Unmanned driving control method and system based on intelligent AI system

Abstract

The invention relates to the technical field of unmanned driving, in particular to an unmanned driving control method and system based on an intelligent AI system. The method comprises the following steps: receiving a riding request; according to the riding request, extracting passenger information, a passenger demand, a first riding position and a destination position; according to the passenger information, determining the type of a to-be-taken unmanned vehicle, and obtaining a first taken vehicle; according to the first riding position, a first riding vehicle which is closest to the first riding position, is in an idle state and / or is about to be in the idle state is searched, and the current position of the first riding vehicle is determined; and planning a driving route of the first riding vehicle according to the first riding position, the destination position and the current position. Through personalized demand identification and customized service provision, diversified demands of different passenger groups are satisfied, especially for the passenger groups needing special care, and the travel experience and satisfaction of the passengers are significantly improved.

Description

Technical Field

[0001] The present application relates to the field of unmanned driving technology, and in particular to an unmanned driving control method and system based on an intelligent AI system. Background Art

[0002] With the rapid progress of autonomous driving technology, driverless taxis, as the core element of intelligent transportation systems, are gradually crossing the theoretical boundaries and entering real life, bringing unprecedented convenience and safety to public travel. These high-tech vehicles integrate cutting-edge sensor kits, high-precision maps accurate to the centimeter level, complex and efficient algorithm models, and powerful computing platforms, which together support the ability to drive autonomously in complex and changing road environments. This technological innovation has undoubtedly injected new vitality into urban transportation and foreshadowed a profound change in future travel methods.

[0003] However, as driverless taxi services become more widely available, a broader and more profound technical challenge is gradually emerging: how to build a more comprehensive, detailed and humanized passenger service system to better respond to and meet the diverse needs of different passenger groups, especially those who need special care, such as disabled people with limited mobility. At present, although the driverless taxi system can efficiently process basic travel information of passengers, such as starting location, number of passengers and destination, it is still insufficient in identifying personalized needs of passengers and providing customized services. Summary of the invention

[0004] The present application provides an unmanned driving control method and system based on an intelligent AI system to solve the problem that existing unmanned driving technology is still insufficient in identifying passengers' personalized needs and providing customized services.

[0005] In a first aspect, the present application provides an unmanned driving control method based on an intelligent AI system, comprising: Receive a ride request; extract passenger information, passenger demand, first ride location, and destination location based on the ride request; According to the passenger information, the type of the driverless vehicle to be taken is determined to obtain a first vehicle; according to the first vehicle position, the first vehicle that is closest to the first vehicle position and is in an idle state and / or is about to be in an idle state is searched, and the current position of the first vehicle is determined; Planning a travel route for the first riding vehicle according to the first riding position, the destination position, and the current position; sending the travel route to the first riding vehicle; and controlling the first riding vehicle to travel according to the travel route; Before the first ride vehicle arrives at the first ride position, the interior environment of the first ride vehicle is adjusted in advance according to the passenger demand.

[0006] The above technical solutions have the following advantages: through personalized demand identification and customized service provision, the diverse needs of different passenger groups are met, especially for passenger groups that need special care, which significantly improves the travel experience and satisfaction of passengers. In addition, vehicles are dynamically dispatched according to real-time vehicle status and passenger needs to achieve optimal allocation of resources, improving the flexibility and response speed of driverless taxi services. At the same time, based on AI intelligent systems, high-precision maps, real-time traffic data and powerful computing platform support, the safe driving of driverless vehicles in complex and changing road environments is ensured, reducing the risk of traffic accidents.

[0007] Optionally, the ride request includes: After the passenger logs into the boarding interface, searching whether there is a history record of the passenger's boarding request; If the passenger has a history record of historical ride requests, the historical ride requests are displayed on the ride interface, so that the passenger can choose to update the historical ride requests and / or use the historical ride requests according to actual conditions; If the passenger has no historical ride request record, the ride request is filled in and the ride request is fed back.

[0008] The above technical solution has the following advantages: by displaying the historical ride request records, passengers can quickly reuse or adjust the previous trip information, eliminating the trouble of repeated input and improving the convenience of use. In addition, the automatic retrieval and display of passengers' historical records reflects the respect and understanding of passengers' usage habits and further enhances the level of intelligence. At the same time, through the analysis and use of historical records, the travel patterns and preferences of passengers can be more accurately grasped, providing passengers with more personalized service suggestions and recommendations.

[0009] Optionally, the passenger information includes the passenger's physical health status, and determining the type of the driverless vehicle to be taken according to the passenger information to obtain the first vehicle includes: Classify driverless vehicles according to preset health status; The passenger's physical health status is matched with a preset physical health status, and based on the matching result, the category of the driverless vehicle to which the passenger's physical health status belongs is determined, and the driverless vehicle of the category is used as a first riding vehicle.

[0010] The above technical solution has the following advantages: by identifying the physical health status of passengers and matching them with the appropriate driverless vehicle category, a more personalized and considerate service experience can be provided. At the same time, for passengers who need special care, such as disabled people with limited mobility, providing suitable types of vehicles such as barrier-free taxis can significantly reduce the risks and inconveniences they may encounter during the ride. In addition, by accurately matching passenger needs with vehicle categories, limited driverless taxi resources can be used more effectively, improving service efficiency and user satisfaction.

[0011] Optionally, the passenger information further includes the number of passengers, and the determining, based on the passenger information and the first boarding position, the first boarding vehicle that is closest to the first boarding position and is in an idle state and / or is about to be in an idle state further includes: Classify driverless vehicles according to the preset number of passengers; The number of passengers is matched with a preset number of passengers, and based on the matching result, the category of the driverless vehicle to which the number of passengers belongs is determined, and the driverless vehicle of the category is used as the first riding vehicle.

[0012] The above technical solution has the following advantages: by comprehensively considering the number of passengers and their physical health status to match the vehicle type, the diverse needs of passengers can be met more accurately. In addition, by dispatching vehicles based on the number of passengers and their physical health status, driverless taxi resources can be used more effectively to avoid resource waste and excessive occupation. In addition, providing suitable vehicle types and services for passengers of different numbers and physical health status can significantly improve passengers' travel experience and satisfaction.

[0013] Optionally, the first vehicle includes air conditioning equipment, and adjusting the interior environment of the first vehicle in advance according to the passenger's needs includes: Determining whether to start the air conditioning device according to the passenger demand; If it is determined to start the air conditioning device, then obtaining current temperature data; According to the current temperature data, the air conditioning equipment is controlled to start and the air conditioning equipment is adjusted.

[0014] The above technical solution has the following advantages: by precisely controlling the air conditioning equipment according to the needs of passengers, it can provide passengers with a more comfortable and personalized riding environment. In addition, the refinement and personalization of the in-car environment adjustment helps to improve the overall service quality and enhance the satisfaction and loyalty of passengers to the driverless taxi service. At the same time, by intelligently adjusting the working state of the air conditioning equipment, it can reduce energy waste and improve energy efficiency while meeting the needs of passengers.

[0015] Optionally, the method further includes: Before the first boarding vehicle arrives at the first boarding position, detecting whether the first boarding position can be parked normally; If it is determined that the first ride position cannot be parked normally, obtaining the first real-time position of the passenger, the second real-time position of the first ride vehicle, the road map, and the traffic conditions of the road; Planning a second boarding location according to the first real-time location, the second real-time location, the road map, and the road traffic conditions; The second boarding position is transmitted to the first boarding vehicle and the passenger so that the first boarding vehicle and the passenger approach the second boarding position.

[0016] The above technical solution has the following advantages: By dynamically adjusting the boarding position, the extended waiting time and inconvenience of passengers caused by the failure of the first boarding position to park normally are avoided. In addition, it can quickly respond to emergencies and plan a more suitable parking position for the driverless vehicle, reducing the invalid driving time and energy consumption caused by looking for parking spaces. At the same time, this function reflects the processing ability and intelligent decision-making ability of driverless taxis for real-time data, and improves the overall intelligence level.

[0017] Optionally, the first riding vehicle includes a laser radar detector, and the detecting whether the first riding position can be parked normally includes: Before the first riding vehicle arrives at the first riding position, sending an obstacle detection instruction to the laser radar detector; Controlling the laser radar detector to perform obstacle detection on the first riding position according to the obstacle detection instruction to obtain a detection result; Based on the detection result, determine whether the first boarding position can be parked normally.

[0018] The above technical solution has the following advantages: Based on the high precision and high resolution of the laser radar detector, it can accurately identify obstacles around the vehicle, thereby improving the accuracy of the first boarding position stop detection. In addition, by real-time detection of obstacles in the first boarding position and its surrounding areas, potential safety hazards can be discovered in a timely manner, and corresponding countermeasures can be taken to ensure the safety of passengers and vehicles. In addition, the introduction of the laser radar detector further improves the intelligence level of driverless taxis, and can more flexibly respond to various complex scenarios and emergencies.

[0019] Optionally, the method further includes: After the trip is over, sending a ride experience questionnaire to the passenger; Receiving the riding experience questionnaire result; Adjustments and improvements are made based on the results of the ride experience questionnaire.

[0020] The above technical solutions have the following advantages: by collecting and analyzing passenger feedback, problems and deficiencies in the service can be discovered and resolved in a timely manner, thereby improving passenger satisfaction and loyalty. In addition, ride experience feedback provides a valuable reference for optimizing service quality. By implementing targeted improvement measures, service quality and operational efficiency can be significantly improved.

[0021] In a second aspect, the present application provides an unmanned driving control system based on an intelligent AI system, comprising: A request processing module, configured to receive a ride request; and extract passenger information, passenger requirements, a first ride location, and a destination location according to the ride request; a vehicle matching module, configured to determine, based on the passenger information and the first riding position, a first riding vehicle that is closest to the first riding position and is in an idle state and / or is about to be in an idle state, and determine a current position of the first riding vehicle; A route planning module, configured to plan a travel route of the first riding vehicle according to the first riding position, the destination position, and the current position; send the travel route to the first riding vehicle; and control the first riding vehicle to travel according to the travel route; The environment control module is used to adjust the interior environment of the first riding vehicle in advance according to the passenger's needs before the first riding vehicle arrives at the first riding position.

[0022] Optionally, the request processing module is specifically used to: After the passenger logs into the boarding interface, searching whether there is a history record of the passenger's boarding request; If the passenger has a history record of historical ride requests, the historical ride requests are displayed on the ride interface, so that the passenger can choose to update the historical ride requests and / or use the historical ride requests according to actual conditions; If the passenger has no historical ride request record, the ride request is filled in and the ride request is fed back.

[0023] Optionally, the vehicle matching module is specifically used to: Classify driverless vehicles according to preset health status; The passenger's physical health status is matched with a preset physical health status, and based on the matching result, the category of the driverless vehicle to which the passenger's physical health status belongs is determined, and the driverless vehicle of the category is used as a first riding vehicle.

[0024] Optionally, the vehicle matching module is specifically used to: Classify driverless vehicles according to the preset number of passengers; The number of passengers is matched with a preset number of passengers, and based on the matching result, the category of the driverless vehicle to which the number of passengers belongs is determined, and the driverless vehicle of the category is used as the first riding vehicle.

[0025] Optionally, the environment control module is specifically used to: Determining whether to start the air conditioning device according to the passenger demand; If it is determined to start the air conditioning device, then obtaining current temperature data; According to the current temperature data, the air conditioning equipment is controlled to start and the air conditioning equipment is adjusted.

[0026] Optionally, the unmanned driving control system further includes a docking detection module, which is used to: Before the first boarding vehicle arrives at the first boarding position, detecting whether the first boarding position can be parked normally; If it is determined that the first ride position cannot be parked normally, obtaining the first real-time position of the passenger, the second real-time position of the first ride vehicle, the road map, and the traffic conditions of the road; Planning a second boarding location according to the first real-time location, the second real-time location, the road map, and the road traffic conditions; The second boarding position is transmitted to the first boarding vehicle and the passenger so that the first boarding vehicle and the passenger approach the second boarding position.

[0027] Optionally, the docking detection module is specifically used to: Before the first riding vehicle arrives at the first riding position, sending an obstacle detection instruction to the laser radar detector; Controlling the laser radar detector to perform obstacle detection on the first riding position according to the obstacle detection instruction to obtain a detection result; Based on the detection result, determine whether the first boarding position can be parked normally.

[0028] Optionally, the unmanned driving control system further includes an experience feedback module, which is used to: After the trip is over, sending a ride experience questionnaire to the passenger; Receiving the riding experience questionnaire result; Adjustments and improvements are made based on the results of the ride experience questionnaire. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0030] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application; Figure 2 A flowchart of an unmanned driving control method based on an intelligent AI system provided in one embodiment of the present application; Figure 3 A schematic diagram of the structure of an unmanned driving control system based on an intelligent AI system provided in one embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0032] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0033] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0034] With the rapid progress of autonomous driving technology, driverless taxis, as the core element of intelligent transportation systems, are gradually crossing the theoretical boundaries and entering real life, bringing unprecedented convenience and safety to public travel. These high-tech vehicles integrate cutting-edge sensor kits, high-precision maps accurate to the centimeter level, complex and efficient algorithm models, and powerful computing platforms, which together support the ability to drive autonomously in complex and changing road environments. This technological innovation has undoubtedly injected new vitality into urban transportation and foreshadowed a profound change in future travel methods.

[0035] However, as driverless taxi services become more widely available, a broader and more profound technical challenge is gradually emerging: how to build a more comprehensive, detailed and humanized passenger service system to better respond to and meet the diverse needs of different passenger groups, especially those who need special care, such as disabled people with limited mobility. At present, although the driverless taxi system can efficiently process basic travel information of passengers, such as starting location, number of passengers and destination, it is still insufficient in identifying personalized needs of passengers and providing customized services.

[0036] Specifically, the system lacks the ability to directly perceive the physical condition of passengers (such as mobility, whether auxiliary facilities are needed, etc.). As a result, when facing disabled passengers with limited mobility, driverless taxis are often unable to provide necessary auxiliary measures, such as automatically opening sliding doors, adjusting seat positions, providing wheelchair fixing devices, etc., thereby increasing the difficulty and risk of passengers getting on and off the vehicle.

[0037] Based on this, the present application provides an unmanned driving control method and system based on an intelligent AI system, which meets the diverse needs of different passenger groups through personalized demand identification and customized service provision, especially for passenger groups that need special care, significantly improving the travel experience and satisfaction of passengers. In addition, the vehicle is dynamically dispatched according to the real-time vehicle status and passenger needs to achieve optimal allocation of resources, thereby improving the flexibility and response speed of the unmanned taxi service. At the same time, based on the support of AI intelligent systems, high-precision maps, real-time traffic data and powerful computing platforms, the safe driving of unmanned vehicles in complex and changeable road environments is ensured, reducing the risk of traffic accidents.

[0038] Figure 1 A schematic diagram of an application scenario provided for this application.

[0039] During the operation of the driverless taxi, the solution of this application is applied for adjustment and scheduling. Specifically, a server is set in the driverless control system, and the server communicates with the passenger terminal, and communicates with the first vehicle. The server receives the ride request sent by the passenger terminal, determines the first vehicle according to the ride request, and plans the driving route according to the ride request and the first vehicle, and sends the driving route to the first vehicle, controls the first vehicle to drive according to the driving route, and adjusts the interior environment of the first vehicle in advance according to the passenger needs. Through personalized demand identification and customized service provision, the diverse needs of different passenger groups are met, especially for passenger groups that need special care, which significantly improves the travel experience and satisfaction of passengers.

[0040] For specific implementation methods, please refer to the following embodiments.

[0041] Figure 2 This is a flow chart of an unmanned driving control method based on an intelligent AI system provided in one embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201, receiving a ride request; based on the ride request, extracting passenger information, passenger needs, first ride location and destination location.

[0042] Specifically, the passenger sends a ride request through a mobile application or a dedicated terminal, including the starting location (first ride location), destination location, number of passengers and any special requirements (such as wheelchair space, low noise mode, etc.).

[0043] S202. Determine the type of the driverless vehicle to be taken based on the passenger information and obtain a first vehicle; based on the first vehicle position, find the first vehicle that is closest to the first vehicle position and is idle and / or is about to be idle, and determine the current position of the first vehicle.

[0044] Specifically, after receiving the request, the passenger information is first parsed, such as the passenger type (ordinary passenger, disabled person, etc.), and then the type of driverless vehicle required is determined according to the passenger's needs, such as an accessible taxi (equipped with a wheelchair lifting system) or an ordinary taxi.

[0045] Next, based on the first boarding location, the nearest unmanned vehicle that is idle or about to complete the current task is searched in the real-time vehicle database as the first boarding vehicle. At the same time, it is confirmed that the type of the vehicle meets the passenger's needs.

[0046] S203, planning a driving route of the first vehicle according to the first vehicle location, the destination location, and the current location; sending the driving route to the first vehicle; and controlling the first vehicle to travel according to the driving route.

[0047] Specifically, high-precision maps and real-time traffic data are used to plan the optimal driving route for the first vehicle, taking into account road conditions, traffic regulations and passenger comfort to ensure safe and efficient arrival at the destination.

[0048] Then, the planned driving route is sent to the first vehicle, and the vehicle is guided to drive along the predetermined route. At the same time, the vehicle status is continuously monitored to ensure safety and stability during driving.

[0049] S204: Before the first vehicle arrives at the first boarding position, adjust the interior environment of the first vehicle in advance according to passenger needs.

[0050] Specifically, before the vehicle approaches the first boarding position, the interior environment is adjusted in advance according to passenger needs, such as adjusting the seat position to accommodate wheelchair passengers, adjusting the air-conditioning temperature to the passenger's preference, turning on the low noise mode, etc., so as to provide a more intimate and comfortable riding experience.

[0051] Through the method provided in this embodiment, through personalized demand identification and customized service provision, the diverse needs of different passenger groups are met, especially for passenger groups that need special care, which significantly improves the travel experience and satisfaction of passengers. In addition, vehicles are dynamically dispatched according to real-time vehicle status and passenger needs to achieve optimal allocation of resources, thereby improving the flexibility and response speed of driverless taxi services. At the same time, based on AI intelligent systems, high-precision maps, real-time traffic data and powerful computing platform support, the safe driving of driverless vehicles in complex and changeable road environments is ensured, reducing the risk of traffic accidents.

[0052] In some embodiments, after the passenger logs into the boarding interface, the process searches to see whether the passenger has a historical record of boarding requests; if the passenger has a historical record of boarding requests, the historical boarding requests are displayed on the boarding interface, so that the passenger can choose to update the historical boarding requests and / or use the historical boarding requests based on actual conditions; if the passenger has no historical record of boarding requests, the boarding request is filled in and the boarding request is fed back.

[0053] Specifically, after a passenger logs into the ride interface through a mobile application or a dedicated terminal, the passenger's account information is first retrieved to check whether there is a historical record of historical ride requests.

[0054] If the passenger has a history of historical ride requests, these records will be displayed in the form of a list or card on the ride interface. Each record contains key information such as the starting location, destination location, number of passengers, special needs, etc., which is convenient for passengers to quickly identify.

[0055] Passengers can choose to update historical ride requests based on actual circumstances (such as modifying the destination, adding additional requirements, etc.), or directly use a historical request to make a ride reservation.

[0056] If the passenger does not have a historical ride request record, or decides not to use the historical record, the passenger is guided to fill out a new ride request. This includes inputting information such as the starting location, destination location, number of passengers, and any special needs. After the passenger has completed the request, the ride request is verified to ensure the completeness and rationality of the information, and then the ride request is fed back.

[0057] Through the solution provided by this embodiment, by displaying historical ride request records, passengers can quickly reuse or adjust previous trip information, eliminating the trouble of repeated input and improving the convenience of use. In addition, the automatic retrieval and display of passengers' historical records reflects the respect and understanding of passengers' usage habits and further enhances the level of intelligence. At the same time, through the analysis and use of historical records, the travel patterns and preferences of passengers can be more accurately grasped, and more personalized service suggestions and recommendations can be provided to passengers.

[0058] In some embodiments, the category of unmanned vehicles is divided according to preset physical health status; the passenger's physical health status is matched with the preset physical health status, and based on the matching result, the category of unmanned vehicle to which the passenger's physical health status belongs is determined, and the unmanned vehicle of the category is used as the first vehicle to be ridden.

[0059] Passenger information includes the passenger's physical health status.

[0060] Specifically, when a passenger logs in to the boarding interface and fills in a boarding request, the passenger is allowed to select or enter information about his or her physical health status, such as mobility, whether assistance is needed, etc. The passenger's physical health data can also be automatically collected through health monitoring devices (such as wearable devices) integrated in mobile applications or terminals.

[0061] Preset health status and vehicle category classification: Preset multiple health states and their corresponding driverless vehicle categories. For example, disabled people with limited mobility are classified as those who need barrier-free taxis, while healthy passengers are classified as ordinary taxis by default. These preset health states and vehicle category mappings are stored in the database for real-time query and matching.

[0062] Passenger health status matches vehicle category: After receiving the passenger's ride request and obtaining the passenger's physical health status information, the information is matched with the preset physical health status. According to the matching result, the driverless vehicle category to which the passenger's physical health status belongs is determined, and the driverless vehicle of this category is dispatched and prepared as the first ride vehicle.

[0063] After the first vehicle is determined, the above steps are followed for subsequent processing, including vehicle dispatching and matching, route planning, vehicle control, and in-vehicle environment adjustment. In particular, during the in-vehicle environment adjustment stage, the system will adjust the in-vehicle facilities (such as turning on the wheelchair lifting system, adjusting the seat position, etc.) according to the passenger's physical health status to ensure the comfort and safety of the passenger.

[0064] Through the solution provided in this embodiment, by identifying the physical health status of passengers and matching them with the appropriate driverless vehicle category, a more personalized and considerate service experience can be provided. At the same time, for passengers who need special care, such as disabled people with limited mobility, providing suitable types of vehicles such as barrier-free taxis can significantly reduce the risks and inconveniences they may encounter during the ride. In addition, by accurately matching passenger needs with vehicle categories, limited driverless taxi resources can be used more effectively, improving service efficiency and user satisfaction.

[0065] In some embodiments, the category of the driverless vehicle is divided according to a preset number of passengers; the number of passengers is matched with the preset number of passengers, and based on the matching result, the category of the driverless vehicle to which the number of passengers belongs is determined, and the driverless vehicle of the category is used as the first vehicle for riding.

[0066] The passenger information also includes the number of passengers.

[0067] Specifically, the number of passengers and their health status are collected: When passengers log in to the ride interface or fill out a ride request, they are not only required to enter or select their health status information, but also the number of passengers. This information will serve as an important basis for subsequent vehicle dispatch and matching.

[0068] Default number of passengers and vehicle types: Preset multiple ranges of passenger numbers and their corresponding driverless vehicle categories. For example, a vehicle that can accommodate 4 passengers is classified as a small taxi, while a vehicle that can accommodate 6 or more passengers is classified as a large taxi or commercial vehicle.

[0069] At the same time, these preset mappings between the number of passengers and vehicle categories also take into account the physical health status of the passengers. For example, large taxis for people with disabilities with limited mobility may be equipped with more barrier-free facilities.

[0070] Comprehensive matching of passenger number and physical health status: When receiving a passenger's ride request and obtaining the number of passengers and health status information, the system first performs a preliminary vehicle category screening based on the number of passengers. Then, it further screens and matches based on the passengers' health status. In this process, the number of passengers and health status requirements are comprehensively considered to find the most suitable driverless vehicle category. Finally, the driverless vehicle category that meets the number of passengers and health status requirements is determined, and the driverless vehicle of this category is dispatched and prepared as the first ride vehicle.

[0071] After the first vehicle is determined, the above steps are followed for subsequent processing, including route planning, vehicle control, and in-vehicle environment adjustment. In particular, in the in-vehicle environment adjustment stage, in-vehicle facilities (such as seat layout, barrier-free facilities, etc.) are adjusted according to the number of passengers and their physical health status to ensure the comfort and safety of passengers.

[0072] Through the solution provided in this embodiment, by comprehensively considering the number of passengers and their physical health status to match the vehicle category, the diverse needs of passengers can be met more accurately. In addition, by dispatching vehicles based on the number of passengers and their physical health status, driverless taxi resources can be used more effectively to avoid resource waste and excessive occupation. In addition, providing suitable vehicle categories and services for passengers of different numbers and physical health status can significantly improve passengers' travel experience and satisfaction.

[0073] In some embodiments, whether to start the air conditioning equipment is determined based on passenger demand; if it is determined to start the air conditioning equipment, the current temperature data is obtained; based on the current temperature data, the air conditioning equipment is controlled to start and the air conditioning equipment is adjusted.

[0074] The first ride vehicle includes air conditioning equipment.

[0075] Specifically, when a passenger submits a ride request, the passenger is allowed to input or select specific ride requirements, including but not limited to temperature preferences, air circulation requirements, etc.

[0076] Next, it is determined whether the air conditioning equipment needs to be activated based on the passenger's needs. If the passenger clearly expresses the need for temperature adjustment or air circulation, the air conditioning equipment is activated. After the decision to activate the air conditioning equipment is made, the vehicle's built-in temperature sensor is used to obtain the current temperature data inside and / or outside the vehicle. This data will serve as an important basis for adjusting the air conditioning equipment.

[0077] The air conditioning equipment is precisely controlled based on the current temperature data and the temperature preferences of the passengers. For example, if the current temperature inside the car is higher than the comfortable temperature set by the passengers, the air conditioning equipment will be adjusted to lower the temperature inside the car; if the passengers need stronger air circulation, the fan speed will be increased or the air outlet settings will be adjusted.

[0078] During the passengers' ride, the temperature and air circulation in the car will be continuously monitored and adjusted in real time as needed to ensure that the interior environment is always kept within the comfort range expected by the passengers. Passengers' feedback on the effect of the interior environment adjustment can also be collected for subsequent service optimization and improvement. For example, if multiple passengers are dissatisfied with the interior temperature during a certain period of time, the default temperature setting for that period of time may be automatically adjusted.

[0079] Through the solution provided by this embodiment, by accurately controlling the air conditioning equipment according to the needs of passengers, a more comfortable and personalized riding environment can be provided for passengers. In addition, the refinement and personalization of the in-car environment adjustment helps to improve the overall service quality and enhance the satisfaction and loyalty of passengers to the driverless taxi service. At the same time, by intelligently adjusting the working state of the air conditioning equipment, energy waste can be reduced while meeting the needs of passengers and improving energy utilization efficiency.

[0080] In some embodiments, before the first vehicle arrives at the first boarding position, it is detected whether the first boarding position can be parked normally; if it is determined that the first boarding position cannot be parked normally, the first real-time position of the passenger, the second real-time position of the first vehicle, the road route map, and the road traffic conditions are obtained; the second boarding position is planned according to the first real-time position, the second real-time position, the road route map, and the road traffic conditions; the second boarding position is sent to the first vehicle and the passenger, so that the first vehicle and the passenger move closer to the second boarding position.

[0081] Specifically, when the first boarding vehicle approaches the first boarding position, the vehicle's onboard sensors or external data sources (such as a traffic monitoring system) detect whether the position can be parked normally. The detection content may include whether the parking space is occupied, whether the road is congested, whether there is construction or traffic accidents, etc.

[0082] If it is determined that the first boarding position cannot be stopped normally, the exception handling process will be immediately initiated.

[0083] First, the first real-time location of the passenger (usually located by the passenger's mobile device) and the second real-time location of the first vehicle (located by the vehicle's GPS) are obtained. At the same time, real-time data such as the road map and road traffic conditions are also collected. These data may come from the traffic information system, map service providers or the vehicle's own sensors.

[0084] Next, based on the collected real-time location data and traffic condition information, the second boarding location is planned using intelligent algorithms (such as path planning algorithms, traffic prediction models, etc.). This location should meet the conditions that the vehicle can stop normally, passengers can easily reach it, and the traffic conditions are relatively good.

[0085] Then, the second ride location information is sent to the first ride vehicle, and the vehicle adjusts navigation according to the information and goes to the new ride location. At the same time, the second ride location information is also sent to the passenger, and navigation guidance is provided (such as pushing route maps and voice prompts through mobile applications) to help the passenger reach the new ride location quickly and accurately.

[0086] As the first vehicle and passengers approach the second vehicle, traffic conditions and location information of both parties are continuously monitored, and dynamic adjustments are made when necessary to ensure a smooth connection.

[0087] Through the solution provided by this embodiment, by dynamically adjusting the boarding position, the extended waiting time and inconvenience of passengers caused by the failure of the first boarding position to park normally are avoided. In addition, it is possible to quickly respond to emergencies and plan a more suitable parking position for the driverless vehicle, reducing the ineffective driving time and energy consumption caused by searching for parking spaces. At the same time, this function reflects the processing ability and intelligent decision-making ability of the driverless taxi for real-time data, and improves the overall intelligence level.

[0088] In some embodiments, before the first ride vehicle arrives at the first ride position, an obstacle detection instruction is sent to the laser radar detector; the laser radar detector is controlled to perform obstacle detection on the first ride position according to the obstacle detection instruction to obtain a detection result; and based on the detection result, it is determined whether the first ride position can be parked normally.

[0089] The first ride vehicle includes a lidar detector.

[0090] Specifically, when the first riding vehicle approaches the first riding position, an obstacle detection instruction is automatically or manually sent to the laser radar detector according to a preset distance threshold or time threshold.

[0091] After receiving the obstacle detection command, the laser radar detector immediately starts to scan the first boarding position and its surrounding area. By emitting laser beams and receiving reflected signals, the laser radar can accurately measure the distance, size, shape and other information of obstacles in the surrounding environment.

[0092] Next, the obstacle detection data returned by the laser radar detector is collected and analyzed in real time. The analysis content includes but is not limited to: whether the detected obstacle conflicts with the first boarding position, whether the obstacle will affect the normal parking of the vehicle, etc.

[0093] According to the obstacle detection result, it is determined whether the first boarding position can be parked normally. If the detection result shows that there is no obstacle or the obstacle will not affect the parking of the vehicle, it is determined that the vehicle can be parked normally; otherwise, it is determined that the vehicle cannot be parked normally.

[0094] Through the solution provided by this embodiment, based on the high-precision and high-resolution characteristics of the laser radar detector, obstacles around the vehicle can be accurately identified, thereby improving the accuracy of the first boarding position stop detection. In addition, by real-time detection of obstacles in the first boarding position and its surrounding areas, potential safety hazards can be discovered in a timely manner, and corresponding countermeasures can be taken to ensure the safety of passengers and vehicles. In addition, the introduction of the laser radar detector further improves the intelligence level of driverless taxis, and can more flexibly respond to various complex scenarios and emergencies.

[0095] In some embodiments, after the trip ends, a ride experience questionnaire is sent to the passenger; the ride experience questionnaire results are received; and adjustments and improvements are made based on the ride experience questionnaire results.

[0096] Specifically, after the trip, a ride experience questionnaire is automatically sent to the passenger. This questionnaire aims to fully understand the passenger's feelings and opinions on the satisfaction, comfort, safety and other aspects of the ride.

[0097] Receive survey results: Provide a convenient channel for passengers to fill out and submit surveys. Once completed, the survey results will be automatically uploaded to the database for storage. Collect these results in real time or periodically for subsequent analysis and processing.

[0098] Analyze the survey results: Conduct statistical analysis on the collected survey results to extract common problems, improvement suggestions, satisfaction scores, etc. These analysis results will serve as an important basis for optimizing service quality.

[0099] Adjustment and improvement of service quality: Based on the analysis of the questionnaire results, formulate corresponding improvement measures. These measures may involve vehicle maintenance, service process optimization and other aspects. By implementing these measures, the aim is to improve passengers' riding experience and service quality.

[0100] Continuous improvement and cycle: The ride experience feedback link is not a one-time activity, but an ongoing process. Regularly send questionnaires to passengers to collect the latest feedback, and continuously adjust and improve based on the feedback results. Through this continuous improvement cycle mechanism, we can ensure the continuous improvement of service quality.

[0101] Through the solution provided in this embodiment, by collecting and analyzing passenger feedback, problems and deficiencies in the service can be discovered and resolved in a timely manner, thereby improving passenger satisfaction and loyalty. In addition, ride experience feedback provides a valuable reference for optimizing service quality. By implementing targeted improvement measures, service quality and operational efficiency can be significantly improved.

[0102] Figure 3 A schematic diagram of the structure of an unmanned driving control system based on an intelligent AI system provided in one embodiment of the present application is shown in FIG. Figure 3 As shown, the unmanned driving control system 300 of this embodiment includes: a request processing module 301, a vehicle matching module 302, a route planning module 303, and an environment control module 304.

[0103] The request processing module 301 is used to receive a ride request; and extract passenger information, passenger demand, first ride location and destination location according to the ride request; The vehicle matching module 302 is used to determine, based on the passenger information and the first riding position, a first riding vehicle that is closest to the first riding position and is in an idle state and / or is about to be in an idle state, and determine the current position of the first riding vehicle; The route planning module 303 is used to plan a driving route of the first riding vehicle according to the first riding position, the destination position, and the current position; send the driving route to the first riding vehicle; and control the first riding vehicle to travel according to the driving route; The environment control module 304 is used to adjust the interior environment of the first ride vehicle in advance according to the passenger's needs before the first ride vehicle arrives at the first ride location.

[0104] Optionally, the request processing module 301 is specifically used to: After the passenger logs into the boarding interface, searching whether there is a history record of the passenger's boarding request; If the passenger has a history record of historical ride requests, the historical ride requests are displayed on the ride interface, so that the passenger can choose to update the historical ride requests and / or use the historical ride requests according to actual conditions; If the passenger has no historical ride request record, the ride request is filled in and the ride request is fed back.

[0105] Optionally, the vehicle matching module 302 is specifically configured to: Classify driverless vehicles according to preset health status; The passenger's physical health status is matched with a preset physical health status, and based on the matching result, the category of the driverless vehicle to which the passenger's physical health status belongs is determined, and the driverless vehicle of the category is used as a first riding vehicle.

[0106] Optionally, the vehicle matching module 302 is specifically configured to: Classify driverless vehicles according to the preset number of passengers; The number of passengers is matched with a preset number of passengers, and based on the matching result, the category of the driverless vehicle to which the number of passengers belongs is determined, and the driverless vehicle of the category is used as the first riding vehicle.

[0107] Optionally, the environment control module 304 is specifically used to: Determining whether to start the air conditioning device according to the passenger demand; If it is determined to start the air conditioning device, then obtaining current temperature data; According to the current temperature data, the air conditioning equipment is controlled to start and the air conditioning equipment is adjusted.

[0108] Optionally, the unmanned driving control system 300 further includes a parking detection module 305, which is used to: Before the first boarding vehicle arrives at the first boarding position, detecting whether the first boarding position can be parked normally; If it is determined that the first ride position cannot be parked normally, obtaining the first real-time position of the passenger, the second real-time position of the first ride vehicle, the road map, and the traffic conditions of the road; Planning a second boarding location according to the first real-time location, the second real-time location, the road map, and the road traffic conditions; The second boarding position is transmitted to the first boarding vehicle and the passenger so that the first boarding vehicle and the passenger approach the second boarding position.

[0109] Optionally, the docking detection module 305 is specifically used to: Before the first riding vehicle arrives at the first riding position, sending an obstacle detection instruction to the laser radar detector; Controlling the laser radar detector to perform obstacle detection on the first riding position according to the obstacle detection instruction to obtain a detection result; Based on the detection result, determine whether the first boarding position can be parked normally.

[0110] Optionally, the unmanned driving control system 300 further includes an experience feedback module 306, which is used to: After the trip is over, sending a ride experience questionnaire to the passenger; Receiving the riding experience questionnaire result; Adjustments and improvements are made based on the results of the ride experience questionnaire.

[0111] The unmanned driving control system of this embodiment can be used to execute the method of any of the above embodiments. Its implementation principles and technical effects are similar and will not be repeated here.

Claims

1. An unmanned driving control method based on an intelligent AI system, characterized in that: include: Receive ride requests; Extracting passenger information, passenger demand, first boarding location and destination location according to the boarding request; Determine the type of the driverless vehicle required to be taken according to the passenger information, and obtain a first vehicle; According to the first riding position, searching for the first riding vehicle which is closest to the first riding position and is in an idle state and / or is about to be in an idle state, and determining the current position of the first riding vehicle; Planning a travel route of the first vehicle according to the first vehicle location, the destination location, and the current location; Sending the driving route to the first riding vehicle; controlling the first riding vehicle to travel according to the driving route; Before the first ride vehicle arrives at the first ride position, the interior environment of the first ride vehicle is adjusted in advance according to the passenger demand.

2. The method according to claim 1, characterized in that The ride request includes: After the passenger logs into the boarding interface, searching whether there is a history record of the passenger's boarding request; If the passenger has a history record of historical ride requests, the historical ride requests are displayed on the ride interface, so that the passenger can choose to update the historical ride requests and / or use the historical ride requests according to actual conditions; If the passenger has no historical ride request record, the ride request is filled in and the ride request is fed back.

3. The method according to claim 2, characterized in that The passenger information includes the passenger's physical health status. The method of determining the type of the driverless vehicle to be taken based on the passenger information to obtain the first vehicle includes: Classify driverless vehicles according to preset health status; The passenger's physical health status is matched with a preset physical health status, and based on the matching result, the category of the driverless vehicle to which the passenger's physical health status belongs is determined, and the driverless vehicle of the category is used as a first riding vehicle.

4. The method according to claim 3, characterized in that The passenger information further includes the number of passengers, and the determining, based on the passenger information and the first boarding position, a first boarding vehicle that is closest to the first boarding position and is in an idle state and / or is about to be in an idle state further includes: Classify driverless vehicles according to the preset number of passengers; The number of passengers is matched with a preset number of passengers, and based on the matching result, the category of the driverless vehicle to which the number of passengers belongs is determined, and the driverless vehicle of the category is used as the first riding vehicle.

5. The method according to claim 1, characterized in that The first vehicle comprises an air conditioning device, and adjusting the interior environment of the first vehicle in advance according to the passenger's needs includes: Determining whether to start the air conditioning device according to the passenger demand; If it is determined to start the air conditioning device, then obtaining current temperature data; According to the current temperature data, the air conditioning equipment is controlled to start and the air conditioning equipment is adjusted.

6. The method according to claim 1, characterized in that The method further comprises: Before the first boarding vehicle arrives at the first boarding position, detecting whether the first boarding position can be parked normally; If it is determined that the first ride position cannot be parked normally, obtaining the first real-time position of the passenger, the second real-time position of the first ride vehicle, the road map, and the traffic conditions of the road; Planning a second boarding location according to the first real-time location, the second real-time location, the road map, and the road traffic conditions; The second boarding position is transmitted to the first boarding vehicle and the passenger so that the first boarding vehicle and the passenger approach the second boarding position.

7. The method according to claim 6, characterized in that The first riding vehicle includes a laser radar detector, and the detecting whether the first riding position can be parked normally includes: Before the first riding vehicle arrives at the first riding position, sending an obstacle detection instruction to the laser radar detector; Controlling the laser radar detector to perform obstacle detection on the first riding position according to the obstacle detection instruction to obtain a detection result; Based on the detection result, determine whether the first boarding position can be parked normally.

8. The method according to claim 7, characterized in that The method further comprises: After the trip is over, sending a ride experience questionnaire to the passenger; Receiving the riding experience questionnaire result; Adjustments and improvements are made based on the results of the ride experience questionnaire.

9. An unmanned driving control system based on an intelligent AI system, characterized in that: include: A request processing module, used to receive ride requests; Extracting passenger information, passenger demand, first boarding location and destination location according to the boarding request; a vehicle matching module, configured to determine, based on the passenger information and the first riding position, a first riding vehicle that is closest to the first riding position and is in an idle state and / or is about to be in an idle state, and determine a current position of the first riding vehicle; a route planning module, configured to plan a travel route of the first vehicle according to the first vehicle location, the destination location, and the current location; Sending the driving route to the first riding vehicle; controlling the first riding vehicle to travel according to the driving route; The environment control module is used to adjust the interior environment of the first riding vehicle in advance according to the passenger's needs before the first riding vehicle arrives at the first riding position.

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