Vehicle dispatching method, device, electronic device and storage medium

Abstract

The present disclosure relates to a vehicle dispatching method, device, electronic device and storage medium. The method comprises: distributing vehicle dispatching information of the current time period in a vehicle dispatching scheme to each target vehicle, acquiring vehicle demand information, real-time vehicle information of each target vehicle and information about the environment in which it is located; determining a pre-adjustment mode of each target vehicle according to the real-time information of each vehicle and the information about the environment in which it is located; updating the vehicle dispatching scheme through simulation according to the vehicle demand information, the vehicle dispatching information of the next time period in the vehicle dispatching scheme and the pre-adjustment mode, and determining the target adjustment mode of each target vehicle, so that simulation is introduced during vehicle dispatching, and the real-time dispatching strategy is adjusted in time according to the real-time situation, and the effectiveness of the adjustment of the dispatching strategy is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of autonomous driving technology, and in particular to a vehicle dispatching method, device, electronic device and storage medium. Background Art

[0002] Vehicle scheduling needs to consider more factors, such as passenger flow, environmental conditions, etc., and it also needs to deal with emergencies reasonably. Therefore, the mathematical model of vehicle scheduling will become extremely complex.

[0003] Therefore, how to improve the matching degree between the vehicle dispatch plan and the actual situation so that the vehicle dispatch strategy plan can respond to emergencies and be corrected in time is a topic that needs to be studied urgently. Summary of the invention

[0004] In order to solve the above technical problems or at least partially solve the above technical problems, the embodiments of the present disclosure provide a vehicle scheduling method, device, electronic device and storage medium, which solve the problems of failure to make timely adjustments according to real-time conditions and unreasonable adjustment strategies during vehicle scheduling.

[0005] In a first aspect, an embodiment of the present disclosure provides a vehicle dispatching method, the method comprising:

[0006] Distribute the vehicle dispatch information of the current period in the vehicle dispatch plan to each target vehicle, obtain vehicle demand information, real-time vehicle information of each target vehicle, and the environment information;

[0007] Determining a pre-adjustment mode for each target vehicle according to the real-time information of each vehicle and the environment information;

[0008] According to the vehicle demand information, the vehicle dispatching information of the next time period in the vehicle dispatching plan and the pre-adjustment mode, the vehicle dispatching plan is updated through simulation, and the target adjustment mode of each target vehicle is determined.

[0009] In a second aspect, the present disclosure also provides a vehicle dispatching device, the device comprising:

[0010] The information acquisition module is used to distribute the vehicle dispatch information of the current period in the vehicle dispatch plan to each target vehicle, and obtain vehicle demand information, real-time vehicle information of each target vehicle, and environmental information;

[0011] A pre-adjustment module, used to determine the pre-adjustment mode of each target vehicle according to the real-time information of each vehicle and the environment information;

[0012] The target adjustment module is used to update the vehicle scheduling plan and determine the target adjustment mode of each target vehicle through simulation according to the vehicle demand information, the vehicle scheduling information of the next period in the vehicle scheduling plan and the pre-adjustment mode.

[0013] In a third aspect, an embodiment of the present disclosure further provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle scheduling method as described above.

[0014] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the vehicle scheduling method as described above.

[0015] A vehicle scheduling method provided by an embodiment of the present disclosure distributes vehicle scheduling information of the current time period in a vehicle scheduling plan to each target vehicle, obtains vehicle demand information, real-time vehicle information of each target vehicle and environmental information, so as to estimate the mode adjustment for each target vehicle, and then determines the pre-adjustment mode of each target vehicle according to the real-time information and environmental information of each vehicle, updates the vehicle scheduling plan through simulation according to the vehicle demand information, the vehicle scheduling information of the next time period in the vehicle scheduling plan and the pre-adjustment mode, and determines the target adjustment mode of each target vehicle, so as to introduce simulation during vehicle scheduling, make timely adjustment of the real-time scheduling strategy according to the real-time situation, and improve the effectiveness of the adjustment of the scheduling strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0017] Figure 1 is a flow chart of a vehicle dispatching method in an embodiment of the present disclosure;

[0018] Figure 2 A schematic diagram of a preliminary simulation in an embodiment of the present disclosure;

[0019] Figure 3 A schematic diagram of a processing method of a control center when a vehicle is disconnected from the network in an embodiment of the present disclosure;

[0020] Figure 4 A schematic diagram of a method for processing a target vehicle when a vehicle is disconnected from the network in an embodiment of the present disclosure;

[0021] Figure 5 This is a schematic diagram of a processing method of a control center for severe weather conditions in an embodiment of the present disclosure;

[0022] Figure 6 A schematic diagram of a processing flow for fault event information in an embodiment of the present disclosure;

[0023] Figure 7 A schematic diagram of a method for handling emergency alarms and first aid in an embodiment of the present disclosure;

[0024] Figure 8 is a schematic diagram of the overall architecture of a simulation platform in an embodiment of the present disclosure;

[0025] Fig. 9 is a flow chart of another vehicle dispatching method in an embodiment of the present disclosure;

[0026] Fig.10 is a structural schematic diagram of a vehicle dispatching device in an embodiment of the present disclosure;

[0027] Fig.11 It is a structural schematic diagram of an electronic device in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0028] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0029] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0030] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0031] The disclosed embodiment provides a vehicle dispatching method, which combines simulation to verify in real time whether a vehicle dispatching plan meets current needs and can adjust the vehicle dispatching plan in a timely manner. Figure 1FIG. 1 is a flow chart of a vehicle dispatching method in an embodiment of the present disclosure. The method can be executed by a vehicle dispatching device, which can be implemented in software and / or hardware, and can be configured in an electronic device. Figure 1 As shown, the method may specifically include the following steps:

[0032] S110, distributing the vehicle dispatching information of the current period in the vehicle dispatching plan to each target vehicle, and obtaining vehicle demand information, real-time vehicle information of each target vehicle, and environment information.

[0033] Among them, vehicle dispatch information includes the timetable assigned to each target vehicle and the current traffic mode. The target vehicle is each vehicle that is subject to dispatch management. Vehicle demand information is to determine the vehicle demand based on the passenger flow in the next period. Vehicle real-time information can include various information during the vehicle's current driving process, such as speed, location, and emergency information. Environmental information is the environmental conditions within a certain range around each target vehicle, which can include road conditions information and weather information.

[0034] Specifically, the vehicle scheduling information of the current time period in the vehicle scheduling plan is distributed to each target vehicle, so that each target vehicle travels according to the vehicle scheduling information of the current time period. Furthermore, during the driving process of each target vehicle, the passenger flow at the next moment can be analyzed to determine the vehicle demand information, and the real-time vehicle information fed back by each target vehicle can be received, and the environmental information around each target vehicle can be detected.

[0035] Based on the above example, before allocating the vehicle dispatch information of the current period in the vehicle dispatch plan to each target vehicle, it is necessary to formulate and simulate the initial vehicle dispatch plan in advance, which can be:

[0036] Determine an initial dispatching plan and a target model corresponding to the initial dispatching plan according to a preset traffic distribution and preset road conditions;

[0037] According to the target model and the initial scheduling plan, simulation is carried out to determine the target indicators;

[0038] In response to the target indicator satisfying the preset indicator condition, the initial dispatching plan is determined as the vehicle dispatching plan;

[0039] In response to the target indicator not satisfying the preset indicator condition, the initial scheduling plan and the target model are updated according to the target indicator and the preset indicator condition, and the step of performing simulation according to the target model and the initial scheduling plan to determine the target indicator is returned.

[0040] Among them, the preset traffic distribution is the expected distribution of passenger flow, such as normal distribution, Poisson distribution, etc. The preset road conditions may include road condition information, traffic flow information, meteorological information, etc. The initial scheduling plan is the scheduling plan to be simulated and verified. The target model is various models used for simulation modeling of the initial scheduling plan, and the target model includes a vehicle model, a road environment model, and a communication model. The target indicator is a calculation indicator output after the simulation, which is used to measure whether the simulation can be passed. The preset indicator conditions include the conditions for each calculation indicator that can pass the simulation.

[0041] Specifically, when planning a route, the passenger flow and road conditions are estimated, and the preset flow distribution and preset road conditions are determined. Then, the preset flow distribution and preset road conditions are analyzed, and an initial scheduling plan is formulated. According to the initial scheduling plan, various corresponding vehicle models, road environment models, and communication models are constructed, and these models are all target models. Furthermore, the initial scheduling plan is simulated using the target model, and various target indicators in the simulation process are calculated and determined. Determine whether each target indicator meets the preset indicator conditions. If so, it means that before the initial scheduling plan is put into use, it has passed the simulation verification and can basically meet the use requirements. Therefore, the initial scheduling plan is determined as the vehicle scheduling plan to be put into use, so as to facilitate the supplementary scheduling of the vehicle scheduling plan during subsequent use; if not, it means that the initial scheduling plan cannot meet the use requirements and needs to be adjusted. Therefore, the initial scheduling plan can be adjusted based on the gap between the target indicator and the preset indicator conditions, the initial scheduling plan and the corresponding target model can be updated, and a new simulation can be successfully performed, that is, return to execute the simulation according to the target model and the initial scheduling plan, and determine the target indicator steps until each target indicator meets the preset indicator conditions, and the initial scheduling plan is determined as the vehicle scheduling plan.

[0042] For example, the establishment of the target model and the simulation use case need to strengthen the robustness of the self-driving related modules, and also need to make the verification of the scheduling strategy and the calculation of the mode parameters more accurate and reliable. The use case library is mainly divided into ODD (Operational Design Domain) design use cases, fault / event injection, self-driving scheduling modeling, and O&M (Operation And Maintenance) modeling. The use cases in ODD design are mainly used for the iteration of self-driving algorithms and related components. In addition to iteration and daily maintenance, fault / event injection is also used for the verification of operation modes and the calculation of mode parameters. Typical faults and events include but are not limited to the following: 1. Error Code & Error Level (fault code and fault level): all fault codes and fault levels of components such as vehicle body, peripherals, algorithms, etc., such as battery switching errors, etc.; 2. Network Vibration (network vibration): random data loss and data delay in network communication, refer to chaos engineering; 3. Latency Formula (delay modeling: delay modeling of communication between all components; 4. Perception Error Formula (self-driving perception error modeling); 5. Localization Error Formula (self-driving positioning error modeling); 6. Heading & Steering Error Formula (heading error modeling and steering error modeling); 7. Traffic Light Detection Error Formula (traffic light detection error modeling); 8. RSU Detection Error Formula (roadside unit detection error modeling); 9. Battery Consumption & Degradation Formula (power usage modeling and battery capacity attenuation modeling); 10. Load Distribution Formula (load distribution modeling); 11. Climate Models (weather modeling): including ground slipperiness, impact on sensing devices, etc.

[0043] It is understandable that adding new routes, adjusting routes and changing vehicle types will trigger the early simulation, such as Figure 2As shown. First, an initial scheduling plan is established to generate use cases, that is, the corresponding target model, which is executed concurrently during the simulation, and the simulated data is analyzed to determine the target indicators. When the target indicators do not meet the preset indicator conditions, the initial scheduling plan is returned to be re-established until the preset indicator conditions are met, and the initial scheduling plan is output as a vehicle scheduling plan. The indicators to be analyzed for the initial scheduling plan may be, for example, the passability of key locations on the route, travel consumption, entry and exit, and turn sweep maps. These indicators can also be used to guide infrastructure (including the setting of via stations, the specific design of station areas, the design of passenger interactions, etc.), the comparative selection of suppliers of equipment such as buses, etc.

[0044] For example, the economic indicators of the scheme can be introduced, such as passenger queuing time (which can be statistically obtained in simulation verification based on the distribution fitted by the prediction model), vehicle unavailability, etc. Other indicators are not listed one by one. These economic indicators can be used to guide the specific procurement and transformation plans, operation time plans, maintenance arrangements, monitoring management, emergency plan reserves, etc. of vehicles and other equipment. For example, the economic indicators are calculated by the following formula:

[0045]

[0046] Among them, A is avg_charging_time, that is, the average charging time, num_A is num_vehicles_charging, that is, the number of charging vehicles, B is routine_checking_time, that is, the average routine inspection time, num_B is num_vehicles_checking, that is, the number of routine inspection vehicles, C1 is preventive_maintenance_time, that is, the average preventive maintenance time, num_C is num_vehicles_maintaining, that is, the number of preventive maintenance vehicles, C2 is corrective_maintenance_time, that is, the average maintenance time, service_hours is the vehicle operation time, and num_vehicles_required is the total number of vehicles.

[0047] It should be noted that early simulations often do not have historical passenger flow data to calibrate prediction models and fault / event modeling. Therefore, different types of distributions or equations need to be built in for verification, that is, preset traffic distributions and preset road conditions, etc., and the parameters of the model can be continuously corrected in the process of simulation operations to make it closer to reality. When the vehicle dispatch plan is put into trial operation and formal operation, a large amount of real operation data can be obtained for autonomous correction of the model. After each correction, it can be automatically put into the simulation platform for simulated operation to verify the new model.

[0048] S120: Determine a pre-adjustment mode for each target vehicle according to the real-time information of each vehicle and the environment information.

[0049] The pre-adjustment mode is a new mode that the target vehicle needs to change to, as determined through calculation and analysis, such as a local speed-up mode, a degraded operation mode, and an empty vehicle mode. Of course, it can also be a normal operation mode.

[0050] Specifically, for each target vehicle, a comprehensive analysis is performed on the real-time vehicle information and the environmental information corresponding to the target vehicle, so as to determine how the driving mode of the target vehicle needs to be adjusted in the next time period, that is, to determine the pre-adjustment mode of the target vehicle to meet the preset vehicle driving requirements.

[0051] Based on the above example, the pre-adjustment mode of each target vehicle can be determined according to the real-time information of each vehicle and the environment information in the following manner:

[0052] For each target vehicle, in response to the real-time vehicle information of the target vehicle being not in operation, determining that the pre-adjustment mode of the target vehicle is an empty vehicle mode;

[0053] In response to the vehicle real-time information indicating that the vehicle is delayed and the road condition ahead of the target vehicle is good, a target speed is determined according to the vehicle dispatch information, and according to the target speed, a pre-adjustment mode of the target vehicle is determined to be a local speed-up mode;

[0054] In response to the surrounding environment information including bad weather, the pre-adjustment mode of the target vehicle is determined to be a degraded operation mode.

[0055] Among them, "not in operation" means that the target vehicle is idle, or may be in the state of maintenance or charging. Delayed driving means that the current driving distance is behind the expected distance. The target speed is the new speed that the target vehicle needs to adjust to, usually the speed of acceleration.

[0056] Specifically, for each target vehicle, the real-time vehicle information and the environmental information corresponding to the target vehicle are analyzed. If the real-time vehicle information of the target vehicle is not in operation, it means that the target vehicle has not been put into use, and the pre-adjustment mode of the target vehicle is determined to be the empty vehicle mode; if the real-time vehicle information is delayed driving, and the road condition ahead of the target vehicle is good, it means that the target vehicle is already behind the expected driving schedule, and the road condition ahead can be accelerated. Therefore, according to the vehicle scheduling information, it can be analyzed and calculated to determine what speed to use for local acceleration to re-conform to the expected driving schedule, that is, determine the target speed and the speed-up section, and then determine the local acceleration mode corresponding to the target speed according to the target speed, and use the local acceleration mode as the pre-adjustment mode of the target vehicle; if the environmental information includes bad weather, it means that due to weather conditions, in order to ensure driving safety, it is impossible to drive at the original speed, that is, it is necessary to reduce the speed. Therefore, the pre-adjustment mode of the target vehicle is determined to be the degraded operation mode.

[0057] It should be noted that the empty vehicle mode is usually a mode without passengers, that is, a mode in which a series of activities that must be considered when carrying passengers are omitted, that is, low load, no stop, no door opening and closing when parking, no passenger safety check, no need to use air conditioning, CCTV (Closed-Circuit Television), information interaction, entertainment and other facilities, relatively high-speed driving, etc. The empty vehicle mode is usually used in one-way high passenger flow, from idle pool scheduling to operation, from operation exit to charging or maintenance. There are two special continuations of the empty vehicle mode, namely the charging mode and the maintenance mode. Among them, the charging mode may need to trigger automatic charging, monitor the charging end event and end charging, and end charging in advance if necessary to join the operation; the maintenance mode mainly starts the self-check mode to assist maintenance personnel in maintenance work, and also includes correcting battery attenuation. The local speed-up mode is delayed for some reason, and the road conditions ahead are good. Under the premise of taking into account passenger comfort and driving safety, the speed required to catch up is calculated, and a small speed-up instruction for the local section containing speed-up parameters is issued to the target vehicle. The main manifestation of the degraded operation mode is speed reduction, which will lead to changes in destinations, schedules, and cancellation of minor stations. The speed reduction is the main parameter of the degraded operation mode. The situations that trigger degraded operations mainly include bad weather and vehicle network disconnection. Bad weather is monitored by a centralized road condition monitoring service, which can be obtained from weather forecasts. Vehicle network disconnection is monitored by a distributed road condition monitoring service. Among them, the reasons for vehicle network disconnection are various, and may even be cloud service failure, so vehicle monitoring is necessary.

[0058] Based on the above example, there may be a situation where the target vehicle is disconnected from the network. In this case, the following methods need to be used to handle it:

[0059] For each target vehicle, in response to failure to obtain the real-time vehicle information of the target vehicle, reestablishing a communication connection with the target vehicle;

[0060] In response to a failure to establish a communication connection, a network disconnection notification message is generated and sent to a target person.

[0061] The network disconnection notification information is the information of the communication interruption between the control center and the target vehicle. The target personnel are the mobile personnel who monitor the driving status of each target vehicle and perform emergency treatment.

[0062] Specifically, for each target vehicle, if the real-time vehicle information of the target vehicle cannot be obtained, it means that the network is disconnected with the target vehicle at this time, and an attempt is made to re-establish the communication connection with the target vehicle. If the communication connection is successfully established, the real-time vehicle information of the target vehicle will continue to be obtained for real-time monitoring and vehicle control. If the communication connection fails to be established, manual processing is required, so a network disconnection notification message is generated and sent to the target personnel so that the target personnel can deal with the network disconnection problem in time.

[0063] For example, when a vehicle is disconnected from the network, the control center handles the following Figure 3 As shown, the target vehicle is handled as follows Figure 4 As shown. The cloud service of the control center (such as the dispatch service center) detects that at least one target vehicle is offline, that is, it is unable to communicate with these target vehicles. It can generate disconnection notification information through sound and light warnings to notify the target personnel to handle it. It can also actively try to reconnect the communication. If the connection is successful, it can inform the target personnel that the connection has been reestablished. If the connection is unsuccessful, it returns to the step where the cloud service of the control center detects that at least one target vehicle is offline. If the target vehicle detects that it cannot connect to the cloud service of the control center, it can switch to a degraded operation mode and reduce the speed through the environmental perception capability of the target vehicle. It can also actively try to reconnect the communication. If the connection is successful, it can resume the normal operation mode. If the connection is unsuccessful, it returns to the step where the target vehicle detects that it cannot connect to the cloud service of the control center.

[0064] For example, in case of severe weather, the control center handles the situation as follows: Figure 5As shown. The control center receives the severe weather level, and through the real-time vehicle information corresponding to the target vehicle, analyzes and determines that the vehicle's environmental perception ability (such as visibility range, etc.) has deteriorated, comprehensively analyzes the severe weather level and environmental perception ability, determines the degradation parameters, and prompts the target personnel through sound and light warnings, and uses the degraded operation mode corresponding to the degradation parameters as the pre-adjustment mode. At this time, in order to ensure safety, the degraded operation mode can be executed first, and the simulation can be triggered to correct the degradation parameters, and then the target vehicle can execute the corrected degraded operation mode.

[0065] Based on the above example, the pre-adjustment mode of each target vehicle can be determined according to the real-time information of each vehicle in the following manner:

[0066] For each target vehicle, in response to the target vehicle's real-time vehicle information including fault event information, the target vehicle is controlled to slow down, perform self-check and self-recovery operations, and generate fault warning information, which is sent to the target personnel;

[0067] In response to the self-check and self-recovery operation being successful, determining that the pre-adjustment mode of the target vehicle is a local speed-up mode;

[0068] In response to the failure of the self-check and self-recovery operation, the target vehicle is controlled to perform a parking operation and a remote recovery and restart operation;

[0069] In response to the remote recovery restart operation being successful, determining that the pre-adjustment mode of the target vehicle is a local speed-up mode;

[0070] In response to the remote recovery restart operation failing, determining whether the arrival time of the target person is earlier than the arrival time of the next vehicle corresponding to the target vehicle;

[0071] If so, when the target person arrives at the location of the target vehicle, the manual operation function is triggered; if not, the remote assisted vehicle change function is triggered.

[0072] Among them, fault event information is information that the target vehicle has a fault and cannot continue to drive. Fault warning information is information that the target vehicle has a fault and needs to be troubleshooted and repaired. Self-check and self-recovery operation is a function of the target vehicle itself, which is used to correct certain faults autonomously. Remote recovery and restart operation is an operation issued by the control center to restart the target vehicle. The manual operation function is a function for the target personnel to assist in changing vehicles, and the remote assisted vehicle change function is a function for assisting the personnel in the vehicle to change vehicles through the control center.

[0073] Specifically, for each target vehicle, if the real-time vehicle information of the target vehicle includes fault event information, it means that the target vehicle has some faults. Therefore, the target vehicle is first controlled to slow down to ensure vehicle safety, and self-check and self-recovery operations are performed to try to recover these problems and generate fault warning information, and the fault warning information is sent to the target personnel so that the target personnel can handle it in time. If the self-check and self-recovery operation is successful, it means that the fault has been eliminated, and the pre-adjustment mode of the target vehicle needs to be determined as a local speed-up mode to catch up with the lag caused by the previous deceleration. If the self-check and self-recovery operation fails, it means that more complex processing is required, so the target vehicle is controlled to perform a parking operation, and a remote recovery and restart operation is performed to restart the vehicle system by remote control to determine whether the fault has been eliminated. If the remote recovery and restart operation is successful, it means that the fault has been eliminated, and the pre-adjustment mode of the target vehicle needs to be determined as a local speed-up mode to catch up with the lag caused by the previous deceleration and parking. If the remote recovery and restart operation fails, it is determined whether the arrival time of the target person is earlier than the next vehicle corresponding to the target vehicle; if so, when the target person arrives at the location of the target vehicle, the manual operation function is triggered so that the target person can assist the passengers on the target vehicle in changing vehicles; if not, the remote assisted vehicle changing function is triggered to enable the passengers on the target vehicle to change to the next vehicle through remote control.

[0074] Exemplary, the process of processing fault event information is as follows: Figure 6 As shown, if a fault event occurs, the target personnel and passengers need to be notified online. If the target vehicle belongs to a fleet, the remaining vehicles in the fleet can overtake autonomously or follow and wait. If the target vehicle still cannot start after waiting for a period of time, the fleet is reorganized, the new fleet is re-dispatched, and the vehicles in the fleet are enabled with a local speed-up mode. In addition, for the target vehicle where the fault event occurs, it is necessary to slow down, that is, downgrade the operating mode, and trigger self-checking. If the self-checking is successful, the self-recovery function is executed. If either the self-checking function or the self-recovery function fails, the target vehicle is controlled to pull over or stop in place, and remote recovery is performed. If the self-recovery or remote recovery is successful, it is adjusted to the local speed-up mode. If the remote recovery fails, the remote restart operation is performed. If successful, it is adjusted to the local speed-up mode. If it fails, wait for the target person to arrive or the next target vehicle (next vehicle) with a vacant space on the same route to arrive. If the target person arrives before the next vehicle, the system will conduct on-site troubleshooting. If successful, the system will adjust to the local speed-up mode and continue driving. If unsuccessful, the system will call a tow truck and manually drive the target vehicle to the next stop, assist the passengers in changing vehicles, and record the fault log. If the next vehicle arrives before the target person, the system will remotely assist the passengers in changing to the next vehicle.

[0075] Among them, the self-check function and the self-recovery function are both functions in the self-check and self-recovery operation. The remote recovery operation and the remote restart operation are both remote recovery and restart operations.

[0076] Based on the above example, if you need to change the destination in case of an emergency, you can also perform the following operations:

[0077] For each target vehicle, in response to the vehicle real-time information of the target vehicle including the target change information, the target change information is sent to the target person;

[0078] In response to receiving the change confirmation information sent by the target person, the vehicle dispatch plan corresponding to the target vehicle is updated according to the target change information.

[0079] The destination change information is information about the destination change caused by an emergency, and the change confirmation information is information about the consent to change the destination.

[0080] Specifically, for each target vehicle, if the received real-time vehicle information of the target vehicle includes target change information, it means that an emergency has occurred on the target vehicle, so the target change information has been sent to the target personnel to enable the target personnel to conduct real-time analysis to determine whether to change the destination and where the new destination is. If the destination is determined to be changed, the target personnel can generate change confirmation information based on the analysis results. If the change confirmation information sent by the target personnel is received, the vehicle dispatch plan corresponding to the target vehicle is updated based on the target change information, and the target vehicle is driven according to the updated vehicle dispatch plan, and simulation is also required later.

[0081] Emergency plans are divided into two situations: one is sudden alarm and first aid, such as a passenger suddenly falling ill and needing first aid, or a dispute or fight that requires both alarm and first aid; the other is vehicle failure and accident. Failure or accident can be handled in the way described in the above examples. Figure 7 As shown, if the passengers in the target vehicle trigger first aid, the target personnel will understand the situation and assist in formulating a rescue plan, change the destination of the target vehicle, and update the vehicle dispatch information; if the passengers in the target vehicle trigger an alarm, the target personnel will understand the situation, maintain order and carry out rescue, change the destination of the target vehicle, and update the vehicle dispatch information.

[0082] S130, updating the vehicle dispatching plan through simulation according to the vehicle demand information, the vehicle dispatching information of the next period in the vehicle dispatching plan, and the pre-adjustment mode, and determining the target adjustment mode of each target vehicle.

[0083] Among them, the target adjustment mode is an operation mode that can be implemented by each target vehicle determined through simulation.

[0084] Specifically, the vehicle demand information, the vehicle scheduling information for the next time period in the vehicle scheduling plan, and the pre-adjustment mode are input into the simulation platform for simulation to determine whether the simulation passes. If passed, it is directly used as the new vehicle scheduling plan, and the target adjustment mode of each target vehicle is determined; if not, it is necessary to re-plan and simulate until the simulation passes, and the new vehicle scheduling plan and the target adjustment mode of each target vehicle are determined.

[0085] Based on the above example, the vehicle dispatching plan can be updated and the target adjustment mode of each target vehicle can be determined through simulation according to the vehicle demand information, the vehicle dispatching information of the next period in the vehicle dispatching plan and the pre-adjustment mode in the following manner:

[0086] Determine supplementary dispatch information based on vehicle demand information, vehicle dispatch information for the next period in the vehicle dispatch plan, and pre-adjustment mode;

[0087] Simulate the supplementary scheduling information to determine whether the target indicators corresponding to the supplementary scheduling information meet the target requirements;

[0088] In response to the target indicator meeting the target requirement, the vehicle dispatch plan is updated according to the supplementary dispatch information, and a target adjustment mode of the target vehicle is determined;

[0089] In response to the target indicator not meeting the target requirement, the supplementary scheduling information is updated according to the target indicator and the target requirement, and the step of simulating the supplementary scheduling information to determine whether the target indicator corresponding to the supplementary scheduling information meets the target requirement is returned.

[0090] Among them, the supplementary dispatch information is the dispatch information that is added or changed on the basis of the original dispatch information calculated through traffic calculation, demand analysis, etc. The target demand is the various types of indicator requirements that vehicle dispatch needs to meet.

[0091] Specifically, according to the vehicle demand information, the vehicle dispatching information of the next period in the vehicle dispatching plan, and the pre-adjustment mode, analysis and calculation are performed to obtain the supplementary dispatching information. Then, the supplementary dispatching information is simulated, and each target indicator after the simulation can be analyzed and calculated, and it is judged whether the target indicator corresponding to the supplementary dispatching information meets the target demand. If the target indicator meets the target demand, it means that the supplementary dispatching information can be put into use after simulation, so according to the supplementary dispatching information, the vehicle dispatching plan is updated, and the target adjustment mode of the target vehicle included therein is determined. If the target indicator does not meet the target demand, the gap between the target indicator and the target demand is analyzed to facilitate the update of the supplementary dispatching information, and the step of simulating the supplementary dispatching information to judge whether the target indicator corresponding to the supplementary dispatching information meets the target demand is returned until the target indicator obtained by the simulation meets the target demand.

[0092] For example, the iteration of the self-driving algorithm will always exist in the life cycle of this business. Each upgrade will be accompanied by various levels of testing, such as static inspection, unit testing, CI / CD (Continuous Integration / Continuous Deployment), functional testing, performance testing, self-testing, interface testing, deployment testing, usability testing, friendliness testing, etc., all of which must comply with target standards, such as ISO 26262-8. The simulation platform is compatible with all the above types of tests and reuses these tests for real-time scheduling and monitoring. The overall architecture of the simulation platform is as follows: Figure 8 As shown. Use the use case library to load it into the simulation platform, use the simulation platform to call each simulated vehicle and the self-driving hardware on the simulated vehicle, V2X (Vehicle To Everything, vehicle-to-external information exchange) equipment, etc., to perform simulation, and interact with the cloud services required for operation in the control center to achieve more accurate simulation.

[0093] Fig. 9 FIG. 1 is a flow chart of another vehicle dispatching method in an embodiment of the present disclosure. Fig. 9As shown in the figure, by collecting various information sources that affect the flow of people (such as station hall flow meter, ticketing and verification system, meteorological system, and flight system, etc.), the flow prediction model can be corrected to output the predicted flow of people in the next period. The division of the period, that is, the discrete value, can be configured according to the operation needs and simulation correction speed. Through the discrete calculation of demand, the demand for the number of passenger seats and standing number of vehicles in both directions of each line in the next period can be obtained, and the most suitable vehicle type and number of vehicles can be matched for each line from the idle vehicle pool, that is, the demand for the next period can be determined. According to the demand for the next period, the scheduling strategy (vehicle scheduling information) for the next period is sent to the simulation platform. In the discrete calculation of demand, the correction of each information data by the target personnel can also be introduced to improve the accuracy of vehicle demand information. The road condition monitoring service determines the pre-adjustment mode according to the environmental information sent by the meteorological system, such as the level of severe weather, and the real-time vehicle information of each target vehicle (position, speed, power, fault, event, real-time number of passengers, etc.), and inputs this information and operational statistical data into the discrete calculation of demand to improve the effectiveness of vehicle demand information. According to the scheduling strategy and adjustment mode of the next period, the simulation platform needs to complete the simulation data correction within a period and provide feedback so as to send the corrected scheduling strategy of the next period to each target vehicle, including the departure station and departure time, the transit station and the expected arrival time and departure time of each station, the destination and arrival time. Since the idle vehicles may be in different locations such as the waiting area, charging area, and maintenance area near each departure station, the location of the idle vehicles, the mileage to the departure station, and the required power are considered in the calculation to achieve the most economical scheduling mode. Generally, it is necessary to leave enough power to deal with emergencies, and the power consumption simulation will be corrected through the real-time information of the vehicle and the environmental information (such as the temperature is too low or too high, the air conditioning power consumption exceeds expectations, and the unknown fault is manifested as abnormal power failure), so as to dispatch the operating vehicles to exit the operation for charging or maintenance, and replenish the fully charged vehicles in time to join the operation. The target vehicle may encounter emergencies during operation, resulting in inaccurate time, power consumption exceeds expectations, temporary vehicle replacement, low speed, etc., in which case it is necessary to switch the operation mode (pre-adjustment mode) of the target vehicle and correct the scheduling strategy for the next period through the simulation platform. If there is a traffic jam that causes the arrival time to be delayed, or if there is difficulty for passengers to get on the bus that causes the departure time to be delayed, etc., which affects the schedule, the road condition monitoring system needs to start the local speed-up mode when it detects that the arrival and departure are not on schedule. In case of extreme weather or minor faults, it is necessary to enter different levels of degraded operation modes. If the power consumption exceeds expectations, a serious fault occurs, an accident occurs, and the vehicle needs to be replaced, an emergency plan needs to be activated. The self-driving system receives instructions from various services (real-time vehicle information), integrates the perceived environmental information of each target vehicle, makes comprehensive decisions, and feeds back information to various centralized services on the cloud in real time, which also facilitates managers to intervene through cloud services.The complete vehicle dispatch system can be divided into three major services: demand calculation, real-time dispatch, and road condition monitoring. The road condition monitoring service includes a centralized main service deployed on the cloud and distributed terminals deployed on vehicles, which can perform road condition monitoring independently or collaboratively.

[0094] Discrete demand calculation can be based on the analysis of the historical data of vehicle operation in the corresponding period, averaging the single-trip consumption in the corresponding period, and then averaging the number of trips in the corresponding period to calculate the demand under the normal operation mode: the number of passengers who need seats, the number of PRMs (passengers with reduced mobility, passengers using wheelchairs), the number of passengers who can stand after excluding the space occupied by luggage and PRMs, etc. Therefore, for the discrete calculation of vehicle demand, in addition to certain parameters, such as whether standing is allowed, one-way or two-way, etc., the type of vehicle is not conventional large, medium or small, and the parameters need to be refined to the number of seats, the number of standing, PRM facilities, luggage racks, etc. Then, calculate the demand in the empty vehicle mode, match the appropriate type and number of idle vehicles from the idle pool for use, plan the mode of each trip of these vehicles in each period, and output the corresponding timetable.

[0095] The input of real-time scheduling is the calculated discrete demand, that is, the vehicle list and the corresponding schedule for each target vehicle, which are output by the above-mentioned demand calculation service. The corrected vehicle list and the corresponding schedule are output through high-speed concurrent simulation and issued to each target vehicle. Monitor the health status of each vehicle, and in the event of a destination change, promptly correct the destination, feedback and recalculate the discrete demand, notify the target personnel to make scheduling changes, and update the station display and / or broadcast reminders of the changes. During the driving process of each target vehicle, monitor the arrival of the vehicle and issue departure instructions on time so that the target vehicle can operate normally according to the corresponding schedule.

[0096] Regarding road condition monitoring, if a vehicle failure event is received, self-recovery is attempted. If self-recovery is not possible, it can be calculated whether it can travel to the corresponding station. If it can, the corresponding station is updated to the new destination. If it cannot, the target personnel need to be notified for processing, and feedback is re-generated to calculate the demand and adjust the vehicle dispatch plan. Monitor whether the power of each target vehicle can support reaching the destination. If not, calculate the last station that can support driving to, perform high-speed concurrent simulation based on the last station, correct the new destination, and update the vehicle dispatch plan. Monitor in real time whether each target vehicle is delayed in arrival. If so, analyze whether it will cause departure delays. If so, analyze the speed limit that can be increased in the subsequent sections, perform high-speed concurrent simulation, correct the speed increase, and switch the corresponding target vehicle to the local speed increase mode. It can also analyze the level of severe weather, determine the speed reduction parameters, and perform high-speed concurrent simulation in combination with the environmental information of each target vehicle, correct the speed reduction parameters, and switch the corresponding target vehicle to the degraded operation mode.

[0097] Regarding real-time scheduling, it is divided into the following two types: one is the scheduling of the next period, which can be called rescheduling; the other is the adjustment of the scheduling strategy introduced by the mode switch, which can be called supplementary scheduling. The process of real-time verification of the scheduling strategy is to parse the vehicle list, generate simulated vehicles and corresponding instances, translate the itinerary description of the timetable, execute the corresponding itinerary, including simulated fault event injection, statistically form data, compare demand, calculate deviations for adjustment. Among them, the high-speed concurrency requirement is that the cluster computing capacity meets the requirements of running a rescheduling verification within a period and counting the deviation from the demand, so as to ensure the scheduling of the next period. At the same time, it meets the requirements of running a supplementary scheduling verification within the passenger tolerance index and counting the deviation from the demand, so as to ensure that passenger complaints in the emergency plan are within the expected range. If a rescheduling correction is not enough to meet the operational requirements, supplementary scheduling optimization is used. If a supplementary scheduling is not enough to meet the operational requirements, it is necessary to review and enable a large number of simulated operations to correct various models and even operational plans. The real-time verification of mode parameters can be done by determining the pre-adjustment mode of the target vehicle, translating the current behavior of each target vehicle into a simulation interface, executing the corresponding trip, counting the trip data, calculating each target indicator, comparing the target demand calculation deviation, and correcting the mode parameters. Among them, the high-speed concurrency requirement is that the cluster computing capability meets the requirement of running a mode parameter calculation within one calculation cycle, so that the mode can be switched seamlessly. If a mode parameter correction is not sufficient to meet the demand, the road condition monitoring service can detect the problem and continuously initiate corrections.

[0098] Exemplarily, regarding the power consumption exceeding expectations, the following processing can be performed: first determine that the power consumption is higher than expected, and calculate the new destination. Specifically, the vehicle factory power consumption data is used to fit the equation group, and the relevant parameters are corrected using the simulated operation of the simulation platform. After the formal operation, the real operation data is used for continuous correction. Determine the minimum power of the target vehicle when it arrives at the destination to ensure that it can be dispatched to charging or maintenance. Through the power loss simulation, the minimum power that each passing station should have can be output. When the target vehicle enters the station, it is found that the remaining power of the target vehicle is lower than the minimum power that the passing station should have, and the following process can be triggered. If there is passenger ticket information, you can choose to cancel some passing stations to ensure that you drive to the original destination; if there is no information or it cannot be ensured that you drive to the original destination, then correct its power loss model according to the historical trip of the target vehicle, recalculate the power that can be retained at each passing station next, and the previous station of the passing station with a power lower than the minimum power is the new destination. Furthermore, the passenger demand after arriving at the new destination can be estimated, and the current passenger data in the car can be used or the prediction model can be triggered for calculation. Supplementary scheduling is required after this. The estimated passenger demand after arriving at the new destination is sent to the dispatch system to calculate whether the next target vehicle can meet the demand, or a new target vehicle is allocated. The initially formulated plan is put into the simulation platform for verification, and the deviation is calculated based on the simulation data to correct the dispatch plan. For example, the original plan is to use the next target vehicle to arrive at the station. It is found from the simulation data that it cannot be met, and the unmet demand is calculated. The plan is adjusted to add a new target vehicle to share the overall demand with the next target vehicle. Similarly, the original plan is to add a new target vehicle. From the simulation data, the utilization rate is analyzed to be lower than the economic index, so the demand can be borne by the next target vehicle. If the verification result meets the demand, the final plan is the original plan. According to the final plan (vehicle dispatch plan), the affected target vehicles are dispatched in real time, which is manifested as sending relevant instructions and information to the bus: for problem vehicles, the new destination and stop, reminder information are sent, and the target vehicle broadcasts an apology and reminds passengers to prepare information; for additional target vehicles, the departure station, destination, stop, and timetable are issued. In addition, the information is organized according to the final plan and sent to the management service to remind the target personnel to pay attention, confirm whether the problem vehicle needs maintenance, and specify the charging or maintenance mode for the problem vehicle.

[0099] The vehicle scheduling method provided in this embodiment distributes the vehicle scheduling information of the current time period in the vehicle scheduling plan to each target vehicle, obtains vehicle demand information, real-time vehicle information of each target vehicle and environmental information, so as to estimate the mode adjustment for each target vehicle, and then determines the pre-adjustment mode of each target vehicle according to the real-time information and environmental information of each vehicle, updates the vehicle scheduling plan through simulation according to the vehicle demand information, the vehicle scheduling information of the next time period in the vehicle scheduling plan and the pre-adjustment mode, and determines the target adjustment mode of each target vehicle, so as to introduce simulation during vehicle scheduling, make timely adjustment of the real-time scheduling strategy according to the real-time situation, and improve the effectiveness of the adjustment of the scheduling strategy.

[0100] Fig.10 FIG. 1 is a schematic diagram of the structure of a vehicle dispatching device in an embodiment of the present disclosure. Fig.10 As shown, the device includes: an information acquisition module 210 , a pre-adjustment module 220 and a target adjustment module 230 .

[0101] Among them, the information acquisition module 210 is used to distribute the vehicle scheduling information of the current time period in the vehicle scheduling plan to each target vehicle, and obtain the vehicle demand information, the real-time vehicle information of each target vehicle and the environmental information; the pre-adjustment module 220 is used to determine the pre-adjustment mode of each target vehicle according to the real-time information of each vehicle and the environmental information; the target adjustment module 230 is used to update the vehicle scheduling plan through simulation according to the vehicle demand information, the vehicle scheduling information of the next time period in the vehicle scheduling plan and the pre-adjustment mode, and determine the target adjustment mode of each target vehicle.

[0102] Based on the above example, optionally, the pre-adjustment module 220 is also used to, for each target vehicle, in response to the real-time vehicle information of the target vehicle being not in operation, determine the pre-adjustment mode of the target vehicle to be an empty vehicle mode; in response to the real-time vehicle information being delayed driving and the road condition ahead of the target vehicle being good, determine the target speed according to the vehicle dispatch information, and determine the pre-adjustment mode of the target vehicle to be a local speed-up mode according to the target speed; in response to the environmental information including bad weather, determine the pre-adjustment mode of the target vehicle to be a degraded operation mode.

[0103] Based on the above example, optionally, the device also includes: a network disconnection processing module, which is used to re-establish a communication connection with each target vehicle in response to an inability to obtain real-time vehicle information of the target vehicle; in response to a failure to establish the communication connection, generate a network disconnection notification message, and send the network disconnection notification message to the target person.

[0104] Based on the above example, optionally, the device also includes: a destination change module, which is used to send the target change information to the target person for each target vehicle in response to the real-time vehicle information of the target vehicle including the target change information; in response to receiving the change confirmation information sent by the target person, update the vehicle scheduling plan corresponding to the target vehicle according to the target change information.

[0105] Based on the above example, optionally, the pre-adjustment module 220 is also used for each target vehicle, in response to the real-time vehicle information of the target vehicle including fault event information, to control the target vehicle to slow down, perform self-check and self-recovery operations, generate fault warning information, and send the fault warning information to the target person; in response to the success of the self-check and self-recovery operation, determine that the pre-adjustment mode of the target vehicle is a local speed-up mode; in response to the failure of the self-check and self-recovery operation, control the target vehicle to perform a parking operation, and perform a remote recovery and restart operation; in response to the success of the remote recovery and restart operation, determine that the pre-adjustment mode of the target vehicle is a local speed-up mode; in response to the failure of the remote recovery and restart operation, determine whether the arrival time of the target person is earlier than the arrival time of the next vehicle corresponding to the target vehicle; if so, trigger the manual operation function when the target person arrives at the location of the target vehicle; if not, trigger the remote assisted vehicle change function.

[0106] Based on the above example, optionally, the target adjustment module 230 is also used to determine the supplementary scheduling information based on the vehicle demand information, the vehicle scheduling information of the next time period in the vehicle scheduling plan and the pre-adjustment mode; simulate the supplementary scheduling information to determine whether the target indicator corresponding to the supplementary scheduling information meets the target demand; in response to the target indicator meeting the target demand, update the vehicle scheduling plan according to the supplementary scheduling information, and determine the target adjustment mode of the target vehicle; in response to the target indicator not meeting the target demand, update the supplementary scheduling information according to the target indicator and the target demand, and return to execute the step of simulating the supplementary scheduling information to determine whether the target indicator corresponding to the supplementary scheduling information meets the target demand.

[0107] Based on the above example, optionally, before the vehicle scheduling information of the current time period in the vehicle scheduling plan is allocated to each target vehicle, it also includes: an initial simulation module for determining the initial scheduling plan and the target model corresponding to the initial scheduling plan according to a preset traffic distribution and a preset road condition; wherein the target model includes a vehicle model, a road environment model and a communication model; according to the target model and the initial scheduling plan, simulation is performed to determine the target indicator; in response to the target indicator satisfying the preset indicator condition, the initial scheduling plan is determined as the vehicle scheduling plan; in response to the target indicator not satisfying the preset indicator condition, the initial scheduling plan and the target model are updated according to the target indicator and the preset indicator condition, and the step of performing simulation and determining the target indicator according to the target model and the initial scheduling plan is returned to be executed.

[0108] The vehicle dispatching device provided in the embodiment of the present disclosure can execute the steps in the vehicle dispatching method provided in the method embodiment of the present disclosure, and the execution steps and beneficial effects are no longer repeated here.

[0109] Fig.11 Schematic diagram of the structure of an electronic device in the embodiment of the present disclosure. Fig.11 , which shows a structural schematic diagram of an electronic device 300 suitable for implementing the embodiments of the present disclosure. Fig.11 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0110] like Fig.11 As shown, the electronic device 300 may include a processing device 301, a read-only memory (ROM) 302, a random access memory (RAM) 303, a bus 304, an input / output (I / O) interface 305, an input device 306, an output device 307, a storage device 308, and a communication device 309. The processing device (e.g., a central processing unit, a graphics processor, etc.) 301 can perform various appropriate actions and processes to implement the method of the embodiment described in the present disclosure according to the program in the ROM 302 or the program loaded from the storage device 308 to the RAM 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other through the bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0111] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains a program code for executing the method shown in the flowchart, thereby implementing the vehicle scheduling method as described above. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0112] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0113] The computer-readable medium may be included in the electronic device, or may exist independently without being installed in the electronic device. The computer-readable medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device:

[0114] Distribute the vehicle dispatch information of the current period in the vehicle dispatch plan to each target vehicle, obtain vehicle demand information, real-time vehicle information of each target vehicle, and the environment information;

[0115] Determining a pre-adjustment mode for each target vehicle according to the real-time information of each vehicle and the environment information;

[0116] According to the vehicle demand information, the vehicle dispatching information of the next time period in the vehicle dispatching plan and the pre-adjustment mode, the vehicle dispatching plan is updated through simulation, and the target adjustment mode of each target vehicle is determined.

[0117] Optionally, when the above one or more programs are executed by the electronic device, the electronic device may also execute other steps described in the above embodiments.

[0118] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0119] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

Claims

1. A vehicle dispatching method, characterized in that: The method comprises: Distribute the vehicle dispatch information of the current period in the vehicle dispatch plan to each target vehicle, obtain vehicle demand information, real-time vehicle information of each target vehicle, and the environment information; Determining a pre-adjustment mode for each target vehicle according to the real-time information of each vehicle and the environment information; According to the vehicle demand information, the vehicle dispatching information of the next time period in the vehicle dispatching plan and the pre-adjustment mode, the vehicle dispatching plan is updated through simulation, and the target adjustment mode of each target vehicle is determined.

2. The method according to claim 1, characterized in that Determining the pre-adjustment mode of each target vehicle according to the real-time information of each vehicle and the environment information includes: For each target vehicle, in response to the real-time vehicle information of the target vehicle being not in operation, determining that the pre-adjustment mode of the target vehicle is an empty vehicle mode; In response to the vehicle real-time information indicating a delayed driving and the road condition ahead of the target vehicle being good, a target speed is determined according to the vehicle dispatch information, and according to the target speed, the pre-adjustment mode of the target vehicle is determined to be a local speed-up mode; In response to the environmental information including bad weather, determining the pre-adjustment mode of the target vehicle to be a degraded operation mode.

3. The method according to claim 1, characterized in that Also includes: For each target vehicle, in response to failure to obtain the real-time vehicle information of the target vehicle, reestablishing a communication connection with the target vehicle; In response to the failure to establish the communication connection, network disconnection notification information is generated and sent to the target person.

4. The method according to claim 1, characterized in that: Also includes: For each target vehicle, in response to the vehicle real-time information of the target vehicle including target change information, the target change information is sent to the target person; In response to receiving the change confirmation information sent by the target person, the vehicle dispatch plan corresponding to the target vehicle is updated according to the target change information.

5. The method according to claim 1, characterized in that According to the real-time information of each vehicle, the pre-adjustment mode of each target vehicle is determined, including: For each target vehicle, in response to the vehicle real-time information of the target vehicle including fault event information, the target vehicle is controlled to decelerate, a self-check and self-recovery operation is performed, and fault warning information is generated, and the fault warning information is sent to the target person; In response to the self-check and self-recovery operation being successful, determining that the pre-adjustment mode of the target vehicle is a local speed-up mode; In response to the failure of the self-check and self-recovery operation, controlling the target vehicle to perform a parking operation and performing a remote recovery and restart operation; In response to the remote recovery restart operation being successful, determining that the pre-adjustment mode of the target vehicle is a local speed-up mode; In response to the remote recovery restart operation failing, determining whether the arrival time of the target person is earlier than the arrival time of the next vehicle corresponding to the target vehicle; If so, when the target person arrives at the location of the target vehicle, the manual operation function is triggered; if not, the remote assisted vehicle change function is triggered.

6. The method according to claim 1, characterized in that The method of updating the vehicle dispatching scheme and determining the target adjustment mode of each target vehicle through simulation according to the vehicle demand information, the vehicle dispatching information of the next time period in the vehicle dispatching scheme, and the pre-adjustment mode includes: Determine supplementary scheduling information according to the vehicle demand information, the vehicle scheduling information for the next period in the vehicle scheduling plan, and the pre-adjustment mode; Performing simulation on the supplementary scheduling information to determine whether the target indicator corresponding to the supplementary scheduling information meets the target requirement; In response to the target indicator meeting the target requirement, updating the vehicle scheduling plan according to the supplementary scheduling information, and determining the target adjustment mode of the target vehicle; In response to the target indicator not meeting the target requirement, the supplementary scheduling information is updated according to the target indicator and the target requirement, and the step of simulating the supplementary scheduling information to determine whether the target indicator corresponding to the supplementary scheduling information meets the target requirement is returned.

7. The method according to claim 1, characterized in that Before allocating the vehicle dispatching information of the current period in the vehicle dispatching scheme to each target vehicle, the method further includes: Determine an initial scheduling scheme and a target model corresponding to the initial scheduling scheme according to a preset traffic distribution and a preset road condition; wherein the target model includes a vehicle model, a road environment model and a communication model; Perform simulation according to the target model and the initial scheduling plan to determine the target indicator; In response to the target indicator satisfying a preset indicator condition, determining the initial dispatching plan as a vehicle dispatching plan; In response to the target indicator not satisfying the preset indicator condition, the initial scheduling plan and the target model are updated according to the target indicator and the preset indicator condition, and the step of performing simulation according to the target model and the initial scheduling plan to determine the target indicator is returned.

8. A vehicle dispatching device, characterized in that: include: The information acquisition module is used to distribute the vehicle dispatch information of the current period in the vehicle dispatch plan to each target vehicle, and obtain vehicle demand information, real-time vehicle information of each target vehicle, and environmental information; A pre-adjustment module, used to determine the pre-adjustment mode of each target vehicle according to the real-time information of each vehicle and the environment information; The target adjustment module is used to update the vehicle scheduling plan and determine the target adjustment mode of each target vehicle through simulation according to the vehicle demand information, the vehicle scheduling information of the next period in the vehicle scheduling plan and the pre-adjustment mode.

9. An electronic device, characterized in that: The electronic device comprises: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle dispatching method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the vehicle dispatching method as described in any one of claims 1 to 7 is implemented.

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