽量按建议行车速度行进，非必需情况下不进行超车，这一 点可以通过动态可变限速来实现；
(3)每当进行动态转向选择时，都按照结合预测的最优策略进行理性决策，并贯彻所选转向直至车辆抵达下一决策点或目的地。
在步骤S5中，由于通过步骤S1至S4中的限流措施，路网内每个路段内的车流已经到达无过饱和的状态，如果当前路段可以排除其他非周期性延误的因素，那么可以通过简单的动态可变限速方式，对机动车的行车速度进行调节，在当前路段的决策点和瓶颈点之间实现无停车出行，消除车队在瓶颈点的停车等待动作。图5展示了无停车出行的原理示意，按图中设定，决策点a和瓶颈点a′之间的动态限速可设置为
其中，θ
ja为进入路段aa′的交叉口中交通流获得的相位，θ
ja′为转向aa′即将进入交叉口的相位差。
基于无过饱和状态的约定出行管控装置，所述管控装置包括处理器以及存储器；所述存储器用于存储程序代码，并将所述程序代码传输给所述处理器；所述处理器用于根据所述程序代码中的指令执行上述的方法。
一种计算机可读存储介质，所述计算机可读存储介质用于存储程序代码，所述程序代码用于执行上述的方法。
本发明中的约定出行机制同样具备稳定、有序、可靠的特点。对个体驾驶者来说，这些特点包括：1)在系统依据最优参数所实现的路网交通流布局中，如果路网不受非周期性因素的影响，那么用户通过在途规划或事后总结所能找到的动态最优出行方案依然是系统原本提供的出行计划；2)同一等级且同一OD的用户出行之间具备FIFO的基本秩序，从而保证基本的公平性；3)只要执行系统提供的出行计划，用户到达目的地的时间与系统提供的交通预测之间的 差异不会超过一个统一时间单元。此外，上述方法通过实现无过饱和状态的交通流布局，保证出行车辆主要的延误都形成在出发之前，而在途中所有路口的延误不超过一个信号周期，再加上无停车出行的实现，可以减少不必要的车辆加减速过程，可以最大程度的降低能源消耗与碳排放，并提高司乘人员出行的舒适度。
值得说明的是，约定出行机制允许出行者在途中不断对出行计划进行考察，根据最新路况选择最优转向，而非强制其始终在具体的某条路径上行驶。因此，尽管上述步骤所提到的方法不能直接应用于非周期性事件影响下的路网交通流引导，但由于车辆保留了随机应变的能力，通过实现无过饱和状态与部署ETA索引值，约定出行机制依然为相应场景引导策略的制定提供了较完善的交通流布局基础和可用的路径信息。更具体的说，如果非周期性事件的影响可以被合理的量化，那么通过对ETA索引值进行相应的修正，并针对不同事件设定合理的修正触发条件，可以快速制定出对应的交通流疏导策略。例如，合理降低路网所有路段最高限速和饱和流率的取值，提高车头时距的数值，生成有针对性的交通预测，从而应对雨雪天气的出行；对于路网出现因意外情况造成的局部拥堵，对受影响的ETA索引值进行事件触发式修正，从而让后发的未受影响用户选择最优的路径绕开事故现场等等。各种非周期性事件的应对策略模型在量化细节和触发变化的条件设定必然不会相同，但在本质上都属于约定出行机制的应用拓展，故而也应在本专利的保护范围之内。
在实现无停车出行之后，本发明完全可以实现类似于精确路权类专利的效果，即每辆出行后的车辆在路网中的每一时刻都有唯一对应的路权位置。但是，与相关专利的区别包括但不限于：
(1)所谓精确路权专利的路径分配缺少交通规划依据，不能保证路网交通 的供需平衡，因此无法保证用户在出行后为了更合理的出行而脱离既定的路径，即无法保证路网的稳定；
(2)不少相关专利依靠所谓的大数据出行，而约定出行机制仅需要收集各个机动车的OD的计划出发时刻，可以在没有其他历史数据的情况下运行，更方便在交通需求发生变化时继续使用；
(3)精确路权完全没有为突发事件做出相应准备。
与这类方法必须指定特定路径的做法不同的是，本发明对于路径的分配有较深厚的理论支持，机动车用户行为更加稳定，因此不仅能够为自动驾驶提供安全责任依据，同时还能兼顾路网整体的运行效率。
此外，值得强调的是，尽管之前的方法步骤在描述路口控制时采用了一些交通信号的概念，如信号周期、红信比等等，但实际上只要系统具备了实现路口延误分配的能力，这套控制策略完全可以推广应用到其他不具备信号控制设施的路网，例如结合可变限速和情报板的高速公路等等，进而在其他路网中实现控制路段及路径内单位流率和密度，并完成整个行程内不遭遇过饱和状态的目的。在一个实施例中，无过饱和状态机制可以被应用到智慧公路中，联合城市路网的约定出行实现节假日出行高峰时期的高精度和高密度错峰出行，具体步骤如下所示：
(1)通过网页端和手机端收集所有用户的出行计划，包括出发时刻意向；
(2)路网管理者实施上述步骤1，并通过仿真，例如假设所有用户按意向出发，以距离最短方式进入路网，获取出行仿真高峰时段结束时刻参数m
C；
(3)使用上述步骤2方法生成交通流布局关键参数；
(4)结合城市路网约定出行，通过匝道及路段监控实现路网监控，以及车载通信终端信息提示，监察和督促用户以真正最优化方式出行。
上述例子中的调度方法还可进一步地扩展改良，例如可以通过分车道出行、休息区作为缓冲区等措施，降低节假日错峰出行对周边城市路网约定出行机制的要求。这种扩展也应属于本专利保护范围。
另一种扩展来源于优化计算对信号相位约束(9)与最小红信号的进一步放松，即不再要求同一周期内同一相位交通流仅得到最多一次的放行机会。在这种情况下，同一相位可以跨越一个以上的时间单位连续获得路口的出行机会，红信号分配仅要求在整个出行高峰期内的总通行延误时间均衡。这种形态的优化策略也属于是无过饱和状态约定出行机制的变种方法。
约定出行机制中对路网并无具体的形式要求，因此除了支持城市路网与高速路网混杂的出行场景，理论上还可以支持接驳其他出行模式，例如公交、地铁、高铁、飞机等等，只要这些出行模式在行程时间上满足可靠性的要求，就可以满足“出行即服务”对稳定、有序、可靠方面的要求。
更进一步地，即使在未来实现立体出行，即依靠个人交通工具即可完成航空/道路网络的切换，本发明依然可以应用在相应的路网管理上，据此发展的管理方法依然在本专利的保护范围之内。
最后再次强调的是：以上实施例仅以说明而非限制本发明的技术方案，尽管参照上述实施例对本发明进行了详细说明，本领域的普通技术人员应当理解：依然可以对本发明进行修改或者等同替换，而不脱离本发明的精神和范围的任何修改或局部替换，包括但不限于针对收费进行扩展、更换不同的信号延误表达式和路权计算方式等等，其均应涵盖在本发明的权利要求范围当中。
Claims (10)
- 一种基于无过饱和状态的约定出行管控方法，其特征在于，包含以下步骤：步骤S1，预先确定路网管控区域范围，并将路网各路段最大承载力、预置交通组织、时间量化单位、信号周期长度参数输入到管控中心系统，计算得到路网静态数据；步骤S2，所述管控中心系统获得所有出行交通量按起讫点OD及报到时刻划分的分类数据后，结合步骤S1的路网静态数据，计算出交通流达到无过饱和状态布局的时序参数，并将所述时序参数发送给交叉口控制系统和出行辅助系统；步骤S3，所述交叉口控制系统对交叉口的信号相位进行流量限制，保证在每个周期内通过不超过所述时序参数所额定的车辆数；步骤S4，所有进入所述路网管控区域的机动车按照所述出行辅助系统的约定出行，完整的出行步骤包括预约、报到并等候、按系统安排的时刻出发、出发后遵循交通组织与交叉口控制并一直按全局最优转向选择完成行程；步骤S5，在满足设定条件下，允许所述机动车对行车速度进行调节，实现路段内无停车出行。
- 根据权利要求1所述的基于无过饱和状态的约定出行管控方法，其特征在于，步骤S1包含以下步骤：步骤S11，将所述路网管控区域的拓扑结构以高精度电子地图数据的形式输入到所述管控中心系统，所述管控中心系统确定所述路网管控区域的静态交通组织信息，静态交通组织信息包括各个路段最大承载力、最高限速，在使用固定周期信号控制模式时还包括各个交叉口发生冲突时每个相位车辆移动的先后顺序、周期内交叉口的每个相位必须通过的最小移动交通流；步骤S12，根据步骤S11中所确定的静态交通组织信息来确定所述路网管控 区域动态的标准时间单元；步骤S13，根据步骤S12中所确定的标准时间单元，计算出量化后的路网静态数据，路网静态数据包括从路段入口到达下一交叉口的自由行驶时间，自由行驶时间为标准时间单元的整数倍，且量化后车辆在路段内的行驶速度不超过原本的最高限速。
- 根据权利要求1所述的基于无过饱和状态的约定出行管控方法，其特征在于，在步骤S2中，管控系统通过预约模式或自适应模式来获取所述起讫点OD数据，将出行者多次进行报到动作的高精度时刻数据按统计规则进行处理得到所述报到时刻，其采样周期与计算规则由系统预先确定，并根据设定的准则得到交通流均衡布局的出发时刻、动态路径、交叉口控制协同优化的规划计算出时序参数；优选地，所述时序参数包括单位时间的决策点通过流率、决策点建立的最优行程时间索引值、本周期可出发的交通量、入口处等待时间、虚拟交通流率、交叉口可承受的交通流量、额外虚拟交通流量池。
- 根据权利要求3所述的基于无过饱和状态的约定出行管控方法，其特征在于，在步骤S3中，进行流量限制的措施包括城市路网的交通信号控制方式、高速路口的匝道控制、以及出行辅助系统控制；优选地，可通过所述虚拟交通流率、交叉口可承受的交通流量、额外虚拟交通流量池三项参量确定每个周期内每个相位的通行与禁行时间比例。
- 根据权利要求4所述的基于无过饱和状态的约定出行管控方法，其特征在于，所述出行辅助系统的载体为车载终端或智能手机，载体的无线通讯方式为移动通信或车联网通信；出行者通过连接云服务器完成预约动作后，出行的车辆按以下步骤完成出行活动：步骤S21，车辆通过远程报到方式表示可以随时出发，出行辅助系统将这一报到时刻记录为高精度时刻数据并上传到管控中心系统，该数据可以作为自适应模式下的预约记录，并作为同一等级同一OD出行者先后次序的判断依据；步骤S22，出行辅助系统在接收管控中心系统分配的出发延时值后，通过专属的信号管控或出行行程预测引导信息，让车辆从报到时刻开始就在原地或虚拟停车场轮候，直至管控中心系统规划的最优出发时刻才进入路网，在预约模式下，如果车辆在所分配的最优出发时刻前仍未报到，则被视为放弃当前预约出行机会；步骤S23，当车辆出发后，出行辅助系统在遵循静态交通组织安排和系统交叉口管控的前提下，不断地为车辆提供更新后的动态路径规划信息服务，使车辆每次进入一个新决策点时，便可对路径进行再规划，保证车辆始终行驶在行程时间最优的时空路径上；步骤S24，可选的，出行辅助系统在出行者完成行程后生成当日出行总结，向出行者展示当日的行车轨迹，基于何种原因造成的非周期性延误，以及是否存在更优的出行方案的信息。
- 根据权利要求5所述的基于无过饱和状态的约定出行管控方法，其特征在于，在步骤S22中，在被分配出发延时值的时候，遵守路网管控区域先进先出FIFO的顺序，具有相同OD且为同一等级的车辆按报到的先后顺序出发进入路网，也按相同的先后顺序到达目的地；同时，在路网中没有发生偶然事件造成延误的情况下，出发后的车辆享有静态交通组织下自由流的通行时间；可选的，根据所述本周期可出发的交通量、入口处等待时间确定可以在本周期内出发的交通流量以及滞留在入口车辆还需要等待的延时。
- 根据权利要求5所述的基于无过饱和状态的约定出行管控方法，其特征在于，在步骤S23中，通过路径切换方式或基于动态转向模式对路径进行再规划，包括以下步骤：步骤S31，当车辆进入决策点时，出行辅助系统允许车辆在决策点根据更新后的路段路况以及各专项背后的交通预测，重新选择行程时间最短的时空路径；步骤S32，在从决策点到瓶颈点的路段内行驶时，出行辅助系统会对车辆编队的行驶速度做出限定，该限定遵守路段内先进先出的顺序理念，使得同一等级的车辆在路段内编队行驶过程中，除了完成选择步骤S31所规划转向所必需的换道动作外，一直在允许的速度范围内行使，既不允许进行未经系统授权的超车行为，也不会让正常运行的车辆在应当正常行进的时空位置上滞留，形成新的瓶颈；可选的，根据所述决策点通过流率、决策点建立的行程时间索引值、额外虚拟交通流量池来确定每个单位时间内每个决策点的最优转向选择及其可容纳车辆上限。
- 根据权利要求7所述的基于无过饱和状态的约定出行管控方法，其特征在于，在步骤S32中，如果路段中不存在发生非周期性延误事件的可能，管控中心系统可以进一步给出具体的推荐速度，使编队车辆可以以恒定速度安全地通过从决策点到瓶颈点的路段内区域，减少停车和加减速次数，以提高驾乘舒适度，降低出行所需能耗和排放。
- 基于无过饱和状态的约定出行管控装置，其特征在于，所述管控装置包括处理器以及存储器；所述存储器用于存储程序代码，并将所述程序代码传输给所述处理器；所述处理器用于根据所述程序代码中的指令执行权利要求1-8任一项所述的方法。
- 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质用于存储程序代码，所述程序代码用于执行权利要求1-8任一项所述的方法。
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117292551A (zh) * | 2023-11-27 | 2023-12-26 | 辽宁邮电规划设计院有限公司 | 基于物联网的城市交通态势调节系统与方法 |
| CN117709495A (zh) * | 2024-02-02 | 2024-03-15 | 深圳大学 | 一种用于预约出行的道路网络时空预留方法及相关设备 |
| CN118735092A (zh) * | 2024-06-12 | 2024-10-01 | 南京工程学院 | 基于动态分时路网的电动汽车实时路径最优引导调度方法、介质及设备 |
| CN118966388A (zh) * | 2024-07-18 | 2024-11-15 | 北京交通发展研究院 | 封闭路网的预约方法、装置及系统 |
| CN119091654A (zh) * | 2024-09-15 | 2024-12-06 | 北京理工大学长三角研究院(嘉兴) | 大规模城市路网交通流的分层与分布式模型预测控制方法 |
| CN119763312A (zh) * | 2025-03-06 | 2025-04-04 | 广东有车科技股份有限公司 | 一种基于人工智能的车辆组队控制方法、设备及介质 |
| CN120472689A (zh) * | 2025-07-17 | 2025-08-12 | 山东理工大学 | 车联网环境下调头受控的干线交叉口感应协调控制方法 |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119250481A (zh) * | 2024-12-04 | 2025-01-03 | 南京凯奥思数据技术有限公司 | 一种基于不确定随机规划的热风炉排程错峰方法及系统 |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060142933A1 (en) * | 2002-11-18 | 2006-06-29 | Lumin Feng | Intelligent traffic system |
| CN103578287A (zh) * | 2012-07-20 | 2014-02-12 | 电信科学技术研究院 | 一种车辆调度系统和车辆调度方法 |
| CN105374206A (zh) * | 2015-12-09 | 2016-03-02 | 敏驰信息科技（上海）有限公司 | 一种主动式交通需求管理的系统及其工作方法 |
| CN106504530A (zh) * | 2016-10-31 | 2017-03-15 | 合肥工业大学 | 一种用户出行路径诱导与管控系统及其方法 |
| CN107045783A (zh) * | 2017-05-19 | 2017-08-15 | 邱惠崧 | 一种基于约定出行的道路路网精准行车运行方法和系统 |
| CN107730877A (zh) * | 2017-11-06 | 2018-02-23 | 上海电机学院 | 面向城市高架快速主干路网的预约出行管理系统及方法 |
| CN108831148A (zh) * | 2018-06-12 | 2018-11-16 | 邱惠崧 | 一种免费通行下高峰拥堵的高速路网管控方法及系统 |
| CN109766405A (zh) * | 2019-03-06 | 2019-05-17 | 路特迩科技(杭州)有限公司 | 基于电子地图的交通和旅行信息服务系统及方法 |
| US20190287396A1 (en) * | 2018-03-19 | 2019-09-19 | Toyota Jidosha Kabushiki Kaisha | Managing roadway intersections for vehicles |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102110362B (zh) * | 2011-02-01 | 2013-05-29 | 北京汉风和科技发展有限公司 | 一种规划出行路线的处理方法及系统 |
| CN106529703A (zh) * | 2016-10-31 | 2017-03-22 | 浙江大学 | 一种基于行使权分配的城市交通高峰错行方法 |
| CN107464417A (zh) * | 2017-07-27 | 2017-12-12 | 温州市鹿城区中津先进科技研究院 | 基于出行路径大数据分析的交通调度管控方法 |
| CN108492558B (zh) * | 2018-03-27 | 2021-08-17 | 深圳大学 | 一种高速公路预约出行方法、存储介质及终端 |
| US20190311616A1 (en) * | 2018-04-10 | 2019-10-10 | Cavh Llc | Connected and automated vehicle systems and methods for the entire roadway network |
| CN108986459B (zh) * | 2018-07-06 | 2020-12-22 | 华南理工大学 | 一种基于预约通行的高速公路拥挤疏导方法 |
| CN110378557B (zh) * | 2019-06-11 | 2023-05-05 | 东南大学 | 一种基于逆向交通分配的错峰出行政策评价方法 |
-
2022
- 2022-01-29 CN CN202210112641.0A patent/CN114519933B/zh active Active
- 2022-04-30 WO PCT/CN2022/090834 patent/WO2023142295A1/zh not_active Ceased
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060142933A1 (en) * | 2002-11-18 | 2006-06-29 | Lumin Feng | Intelligent traffic system |
| CN103578287A (zh) * | 2012-07-20 | 2014-02-12 | 电信科学技术研究院 | 一种车辆调度系统和车辆调度方法 |
| CN105374206A (zh) * | 2015-12-09 | 2016-03-02 | 敏驰信息科技（上海）有限公司 | 一种主动式交通需求管理的系统及其工作方法 |
| CN106504530A (zh) * | 2016-10-31 | 2017-03-15 | 合肥工业大学 | 一种用户出行路径诱导与管控系统及其方法 |
| CN107045783A (zh) * | 2017-05-19 | 2017-08-15 | 邱惠崧 | 一种基于约定出行的道路路网精准行车运行方法和系统 |
| CN107730877A (zh) * | 2017-11-06 | 2018-02-23 | 上海电机学院 | 面向城市高架快速主干路网的预约出行管理系统及方法 |
| US20190287396A1 (en) * | 2018-03-19 | 2019-09-19 | Toyota Jidosha Kabushiki Kaisha | Managing roadway intersections for vehicles |
| CN108831148A (zh) * | 2018-06-12 | 2018-11-16 | 邱惠崧 | 一种免费通行下高峰拥堵的高速路网管控方法及系统 |
| CN109766405A (zh) * | 2019-03-06 | 2019-05-17 | 路特迩科技(杭州)有限公司 | 基于电子地图的交通和旅行信息服务系统及方法 |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117292551A (zh) * | 2023-11-27 | 2023-12-26 | 辽宁邮电规划设计院有限公司 | 基于物联网的城市交通态势调节系统与方法 |
| CN117292551B (zh) * | 2023-11-27 | 2024-02-23 | 辽宁邮电规划设计院有限公司 | 基于物联网的城市交通态势调节系统与方法 |
| CN117709495A (zh) * | 2024-02-02 | 2024-03-15 | 深圳大学 | 一种用于预约出行的道路网络时空预留方法及相关设备 |
| CN118735092A (zh) * | 2024-06-12 | 2024-10-01 | 南京工程学院 | 基于动态分时路网的电动汽车实时路径最优引导调度方法、介质及设备 |
| CN118966388A (zh) * | 2024-07-18 | 2024-11-15 | 北京交通发展研究院 | 封闭路网的预约方法、装置及系统 |
| CN118966388B (zh) * | 2024-07-18 | 2025-04-18 | 北京交通发展研究院 | 封闭路网的预约方法、装置及系统 |
| CN119091654A (zh) * | 2024-09-15 | 2024-12-06 | 北京理工大学长三角研究院(嘉兴) | 大规模城市路网交通流的分层与分布式模型预测控制方法 |
| CN119763312A (zh) * | 2025-03-06 | 2025-04-04 | 广东有车科技股份有限公司 | 一种基于人工智能的车辆组队控制方法、设备及介质 |
| CN120472689A (zh) * | 2025-07-17 | 2025-08-12 | 山东理工大学 | 车联网环境下调头受控的干线交叉口感应协调控制方法 |
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