CN115727862A

CN115727862A - Control method and control system of unmanned vehicle, unmanned vehicle and readable storage medium

Info

Publication number: CN115727862A
Application number: CN202110988327.4A
Authority: CN
Inventors: 梁烁斌; 夏友祥; 冯鸿博; 张阳阳
Original assignee: BOE Technology Group Co Ltd; Beijing BOE Technology Development Co Ltd
Current assignee: BOE Technology Group Co Ltd; Beijing BOE Technology Development Co Ltd
Priority date: 2021-08-26
Filing date: 2021-08-26
Publication date: 2023-03-03

Abstract

The application discloses a control method of an unmanned vehicle. The method comprises the following steps: acquiring a riding request of a user, the current position of the user and road information; determining at least one alternative boarding point according to a user riding request and the current position of a user; carrying out route planning according to the road information and the alternative boarding points to obtain at least one alternative route; and determining the expected passing time of each alternative route to determine the target boarding point. According to the unmanned vehicle control method, the user can select a target route from the alternative routes by himself to control the unmanned vehicle to drive to the target getting-on point, the mode of meeting people and vehicles is flexible, and the efficiency of meeting people and vehicles is improved. The application also discloses a control system of the unmanned vehicle, the unmanned vehicle and a readable storage medium.

Description

Control method and control system of unmanned vehicle, unmanned vehicle and readable storage medium

Technical Field

The application relates to the technical field of intelligent automobiles, in particular to a control method and a control system of an unmanned vehicle, the unmanned vehicle and a readable storage medium.

Background

At present, a user can only get on the taxi from a fixed station after calling the unmanned taxi, and often needs to spend more time to reach a riding point of the unmanned taxi, so that in the actual riding process of the unmanned taxi, how to enable a human-vehicle meeting mode to be more flexible is needed, and therefore the efficiency of the human-vehicle meeting is improved.

Disclosure of Invention

In view of the above, the present invention is directed to solving, at least to some extent, one of the problems in the related art. Therefore, the present application is directed to a method of controlling an unmanned vehicle, a control system thereof, an unmanned vehicle, and a readable storage medium.

The embodiment of the application provides a control method of an unmanned vehicle. The control method of the unmanned vehicle comprises the following steps: acquiring a user riding request, a user current position and road information; determining at least one alternative boarding point according to the user riding request and the current position of the user; carrying out route planning according to the road information and the alternative boarding points to obtain at least one alternative route; and determining the expected passing time of each alternative route to determine the target boarding point.

In some embodiments, the determining at least one alternative boarding point according to the user boarding request and the user current location includes: determining an original boarding point according to the user riding request; under the condition that the original vehicle getting-on point is positioned behind the U-turn driving road section and/or the congested road section, selecting a replacement point on the non-U-turn driving road section and/or the uncongested road section; calculating the first step time length from the current position of the user or the original vehicle-loading point to the replacement point and the first running time length of the unmanned vehicle passing through the U-turn running road section and/or the congested road section; and under the condition that the first step traveling time length is smaller than the first traveling time length, newly adding the replacement point as the alternative boarding point.

In some embodiments, the determining at least one alternative boarding point according to the user boarding request and the user current location includes: determining an original boarding point and a target point according to the user riding request; under the condition that the U-turn driving section and/or the congested road section are/is positioned behind the original vehicle-entering point, selecting a replacement point on the non-U-turn driving section and/or the non-congested road section; calculating a second step time length from the current position of the user to the replacement point, a second driving time length from the replacement point to the target point of the unmanned vehicle, and a third driving time length from the original driving point to the target point of the unmanned vehicle; and under the condition that the sum of the second driving time length and the second driving time length is smaller than the third driving time length, adding the replacement point as the alternative getting-on point.

In some embodiments, the determining at least one alternative boarding point according to the user boarding request and the user current location includes: obtaining historical vehicle-boarding point data of the user in an area corresponding to the current position of the user; performing density analysis on the historical vehicle-entering point data to obtain common vehicle-entering points; and determining the alternative boarding points according to the common boarding points.

In some embodiments, the performing the density analysis on the historical boarding point data to obtain a frequent boarding point includes: determining the longitude and latitude of the historical vehicle point data to draw a corresponding coordinate map; aggregating the historical boarding point data according to a preset range on the coordinate map to obtain a boarding point cluster; and determining the common boarding points according to the boarding point clusters.

In some embodiments, the determining the common pick-up point from the pick-up point cluster comprises: performing iterative aggregation on the historical boarding point data corresponding to the boarding point cluster by using a cluster analysis algorithm to obtain a centroid position; and taking the centroid position as the common boarding point.

In some embodiments, the iteratively aggregating the historical boarding point data corresponding to the boarding point cluster by using a cluster analysis algorithm to obtain a centroid position includes: acquiring data creating time corresponding to the historical vehicle point data; determining a weighted value of the corresponding historical vehicle point data according to the data creation time; and performing iterative aggregation on the historical vehicle-entering point data corresponding to the vehicle-entering point cluster by utilizing the cluster analysis algorithm according to the weighted value to obtain the centroid position.

In certain embodiments, the control method comprises: automatically calculating an optimal scheme to determine the target route in the case that the operation of the user for the alternative route is not received; a route confirmation message is sent to notify the user and give the route guidance.

In some embodiments, after the obtaining of the riding request of the user, the current position of the user and the road information, the control method includes: obtaining a user route preference; the determining at least one alternative boarding point according to the user riding request and the current position of the user comprises the following steps: and determining at least one alternative boarding point according to the user route preference, the user riding request and the current position of the user.

In some embodiments, the obtaining the user route preference includes: sending preference selection information to the user mobile terminal; and receiving the operation of the user aiming at the preference selection information to determine the route preference of the user.

In some embodiments, the obtaining the user route preference includes: acquiring historical trip information of a user, wherein the historical trip information comprises a preset user label; and analyzing the historical travel information according to a word frequency calculation algorithm to obtain the route preference of the user.

In some embodiments, the preset user label is learned from a neural network.

In certain embodiments, the control method comprises: acquiring environmental information around the target getting-on point under the condition that the unmanned vehicle runs to the first preset distance of the target getting-on point; and under the condition that the environmental information around the target boarding point is not suitable for the parking of the vehicle, re-determining the target boarding point and informing the user.

In some embodiments, after the unmanned vehicle travels to the target boarding point, the control method includes: and controlling the unmanned vehicle to select a parking space near the target getting-on point to park under the condition that the distance between the user and the target getting-on point is greater than a second preset distance or the waiting time is greater than a preset time.

The application also provides a control system of the unmanned vehicle. The control system of the unmanned vehicle comprises: the system comprises an acquisition module, a boarding point determining module, a route planning module, a duration determining module, a route determining module and a control module. The acquisition module is used for acquiring a riding request of a user, the current position of the user and road information; the boarding point determining module is used for determining at least one alternative boarding point according to the user riding request and the current position of the user; the route planning module is used for carrying out route planning according to the road information and the alternative vehicle-loading points to obtain at least one alternative route; the determining module is used for determining the predicted passing time of each alternative route to determine the target boarding point.

The application also provides an unmanned vehicle. The unmanned vehicle comprises a processor and a memory, the memory is used for storing a computer program, and the processor realizes the control method of any one of the above embodiments when executing the computer program.

The present application also provides a non-transitory computer-readable storage medium of a computer program. The computer program, when executed by one or more processors, implements the control method of any of the above embodiments.

According to the control method of the unmanned vehicle, the user can select a target route from the alternative routes by himself to control the unmanned vehicle to travel to the target getting-on point, the mode of meeting people and vehicles is flexible, and the efficiency of meeting people and vehicles is improved.

Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.

Drawings

The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:

FIG. 1 is a flow chart schematic of a method of controlling an unmanned vehicle according to certain embodiments of the present application;

FIG. 2 is a schematic block diagram of a control system for an unmanned vehicle according to certain embodiments of the present application;

FIG. 3 is a schematic illustration of a scenario of a control method of an unmanned vehicle according to some embodiments of the present application;

FIG. 4 is a schematic illustration of a scenario of a control method of an unmanned vehicle according to some embodiments of the present application;

FIG. 5 is a schematic illustration of a scenario of a control method of an unmanned vehicle according to some embodiments of the present application;

FIG. 6 is a flow chart illustrating a method of controlling an unmanned vehicle according to some embodiments of the present application;

FIG. 7 is a block diagram illustrating a pick-up point determination module in an unmanned vehicle control system according to some embodiments of the present disclosure;

FIG. 8 is a schematic illustration of a scenario of a control method of an unmanned vehicle according to some embodiments of the present application;

FIG. 9 is a schematic flow chart diagram of a method of controlling an unmanned vehicle according to certain embodiments of the present application;

FIG. 10 is a schematic illustration of a scenario for a method of controlling an unmanned vehicle in accordance with certain embodiments of the present application;

FIG. 11 is a schematic flow chart diagram of a method of controlling an unmanned vehicle according to certain embodiments of the present application;

FIG. 12 is a schematic block diagram of a determination unit in the pick-up point determination module in accordance with certain embodiments of the present application;

FIG. 13 is a schematic flow chart diagram of a method of controlling an unmanned vehicle according to certain embodiments of the present application;

FIG. 14 is a schematic diagram of the structure of an analysis unit in a determination unit in accordance with certain embodiments of the present application;

FIG. 15 is a flow chart illustrating a method of controlling an unmanned vehicle according to certain embodiments of the present application;

FIG. 16 is a schematic flow chart diagram of a method of controlling an unmanned vehicle according to certain embodiments of the present application;

FIG. 17 is a schematic structural diagram of a common pick-up point determining unit in an analysis unit according to some embodiments of the present application;

FIG. 18 is a flow chart illustrating a method of controlling an unmanned vehicle according to some embodiments of the present application;

FIG. 19 is a schematic block diagram of a control system for an unmanned vehicle according to some embodiments of the subject application;

FIG. 20 is a schematic flow chart diagram of a control method for an unmanned vehicle according to some embodiments of the present application;

FIG. 21 is a schematic flow chart diagram of a control method for an unmanned vehicle according to some embodiments of the present application;

FIG. 22 is a flow chart illustrating a method of controlling an unmanned vehicle according to certain embodiments of the present application;

FIG. 23 is a schematic diagram of the formula of the TF-IDF algorithm of certain embodiments of the present application;

FIG. 24 is a schematic flow chart diagram of a control method for an unmanned vehicle according to some embodiments of the present application;

FIG. 25 is a schematic block diagram of a control module in the control system of an unmanned vehicle according to some embodiments of the subject application;

FIG. 26 is a schematic flow chart diagram of a control method for an unmanned vehicle according to some embodiments of the present application;

FIG. 27 is a schematic block diagram of a control system for an unmanned vehicle according to certain embodiments of the subject application;

FIG. 28 is a schematic flow chart diagram of a control method for an unmanned vehicle according to some embodiments of the present application;

FIG. 29 is a schematic block diagram of a control system for an unmanned vehicle according to certain embodiments of the subject application;

FIG. 30 is a schematic illustration of the structure of an unmanned vehicle according to certain embodiments of the present application;

FIG. 31 is a schematic diagram of a computer-readable storage medium according to some embodiments of the present application.

Detailed Description

Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative and are only for the purpose of explaining the present application and are not to be construed as limiting the present application.

In the description of the present application, it is to be understood that the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or as implying that the number of indicated technical features is indicated. Thus, features defined as "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present application, "a plurality" means two or more unless specifically defined otherwise.

In the description of the present application, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; may be mechanically connected, may be electrically connected or may be in communication with each other; they may be directly connected or indirectly connected through intervening media, or may be connected through the use of two elements or the interaction of two elements. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art as appropriate.

The following disclosure provides many different embodiments or examples for implementing different features of the application. In order to simplify the disclosure of the present application, specific example components and arrangements are described below. Of course, they are merely examples and are not intended to limit the present application. Further, the present application may repeat reference numerals and/or reference letters in the various examples for simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or arrangements discussed.

In view of the above, referring to fig. 1, the present application provides a control method for an unmanned vehicle. The control method of the unmanned vehicle comprises the following steps:

01: acquiring a riding request of a user, the current position of the user and road information;

02: determining at least one alternative boarding point according to a user riding request and the current position of a user;

03: carrying out route planning according to the road information and the alternative boarding points to obtain at least one alternative route;

04: and determining the expected passing time of each alternative route to determine the target boarding point.

Referring to fig. 2, the present application further provides a control system 10 for an unmanned vehicle. The control system 10 of the unmanned vehicle includes: an acquisition module 11, an upper vehicle point determination module 12, a route planning module 13 and a determination module 14. The control system 10 of the unmanned vehicle may be internally connected to the unmanned vehicle, or may be a control device externally connected to the unmanned vehicle, and the present application takes the case where the control system 10 of the unmanned vehicle is internally connected to the unmanned vehicle as an example. The unmanned vehicle's control system 10 may also be part of the unmanned vehicle's mesh platform.

Step 01 can be implemented by the obtaining module 11, step 02 can be implemented by the boarding point determining module 12, step 03 can be implemented by the route planning module 13, and step 04 can be implemented by the determining module 14. That is, the obtaining module 11 is configured to obtain a riding request of a user, a current location of the user, and road information. The boarding point determining module 12 is configured to determine at least one candidate boarding point according to the user riding request and the current position of the user. The route planning module 13 is configured to perform route planning according to the road information and the alternative boarding points to obtain at least one alternative route. The determination module 14 is used for determining the expected passing time of each alternative route to determine the target boarding point.

Specifically, first, the control system 10 of the unmanned vehicle may obtain a user riding request, may determine a current location of the user (for example, point O in fig. 3, or fig. 4 and fig. 5) according to the user riding request, and may determine road information near the boarding point of the unmanned vehicle according to the current location of the user and the location of the unmanned vehicle itself. For example, when the user requests to take a vehicle from point a to point B, the area near point a is the point where no vehicle is getting on, and road information near the area near point a and point O can be acquired, where the road information includes the traffic congestion situation of the road near point a, and the road information such as the time when the user needs to turn around, turn, and pass forward.

And then, determining at least one alternative boarding point according to the riding request of the user and the current position of the user. At least one alternative boarding point means that one alternative boarding point A1 or a plurality of alternative boarding points A2, A3 and A4 \8230canbe arranged near the area of the point A.

When there is only one alternative boarding point A1, route planning may be performed according to the road information and the target boarding point to obtain multiple alternative routes, such as planning 3 alternative routes A1O1, A1O2, and A1O3 as shown in fig. 3.

When there are multiple candidate pick-up points, for example, 4 candidate pick-up points A2, A3, A4, and A5, the control system of the unmanned vehicle may perform route planning according to multiple target pick-up points to obtain one or more candidate routes corresponding to each target pick-up point, so as to obtain multiple candidate routes.

In one example, each alternative boarding point is only correspondingly planned to obtain one alternative route, that is, the number of the alternative boarding points is the same as that of the alternative routes. For example, as shown in fig. 4, the alternative route corresponding to the alternative boarding point A2 may be one, and be the alternative route A2O1, the alternative route corresponding to the alternative boarding point A3 may be one, and be the alternative route A3O1, and the alternative route corresponding to the alternative boarding point A4 may be one, and be the alternative route A4O1, and the alternative route corresponding to the target boarding point A5 may be one, and be the alternative route A5O1. At this time, route planning is performed on 4 target boarding points A2, A3, A4, and A5 to obtain 4 alternative routes A2O1, A3O1, A4O1, and A5O1.

In another example, multiple alternative routes may be planned for each alternative pick-up point. As shown in fig. 5, for example, there may be 3 alternative routes corresponding to alternative boarding point A2, which are alternative routes A2O2, A2O3, and A2O4, respectively, there may also be 3 alternative routes corresponding to alternative boarding point A3, which are alternative routes A3O2, A3O3, and A3O4, respectively, there may also be 3 alternative routes corresponding to alternative boarding point A4, which are alternative routes A4O2, A4O3, and A4O4, respectively, and there may also be 3 alternative routes corresponding to alternative boarding point A5, which are alternative routes A5O2, A5O3, and A5O4, respectively.

In other embodiments of the present application, when there are multiple alternative boarding points, one alternative route may be obtained by planning on alternative target boarding points, multiple alternative routes are obtained by planning on the remaining alternative boarding points, and the planning condition of the specific alternative route is determined according to the actual road condition.

Then, the expected passing time of each alternative route is determined to determine the target boarding point. Specifically, determining the expected passing time of each alternative route to determine the target boarding point may determine the expected passing time of each alternative route to send the alternative route and the expected passing time to the user mobile terminal, and then receive an operation of the user on the alternative route to determine the target boarding point. And finally, controlling the unmanned vehicle to travel to the corresponding target boarding point along the target route.

In detail, the expected passing time of each alternative route can be calculated and determined according to the distance of each alternative route and the real-time congestion condition of the vehicle and the running speed of the unmanned vehicle. For example, as shown in FIG. 3, the predicted transit times for the three alternative routes A1O1, A1O2, A1O3 are 4 minutes, 5 minutes, and 6 minutes, respectively. Since the alternative route A1O3 is a main traffic road and has a large traffic flow and is congested, the predicted passing time of the alternative route A1O3 is the longest, and the time duration is 6 minutes, including the predicted congestion time being 2 minutes. The alternative route A1O2 may require that the unmanned vehicle turn around or that the unmanned vehicle is far from the user location, so the expected transit time of the alternative route A1O2 is long; alternative route A1O1 may not require that the unmanned vehicle turn around to a straight line segment or that the unmanned vehicle be closer to the user location, so the expected transit time for alternative route A1O1 is shortest.

The control system 10 of the unmanned vehicle may then receive a user determination of a target route for operation of an alternate route. For example, the alternative route A1O1 with the shortest expected passing time in fig. 3 is selected as the target route, and the target boarding point is determined to be the point A1. The operation of the user on the alternative route may refer to that the user touches a certain alternative route with a finger as a target route after seeing the alternative route and the corresponding expected passing time at a user moving end (for example, a mobile device such as a mobile phone, an intelligent bracelet, a computer, and the like), or the user selects a certain alternative route as a target route by using a language function.

Finally, the control system 10 of the unmanned vehicle may control the unmanned vehicle to travel along the target route to the corresponding target pick-up point. For example, the control system 10 of the unmanned vehicle may control the unmanned vehicle to travel along the target route A1O1 to the corresponding target boarding point A1.

According to the unmanned vehicle control method, at least one alternative boarding point can be determined according to a user riding request and the current position of the user, then at least one alternative route is planned according to road information and the alternative boarding points, and the predicted passing time of each alternative route is determined to determine the target boarding point, so that the meeting mode of the user and the unmanned vehicle is more flexible, and the meeting efficiency of the user and the vehicle is improved.

Referring to fig. 6, in some embodiments, step 02 includes:

021: determining an original boarding point according to a user riding request;

022: under the condition that the original vehicle-getting point is positioned behind the U-turn driving road section and/or the congested road section, selecting a replacement point on the non-U-turn driving road section and/or the uncongested road section;

023: calculating the first step time length from the current position of the user or the original vehicle-loading point to the replacement point, and the first driving time length of the unmanned vehicle through the U-turn driving road section and/or the congestion road section;

024: and under the condition that the first-step driving time length is less than the first driving time length, newly adding the replacement point as an alternative vehicle-entering point.

Referring to fig. 7, in some embodiments, the pick-up point determining module 12 includes a determining unit 121, a replacement point selecting unit 122, a duration calculating unit 123, and a pick-up point adding unit 124.

Step 021 may be implemented by the determining unit 121, step 022 may be implemented by the replacement point selecting unit 122, step 023 may be implemented by the duration calculating unit 123, and step 024 may be implemented by the boarding point newly-adding unit 124. That is, the determining unit 121 is configured to determine an original boarding point according to the user boarding request; the replacement point selection unit 122 is configured to select a replacement point on a non-u-turn driving road section and/or a non-congested road section when the original boarding point is located behind the u-turn driving road section and/or the congested road section; the duration calculating unit 123 is configured to calculate a first step duration from the current location of the user or the original boarding point to the replacement point, and a first driving duration of the unmanned vehicle passing through the u-turn driving road segment and/or the congested road segment; the boarding point addition unit 124 is configured to add the replacement point as the alternative boarding point if the first travel time period is less than the first travel time period.

Specifically, for example, as shown in fig. 8, when the user takes the vehicle from point a to point B in order to take the unmanned vehicle, and the original boarding point determining unit determines that point A1 near point a is the original boarding point, in the case where the original boarding point A1 is located behind the u-turn driving link and/or the congested link, that is, in the case where the unmanned vehicle needs to pass through the u-turn driving link and/or the congested link in order to reach the original boarding point A1, the replacement point may be selected correspondingly on the non-u-turn driving link and/or the uncongested link. The situation that no vehicle reaches the original driving point A1 and needs to pass through a U-turn driving road section and/or a congestion road section comprises three situations: the unmanned vehicle only needs to pass through the turning-around driving road section when reaching the original boarding point A1; the unmanned vehicle only needs to pass through the congested road section when reaching the original boarding point A1; the unmanned vehicle needs to pass through a U-turn driving road section and a congestion road section when arriving at the original vehicle-entering point A1.

The present application takes an example that an unmanned vehicle needs to pass through a u-turn driving section and a congested section when arriving at an original vehicle-entering point A1, that is, as shown in fig. 8, a u-turn driving section ab and a congested section ad exist at the same time, so that a new alternative vehicle-entering point C1 point that can be selected is a section position close to the unmanned vehicle, which is outside the u-turn driving section (ab) or the congested section (cd). In addition, whether the first step traveling time length of the user walking from the current position of the user to the point C1 is shorter than the first traveling time length of the unmanned vehicle which completely falls off and passes through the congested road section or not can be calculated, and if the first step traveling time length is shorter than the first traveling time length, the point C1 of the new candidate getting-on point can be selected as the replacement point. Or when the user has reached the original boarding point A1 and the unmanned vehicle still does not reach the original boarding point A1, the new alternative boarding point C1 may be temporarily selected as the replacement point by calculating that the first-step travel time for the user to walk from the original boarding point to the new alternative boarding point C1 is shorter than the first travel time for the unmanned vehicle to end up and pass through the congested road segment.

The scheme that the unmanned vehicle only needs to pass through the U-turn driving road section and only needs to pass through the congestion road section to select the replacement point to get on the vehicle when arriving at the original getting-on point A1 is the same as the scheme that the unmanned vehicle only needs to pass through the U-turn driving road section and the congestion road section to select the replacement point to get on the vehicle when arriving at the original getting-on point A1. Specifically, when the unmanned vehicle reaches the original boarding point A1 and only passes through the u-turn driving section, only the first driving time length after the unmanned vehicle finishes turning is calculated, and when the unmanned vehicle reaches the original boarding point A1 and only passes through the congested section, only the first driving time length after the unmanned vehicle passes through the congested section is calculated. Accordingly, the first travel time length and the first step travel time length when the current position of the user reaches the selected new boarding point are compared, and the first step travel time length is smaller than the first travel time length, so that the selected new boarding point can be used as a replacement point.

In one example, the control system 10 of the unmanned vehicle calculates the first step time length from the current position O of the user to the replacement point C1 by the time length calculation unit 123 to be 2.5 minutes, or the first step time length from the previous vehicle point A1 to the replacement point C1 to be 2 minutes. In addition, the control system 10 of the unmanned vehicle may also calculate the first travel time period for the unmanned vehicle to pass through the u-turn travel section and/or the congested section through the time period calculation unit 123, for example, the first travel time period for the unmanned vehicle to simultaneously pass through the u-turn travel section and the congested section is 6 minutes in fig. 8. At this time, the first-step traveling time (2 minutes or 2.5 minutes) is shorter than the first traveling time (6 minutes), so the replacement point C1 can be newly added as an alternative boarding point, that is, the user can select to walk from the current position O point of the user or the original boarding point A1 to the replacement point C1 to get on the vehicle, and the unmanned vehicle does not need to reach the boarding point through the u-turn traveling road section or the congested road section, so that the time for meeting people and vehicles is shortened, the mode for meeting people and vehicles is flexible, and the efficiency for meeting people and vehicles is improved.

Referring to fig. 9, in some embodiments, step 02 includes:

025: determining an original boarding point and a target point according to a user riding request;

026: under the condition that the U-turn driving section and/or the congested road section are/is positioned behind the original vehicle-entering point, selecting a replacement point on the non-U-turn driving section and/or the non-congested road section;

027: calculating the second step driving time length from the current position of the user to the replacement point, the second driving time length from the replacement point to the target point of the unmanned vehicle, and the third driving time length from the original vehicle-loading point to the target point of the unmanned vehicle;

028: and under the condition that the sum of the second driving time length and the second driving time length is less than the third driving time length, adding the replacement point as the alternative getting-on point.

Referring to fig. 7, step 025 may be implemented by the determining unit 121, step 026 may be implemented by the replacement point selecting unit 122, step 027 may be implemented by the duration calculating unit 123, and step 028 may be implemented by the boarding point newly adding unit 124. That is, the determining unit 121 is configured to determine the original boarding point and the target point according to the user request; the replacement point selection unit 122 is configured to select a replacement point on the non-u-turn driving road section and/or the non-congested road section when the u-turn driving section and/or the congested road section are located behind the original vehicle-entering point; the duration calculation unit 123 is configured to calculate a second step duration from the current location of the user to the replacement point, a second driving duration from the replacement point to the target point of the unmanned vehicle, and a third driving duration from the original boarding point to the target point of the unmanned vehicle; the boarding point adding unit 124 is configured to add the replacement point as the alternative boarding point if the second travel time period plus the second travel time period is less than the third travel time period.

Specifically, referring to fig. 10, if the user takes the bus from point a (supermarket location or cell location) to point B, it can be determined that the original bus point is point A1 and the target point is point B. Under the condition that the U-turn driving section (ab section) and/or the congestion section (cd section) are located behind the original vehicle-entering point A1, the fact that the unmanned vehicle can pass through the U-turn driving section (ab section) and/or the congestion section (cd section) after meeting with the user at the original vehicle-entering point A1 is meant. The following three situations that the unmanned vehicle can pass through a turning-around driving section (ab section) and/or a congestion section (cd section) after meeting with a user at an original vehicle-entering point A1 include: the unmanned vehicle only passes through a turning-around driving section (ab section) after meeting with a user at an original vehicle-entering point A1; the unmanned vehicle only passes through a congestion road section (cd section) after meeting with the user at the original vehicle getting-on point A1; the unmanned vehicle can also pass through a turning-around driving section (ab section) and a congestion section (cd section) after meeting with the user at the original vehicle-entering point A1.

The present application takes as an example that the unmanned vehicle shown in fig. 10 passes through a u-turn traveling section (ab section) and a congested road section (cd section) after meeting with the user at the original boarding point A1. As shown in fig. 10, at this time, the time for the unmanned vehicle to reach the target point B from the original boarding point A1 consumes much time due to the need for turning around and traffic jam, so when selecting the boarding point, a replacement point may be selected on the non-turning-around driving road segment and the non-traffic jam road segment, for example, a replacement point D1 may be selected on another alternative route 2 of the non-turning-around road segment and the non-traffic jam road segment without traffic jam, and the user walks to the replacement point D1 to get on the vehicle, thereby avoiding the occurrence of the situation that the time for the unmanned vehicle to reach the target point B from the original boarding point A1 consumes much time due to the need for turning around and traffic jam.

Further, a second driving duration from the current location of the user to the replacement point, a second driving duration from the replacement point to the target point of the unmanned vehicle, and a third driving duration from the original driving point to the target point of the unmanned vehicle may be calculated by the duration calculating unit 123, and when the second driving duration plus the second driving duration is smaller than the third driving duration, the replacement point is newly added as the target driving point. For example, the current position of the user is the point O1, the replacement point is the point D1, the second travel time of the user from the current position O1 of the user to the replacement point D1 is 2 minutes, the second travel time of the unmanned vehicle from the replacement point D1 (a new target boarding point) to the point B of the target point is 4 minutes, at this time, since the unmanned vehicle passes through a u-turn road section or a congested road section after being loaded to the user at the original boarding point A1, the third travel time of the unmanned vehicle from the original boarding point A1 to the point B of the target point is longer and possibly 10 minutes, that is, the total required time for the unmanned vehicle to meet the user and reach the target point after receiving the user boarding request is shortened by the second travel time of 2 minutes plus the second travel time of 6 minutes to be less than 10 minutes, at this time, the replacement point D1 may be newly added to the boarding point, thereby shortening the total required time for the unmanned vehicle to meet the user and carry the user to reach the target point, and improving the driving efficiency of the unmanned vehicle.

The scheme that the unmanned vehicle only needs to pass through the U-turn road section and only needs to pass through the congested road section after the original vehicle-entering point A1 meets the user is the same as the principle that the unmanned vehicle only needs to pass through the U-turn road section and the congested road section at the same time, and the driving time of the third route from the original vehicle-entering point A1 to the target point B is different because the time of the third route only needs to turn around or only needs to pass through the congested road section, so that the repeated description is omitted.

Referring to fig. 11, step 021 includes:

0211: acquiring historical vehicle-boarding point data of a user in an area corresponding to the current position of the user;

0212: carrying out density analysis on historical boarding point data to obtain a common boarding point;

0213: and determining alternative boarding points according to the common boarding points.

Referring to fig. 12, the determination unit 121 may include an acquisition unit 1211, an analysis unit 1212, and an boarding point determination unit 1213.

Step 0211 may be implemented by the acquisition unit 1211, step 0212 may be implemented by the analysis unit 1212, and step 0213 may be implemented by the boarding point determination unit 1213. That is, the obtaining unit 1211 is configured to obtain historical boarding point data of the user in an area corresponding to the current location of the user; the analysis unit 1212 is configured to perform density analysis on the historical boarding point data to obtain a common boarding point; the boarding point determination unit 1213 is configured to determine a target boarding point from the common boarding points.

Specifically, when a boarding point is selected, the boarding point data of a plurality of taxis within a certain time period can be obtained to obtain historical boarding point data in an area corresponding to the current position of the user, density analysis is performed on the historical boarding point data, common boarding points most frequently used by the user in the area close to the area corresponding to the current position of the user are collected, a coordinate map can be drawn by taking longitude and latitude as horizontal and vertical coordinates to mark the common boarding points of the user, and then an alternative boarding point is determined according to the common boarding points, for example, the common boarding points can be used as alternative boarding points.

Referring to fig. 13, step 0212 includes:

02121: determining longitude and latitude of historical vehicle point data to draw a corresponding coordinate map;

02122: aggregating historical boarding point data according to a preset range on a coordinate map to obtain a boarding point cluster;

02123: and determining a common boarding point according to the boarding point cluster.

Referring to fig. 14, the analysis unit 1212 includes a mapping unit 12121, a boarding point cluster acquisition unit 12122, and a common boarding point determination unit 12123.

Step 02121 may be implemented by the mapping unit 12121, step 02122 may be implemented by the last vehicle point cluster acquisition unit 12122, and step 02123 may be implemented by the common last vehicle point determination unit 12123. That is, the map drawing unit 12121 is configured to determine the longitude and latitude of the historical vehicle-point data to draw a corresponding coordinate map; the boarding point cluster acquisition unit 12122 is configured to aggregate historical boarding point data according to a preset range on the coordinate map to obtain a boarding point cluster; the frequent boarding point determination unit 12123 is configured to determine a frequent boarding point from the cluster of boarding points.

Specifically, the historical boarding point data includes boarding points collected that are most frequently used by nearby users, and then a coordinate map is drawn with longitude and latitude as horizontal and vertical coordinates. The historical taxi-taking point data can be determined based on the selection of other taxi-taking points within a certain time.

Then, the boarding data sets can be aggregated into a plurality of clusters according to a certain active radius (for example, 10 meters as the active radius) based on the DBSCAN algorithm, so as to distinguish data clusters in different directions, for example, different data clusters on the east side or the west side of the cell gate, and the interference generated between the data clusters with different boarding position preferences can be prevented. And finally, taking the data set of each cluster as new input data to obtain a plurality of boarding point clusters, thereby determining common boarding points according to the boarding point clusters.

Referring to fig. 15, step 02123 includes:

021231: carrying out iterative aggregation on historical boarding point data corresponding to the boarding point cluster by utilizing a cluster analysis algorithm to obtain a centroid position;

021232: and taking the position of the mass center as a common boarding point.

Referring to fig. 14,

steps

021231 and 021232 can be implemented by the frequent pick-up point determination unit 12123. That is, the common boarding point determining unit 12123 is configured to perform iterative aggregation on historical boarding point data corresponding to a boarding point cluster by using a cluster analysis algorithm to obtain a centroid position; and taking the position of the mass center as a common boarding point.

Specifically, the cluster analysis algorithm includes a Kmeans algorithm, that is, the iterative aggregation function of the Kmeans algorithm can be used to calculate the position of the centroid as a common boarding point according to a plurality of boarding point clusters.

Referring to fig. 16, step 021231 includes:

0212311: acquiring data creating time corresponding to historical vehicle point data;

0212312: determining a weighted value of corresponding historical vehicle point data according to the data creation time;

0212313: and performing iterative aggregation on historical vehicle-entering point data corresponding to the vehicle-entering point cluster by utilizing a clustering analysis algorithm according to the weighted value to obtain the centroid position.

Referring to fig. 17, the common boarding point determination unit 12123 further includes a centroid determination unit 121231.

Steps

0212311, 0212312 and 0212313 may each be implemented by the centroid determining unit 121231. That is, the centroid determining unit 121231 is configured to acquire the data creation time corresponding to the historical point data; determining a weighted value of corresponding historical vehicle point data according to the data creation time; and performing iterative aggregation on historical vehicle-entering point data corresponding to the vehicle-entering point cluster by utilizing a clustering analysis algorithm according to the weighted value to obtain the centroid position.

It can be understood that based on the analysis of the selection conditions of the taxi-boarding points of other taxis within a certain time, the situation that the unmanned taxi selects the taxi-boarding point which is forbidden to park according to other rules, such as a residential quarter front door, for parking can be avoided, and therefore a user is inconvenient to meet the unmanned taxi.

Specifically, since the rule of prohibiting parking at a certain boarding point may change over time, that is, the position may prohibit parking for a certain period of time, and the position may be parked again after the period of time, the time dependency needs to be considered. Therefore, when the Kmeans algorithm is used, a time label is added, the weighted value of the corresponding historical vehicle-entering point data is determined according to the data creation time, and then the historical vehicle-entering point data corresponding to the vehicle-entering point cluster is subjected to iterative aggregation by using the cluster analysis algorithm according to the weighted value to obtain the centroid position.

The determination of the weighted value of the corresponding historical point-to-point data according to the data creation time means that, for example, the data weight within 1 hour is 1, and the data weight before 1 week is 0.1.

According to the control method, the data in one data cluster are weighted according to time, and clustering analysis of the data in a short term can be achieved. In other embodiments of the present application, for example, the weight of the historically same time period may also be set to 1, and the weight of the other time period may be set to 0.1, so as to avoid the influence of other historically same factors on the boarding point.

Referring to fig. 18, the control method further includes:

07: under the condition that the operation of a user for the alternative route is not received, automatically calculating an optimal scheme to determine a target route;

08: a route confirmation message is sent to notify the user and give the route guidance.

Referring to fig. 19, the control system 10 of the unmanned vehicle further includes an automatic optimization module 17 and a route confirmation and guidance module 18.

Step 07 may be implemented by the automatic optimization module 17 and step 08 may be implemented by the route confirmation and guidance module 18. That is, the automatic optimization module 17 is configured to automatically calculate an optimal solution to determine the target route without receiving the operation of the user on the alternative route; the route confirmation and guidance module 18 is used to send route confirmation messages to inform the user and give route guidance.

Specifically, if the user placing the order fails to respond to the selection of the alternative in real time, that is, under the condition that the unmanned vehicle does not receive the operation of the user on the alternative route, the unmanned vehicle can automatically select and calculate the optimal scheme, notify the user through the telephone, the unmanned vehicle network platform to send messages and the like before arriving, and give a path guide.

Referring to fig. 20, after step 01, the control method includes:

011: obtaining a user route preference;

step 02 comprises:

021: and determining at least one alternative boarding point according to the user route preference, the user riding request and the current position of the user.

Referring to fig. 1, step 011 can be implemented by the obtaining module 11, and step 021 can be implemented by the boarding point determining module 12. That is, the obtaining module 11 is configured to obtain the route preference of the user; the pick-up point determination module 12 is configured to determine at least one alternative pick-up point based on the user route preference, the user request for a ride, and the user's current location.

It can be understood that each user has different preferences and different favorite selected boarding points, and the determination of at least one target boarding point by combining the route preferences of the user can better adapt to the preferences of the user and improve the user experience.

Specifically, the preference of the user in terms of riding can be collected in a question and answer mode when the user places an order on an unmanned vehicle network platform for the first time. For example, the user may be asked whether he would like to spend 5 minutes more, 10 minutes more, to avoid walking as much as possible, or to prioritize efficiency.

Referring to fig. 21, further, step 011 includes:

0111: sending preference selection information to a user mobile terminal;

0112: and receiving the operation of the user on the preference selection information to determine the route preference of the user.

Referring to fig. 1, step 0111 and step 0112 may be implemented by the obtaining module 11. That is, the obtaining module 11 may be specifically configured to send preference selection information to the user mobile terminal; and receiving the operation of the user on the preference selection information to determine the route preference of the user.

Specifically, the preference selection information may be sent to the user mobile terminal in a form of a question and answer on an ordering platform of the unmanned vehicle network contract, or may be sent to the user mobile terminal in a form of a questionnaire or in other forms. The drone vehicle may then receive the user-selected preference selection information to determine the user route preferences.

Referring to fig. 22, step 011 includes:

0113: acquiring historical trip information of a user, wherein the historical trip information comprises a preset user label;

0114: and analyzing historical travel information according to a word frequency calculation algorithm to obtain the route preference of the user.

Referring to fig. 1, step 0113 and step 0114 may be implemented by the obtaining module 11. That is, the obtaining module 11 may be specifically configured to obtain historical trip information of the user, where the historical trip information includes a preset user tag; and analyzing historical travel information according to a word frequency calculation algorithm to obtain the route preference of the user.

Specifically, for a user with too many riding histories, analysis may be performed in combination with the trip record of the past period, for example, to determine which time period the user prefers to save the trip time, and in which vicinity of the boarding point the user prefers to reduce the walking distance, etc., so as to help the user generate a more appropriate trip plan.

For example, when analyzing the user preference, a TF-IDF algorithm may be used to analyze the user preference to obtain the travel preference of the user (as shown in fig. 23, where P is a user identifier used to distinguish different users, and Ti includes all preset user tags of the user identified as P). According to the control method of the unmanned vehicle, the preference of a certain user and the preset user label of the user can be marked in a one-to-one correspondence mode through the preset user label, and the travel preference of the user can be analyzed.

The preset user label may be a yellow triangle mark or other color or shape representation, for example, the yellow triangle mark represents that the user does not like walking, and the red triangle mark represents that the user likes to save travel time during 8 o 'clock to 9 o' clock.

In particular, the user's label can also be continuously learned through a neural network.

Referring to fig. 24, in some embodiments, step 04 includes:

041: under the condition that the unmanned vehicle drives to a first preset distance of a target boarding point, acquiring environmental information around the target boarding point;

042: and under the condition that the environmental information around the target boarding point is not suitable for the parking of the vehicle, re-determining the target boarding point and informing the user.

Referring to fig. 25, the determination module 14 includes an environment information acquisition unit 141 and a re-determination unit 142.

Step 041 may be implemented by the environment information obtaining unit 141, and step 042 may be implemented by the re-determination unit 142. That is, the environment information acquiring unit 141 is configured to acquire the environment information around the target boarding point when the unmanned vehicle travels within the first preset distance of the target boarding point; the re-determination unit 142 is configured to re-determine the target boarding point and notify the user in a case where the environmental information around the target boarding point is not suitable for the parking of the vehicle.

Specifically, when the unmanned vehicle runs to the vicinity of the target boarding point, if the user has a certain distance, and the user finds that certain obstacles exist in the vicinity of the target boarding point through image analysis, for example, shared single vehicle parking, other vehicle parking, temporary building maintenance and other conditions exist, and the situations are not suitable for the unmanned vehicle to park for a long time.

And replanning the boarding point and informing the user of collecting road conditions near the boarding point for the network car-booking cloud platform, wherein the road conditions comprise vehicle congestion conditions, whether turning and turning are needed, when the vehicle passes through the boarding point in future and the like, the time when the user arrives at the boarding point and the waiting time of an unmanned vehicle are analyzed, and other alternative schemes and corresponding passing time are provided and sent to the user mobile terminal.

Referring to fig. 26, after the unmanned vehicle travels to the target boarding point, the control method includes:

051: acquiring user identity information for identity matching;

052: and after the identity matching is successful, allowing the user to get on the bus to complete the getting on task.

Referring to fig. 27, the control system 10 of the unmanned vehicle further includes an identity matching module 151.

Both

steps

051 and 052 may be implemented by identity matching module 151. That is, the identity matching module 151 is configured to obtain the user identity information for identity matching; and after the identity matching is successful, allowing the user to get on the bus to complete the getting on task.

Specifically, the online booking platform can analyze the distance between the user and the unmanned workshop in real time. When the unmanned vehicle runs near the boarding point, if the user is also located near the boarding point, the unmanned vehicle stops at the selected boarding point, and then the user finishes boarding after identity matching is carried out by scanning the two-dimensional code. The identity matching mode is not limited to the mode of scanning the two-dimensional code, and may be other forms, which is not limited herein.

Referring to fig. 28, after the unmanned vehicle travels to the target boarding point, the control method includes:

053: and under the condition that the distance between the user and the target boarding point is greater than a second preset distance or the waiting time is greater than preset time, controlling the unmanned vehicle to select a parking space near the target boarding point to park.

Referring to fig. 29, the control system 10 of the unmanned vehicle further includes a docking module 153.

Step 053 may be implemented by the parking module 153, that is, the parking module 153 is configured to control the unmanned vehicle to select a parking space near the target pick-up point to park if the distance between the user and the target pick-up point is greater than the second preset distance or the waiting time is greater than the preset time.

Specifically, if the user is far away from the boarding point or delays for a long time due to other things, the unmanned vehicle selects a parking lot near the boarding point or a fixed parking space of the unmanned vehicle to park, and resumes running when waiting for the user to go out or walk to the vicinity of the boarding point.

Referring to fig. 30, the present application further provides an unmanned vehicle 100. The unmanned vehicle 100 comprises a processor 110 and a memory 120, the memory 120 is used for storing a computer program 121, and the processor 110 implements the control method of the unmanned vehicle according to any one of the above embodiments when executing the computer program 121.

The unmanned vehicle can determine at least one alternative boarding point according to a user riding request and the current position of the user, then plan at least one alternative route according to road information and the alternative boarding points, and determine the expected passing time of each alternative route to be sent to the user mobile terminal. The user can select a target route from the alternative routes by himself to control the unmanned vehicle to drive to a target boarding point according to the target route, so that the meeting mode of the user and the unmanned vehicle is more flexible, and the meeting efficiency of the user and the vehicle is improved.

Referring to fig. 31, the present application also provides a non-volatile computer-readable storage medium 200 of a computer program. The computer program 210, when executed by the one or more processors 220, implements the method of controlling an unmanned vehicle as described in any of the embodiments above.

The unmanned vehicle control method and the control system thereof, the unmanned vehicle and the readable storage medium determine at least one alternative boarding point according to a user riding request and the current position of a user, then plan at least one alternative route according to road information and the alternative boarding point, determine the expected passing time of each alternative route, and send the expected passing time to the user mobile terminal. The user can select a target route from the alternative routes by himself to control the unmanned vehicle to travel to the target boarding point according to the target route, so that the meeting mode of the user and the unmanned vehicle is more flexible, and the meeting efficiency of the user and the vehicle is improved.

The above examples only express several embodiments of the present application, and the description thereof is more specific and detailed, but not to be construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present patent application shall be subject to the appended claims.

Claims

1. A control method of an unmanned vehicle, comprising:

acquiring a user riding request, a user current position and road information;

determining at least one alternative boarding point according to the user riding request and the current position of the user;

carrying out route planning according to the road information and the alternative boarding points to obtain at least one alternative route;

and determining the predicted passing time of each alternative route to determine a target boarding point.

2. The control method according to claim 1, wherein the determining at least one alternative boarding point according to the user boarding request and the user current position comprises:

determining an original boarding point according to the user riding request;

under the condition that the original vehicle getting-on point is positioned behind the U-turn driving road section and/or the congested road section, selecting a replacement point on the non-U-turn driving road section and/or the uncongested road section;

calculating the first step time length from the current position of the user or the original vehicle-loading point to the replacement point and the first running time length of the unmanned vehicle passing through the U-turn running road section and/or the congested road section;

and under the condition that the first step traveling time length is smaller than the first traveling time length, newly adding the replacement point as the alternative boarding point.

3. The control method according to claim 1, wherein the determining at least one alternative boarding point according to the user boarding request and the user current position comprises:

determining an original boarding point and a target point according to the user riding request;

under the condition that the turning-around driving section and/or the congested section are/is positioned behind the original vehicle-entering point, selecting a replacement point on the non-turning-around driving section and/or the uncongested section;

calculating a second step driving time length from the current position of the user to the replacement point, a second driving time length from the replacement point to the target point of the unmanned vehicle, and a third driving time length from the original driving point to the target point of the unmanned vehicle;

and under the condition that the sum of the second step driving time length and the second driving time length is smaller than the third driving time length, adding the replacement point as the alternative getting-on point.

4. The control method of claim 1, wherein the determining at least one alternative pick-up point based on the user ride request and the user current location comprises:

obtaining historical vehicle-boarding point data of the user in an area corresponding to the current position of the user;

performing density analysis on the historical boarding point data to obtain a common boarding point;

and determining the alternative boarding points according to the common boarding points.

5. The control method according to claim 4, wherein the performing density analysis on the historical boarding point data to obtain frequent boarding points comprises:

determining the longitude and latitude of the historical vehicle point data to draw a corresponding coordinate map;

aggregating the historical boarding point data according to a preset range on the coordinate map to obtain a boarding point cluster;

and determining the common boarding points according to the boarding point clusters.

6. The control method according to claim 5, wherein the determining the common pick-up point according to the pick-up point cluster includes:

performing iterative aggregation on the historical boarding point data corresponding to the boarding point cluster by using a cluster analysis algorithm to obtain a centroid position;

and taking the position of the center of mass as the common boarding point.

7. The control method according to claim 6, wherein the iteratively aggregating the historical boarding point data corresponding to the boarding point cluster by using a cluster analysis algorithm to obtain a centroid position comprises:

acquiring data creating time corresponding to the historical vehicle point data;

determining a weighted value of the corresponding historical vehicle point data according to the data creation time;

and performing iterative aggregation on the historical vehicle-entering point data corresponding to the vehicle-entering point cluster by utilizing the cluster analysis algorithm according to the weighted value to obtain the centroid position.

8. The control method according to claim 1, characterized by comprising:

automatically calculating an optimal scheme to determine the target route without receiving user operation on the alternative route;

a route confirmation message is sent to notify the user and give the route guidance.

9. The control method according to claim 1, wherein after the obtaining of the user riding request, the user current position, and the road information, the control method comprises:

obtaining a user route preference;

the determining at least one target boarding point according to the user riding request and the current position of the user comprises the following steps:

and determining at least one alternative boarding point according to the user route preference, the user boarding request and the current position of the user.

10. The control method of claim 9, wherein the obtaining the user route preference comprises:

sending preference selection information to the user mobile terminal;

and receiving the operation of the user on the preference selection information to determine the route preference of the user.

11. The control method of claim 9, wherein the obtaining the user route preference comprises:

acquiring historical trip information of a user, wherein the historical trip information comprises a preset user label;

and analyzing the historical travel information according to a word frequency calculation algorithm to obtain the route preference of the user.

12. The control method of claim 11, wherein the predetermined user label is learned from a neural network.

13. The control method according to claim 1, characterized by comprising:

under the condition that the unmanned vehicle runs to the first preset distance of the target boarding point, acquiring the environmental information around the target boarding point;

and under the condition that the environmental information around the target boarding point is not suitable for the parking of the vehicle, re-determining the target boarding point and informing the user.

14. The control method according to claim 1, characterized in that after the unmanned vehicle travels to the target boarding point, the control method includes:

and under the condition that the distance between the user and the target boarding point is greater than a second preset distance or the waiting time is greater than preset time, controlling the unmanned vehicle to select a parking space near the target boarding point to park.

15. A control system for an unmanned vehicle, comprising:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a riding request of a user, the current position of the user and road information;

the boarding point determining module is used for determining at least one alternative boarding point according to the riding request of the user and the current position of the user;

the route planning module is used for carrying out route planning according to the road information and the alternative vehicle-loading points to obtain at least one alternative route;

a determination module for determining an expected transit time for each of the alternative routes to determine the target pick-up point.

16. An unmanned vehicle comprising a processor and a memory, the memory for storing a computer program, the processor implementing the control method of any one of claims 1 to 14 when executing the computer program.

17. A non-transitory computer-readable storage medium of a computer program, characterized in that, when the computer program is executed by one or more processors, the control method of any one of claims 1 to 14 is implemented.