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CN111508276B - High-precision map-based V2X reverse overtaking early warning method, system and medium - Google Patents

High-precision map-based V2X reverse overtaking early warning method, system and medium Download PDF

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Publication number
CN111508276B
CN111508276B CN202010328290.8A CN202010328290A CN111508276B CN 111508276 B CN111508276 B CN 111508276B CN 202010328290 A CN202010328290 A CN 202010328290A CN 111508276 B CN111508276 B CN 111508276B
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lane
vehicle
main vehicle
precision map
time
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CN111508276A (en
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王延
缪国栋
孟念鹏
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SAIC General Motors Corp Ltd
Pan Asia Technical Automotive Center Co Ltd
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SAIC General Motors Corp Ltd
Pan Asia Technical Automotive Center Co Ltd
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    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/16Anti-collision systems
    • G08G1/166Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/28Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
    • G01C21/30Map- or contour-matching
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88Lidar systems specially adapted for specific applications
    • G01S17/93Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/931Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13Receivers
    • G01S19/14Receivers specially adapted for specific applications
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/16Anti-collision systems
    • G08G1/167Driving aids for lane monitoring, lane changing, e.g. blind spot detection
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02Services making use of location information
    • H04W4/025Services making use of location information using location based information parameters
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02Services making use of location information
    • H04W4/025Services making use of location information using location based information parameters
    • H04W4/027Services making use of location information using location based information parameters using movement velocity, acceleration information
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02Services making use of location information
    • H04W4/029Location-based management or tracking services
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30Services specially adapted for particular environments, situations or purposes
    • H04W4/40Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H04W4/44Services 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]
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30Services specially adapted for particular environments, situations or purposes
    • H04W4/40Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H04W4/46Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Signal Processing (AREA)
  • Electromagnetism (AREA)
  • Automation & Control Theory (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention provides a high-precision map-based V2X reverse overtaking early warning method, a system and a medium, wherein the method comprises the following steps: acquiring high-precision map data and real-time acquisition data of a main vehicle driving section; judging whether the current moment accords with a reverse overtaking scene or not according to the high-precision map data and the real-time collected data; receiving a plurality of remote vehicle messages, wherein a remote vehicle which is positioned in front of the left of the main vehicle on an adjacent reverse lane of the lane where the main vehicle is positioned and is closest to the main vehicle is a target remote vehicle; calculating the time TTC and the collision position required by the main vehicle lane change, the target remote vehicle and the main vehicle at the current moment; calculating whether the main vehicle can finish lane change and overtaking in a TTC time period and returns to an original lane before a preset distance from a collision position; and giving an early warning prompt according to whether the vehicle can return to the original lane. The invention solves the technical problem that the prior art can cause the interference to the driver of the main vehicle due to the false alarm or the missing report when the traditional map information and GNSS positioning are used for carrying out reverse overtaking guidance.

Description

High-precision map-based V2X reverse overtaking early warning method, system and medium
Technical Field
The invention relates to the field of vehicles, in particular to a high-precision map-based reverse overtaking early warning method and system for V2X and a storage medium.
Background
V2X is a car networking technology for implementing information interaction between car and outside world through relevant protocol standards, including car-to-car communication (V2V), car-to-infrastructure communication (V2I), car-to-person communication (V2P), and car-to-network communication (V2N), and V2X is a development direction of future car technologies and is one of key technologies for implementing high-level automatic driving, as shown in fig. 2.
In the prior art, a traditional electronic map serves a driver, and due to low precision, when reverse overtaking guidance is carried out by utilizing traditional map information and GNSS positioning, false alarm or missing alarm can be caused to cause interference to the driver of a main vehicle, so that serious accidents are caused.
Disclosure of Invention
Based on the problems, the invention provides a V2X reverse overtaking early warning method, a system and a storage medium based on a high-precision map, which solve the technical problem that in the prior art, a driver is served by a traditional electronic map, and due to low precision, when reverse overtaking guidance is carried out by utilizing traditional map information and GNSS positioning, false alarm or missing alarm is possibly caused to cause interference to the driver of a main vehicle, so that serious accidents are caused.
The invention provides a high-precision map-based V2X reverse overtaking early warning method, which comprises the following steps:
acquiring high-precision map data and real-time acquisition data of a main vehicle driving section;
judging whether the current moment accords with a reverse overtaking scene or not according to the high-precision map data and the real-time collected data;
receiving a plurality of remote vehicle messages, wherein a remote vehicle which is positioned in front of the left of the main vehicle on an adjacent reverse lane of the lane where the main vehicle is positioned and is closest to the main vehicle is a target remote vehicle;
calculating the time TTC and the collision position required by the main vehicle lane change, the target remote vehicle and the main vehicle at the current moment;
calculating whether the main vehicle can finish lane change and overtaking in a TTC time period and returns to an original lane before a preset distance from a collision position;
and giving an early warning prompt according to whether the vehicle can return to the original lane.
Further, the high-precision map data includes: road surface geometry, lane line properties, lane edge line positions, lane properties, sign line positions and/or a model of the surroundings.
In addition, the real-time collected data is real-time data of the driving environment of the main vehicle at the current moment collected through the camera and the laser radar, and positioning data obtained through GNSS.
In addition, judging whether the current moment accords with a reverse overtaking scene according to the high-precision map data and the real-time collected data comprises the following steps:
firstly, judging whether a left steering lamp of the main vehicle is turned on, if so, considering that the main vehicle has a lane change attempt, then judging whether the main vehicle is in the leftmost lane in the driving direction, and finally judging whether a lane line between the current driving lane and the adjacent reverse lane supports lane change.
Further, calculating the lane change of the host vehicle at the current time, the time TTC required for the target distant vehicle to collide with the host vehicle, and the collision position includes: and calculating the time TTC and the collision position required by the collision between the target remote vehicle and the main vehicle through the longitude and latitude, the altitude, the speed and the acceleration information of the remote vehicle in the remote vehicle message.
In addition, giving an early warning prompt according to whether the vehicle can return to the original lane comprises the following steps:
if so, prompting that the vehicle can be overtaken reversely;
if not, outputting reverse overtaking collision early warning information to a human-computer interaction interface, and displaying information for reminding the main vehicle of forbidding reverse overtaking on the human-computer interaction interface.
The invention also provides a storage medium which stores computer instructions and is used for executing any one of the high-precision map-based V2X reverse overtaking early warning methods when the computer executes the computer instructions.
The invention also provides a high-precision map-based V2X reverse overtaking early warning system, which comprises at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the one processor to cause the at least one processor to:
acquiring high-precision map data and real-time acquisition data of a main vehicle driving section;
judging whether the current moment accords with a reverse overtaking scene or not according to the high-precision map data and the real-time collected data;
receiving a plurality of remote vehicle messages, wherein a remote vehicle which is positioned in front of the left of the main vehicle on an adjacent reverse lane of the lane where the main vehicle is positioned and is closest to the main vehicle is a target remote vehicle;
calculating the time TTC and the collision position required by the main vehicle lane change, the target remote vehicle and the main vehicle at the current moment;
calculating whether the main vehicle can finish lane change and overtaking in a TTC time period and returns to an original lane before a preset distance from a collision position;
and giving an early warning prompt according to whether the vehicle can return to the original lane.
Through adopting above-mentioned technical scheme, have following beneficial effect:
the invention solves the technical problem that the traditional electronic map serves the driver, and the serious accident is caused by the interference on the driver of the main vehicle caused by false alarm or missing alarm when the traditional map information and GNSS positioning are utilized to carry out reverse overtaking guidance due to low precision in the prior art. By adopting the high-precision map-based reverse overtaking early warning method for V2X, a more accurate early warning method for guiding reverse overtaking can be provided, so that a driver can drive more safely, the accident rate is reduced, and congestion is relieved.
Drawings
Fig. 1 is a flowchart of a high-precision map-based reverse overtaking warning method of V2X according to an embodiment of the present invention;
FIG. 2 is a schematic view of V2X;
FIG. 3 is a schematic diagram of the relationship between various modules and sensors provided by one embodiment of the present invention;
fig. 4 is a flowchart of a high-precision map-based reverse overtaking warning method of V2X according to an embodiment of the present invention.
Detailed Description
The present invention is described in further detail below with reference to specific embodiments and the attached drawings. It is intended that the present invention not be limited to the particular embodiments disclosed, but that the present invention be limited only by the appended claims.
Referring to fig. 1, the invention provides a high-precision map-based reverse overtaking early warning method for V2X, which comprises the following steps:
s001, acquiring high-precision map data and real-time acquisition data of a main vehicle driving section;
s002, judging whether the current moment accords with a reverse overtaking scene or not according to the high-precision map data and the real-time collected data;
step S003, receiving a plurality of remote vehicle messages, wherein a remote vehicle which is positioned at the left front of the main vehicle and is closest to the main vehicle on an adjacent reverse lane of the lane where the main vehicle is positioned is a target remote vehicle;
step S004, calculating the time TTC and the collision position required by the main vehicle lane change, the target remote vehicle and the main vehicle at the current time;
step S005, calculating whether the main vehicle can finish lane change overtaking within the TTC time period and returns to the original lane before the preset distance from the collision position;
and step S006, giving an early warning prompt according to whether the vehicle can return to the original lane.
When a reverse overtaking is carried out, the lane and the position of the main vehicle need to be accurately positioned, the position of a far vehicle on the reverse lane needs to be accurately positioned, the traditional map information and GNSS are utilized for positioning, the possibility of causing false alarm or missing report causes interference to a driver of the main vehicle, and the technical problem can be fundamentally solved by introducing a high-precision map and high-precision positioning.
The V2X technology is largely divided into two camps DSRC and CV2X, both supporting a range of short-range communications, with CV2X additionally supporting cellular network-based long-range communications. The related traffic information such as real-time road conditions, road information, other vehicle information and the like can be obtained through the V2X technology.
Vehicle-to-vehicle communication, vehicle-to-infrastructure communication are communicated via short-range communication technology (DSRC or PC5 interface of CV 2X), and the information that can be interacted with includes information such as far vehicle speed, longitude and latitude, altitude, acceleration, heading, etc. Optionally, the system further comprises traffic light phase, countdown time, road speed limit and other information. The vehicle-to-network communication is realized through a Uu interface of the CV2X, and beyond-the-horizon driving information such as information related to a front congestion road section, front accident information, map information and the like can be obtained.
The high-precision map is different from a traditional electronic map, which serves a driver, and a vehicle-mounted system. The high-precision map contains a large amount of driving auxiliary information such as lane models, positions of road indication lines, surrounding road environment models and other high-precision 3D representation information.
In the following scenario: the main vehicle HV runs on the current lane, and when the adjacent reverse lane needs to be used for overtaking, if the collision risk with the far vehicle RV of the reverse lane is detected in advance, early warning is generated on the main vehicle, and the collision accident is avoided. By adopting the high-precision map-based reverse overtaking early warning method for V2X, the overtaking safety of a reverse lane can be greatly improved.
In step S001, high-precision map data and real-time acquired data of the traveling section of the host vehicle are acquired.
The high-precision map data can provide high-precision 3D representation information such as lane models, surrounding environment models, lane line positions, lane attributes, lane models and the like, and the high-precision map data are compared with GNSS positioning information and data collected by the main vehicle to obtain high-precision positioning of the position of the main vehicle, and the position and lane line information of adjacent reverse lanes.
Optionally, the high-precision map data includes lane information such as a position, a type, a width, a gradient, and a curvature of a lane line. And fixed object information around the lane, such as traffic signs, traffic lights, etc., lane limits, junctions, obstacles, and other road details, and further includes infrastructure information such as overhead objects, guard rails, number, road edge types, roadside landmarks, etc.
GNSS (Global Navigation Satellite System) is a global Navigation Satellite system. The V2X includes a GNSS chip, and the GNSS chip acquires a positioning signal from GNSS.
The real-time acquisition data is data acquired by sensors such as a camera and a radar in real time.
In step S002, it is determined whether the current time corresponds to a reverse overtaking scene according to the high-precision map data and the real-time collected data;
judging whether the current moment accords with a reverse overtaking scene: and judging whether a left steering lamp of the main vehicle is turned on or not, and if so, considering that the main vehicle has a lane change attempt. Then, it is judged whether the host vehicle is in the leftmost lane in the traveling direction, and whether the lane line between the current traveling lane and the adjacent reverse lane supports lane change (if a dotted line, lane change is allowed; if a solid line, lane change is not allowed). If the conditions are met, the reverse overtaking scene is considered.
Judging whether the main vehicle is on the leftmost lane in the driving direction and judging whether the lane line between the current driving lane and the adjacent reverse lane supports lane change or not according to the high-precision map data and the real-time collected data.
The judgment basis comprises: lane information such as the position, type, width, gradient, and curvature of the lane lines. And fixed object information around the lane, such as traffic signs, traffic lights, etc., lane limits, junctions, obstacles, and other road details, and further includes infrastructure information such as overhead objects, guard rails, number, road edge types, roadside landmarks, etc.
When judging whether the scene is a reverse overtaking scene, data needs to be collected in real time for accurate positioning, so that the driver can know which lane the driver is located on, and whether the scene is the reverse overtaking scene is judged based on which lane the driver is located on.
When judging whether the lane is the leftmost lane, firstly, judging according to a high-precision map, wherein the high-precision map comprises the number of lanes in the driving direction of the current main vehicle and the number of lanes in the reverse driving direction and comprises lane line types, and knowing whether the lane where the main vehicle is located is the leftmost lane in the driving direction according to an accurate positioning result.
Secondly, when the main vehicle is positioned on the leftmost lane in the driving direction, whether the lane line on the left side of the lane is a dotted line (including the situations of a single dotted line, a dotted solid line and the like) or not can be known according to the type of the lane line in the high-precision map data, and if so, the lane line can be judged to support reverse lane-borrowing and overtaking.
In step S003, a plurality of remote vehicles are received, and a remote vehicle that is located in front of the host vehicle on the left side of the host vehicle on the adjacent reverse lane of the lane where the host vehicle is located and that is closest to the host vehicle is a target remote vehicle;
the remote vehicle RV in the reverse lane can send RV messages outwards, namely each running vehicle can send the RV messages outwards, the RV messages are sent out through a PC5 interface of a vehicle-mounted V2X module of the RV, and the HV receives the RV messages through a PC5 interface of a vehicle-mounted V2X module of the HV.
And filtering the RV in a certain range running in the reverse lane by analyzing the received RV message, wherein a far vehicle which is positioned in the left front of the main vehicle and is closest to the main vehicle on the adjacent reverse lane of the lane where the main vehicle is positioned is a target far vehicle.
Step S004, calculating the time TTC and the collision position required by the main vehicle lane change, the target remote vehicle and the main vehicle at the current time;
the time TTC required for the target distant vehicle to collide with the host vehicle and the collision position are calculated. Ttc (time to collision) is the collision time, which refers to how much more time a collision occurs.
The main vehicle and the target remote vehicle move in the same direction, so that the distance between the two vehicles can be determined according to the longitude and latitude, the altitude, the speed and the acceleration information of the two vehicles, and the collision time and the collision position can be calculated according to the speed of the two vehicles. Since the distance between the two vehicles is not only related to the linear distance between the two vehicles, but also related to the altitude of the sea level where the two vehicles are located, the sea level and acceleration information are introduced to determine the distance between the two vehicles.
Step S005, calculating whether the main vehicle can finish lane change overtaking within the TTC time period and returns to the original lane before the preset distance from the collision position;
and judging whether the main vehicle can realize lane change overtaking according to the collision time and the collision position and the current speed of the main vehicle.
And step S006, giving an early warning prompt according to whether the vehicle can return to the original lane.
If the safe lane change can be carried out for reverse overtaking, the prompt can be carried out, and if the safe lane change can not be carried out for reverse overtaking, the prompt cannot be carried out.
The embodiment solves the technical problem that in the prior art, a driver is served by a traditional electronic map, and due to low precision, when reverse overtaking guidance is carried out by utilizing traditional map information and GNSS positioning, false alarm or missing alarm is possibly caused to cause interference to the driver of a main vehicle, so that serious accidents are caused. By adopting the high-precision map-based reverse overtaking early warning method for V2X, a more accurate early warning method for guiding reverse overtaking can be provided, so that a driver can drive more safely, the accident rate is reduced, and congestion is relieved.
In one embodiment thereof, the high-precision map data comprises: road surface geometry, lane line properties, lane edge line positions, lane properties, sign line positions and/or a model of the surroundings.
These data are used for feature matching with the data collected in real time for accurate positioning.
The feature information of the lane lines and the surrounding of the lanes can be identified in the real-time collected data, and the high-precision map data and the real-time collected data are subjected to feature matching to realize accurate positioning.
In the feature matching, three lanes in the driving direction are assumed, and the lanes are L1, L2 and L3 from left to right. The system needs to calculate the matching degree of each lane according to the data collected in real time. The degree of matching can be considered from multiple dimensions. If the left side of the lane where the main vehicle is located is the road edge collected by the camera, the road edge matching degree of the lane L1 is high; if the collected lane line type on the left side of the lane where the main vehicle is located is a solid line, and the collected lane line type on the right side is a dotted line, the lane line type matching degree of each lane can also be calculated; if the collected ground driving indication marks indicate that the lane is a straight lane, the adjacent lane on the left side is a straight left turn, and the right side is a right turn, the ground identification matching degree of each lane is calculated according to the left turn, the right turn and the left turn; similarly, the matching degree of the environmental model (roadside fixed traffic signs, portal frames and the like) is also provided. And finally, calculating the matching degree of each lane according to the multidimensional matching degree weighting, wherein the lane with the highest matching degree is the current lane. Meanwhile, the specific position of the main vehicle in the lane can be corrected according to the information of fixed objects around the lane, such as traffic signs, signal lamps, guard rails and the like, which is recognized by the camera.
In one embodiment, the real-time data is acquired by a camera and a laser radar, and the real-time data of the driving environment of the host vehicle at the current moment and the positioning data acquired by the GNSS.
The method comprises the steps of obtaining information of surrounding roads and vehicles of the vehicles through a camera, and obtaining distance information between a main vehicle and a distant vehicle by adopting a laser radar.
The laser radar acquires the distance information between the main vehicle and the distant vehicle, and is used for calculating TTC (time to live) to decide whether safe reverse overtaking is available.
In one embodiment, the step of judging whether the current time accords with a reverse overtaking scene according to the high-precision map data and the real-time collected data comprises the following steps:
firstly, judging whether a left steering lamp of the main vehicle is turned on, if so, considering that the main vehicle has a lane change attempt, then judging whether the main vehicle is in the leftmost lane in the driving direction, and finally judging whether a lane line between the current driving lane and the adjacent reverse lane supports lane change.
In one embodiment, calculating the lane change of the host vehicle at the current time, the time TTC required for the target remote vehicle to collide with the host vehicle, and the collision position includes: and calculating the time TTC and the collision position required by the collision between the target remote vehicle and the main vehicle through the longitude and latitude, the altitude, the speed and the acceleration information of the remote vehicle in the remote vehicle message.
The relationship between the various modules and sensors is shown in FIG. 3:
the CAN BUS is interactive with the OBU, the CAN BUS is connected with the CAN chip in V2X, the GNSS chip in V2X obtains positioning data from an external GNSS, high-precision map data are obtained from an external Cloud or an RSU, V2X is also used for receiving faraway RV messages, and Sensor data, namely Sensor data, comprise Camera data and LiDAR data. And the final early warning information is displayed on the HMI module.
The OBU is an On-Board Unit and a vehicle-mounted Unit.
HMI: human Machine Interface, Human Machine Interface or Human Machine Interface.
LiDAR: light Detection And Ranging, lidar.
Cloud is Cloud.
RSU (roadside unit) is the road side unit.
In one embodiment, the giving of the warning prompt according to whether the vehicle can return to the original lane comprises the following steps:
if so, prompting that the vehicle can be overtaken reversely;
if not, outputting reverse overtaking collision early warning information to a human-computer interaction interface, and displaying information for reminding the main vehicle of forbidding reverse overtaking on the human-computer interaction interface.
Referring to fig. 4, in one embodiment, a high-precision map-based reverse overtaking early warning method for V2X is provided, including:
the system obtains high-precision map data of the current road section through a road side unit or a rear cloud end, wherein the high-precision map data comprises a road surface geometric structure, lane line attributes, lane edge line positions, lane attributes, marking line positions, a surrounding environment model and the like. Meanwhile, real-time data of the driving environment of the current main vehicle is collected through the camera and the laser radar, and the current position of the main vehicle can be accurately confirmed by matching the high-precision map data, the real-time collected data and the GNSS real-time positioning.
And judging whether a left steering lamp of the main vehicle is turned on or not, and if so, considering that the main vehicle has a lane change attempt. Then, it is judged whether the host vehicle is in the leftmost lane in the traveling direction, and whether the lane line between the current traveling lane and the adjacent reverse lane supports lane change (if a dotted line, lane change is allowed; if a solid line, lane change is not allowed). If the conditions are met, the reverse overtaking scene is considered.
And filtering out the distant vehicles which are positioned on the adjacent reverse lane of the main vehicle, are positioned in the left front of the main vehicle and are closest to the main vehicle from all the received distant vehicle messages.
And calculating the time TTC required by the nearest distant vehicle to collide with the main vehicle and the collision position under the condition that the main vehicle changes lanes at the moment according to the information of the longitude and latitude, the altitude, the speed, the acceleration and the like of the distant vehicle.
It is calculated whether the host vehicle can complete a lane change overtaking within the TTC time and safely return to the original lane before reaching the location of the collision by a certain distance. This step needs to consider the speed, acceleration, etc. of the vehicle ahead of the host vehicle's driving lane so that the host vehicle can safely change its lane to the original lane after passing by.
And if the lane can not be safely changed to the original lane, outputting a reverse overtaking collision early warning to a human-computer interaction interface to remind a driver of the main vehicle of forbidding reverse overtaking.
The high-precision map-based reverse overtaking early warning method for V2X improves safety of reverse overtaking.
The invention further provides a storage medium, which stores computer instructions, and when a computer executes the computer instructions, the storage medium is used for executing the high-precision map-based V2X reverse overtaking early warning method according to any one of the above embodiments.
The invention also provides a high-precision map-based V2X reverse overtaking early warning system, which comprises at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the one processor to cause the at least one processor to:
acquiring high-precision map data and real-time acquisition data of a main vehicle driving section;
judging whether the current moment accords with a reverse overtaking scene or not according to the high-precision map data and the real-time collected data;
receiving a plurality of remote vehicle messages, wherein a remote vehicle which is positioned in front of the left of the main vehicle on an adjacent reverse lane of the lane where the main vehicle is positioned and is closest to the main vehicle is a target remote vehicle;
calculating the time TTC and the collision position required by the main vehicle lane change, the target remote vehicle and the main vehicle at the current moment;
calculating whether the main vehicle can finish lane change and overtaking in a TTC time period and returns to an original lane before a preset distance from a collision position;
and giving an early warning prompt according to whether the vehicle can return to the original lane.
The foregoing is considered as illustrative only of the principles and preferred embodiments of the invention. It should be noted that, for those skilled in the art, several other modifications can be made on the basis of the principle of the present invention, and the protection scope of the present invention should be regarded.

Claims (7)

1. A high-precision map-based reverse overtaking early warning method for V2X is characterized by comprising the following steps:
acquiring high-precision map data and real-time acquisition data of a main vehicle driving section;
judging whether the current moment accords with a reverse overtaking scene or not according to the high-precision map data and the real-time collected data;
receiving a plurality of remote vehicle messages, wherein a remote vehicle which is positioned in front of the left of the main vehicle on an adjacent reverse lane of the lane where the main vehicle is positioned and is closest to the main vehicle is a target remote vehicle;
calculating the time TTC and the collision position required by the main vehicle lane change, the target remote vehicle and the main vehicle at the current moment;
calculating whether the main vehicle can finish lane change and overtaking in a TTC time period and returns to an original lane before a preset distance from a collision position;
giving an early warning prompt according to whether the vehicle can return to the original lane or not;
the high-precision map data includes: the method comprises the following steps of (1) carrying out road surface geometric structure, lane line attribute, lane edge line position, lane attribute, marking line position and surrounding environment model;
the high-precision map data is used for performing characteristic matching with the data acquired in real time so as to perform accurate positioning;
calculating the matching degree of each lane according to the data collected in real time, wherein the matching degree is considered from multiple dimensions;
weighting the matching degrees of multiple dimensions to calculate the matching degree of each lane, wherein the lane with the highest matching degree is the current lane;
correcting the specific position of the main vehicle in the lane according to the fixed objects around the lane recognized by the camera, wherein the fixed objects around the lane comprise: traffic signs, signal lights and guard rails.
2. The high-precision map-based V2X reverse overtaking warning method as claimed in claim 1,
the real-time data acquisition is that real-time data of the driving environment of the main vehicle at the current moment is acquired through the camera and the laser radar, and positioning data is acquired through GNSS.
3. The high-precision map-based V2X reverse overtaking warning method as claimed in claim 1,
judging whether the current moment accords with a reverse overtaking scene according to the high-precision map data and the real-time collected data comprises the following steps:
firstly, judging whether a left steering lamp of the main vehicle is turned on, if so, considering that the main vehicle has a lane change attempt, then judging whether the main vehicle is in the leftmost lane in the driving direction, and finally judging whether a lane line between the current driving lane and the adjacent reverse lane supports lane change.
4. The high-precision map-based V2X reverse overtaking warning method as claimed in claim 1,
calculating the time TTC and the collision position required by the target remote vehicle to collide with the main vehicle at the current time of the lane change of the main vehicle comprises the following steps: and calculating the time TTC and the collision position required by the collision between the target remote vehicle and the main vehicle through the longitude and latitude, the altitude, the speed and the acceleration information of the remote vehicle in the remote vehicle message.
5. The high-precision map-based V2X reverse overtaking warning method according to any one of claims 1-4,
giving an early warning prompt according to whether the vehicle can return to the original lane comprises the following steps:
if so, prompting that the vehicle can be overtaken reversely;
if not, outputting reverse overtaking collision early warning information to a human-computer interaction interface, and displaying information for reminding the main vehicle of forbidding reverse overtaking on the human-computer interaction interface.
6. A storage medium storing computer instructions for performing the high precision map-based V2X reverse overtaking warning method according to any one of claims 1 to 5 when executed by a computer.
7. A high-precision map-based V2X reverse overtaking early warning system is characterized by comprising at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the one processor to cause the at least one processor to:
acquiring high-precision map data and real-time acquisition data of a main vehicle driving section;
judging whether the current moment accords with a reverse overtaking scene or not according to the high-precision map data and the real-time collected data;
receiving a plurality of remote vehicle messages, wherein a remote vehicle which is positioned in front of the left of the main vehicle on an adjacent reverse lane of the lane where the main vehicle is positioned and is closest to the main vehicle is a target remote vehicle;
calculating the time TTC and the collision position required by the main vehicle lane change, the target remote vehicle and the main vehicle at the current moment;
calculating whether the main vehicle can finish lane change and overtaking in a TTC time period and returns to an original lane before a preset distance from a collision position;
giving an early warning prompt according to whether the vehicle can return to the original lane or not;
the high-precision map data includes: the method comprises the following steps of (1) carrying out road surface geometric structure, lane line attribute, lane edge line position, lane attribute, marking line position and surrounding environment model;
the high-precision map data is used for performing characteristic matching with the data acquired in real time so as to perform accurate positioning;
calculating the matching degree of each lane according to the data collected in real time, wherein the matching degree is considered from multiple dimensions;
weighting the matching degrees of multiple dimensions to calculate the matching degree of each lane, wherein the lane with the highest matching degree is the current lane;
correcting the specific position of the main vehicle in the lane according to the fixed objects around the lane recognized by the camera, wherein the fixed objects around the lane comprise: traffic signs, signal lights and guard rails.
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