CN113066303A - Intelligent bus stop combined positioning system based on vehicle-road cloud cooperation - Google Patents
Intelligent bus stop combined positioning system based on vehicle-road cloud cooperation Download PDFInfo
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- CN113066303A CN113066303A CN202110317093.0A CN202110317093A CN113066303A CN 113066303 A CN113066303 A CN 113066303A CN 202110317093 A CN202110317093 A CN 202110317093A CN 113066303 A CN113066303 A CN 113066303A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/123—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention relates to an intelligent bus stop combined positioning system based on vehicle path cloud cooperation, wherein a vehicle end subsystem is used for acquiring peripheral environment data of a bus stop, bus movement data and RTK-GPS information; the road end subsystem comprises a road end UWB base station; the cloud subsystem is used for acquiring map information of the bus stop; a vehicle end UWB communication module of the communication subsystem obtains a vehicle pose a based on a signal of a road end UWB base station; and the positioning subsystem obtains the final position and posture of the bus according to the peripheral environment data of the bus stop, the bus motion data, the bus stop map information and the vehicle position and posture a. Compared with the prior art, the method and the device fully utilize the vehicle-end sensing information, the road-end sensing information and the cloud map information, improve the accuracy and stability of the positioning of the bus at the bus station by a multi-source, redundant and reliable combined positioning mode, and ensure the positioning accuracy under special working conditions such as GPS signal shielding, weather/light change, complex dynamic environment and the like.
Description
Technical Field
The invention relates to the technical field of intelligent bus positioning, in particular to an intelligent bus stop combined positioning system based on bus route cloud cooperation.
Background
Buses are important public transport means, and along with the development of society and the progress of science and technology, buses are gradually developed towards intellectualization, and particularly, buses which are automatically driven are the key points of current research. When the intelligent bus automatically approaches the station platform, on one hand, the size of a transverse gap between the bus and the station platform needs to be controlled, if the transverse gap is too large, passengers are not facilitated to get on or off the bus, and if the transverse gap is too small, the vehicles are easy to scratch and even collide; on the other hand, the vehicle door is basically aligned with the longitudinal direction of the gate opening.
The positioning performance of the intelligent bus at the stop is a key factor for realizing automatic and accurate stop, and a general positioning method is to install a vehicle-mounted positioning module on the bus, wherein the vehicle-mounted positioning module receives an identification signal transmitted by a wireless stop board of the stop, so that the positioning is completed. However, such positioning accuracy is extremely low, and the positioning performance requirements of the automatic accurate parking station cannot be satisfied.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide an intelligent bus stop combined positioning system based on vehicle-road-cloud cooperation, which makes full use of vehicle-end sensing information, road-end sensing information and cloud map information, improves the accuracy and stability of positioning of a bus at a bus stop in a multi-source, redundant and reliable combined positioning mode, greatly improves the positioning precision, and ensures the positioning precision under special working conditions such as GPS signal shielding, weather/light change, complex dynamic environment and the like.
The purpose of the invention can be realized by the following technical scheme:
an intelligent bus stop combined positioning system based on vehicle road cloud cooperation comprises: vehicle end subsystem, way end subsystem, high in the clouds subsystem, communication subsystem and location subsystem, wherein:
the bus-end subsystem is used for acquiring bus station peripheral environment data, bus motion data and RTK-GPS information and comprises a bus-end laser radar, a bus-end inertial navigation device, a bus-end wheel speed meter and an RTK-GPS sensor;
the terminal system comprises a terminal UWB base station, wherein the terminal UWB base station is used for sending an ultra wide band wireless communication signal;
the cloud subsystem is in communication connection with the RTK-GPS sensor through the communication subsystem and is used for acquiring map information of the bus stop according to the RTK-GPS information acquired by the RTK-GPS sensor, and the cloud subsystem comprises a cloud map module and a cloud map broadcasting module;
the communication subsystem is respectively in communication connection with the vehicle-end subsystem, the road-end subsystem, the cloud-end subsystem and the positioning subsystem and is used for realizing communication among the vehicle-end subsystem, the road-end subsystem, the cloud-end subsystem and the positioning subsystem, and comprises a vehicle-end UWB communication module, wherein the vehicle-end UWB communication module is used for obtaining a vehicle pose a of the bus relative to a bus stop based on an ultra-wideband wireless communication signal sent by a road-end UWB base station;
and the positioning subsystem is used for obtaining the final position of the bus relative to the bus stop according to the peripheral environment data of the bus stop, the bus motion data, the bus stop map information and the bus position a of the bus relative to the bus stop.
Further, the vehicle-end laser radar is used for acquiring surrounding environment data of the bus station and transmitting the surrounding environment data to the positioning subsystem through the Ethernet; the bus motion data comprises bus-end inertial navigation data and bus-end wheel speed data, the bus-end inertial navigation data is used for acquiring the bus-end inertial navigation data and transmitting the bus-end inertial navigation data to the positioning subsystem through a CAN bus, and the bus-end wheel speed meter is used for acquiring the bus-end wheel speed data and transmitting the bus-end wheel speed data to the positioning subsystem through a signal cable.
Furthermore, the number of the road end UWB base stations is determined according to the space size of the bus stop.
Further, the cloud map module comprises type information of peripheral static obstacles of each bus stop and position information of the peripheral static obstacles of each bus stop relative to the bus stop; the cloud map broadcasting module selects a map of bus stops around the bus based on RTK-GPS information acquired by the RTK-GPS sensor and transmits the map information of the bus stops to the positioning subsystem.
Further, the cloud end V2X communication module is in communication connection with the cloud end subsystem through the Ethernet, the vehicle end V2X communication module is in communication connection with the vehicle end subsystem and the positioning subsystem through the Ethernet, and the cloud end V2X communication module is connected with the vehicle end V2X communication module in a wireless communication mode.
Further, the wireless communication means includes 5G, LTE-V and DSRC communication.
Further, the vehicle end UWB communication module is in communication connection with the road end UWB base station through a UWB wireless communication mode, and the vehicle position and pose a of the bus relative to the bus stop is obtained through resolving by utilizing the TDOA positioning mode and is transmitted to the positioning subsystem.
Furthermore, the bus-end UWB communication module transmits the vehicle pose a of the bus relative to the bus stop to the positioning subsystem through the CAN bus.
Further, the positioning subsystem processes the surrounding environment data of the bus station based on a pre-trained deep learning neural network to obtain environment structural characteristic information; the positioning subsystem matches the environment structural feature information with the bus stop map information, and obtains the rough pose of the bus relative to the bus stop through coordinate transformation.
Furthermore, the environment structured feature information includes type information of the static obstacle and position information of the static obstacle relative to the bus stop, and the bus stop map information includes type information of the static obstacle around the bus stop and position information of the static obstacle around the bus stop relative to the bus stop.
Still further, the static barriers include stop boards, stations, gates, and curbs.
Furthermore, the positioning subsystem processes the bus motion data based on the ackerman steering model to obtain bus motion information; the positioning subsystem fuses the coarse position and the movement information of the bus relative to the bus stop by using a Kalman filtering algorithm, and obtains the vehicle position and the attitude b of the bus relative to the bus stop through coordinate transformation.
Furthermore, the positioning subsystem fuses the vehicle pose a of the bus relative to the bus stop and the vehicle pose b of the bus relative to the bus stop by using a Kalman filtering algorithm to obtain the final pose of the bus relative to the bus stop.
Compared with the prior art, the method and the device fully utilize the vehicle-end sensing information, the road-end sensing information and the cloud map information, improve the accuracy and stability of the positioning of the bus at the bus station by a multi-source, redundant and reliable combined positioning mode, greatly improve the positioning precision, and ensure the positioning precision under special working conditions such as GPS signal shielding, weather/light change, complex dynamic environment and the like.
Drawings
FIG. 1 is a schematic structural view of the present invention;
FIG. 2 is a schematic diagram of data flow of a bus stop combined positioning system;
reference numerals: 1. vehicle end subsystem, 11, vehicle end laser radar, 12, vehicle end are used to lead, 13, vehicle end wheel speedometer, 14, RTK-GPS sensor, 2, way end subsystem, 21, way end UWB basic station, 3, the high in the clouds subsystem, 31, high in the clouds map module, 32, high in the clouds map broadcast module, 4, communication subsystem, 41, vehicle end UWB communication module, 42, high in the clouds V2X communication module, 43, vehicle end V2X communication module, 5, positioning subsystem.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Example 1:
an intelligent bus stop combined positioning system based on vehicle road cloud cooperation is shown in figure 1 and comprises: the system comprises a vehicle-end subsystem 1, a road-end subsystem 2, a cloud-end subsystem 3, a communication subsystem 4 and a positioning subsystem 5.
The vehicle-end subsystem 1 is used for acquiring peripheral environment data of a bus station, bus movement data and RTK-GPS information, and comprises a vehicle-end laser radar 11, a vehicle-end inertial navigation device 12, a vehicle-end wheel speed meter 13 and an RTK-GPS sensor 14;
the vehicle-end laser radar 11 is used for acquiring surrounding environment data of the bus station and transmitting the surrounding environment data to the positioning subsystem 5 through the Ethernet; the bus motion data comprises bus-end inertial navigation data and bus-end wheel speed data, the bus-end inertial navigation 12 is used for acquiring the bus-end inertial navigation data and transmitting the bus-end inertial navigation data to the positioning subsystem 5 through a CAN bus, and the bus-end wheel speed meter 13 is used for acquiring the bus-end wheel speed data and transmitting the bus-end wheel speed data to the positioning subsystem 5 through a signal cable; the RTK-GPS sensor 14 is used for acquiring RTK-GPS information of the bus and transmitting the RTK-GPS information to the cloud subsystem 3 through the communication subsystem 4.
The road end subsystem 2 comprises a road end UWB base station 21, and the road end UWB base station 21 is used for sending an ultra-wideband wireless communication signal; the number of the road end UWB base stations 21 is determined according to the space size of the bus stop, the number of the road end UWB base stations 21 can be properly increased for a larger bus stop so as to improve the positioning accuracy, and each bus stop is provided with at least 1 road end UWB base station 21.
The cloud subsystem 3 is in communication connection with the RTK-GPS sensor 14 through the communication subsystem 4, is used for acquiring map information of the bus stop according to the RTK-GPS information acquired by the RTK-GPS sensor 14, and comprises a cloud map module 31 and a cloud map broadcasting module 32;
the cloud map module 31 includes type information of peripheral static obstacles of each bus stop and position information of the peripheral static obstacles of each bus stop relative to the bus stop; the cloud map broadcasting module 32 selects a map of bus stops around the bus based on the RTK-GPS information acquired by the RTK-GPS sensor 14 and transmits the map information of the bus stops to the positioning subsystem 5 through the communication subsystem 4.
The communication subsystem 4 is in communication connection with the vehicle-end subsystem 1, the road-end subsystem 2, the cloud-end subsystem 3 and the positioning subsystem 5 respectively, is used for realizing communication among the vehicle-end subsystem 1, the road-end subsystem 2, the cloud-end subsystem 3 and the positioning subsystem 5, and comprises a vehicle-end UWB communication module 41, a cloud-end V2X communication module 42 and a vehicle-end V2X communication module 43; the vehicle-end UWB communication module 41 obtains the vehicle pose a of the bus relative to the bus stop based on the ultra-wideband wireless communication signal sent by the road-end UWB base station 21 and transmits the vehicle pose a to the positioning subsystem 5.
The bus end UWB communication module 41 is installed on a bus, the road end UWB base station 21 is installed at a bus stop, the bus end UWB communication module 41 is in communication connection with the road end UWB base station 21 in a UWB wireless communication mode and is used for resolving a vehicle position a of the bus relative to the bus stop in a TDOA locating mode, and the bus end UWB communication module 41 transmits the vehicle position a of the bus relative to the bus stop to the locating subsystem 5 through a CAN bus.
In this embodiment, the vehicle-end laser radar 11, the vehicle-end inertial navigation device 12, the vehicle-end wheel speed meter 13 and the RTK-GPS sensor 14 are installed on the bus, the vehicle-end laser radar 11 is in communication connection with the positioning subsystem 5 through the ethernet, the vehicle-end inertial navigation device 12 is in communication connection with the positioning subsystem 5 through the CAN bus, and the vehicle-end wheel speed meter 13 is in communication connection with the positioning subsystem 5 through the signal cable.
The cloud subsystem 3 is arranged at the cloud end, the cloud V2X communication module 42 is arranged at the cloud end, the cloud end is in communication connection with the cloud subsystem 3 through the Ethernet, the vehicle end V2X communication module 43 is arranged on the bus, the cloud end V2X communication module 42 is in communication connection with the vehicle end subsystem 1 and the positioning subsystem 5 through the Ethernet, and the cloud end V2X communication module 43 is connected with the vehicle end V2X communication module 43 in a wireless communication mode. The wireless communication means includes 5G, LTE-V and DSRC communication. The vehicle-end V2X communication module 43 is installed on a running vehicle, the cloud V2X communication module 42 with fixed positions is arranged, the cloud V2X communication module 42 and the vehicle-end V2X communication module 43 are communicated based on advanced vehicle networking technologies such as LTE-V and 5G, and information transmission is more reliable.
RTK-GPS information acquired by the RTK-GPS sensor 14 is transmitted to the vehicle-end V2X communication module 43 through the Ethernet, and the vehicle-end V2X communication module 43 is transmitted to the cloud end V2X communication module 42 through wireless communication modes such as 5G, LTE-V or DSRC and the like, so that the information is acquired by the cloud end subsystem 3.
The cloud subsystem 3 transmits the bus stop map information to the cloud V2X communication module 42 through the Ethernet, and the cloud V2X communication module 42 transmits the bus stop map information to the vehicle end V2X communication module 43 through wireless communication modes such as 5G, LTE-V and DSRC, so that the bus stop map information can be acquired by the positioning subsystem 5.
The positioning subsystem 5, as shown in fig. 2, is configured to obtain a final position of the bus relative to the bus stop according to the peripheral environment data of the bus stop, the bus motion data, the bus stop map information, and the vehicle position a of the bus relative to the bus stop.
The positioning subsystem 5 processes the surrounding environment data of the bus stop based on a pre-trained deep learning neural network to obtain environment structural feature information, wherein the environment structural feature information comprises type information of static obstacles (such as stop boards, stations and the like) and position information of the static obstacles relative to the bus stop.
The positioning subsystem 5 matches the environment structural feature information with the bus stop map information, and obtains the rough pose of the bus relative to the bus stop through coordinate transformation. The bus stop map information comprises type information of static obstacles around the bus stop and position information of the static obstacles around the bus stop relative to the bus stop, and the static obstacles comprise barriers such as stop boards, stations, gates, road edges and the like.
The positioning subsystem 5 processes bus movement data (namely, bus end inertial navigation data and bus end wheel speed data) based on the ackerman steering model to obtain bus movement information. The positioning subsystem 5 fuses the coarse position and the movement information of the bus relative to the bus stop by using a Kalman filtering algorithm, and obtains the vehicle position and the vehicle position b of the bus relative to the bus stop through coordinate transformation.
And the positioning subsystem 5 fuses the vehicle pose a of the bus relative to the bus stop and the vehicle pose b of the bus relative to the bus stop by using a Kalman filtering algorithm to obtain the final pose of the bus relative to the bus stop.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (10)
1. The utility model provides an intelligence bus stop combined positioning system based on car route cloud is in coordination which characterized in that includes: car end subsystem (1), way end subsystem (2), high in the clouds subsystem (3), communication subsystem (4) and location subsystem (5), wherein:
the bus terminal subsystem (1) is used for acquiring bus station peripheral environment data, bus motion data and RTK-GPS information and comprises a bus laser radar (11), a bus inertial navigation unit (12), a bus wheel speed meter (13) and an RTK-GPS sensor (14);
a line-end subsystem (2) comprising a line-end UWB base station (21), the line-end UWB base station (21) being configured to transmit an ultra-wideband wireless communication signal;
the cloud subsystem (3) is in communication connection with the RTK-GPS sensor (14) and is used for acquiring map information of the bus stop according to the RTK-GPS information, and comprises a cloud map module (31) and a cloud map broadcasting module (32);
the communication subsystem (4) is respectively in communication connection with the vehicle-end subsystem (1), the road-end subsystem (2), the cloud-end subsystem (3) and the positioning subsystem (5) and is used for realizing communication among the vehicle-end subsystem (1), the road-end subsystem (2), the cloud-end subsystem (3) and the positioning subsystem (5), the communication subsystem comprises a vehicle-end UWB communication module (41), and the vehicle-end UWB communication module (41) obtains a vehicle pose a of the bus relative to a bus stop based on an ultra-wideband wireless communication signal sent by a road-end UWB base station (21);
and the positioning subsystem (5) is used for obtaining the final position of the bus relative to the bus stop according to the peripheral environment data of the bus stop, the bus motion data, the bus stop map information and the bus position a of the bus relative to the bus stop.
2. The intelligent bus stop combined positioning system based on the vehicle-road cloud cooperation as claimed in claim 1, wherein the vehicle-end laser radar (11) is used for acquiring peripheral environment data of the bus stop and transmitting the peripheral environment data to the positioning subsystem (5); the bus movement data comprise vehicle-end inertial navigation data and vehicle-end wheel speed data, the vehicle-end inertial navigation (12) is used for acquiring the vehicle-end inertial navigation data and transmitting the vehicle-end inertial navigation data to the positioning subsystem (5), and the vehicle-end wheel speed meter (13) is used for acquiring the vehicle-end wheel speed data and transmitting the vehicle-end wheel speed data to the positioning subsystem (5).
3. The intelligent bus stop combined positioning system based on the vehicle-road cloud cooperation as claimed in claim 1, wherein the number of the road-end UWB base stations (21) is determined according to the space size of the bus stop.
4. The intelligent bus stop combined positioning system based on vehicle-road-cloud cooperation as claimed in claim 1, wherein the communication subsystem (4) further comprises a cloud end V2X communication module (42) and a vehicle end V2X communication module (43), the cloud end V2X communication module (42) is in communication connection with the cloud end subsystem (3) through the Ethernet, the vehicle end V2X communication module (43) is in communication connection with the vehicle end subsystem (1) and the positioning subsystem (5) through the Ethernet, and the cloud end V2X communication module (42) is connected with the vehicle end V2X communication module (43) in a wireless communication mode.
5. The intelligent bus stop combined positioning system based on vehicle-road cloud coordination as claimed in claim 4, wherein said wireless communication mode comprises 5G, LTE-V and DSRC communication.
6. The intelligent bus stop combined positioning system based on the vehicle-road cloud cooperation as claimed in claim 1, wherein the vehicle-end UWB communication module (41) is in communication connection with the road-end UWB base station (21) through a UWB wireless communication mode, and the vehicle pose a of the bus relative to the bus stop is obtained by resolving through a TDOA positioning mode and transmitted to the positioning subsystem (5).
7. The intelligent bus stop combined positioning system based on vehicle-road cloud cooperation as claimed in claim 1, wherein the positioning subsystem (5) processes the peripheral environment data of the bus stop based on a pre-trained deep learning neural network to obtain environment structural feature information; the positioning subsystem (5) matches the environment structural feature information with the bus stop map information, and obtains the rough pose of the bus relative to the bus stop through coordinate transformation.
8. The intelligent bus stop combined positioning system based on the bus route cloud coordination as claimed in claim 7, wherein the environment structured feature information includes type information of static obstacles and position information of the static obstacles relative to the bus stop, and the bus stop map information includes type information of the static obstacles around the bus stop and position information of the static obstacles around the bus stop relative to the bus stop.
9. The intelligent bus stop combined positioning system based on the vehicle-road cloud cooperation as claimed in claim 7, wherein the positioning subsystem (5) processes bus movement data based on an ackerman steering model to obtain bus movement information; and the positioning subsystem (5) fuses the coarse position and the movement information of the bus relative to the bus stop by using a Kalman filtering algorithm, and obtains the vehicle position and the attitude b of the bus relative to the bus stop through coordinate transformation.
10. The intelligent bus stop combined positioning system based on the bus route cloud coordination of claim 9, wherein the positioning subsystem (5) utilizes a Kalman filtering algorithm to fuse a vehicle pose a of the bus relative to the bus stop and a vehicle pose b of the bus relative to the bus stop to obtain a final pose of the bus relative to the bus stop.
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| CN115406439A (en) * | 2022-08-16 | 2022-11-29 | 中国第一汽车股份有限公司 | Vehicle positioning method, system, device and nonvolatile storage medium |
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