CN114219535A

CN114219535A - Method for adjusting preset selling place of unmanned vehicle by using electronic map

Info

Publication number: CN114219535A
Application number: CN202111553330.XA
Authority: CN
Inventors: 杨哲
Original assignee: Neolix Technologies Co Ltd
Current assignee: Neolix Technologies Co Ltd
Priority date: 2021-12-17
Filing date: 2021-12-17
Publication date: 2022-03-22

Abstract

The invention relates to a method for adjusting a preset selling place of an unmanned vehicle by using an electronic map. Unmanned vehicles are also called intelligent networked automobiles and automatic driven vehicles, unmanned vehicles are expected to be close to crowded areas for selling when the unmanned vehicles are in retail operation, selling areas are planned ahead by unmanned vehicle operation companies, the selling areas are people gathering areas such as industrial parks, subway exits, commercial streets and residential areas, the areas can be known from multiple channels, the unmanned vehicles are usually parked at places where people flow to the gathering areas for selling, the places do not belong to the crowd gathering areas, but the people flow to the gathering areas from the places, so that the unmanned vehicles can touch the most pedestrians in a certain period of time. In fact, the positions of the places are not proper enough, but the unmanned vehicle cannot catch the stream of people, so that the unmanned vehicle stops at a place which is neither in a people stream dense area nor can touch more streams of people within a certain time period, and the touching number of the pedestrians is greatly reduced. According to the invention, a more accurate parking place can be found by using the POI in the electronic map.

Description

Method for adjusting preset selling place of unmanned vehicle by using electronic map

Technical Field

The invention relates to the technical field of automatic driving, in particular to a method for adjusting a preset selling place of an unmanned vehicle by using an electronic map.

Background

With the development of the automatic driving technology, unmanned vehicles have been commercially used on a large scale, such as unmanned taxis, unmanned trucks, unmanned distribution vehicles, and unmanned retail vehicles.

Unmanned retail vehicle does not have the driver, and its driving mode includes automatic driving mode or remote driving mode, has deposited commodity in unmanned vehicle retail vehicle's the packing box, when selling, can take multiple mode of selling, for example, patrol and sell, the order is delivered goods, the fixed point is sold, wherein the fixed point is sold under the mode, and unmanned vehicle can reduce the distance of traveling, save the power, improves and sells efficiency. The unmanned vehicle stops at a region with dense pedestrian flow, and when pedestrians pass the unmanned vehicle or find the unmanned vehicle, the unmanned vehicle can be selected to purchase commodities.

However, although the crowded area has a lot of crowds, it cannot be guaranteed that most of the crowds can pass through the unmanned vehicle or see the unmanned vehicle, and therefore, it is better to stop the unmanned vehicle at the entrance of the passage through which the crowds flow into the crowded area or the exit of the passage through which the crowds flow out of the crowded area, so as to guarantee that the most crowds pass through the unmanned vehicle. The choice of parking place becomes a key factor for improving the sales revenue of the unmanned retail vehicle.

Disclosure of Invention

In order to solve the technical problem or at least partially solve the technical problem, the invention provides a method for adjusting a preset selling place of an unmanned vehicle by using an electronic map, which comprises the following specific contents:

a method for adjusting a preset selling place of an unmanned vehicle by using an electronic map comprises the following steps:

setting a predicted selling place of the unmanned vehicle, wherein a preset range near the predicted selling place comprises a plurality of POIs;

finding a POI gathering area in a plurality of POIs;

acquiring time information of the unmanned vehicle arriving at the preset selling place;

screening POI types with the number of the POIs larger than a preset threshold value in the POI gathering area;

screening POI types matched with the time information according to a preset rule;

if the POI types matched with the time information exist, further judging whether people flow out/enter exists between the preset selling place and the gathering area, if so, adjusting the position of the preset selling place so that people do not flow out/enter between the preset selling place and the gathering area; if not, the expected selling place is taken as the actual selling place.

Preferably, the types of the POI include shopping malls, districts, parking lots, transportation facilities, restaurants, schools, office areas, life service places, hospitals, scenic spots, banks, vegetable markets, supermarkets, factories and/or construction sites;

preferably, the entrance/exit port includes a road surface extending in an opening direction of the entrance/exit port;

preferably, the preset range includes 1 km, 2 km or 5 km;

preferably, the human outflow/population includes: the system comprises a bus station, an exit/entrance of a subway station, an exit/entrance of a railway station, an exit/entrance of a mall, an exit/entrance of a scenic spot, an exit/entrance of a community, an exit/entrance of an industrial park or an exit/entrance of a campus;

preferably, the preset threshold is greater than 1;

preferably, the preset rules comprise that factories, schools, traffic facilities and parks are matched with rush hours on work and off work, life service places, shopping malls and supermarkets are matched with evening hours, scenic spots are matched with holiday hours, and hospitals are matched with daytime hours;

preferably, the POI is an information point included in the electronic map database, and the information point includes a name, a category, location information, an address, and a telephone;

preferably, the POIs include a parent POI and a child POI;

preferably, the expected selling place is set manually or the unmanned retail vehicle is automatically set according to the historical selling condition or the electronic map data information;

preferably, the position adjustment of the expected selling places comprises the step of adjusting the positions of the unmanned retail vehicles through operating the unmanned retail vehicles by a remote driving system or automatically adjusting the expected selling places through an automatic driving system.

In addition, the device can realize the method for adjusting the preset selling place of the unmanned vehicle by using the electronic map.

Compared with the prior art, the technical scheme provided by the embodiment of the invention has the following advantages:

no matter the preset selling place of the unmanned vehicle is manually arranged or automatically selected, the position of the unmanned vehicle is accurately adjusted based on the POI gathering area in the map, the number of people passing through the unmanned vehicle can be maximized, and the selling amount of the unmanned vehicle is increased.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.

Fig. 1 is a schematic flowchart illustrating a method for adjusting a preset selling location of an unmanned vehicle by using an electronic map according to an embodiment of the present invention;

fig. 2 is a schematic diagram of adjusting a predetermined selling location according to an embodiment of the present invention.

Detailed Description

In order that the above objects, features and advantages of the present invention may be more clearly understood, a solution of the present invention will be further described below. It should be noted that the embodiments of the present invention and features of the embodiments may be combined with each other without conflict.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those described herein; it is to be understood that the embodiments disclosed in the specification are only a few embodiments of the present disclosure, and not all embodiments.

Aiming at the technical problem that more users cannot be touched at the parking position of an unmanned vehicle in the prior art, the application provides the following solution.

As shown in fig. 1, in a first step, an intended sales location for an unmanned vehicle is set. The operation scene of the unmanned vehicle comprises an unmanned taxi, an unmanned delivery vehicle, an unmanned retail vehicle, an unmanned truck and the like, and for the unmanned retail vehicle, during daily actual operation, an operator needs to input a predicted selling place in the dispatching system in advance, or the dispatching system statistically analyzes the predicted selling place of the current day or the next day according to historical selling data and factors such as supply condition, date and weather.

In the geographic information system, one POI may be one house, one shop, one mailbox, one bus station, and the like. The POI is an information point recorded in an electronic map database, and the information point comprises a name, a category, position information, an address and a telephone; specifically, the POI includes a parent POI and a child POI.

The expected sales location should include a plurality of POIs, wherein the scheduling system can acquire POIs near each geographic position from electronic map information so as to meet the requirement that no person touches the people, and the POIs are 'points of interest'. POIs are most often signage to accommodate people, so it is expected that more POIs near a sales location means that an unmanned vehicle may reach more people. Generally, the POI is limited within a certain range of the unmanned vehicle, the range belongs to a preset range, and may be 1 km, 2 km or 5 km, the larger the range is, the larger the area served by the unmanned vehicle is, but the longer the unmanned vehicle needs to operate, this is because an excessively large range may cause a decrease in the possibility that the crowd may reach the unmanned vehicle, and by lengthening the selling time, the possibility of reaching the crowd may be increased.

If only the unmanned vehicle arrives at the expected selling location for selling, because the expected selling location is selected manually or the system automatically generates according to factors influencing the selling of the goods, and how to make the target people pass through the unmanned vehicle is not considered, the unmanned vehicle cannot obtain better selling effect, and is even not as good as the selling effect of areas except the vicinity of a plurality of POI areas.

In order to enable the crowd related to the multiple POI areas of the target to pass by the unmanned vehicle to the greatest extent possible, the scheme of the application needs to further adjust the expected selling places.

When the unmanned vehicle approaches to a position where the POI is dense as much as possible, the unmanned vehicle can reach more people streams more quickly, if the POI near the selling place where the unmanned vehicle is located is too dispersed, the people streams can not move to be concentrated, the unmanned vehicle can not reach more people groups by legal points, and therefore, in the second step, a POI gathering area needs to be found in a plurality of POI;

the method for finding the POI gathering area can be as follows: dividing a preset range near a predicted selling place into four directional areas according to the south, the east and the south, calculating the number of POI in each area, and taking the area with the largest number as a POI gathering area.

After the POI gathering area is determined, whether the selling time period of the unmanned vehicles is suitable for people related to the gathering area or not needs to be judged, whether the related people in the gathering area flow into or out of the gathering area in the time period or not needs to be judged, if the unmanned vehicles are sold in an improper time period, people flow does not flow into or out of the gathering area in the time period, and even if the parking positions of the unmanned vehicles are selected properly, the unmanned vehicles cannot touch more people flow.

Due to the fact that different crowds flow into or out of the gathering area at different times, after the time information is determined, the type situation of POI in the gathering area needs to be further confirmed. And fourthly, screening POI types containing POI, the number of which is greater than a preset threshold value, in the POI gathering area, wherein the preset threshold value is greater than 1 or greater than 5, if the POI types meeting the requirements are not selected, taking the area with the second position of the POI number rows in the direction area as the gathering area, re-screening the POI types, if the POI types cannot meet the requirements to continue to replace the gathering area, and if the four direction areas do not have the areas meeting the requirements, sending a prompt to a scheduling system to replace the preset selling place.

And fifthly, screening out POI types matched with the time information according to preset rules, wherein the preset rules comprise that factories, schools, traffic facilities and parks are matched with rush hours on duty, life service places, markets and supermarkets are matched with evening hours, scenic spots are matched with holiday hours, and hospitals are matched with daytime hours. The matching rules may be pre-stored in the dispatch system or in the vehicle control system.

For example, when the number of POIs in a residential area is greater than a preset threshold value 5 in the gathering area, whether the time "7 o 'clock at night" when the unmanned vehicle arrives at the preset selling place is matched with the residential area is further judged, obviously, the time period of going home after work of the crowd at 7 o' clock at night is a time period, and probably, the time period flows into the residential area, so the time period is matched with the types of the POIs.

Sixthly, if POI types matched with the time information exist, further judging whether people flow out or enter between the preset selling place and the gathering area, if so, adjusting the position of the preset selling place so that people do not flow out or enter between the preset selling place and the gathering area, wherein the adjustment of the position of the preset selling place comprises adjusting the position of an unmanned retail vehicle through a remote driving system or automatically adjusting the preset selling place through an automatic driving system; if not, taking the expected selling place as an actual selling place;

and if the POI type matched with the time information does not exist, changing the time information of arriving at the preset selling place or replacing the preset selling place with a new preset selling place.

For example, as shown in fig. 2, in the vicinity of a subway station 3, ABCD is subway entrance in four directions of south, east, west and north, D is predetermined selling place, 2 is unmanned vehicle to be parked or parked, and 1 is POI gathering area, since there is entrance and exit B for people stream between the predetermined selling place and the gathering area, it is necessary to adjust the position of the unmanned vehicle and modify the predetermined selling place to B, otherwise, the people stream flows from B to the gathering area and does not pass D, and the unmanned vehicle cannot reach the people stream.

The types of the POI comprise shopping malls, districts, parking lots, transportation facilities, restaurants, schools, office areas, life service places, hospitals, scenic spots, banks, vegetable markets, supermarkets, factories and/or construction sites; the human outflow/population includes: the system comprises a bus station, an exit/entrance of a subway station, an exit/entrance of a railway station, an exit/entrance of a mall, an exit/entrance of a scenic spot, an exit/entrance of a community, an exit/entrance of an industrial park or an exit/entrance of a campus;

in addition, the entrance/exit port may further include a road surface extending in the opening direction of the entrance/exit port.

The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for adjusting a preset selling place of an unmanned vehicle by using an electronic map is characterized by comprising the following steps:

finding a POI gathering area in a plurality of POIs;

2. The method of claim 1, wherein the categories of POIs include shopping malls, cells, parking lots, transportation facilities, restaurants, schools, office areas, places of living services, hospitals, attractions, banks, vegetable markets, supermarkets, factories, and/or construction sites.

3. The method of claim 2, wherein the access port comprises a road surface extending along the direction of the opening of the access port.

4. The method of claim 3, wherein the predetermined range comprises 1 kilometer, 2 kilometers, or 5 kilometers.

5. The method of claim 4, wherein the people outflow/population comprises: a bus station, an exit/entrance of a subway station, an exit/entrance of a railway station, an exit/entrance of a mall, an exit/entrance of a scenic spot, an exit/entrance of a cell, an exit/entrance of an industrial park or an exit/entrance of a campus.

6. The method of claim 5, wherein: the preset threshold is greater than 1.

7. The method of claim 6, wherein: the preset rules comprise that factories, schools, traffic facilities and parks are matched with rush hours on duty and off duty, life service places, shopping malls and supermarkets are matched with evening hours, scenic spots are matched with holiday hours, and hospitals are matched with daytime hours.

8. The method of claim 7, wherein: the POI is an information point included in the electronic map database, and the information point includes a name, a category, location information, an address, and a telephone.

9. The method of claim 8, wherein: the POIs include parent POIs and child POIs.

10. The method of claim 1, wherein: the expected selling place is set manually or automatically according to the historical selling condition of the unmanned retail vehicle or the data information of the electronic map.

11. The method of claim 1, wherein: and the position adjustment of the expected selling places comprises the step of adjusting the positions of the unmanned retail vehicles by operating the unmanned retail vehicles through a remote driving system or automatically adjusting the expected selling places through an automatic driving system.

12. The utility model provides an adjustment unmanned car is scheduled to sell device in place which characterized in that: the device can implement the method for adjusting the preset selling point of the unmanned vehicle by using the electronic map as claimed in claims 1-11.