CN115688949A - Booking riding method and system for automatic driving vehicle - Google Patents
Booking riding method and system for automatic driving vehicle Download PDFInfo
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Abstract
The invention provides a method and a system for reserving riding of an automatic driving vehicle; wherein the method comprises the following steps: determining a scheduled ride implementation according to the scheduled ride instructions; scheduling the autonomous vehicle according to the scheduled ride embodiment. The scheme of the invention is based on the automatic driving vehicle, the automatic driving vehicle can accurately execute the determined appointed riding implementation scheme, and compared with a manned driving mode, a passenger can obtain better appointed riding experience.
Description
Technical Field
The invention relates to the technical field of automatic driving, in particular to a reserved riding method and system for an automatic driving vehicle, electronic equipment and a computer storage medium.
Background
With the gradual maturity and wide application of the automatic driving technology, the reserved riding based on the automatic driving vehicle has wide market prospect. The prior art is not sufficiently researched for booking taking based on an automatic driving vehicle at present, only some taxi taking APPs in the prior art can provide the booking service for the taking of a taxi/a windward vehicle, but the booking service based on the automatic driving vehicle is researched less 23577, and particularly, the technical problems of providing accurate service, good interaction with traffic conditions and the like cannot be effectively solved.
Disclosure of Invention
To solve at least the above technical problems in the background art, the present invention provides a method, a system, an electronic device, and a computer storage medium for reserving a ride for an autonomous vehicle.
A first aspect of the present invention provides a scheduled ride method for an autonomous vehicle, comprising the steps of:
determining a scheduled ride implementation according to the scheduled ride instructions;
an autonomous vehicle is scheduled according to the reserved ride embodiment.
Further, the determining a scheduled ride embodiment from the scheduled ride instructions comprises:
parsing the reserved ride instructions to obtain first data, determining a first implementation based on the reserved ride demand data;
acquiring second data according to the first data, and optimizing the first embodiment according to the second data to obtain a second embodiment;
the second embodiment is referred to as the reserved ride embodiment.
Further, the first data comprises a reserved boarding place;
then, the obtaining second data according to the first data includes:
regional geographic data are called according to the reserved boarding place, and berthable position data are determined according to the regional geographic data;
taking the posable location data as the second data.
Further, said optimizing said first embodiment based on said second data to obtain a second embodiment comprises:
a target parking location is determined from the berthable location data, which is added to the first embodiment to obtain the second embodiment.
Further, the berthable position data includes attribute data of each parking space;
determining a target parking location according to the berthable location data includes:
judging whether the parking space state of each parking space can be obtained or not according to the attribute data, and if so, taking the parking space with the free parking space state as the target parking position; and if not, determining a plurality of parking spaces as the target parking positions according to the attribute data of each parking space.
Further, the first data further comprises a first reserved time;
after determining a plurality of parking spots as the target parking positions according to the grouping result, the method further includes:
and carrying out delay correction on the first reserved time to obtain a second reserved time.
Further, the attribute data comprises parking space attraction;
determining a plurality of parking spaces as the target parking positions according to the attribute data of each parking space, including:
calculating the idle probability of each parking space according to the parking space attraction, and determining a plurality of parking spaces as the target parking positions according to the idle probability and the distance between the parking spaces and the reserved boarding place;
the parking space attraction force is determined according to the place attributes of all places in the preset range and the distance between the parking space attraction force and the corresponding place.
The invention provides an automatic driving vehicle reservation riding system, which comprises a communication module, a processing module and a storage module, wherein the processing module is used for processing the communication module; the processing module is connected with the communication module and the storage module;
the storage module is used for storing executable computer program codes;
the communication module is used for receiving the reserved riding instruction, transmitting the reserved riding instruction to the processing module, and sending the scheduling instruction of the processing module to the automatic driving vehicle;
the processing module is configured to execute the method according to any one of the preceding claims by calling the executable computer program code in the storage module.
A third aspect of the present invention provides an electronic device comprising: a memory storing executable program code; a processor coupled with the memory; the processor calls the executable program code stored in the memory to perform the method of any of the preceding claims.
A fourth aspect of the invention provides a computer storage medium having stored thereon a computer program which, when executed by a processor, performs the method as set out in any one of the preceding claims.
According to the scheme, the automatic driving vehicle is used as a basis, the automatic driving vehicle can accurately execute the determined scheduled riding implementation scheme, and compared with a manned driving mode, a passenger can obtain better scheduled riding experience.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
FIG. 1 is a schematic flow chart illustrating a method for reserving a ride for an autonomous vehicle according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a reserved riding system of an autonomous vehicle according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Referring to fig. 1, fig. 1 is a schematic flow chart illustrating a method for reserving a ride for an autonomous vehicle according to an embodiment of the present invention. As shown in fig. 1, a reserved riding method for an autonomous vehicle according to an embodiment of the present invention includes the following steps:
determining a scheduled ride implementation according to the scheduled ride instructions;
scheduling the autonomous vehicle according to the scheduled ride embodiment.
In the ride reservation method for the automatic driving vehicle, the passenger can send the reserved ride instruction to the platform in advance through various ways, and the platform can acquire the specific ride requirement of the passenger after analyzing the reserved ride instruction, so that the optimal reserved ride implementation scheme can be generated, and the corresponding automatic driving vehicle is scheduled to go to the corresponding station to complete the reserved ride. According to the scheme, the automatic driving vehicle is used as a basis, the determined appointed riding implementation scheme can be accurately executed by the automatic driving vehicle, and compared with a manned driving mode, a passenger can obtain better appointed riding experience.
The autonomous vehicle in the present invention may be an automobile, a two-wheel vehicle, a three-wheel vehicle, an unmanned aerial vehicle, an unmanned ship, an air-ground vehicle, a sea-air vehicle, an air-ground vehicle, etc. with an autonomous driving function, and the power form thereof includes, but is not limited to, fuel, electric energy, hydrogen energy, solar energy, etc., and the specific form thereof is not limited.
In addition, the same operation manner as that of the manned vehicle may be adopted for the operations of identity verification, destination confirmation, fee payment and the like after the passenger gets on the vehicle, and the present invention is not limited thereto.
Further, the determining a scheduled ride embodiment from the scheduled ride instructions comprises:
parsing the reserved ride instructions to obtain first data, determining a first implementation based on the reserved ride demand data;
acquiring second data according to the first data, and optimizing the first embodiment according to the second data to obtain a second embodiment;
the second embodiment is considered the reserved ride embodiment.
The reserved riding instructions submitted by the passengers to the platform may be appended with first data describing the riding requirements of the passengers, including the reserved boarding location, the reserved time, the number of passengers, etc., and the platform may determine an initial first embodiment based on these data, for example, the time: 12, and the following steps: exit of subway station No. 2, destination: XX road and B mansion. Second data relating to the ride requirements may then be retrieved and the initial first embodiment optimized so that a more optimal second embodiment may be obtained. The meaning is that the automatic driving vehicle is dispatched to an exit No. 2 of a subway station A at 12.
Further, the first data comprises a reserved boarding place;
then, the obtaining second data according to the first data includes:
regional geographic data are called according to the reserved boarding place, and berthable position data are determined according to the regional geographic data;
taking the berthable position data as the second data.
In order to avoid waiting for passengers at the scheduled boarding site, the autonomous vehicle is set to appropriately arrive at the scheduled boarding site in advance, which requires the autonomous vehicle to perform parking waiting at a berthable position around the scheduled boarding site. Aiming at the problem, the regional geographic data in the preset range around the reserved getting-on place is called and reserved, so that whether parking positions and position distribution of the parking positions exist nearby the reserved getting-on place can be determined, and the parking positions can be roadside parking places, paid parking places, temporary parking places of non-parking places and the like. Thus, the automatically driven vehicle can be parked at a suitable parking position for waiting for passengers after arriving at the reserved boarding site in advance.
Regional geographic data may be obtained from third party map service providers, and the "regions" therein may be used to determine appropriate filtering rules based on the actual road configuration of the reserved pick-up location, e.g., easy to find by reserved passengers, appropriate distances, no lateral crossing of roads, etc.
Further, the optimizing the first embodiment according to the second data to obtain a second embodiment comprises:
determining a target parking location from the berthable location data, and adding the target parking location to the first embodiment to obtain the second embodiment.
After the berthable position data is obtained, an appropriate target parking position can be selected according to a certain rule and added to the original first embodiment, for example, the second embodiment may be: time: 12, and the following steps: a subway station No. 2 export 054 parking stall, destination: XX way B mansion.
Further, the berthable position data includes attribute data of each parking space;
determining a target parking location according to the berthable location data includes:
judging whether the parking space state of each parking space can be obtained or not according to the attribute data, and if so, taking the parking space with the free parking space state as the target parking position; and if not, determining a plurality of parking spaces as the target parking positions according to the attribute data of each parking space.
The latest map data can already support high-precision geographic data, and the specific position, size, attribute (public/private use, service time interval, whether to charge or not, and the like), idle state and other attribute data of each parking space in the area are accurately marked in the map. The invention obtains the attribute data of each parking space from the map data, judges whether the parking space state (namely whether the parking space is free) of the parking space is included, and can screen the parking spaces (such as the parking spaces of a charging parking lot) synchronously added with the real-time state of the parking spaces according to factors such as distance, price and the like, even reserve and lock the parking spaces; and for parking spaces which do not provide real-time parking spaces (such as roadside non-operating public parking spaces), grouping can be performed based on the adjacency relation, and suitable target parking positions can be screened out. Therefore, the optimal target parking position is determined through the reasonable target parking position screening rule, the automatic driving vehicle can be ensured to smoothly park after reaching the reserved boarding place, more time is not spent on finding the parking position, and the on-time aiming at the reserved time can be guaranteed.
Further, the first data further comprises a first reserved time;
after determining a plurality of parking spots as the target parking positions according to the grouping result, the method further includes:
and carrying out delay correction on the first reserved time to obtain a second reserved time.
For the situation that the parking space state of the parking space at the reserved getting-on place cannot be accurately obtained, although the probability of having free parking spaces can be improved by roughly determining a plurality of parking spaces, the automatic driving vehicle still needs to spend much time to search for the parking position meeting the intersection rule again after arriving, so that the 'on-time' of a corresponding passenger cannot be guaranteed, and extra burden and even potential safety hazards are easily brought to local traffic. In view of the above, the present invention provides a method for automatically driving a vehicle, which is capable of effectively solving or partially solving the above-mentioned problems by delaying an original first reserved time, that is, delaying the time for arriving at a reserved boarding location, so as to ensure that a passenger is in place when the automatically driven vehicle arrives, and easily finding a temporary parking location to allow the passenger to get on the vehicle quickly even if the original target parking location cannot be parked.
The degree of delay correction can be determined according to the traffic complexity of the reserved boarding location, i.e. the higher the traffic complexity, the higher the degree of delay correction. The traffic complexity can be determined according to the road structure complexity (road intersection condition, motor lane and non-motor lane isolation condition and the like), traffic flow condition, accident statistical data and the like in the region corresponding to the reserved boarding place.
Further, the attribute data comprises parking space attraction;
determining a plurality of parking spaces as the target parking positions according to the attribute data of each parking space, including:
calculating the idle probability of each parking space according to the parking space attraction, and determining a plurality of parking spaces as the target parking positions according to the idle probability and the distance between the parking spaces and the reserved boarding place;
the parking space attraction force is determined according to the place attributes of all places in the preset range and the distance between the parking space attraction force and the corresponding place.
For parking spaces of which the idle state cannot be obtained, the method calculates the idle probability of the parking spaces through the parking space attraction, and then performs comprehensive screening on the basis of the idle probability of each parking space and the distance between the reserved boarding places, so that the parking success rate of the automatic driving vehicle is improved, and passengers do not need to transit and walk for too long distance.
The parking space attraction refers to the attraction capability of multidimensional attributes of places around the parking space to an owner. Examples are as follows:
1) The reserved boarding place A is a subway station, and commercial vehicles such as taxies parked for a short time tend to temporarily park in parking spaces close to the subway station for carrying passengers, namely, the attractiveness of the parking spaces to the commercial vehicles is high (is reduced along with the increase of the first distance), and the vehicle alternation frequency is high. Therefore, the probability that roadside parking spaces near the subway station are occupied by parked short-time vehicles is reduced along with the increase of the first distance, then the parking space attraction can be calculated according to the first distance, and the idle probability is determined. Aiming at the situation, the target parking positions with high idle probability can be selected to be screened from the roadside parking spaces far away from the subway station, the probability that the parking spaces are occupied by the short-time parking vehicles is small, and the parking success rate of the automatic driving vehicles is high.
2) The position B within the preset range is a paid parking lot, long-time parking vehicles are more prone to parking in the paid parking lot, and short-time parking vehicles are more prone to parking outside roadside parking spaces. Therefore, the probability that the parking spaces on the outer road side are occupied by the long-term parked vehicles increases along with the increase of the second distance, the parking space attraction force can be calculated according to the second distance, and the idle probability can be determined. Aiming at the situation, the target parking position can be selected from roadside parking spaces close to the paid parking lot, the probability of long-term parking on the parking spaces is low, and the parking success rate of the automatic driving vehicle is high.
In addition, the places with different attractions, such as the subway station, the paid parking lot, and the like, referred to in the above example may be simultaneously within a preset range, and at this time, only respective parking space attractions need to be respectively calculated, and are fused by distance factors, for example, if a certain parking space is closer to a certain place a, the weighting of the parking space attractions of the certain place a is larger, and otherwise, the weighting is smaller.
And the comparison relationship (related to the place attribute and the distance) between the parking space attraction and the idle probability can be preset, and a more detailed comparison relationship can be specifically set according to different kinds of places, and the specific preset process of the comparison relationship is not repeated.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a reserved riding system of an autonomous vehicle according to an embodiment of the present invention. As shown in fig. 2, the reserved riding system for an autonomous vehicle according to an embodiment of the present invention includes a communication module (101), a processing module (102), and a storage module (103); the processing module (102) is connected with the communication module (101) and the storage module (103);
the storage module (103) for storing executable computer program code;
the communication module (101) is used for receiving a scheduled ride instruction, transmitting the scheduled ride instruction to the processing module (102), and sending a scheduling instruction of the processing module (102) to an automatic driving vehicle;
the processing module (102) is configured to execute the method according to any of the preceding claims by calling the executable computer program code in the storage module (103).
The specific functions of the reservation ride system for the autonomous vehicle in this embodiment refer to the above embodiment, and since the system in this embodiment adopts all technical solutions of the above embodiment, at least all beneficial effects brought by the technical solutions of the above embodiment are achieved, and are not described in detail herein.
Referring to fig. 3, fig. 3 is an electronic device according to an embodiment of the present invention, including: a memory storing executable program code; a processor coupled with the memory; the processor calls the executable program code stored in the memory to execute the method according to the previous embodiment.
The embodiment of the invention also discloses a computer storage medium, wherein a computer program is stored on the storage medium, and when the computer program is executed by a processor, the method of the embodiment is executed.
The processor in the electronic device of the present invention may perform various appropriate actions and processes in accordance with a computer program stored in a Read Only Memory (ROM) or a computer program loaded from a memory into a Random Access Memory (RAM). In the RAM, various programs and data required for operations can also be stored. The processor, the ROM, and the RAM are connected to each other through a bus. An input/output (I/O) interface is also connected to the bus.
A plurality of components in an electronic device are connected to an I/O interface, including: an input unit such as a keyboard, a mouse, or the like; an output unit such as various types of displays, speakers, and the like; storage units such as magnetic disks, optical disks, and the like; and a communication unit such as a network card, modem, wireless communication transceiver, etc. The communication unit allows the device to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The processor may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of processors include, but are not limited to, central Processing Units (CPUs), graphics Processing Units (GPUs), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processors, controllers, microcontrollers, and the like. The processor performs the various methods and processes described above, such as a scheduled ride method for an autonomous vehicle. For example, in some embodiments, an autonomous vehicle scheduled ride method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as a memory. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device via the ROM and/or the communication unit. When the computer program is loaded into RAM and executed by the processor, one or more steps of the above-described automated vehicle scheduled ride method may be performed. Alternatively, in other embodiments, the processor may be configured to perform the autonomous vehicle scheduled ride method by any other suitable means (e.g., by way of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The 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, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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 compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with passengers, the systems and techniques described herein may be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to passengers; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a passenger may provide input to the computer. Other kinds of devices may also be used to provide interaction with the passenger; for example, feedback provided to the occupant may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the occupant may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a passenger computer having a graphical passenger interface or a web browser through which a passenger can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server combining a blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (10)
1. A method for reserving a ride for an autonomous vehicle, comprising the steps of:
determining a scheduled ride implementation according to the scheduled ride instructions;
scheduling the autonomous vehicle according to the scheduled ride embodiment.
2. The automated vehicle ride-appointment method according to claim 1, characterized in that: the determining a scheduled ride embodiment according to the scheduled ride instructions comprises:
parsing the reservation ride command to obtain first data, determining a first implementation according to the reservation ride demand data;
acquiring second data according to the first data, and optimizing the first embodiment according to the second data to obtain a second embodiment;
the second embodiment is referred to as the reserved ride embodiment.
3. The automated vehicle ride-appointment method according to claim 2, wherein: the first data comprises a reserved boarding place;
then, the obtaining second data according to the first data includes:
regional geographic data are called according to the reserved boarding place, and berthable position data are determined according to the regional geographic data;
taking the posable location data as the second data.
4. The automated vehicle ride-appointment method according to claim 3, wherein: said optimizing said first embodiment based on said second data to obtain a second embodiment comprising:
determining a target parking location from the berthable location data, and adding the target parking location to the first embodiment to obtain the second embodiment.
5. The automated vehicular scheduled ride method of claim 3 or 4, wherein: the berthable position data comprise attribute data of each parking space;
determining a target parking location according to the berthable location data includes:
judging whether the parking space state of each parking space can be obtained or not according to the attribute data, and if so, taking the parking space with the free parking space state as the target parking position; and if not, determining a plurality of parking spaces as the target parking positions according to the attribute data of each parking space.
6. The reserved riding method for an autonomous vehicle of claim 5, wherein: the first data further comprises a first reserved time;
after determining a plurality of parking spots as the target parking positions according to the grouping result, the method further includes:
and carrying out delay correction on the first reserved time to obtain a second reserved time.
7. The automated vehicle ride-appointment method according to claim 6, wherein: the attribute data comprises parking space attraction;
determining a plurality of parking spaces as the target parking positions according to the attribute data of each parking space, including:
calculating the idle probability of each parking space according to the parking space attraction, and determining a plurality of parking spaces as the target parking positions according to the idle probability and the distance between the parking spaces and the reserved boarding place;
the parking space attraction force is determined according to the place attributes of all places in the preset range and the distance between the parking space attraction force and the corresponding place.
8. An automatic driving vehicle reservation riding system comprises a communication module, a processing module and a storage module; the processing module is connected with the communication module and the storage module;
the storage module is used for storing executable computer program codes;
the communication module is used for receiving the reservation riding instruction, transmitting the reservation riding instruction to the processing module and sending the scheduling instruction of the processing module to the automatic driving vehicle;
the method is characterized in that: the processing module for executing the method according to any one of claims 1-7 by calling the executable computer program code in the storage module.
9. An electronic device, comprising: a memory storing executable program code; a processor coupled with the memory; the method is characterized in that: the processor calls the executable program code stored in the memory to perform the method of any of claims 1-7.
10. A computer storage medium having a computer program stored thereon, characterized in that: the computer program, when executed by a processor, performs the method of any one of claims 1-7.
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