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CN-116935686-B - Holographic vehicle track deviation correcting algorithm for abnormal data of road sensing equipment

CN116935686BCN 116935686 BCN116935686 BCN 116935686BCN-116935686-B

Abstract

The invention discloses a holographic vehicle track deviation correcting algorithm aiming at abnormal data of road sensing equipment, which solves the problems of reduced authenticity and reliability of holographic digital road vehicle tracks caused by the disorder of millimeter wave Lei Dadian cloud and abnormal position in the prior art and comprises the following steps that S1, position points of all exit lanes of a current intersection are obtained, and the exit lanes are numbered; S2, calculating the current target exit lane of each vehicle according to the existing track of each vehicle in the current intersection, S3, calculating the position relation among the current vehicles in the intersection, and S4, correcting the vehicle in the intersection based on the target exit lane in sequence based on the position relation among the vehicles to realize the vehicle track correction. When the original track data of the road sensing device is abnormally deviated, the vehicle track in the holographic digital road is timely corrected, and the authenticity and reliability of the vehicle track of the holographic digital road are effectively improved.

Inventors

  • MA ZHENGYANG
  • QIU REN
  • SUN LIBIN
  • ZHOU JUNJIE
  • MO WANGZHONG

Assignees

  • 浙江中控信息产业股份有限公司

Dates

Publication Date
20260505
Application Date
20230719

Claims (8)

  1. 1. A holographic vehicle track deviation correcting algorithm for data anomalies of road sensing equipment, comprising: S1, acquiring position points of each exit lane of a current intersection, and numbering the exit lanes; S2, calculating the current target exit lane of each vehicle according to the existing track of each vehicle in the current intersection; acquiring a latest original track point P 1 of a vehicle and a latest original track point P 2 which is far away from the latest original track point D dist m, connecting the track point P 1 by taking the track point P 2 as a starting point, and acquiring the slope k and the intercept b of a straight line where a ray in the current target direction of the vehicle is positioned; calculating the vertical foot Q of the position point Q of a certain exit lane on the straight line of the ray in the target direction of the vehicle, the distance D 1 between the vertical foot Q and P 1 , the distance D 12 between the distance D 2 ,P 1 between the vertical foot Q and P 2 and the distance D 12 between the P 2 , if D 1 >D 2 and D 1 >D 12 are carried out, eliminating the position point Q, otherwise, calculating the distance D Q between the position point Q and the ray in the current target direction of the vehicle; s3, calculating the position relation among the current vehicles in the intersection; and S4, correcting the deviation of the vehicles in the intersection based on the target exit lane sequentially based on the position relation among the vehicles, so as to realize the vehicle track deviation correction.
  2. 2. The method according to claim 1, wherein the step S2 comprises traversing all vehicles in the current intersection in turn and calculating the current target exit lane corresponding to the vehicle, respectively.
  3. 3. The holographic vehicle track deviation correcting algorithm for road sensing equipment data anomalies according to claim 1, wherein the step S4 further comprises: s4.1, calculating the maximum target exit lane number N of other vehicles in the left side direction of a certain vehicle in the intersection, wherein the target exit lane number of the vehicle is M; and S4.2, judging the relation between N and M, if N is less than M, correcting the deviation, and if N is more than or equal to M, correcting the deviation of the vehicle based on the target exit lane, and planning a new travelling route.
  4. 4. The method of claim 3, wherein the step S4.2 further comprises updating the number of the lane of the exit of the vehicle to be N+1, and connecting the current track point of the vehicle with the updated position point of the lane of the exit of the vehicle to obtain a corrected route, and the vehicle proceeds along the corrected route according to the last traveling speed before the abnormal deviation of the track.
  5. 5. The algorithm of claim 1,2 or 3, wherein the step S3 is further expressed as that for each vehicle at the intersection, the current latest original track point P 1 (lon 1 ,lat 1 ) is used as a center, the current target direction Angle is used as a reference Angle, the left distance threshold value is D left m, and whether other vehicles exist in the sector range with the Angle threshold value [ Angle 1 ,Angle 2 ] is detected and recorded.
  6. 6. The algorithm of claim 1,2 or 3, wherein in step S4, the method further comprises determining whether other vehicles exist on the left side of all vehicles in the intersection, sorting the vehicles from small to large according to the number of other vehicles on the left side of the vehicles, and correcting the vehicles in the intersection based on the target exit lane sequentially based on the order.
  7. 7. The algorithm of correcting the holographic vehicle track for the abnormal data of the road sensing apparatus according to claim 1,2 or 3, wherein the step S1 further comprises the steps of obtaining the middle point of the start line of each exit lane of the current intersection as the position point of the exit lane, and numbering the exit lanes from small to large in the order from the inner side to the outer side.
  8. 8. The method of claim 4, wherein in the step S4.2, if N+1 is greater than the maximum number of the exit lane, the number of the target exit lane of the vehicle is updated to N.

Description

Holographic vehicle track deviation correcting algorithm for abnormal data of road sensing equipment Technical Field The invention relates to the technical field of holographic digital road vehicle track correction, in particular to a holographic vehicle track correction algorithm aiming at abnormal data of road sensing equipment. Background Intelligent traffic refers to a mode for optimizing operation and management of a traffic system and improving traffic efficiency and safety by using modern information technology and intelligent equipment. Holographic digital roads are important components of intelligent traffic, sense the running conditions of road traffic in the real world through various sensors (such as millimeter wave radar, video cameras and the like), and project the road traffic data in the real world into a virtual platform in a simulation modeling mode so as to construct a real-time road traffic model. In the process, the quality of traffic track data detected by sensing equipment such as millimeter wave radar or video cameras directly determines the reliability of the holographic digital road. The method is limited by limitations of current road traffic sensing equipment (millimeter wave radar or video camera and the like), namely the detection range of the traffic sensing equipment often cannot cover the whole intersection, so that a single equipment cannot completely acquire whole-process track data of a certain vehicle entering the intersection from an entrance road and exiting the intersection, and the track of the vehicle at the view edge of the single equipment can generate larger position deviation, wherein the track data of the millimeter wave radar can generate track position deviation and disordered point cloud in the whole view range, and the video camera can generate track deviation, large-angle abnormal deflection and the like at the view edge of the single equipment. These problems may reduce the track authenticity and reliability of vehicles in the holographic digital road, and even a collision phenomenon of vehicles in the holographic digital road may occur due to abnormal track data of the millimeter wave radar or the video camera. The patent CN114910912A discloses a multi-radar track relay method, a device, a storage medium and equipment, solves the problem that a single sensor equipment is difficult to effectively cover the whole range of an intersection through track relay of multiple equipment on the same vehicle, but does not solve the influence of cloud disorder and position abnormality of millimeter waves Lei Dadian on a holographic digital road. Disclosure of Invention The invention aims to solve the problems of the prior art that the authenticity and reliability of the holographic digital road vehicle track are reduced due to the fact that millimeter wave Lei Dadian clouds are disordered and the position of the holographic digital road vehicle track is abnormal, and provides a holographic vehicle track correction algorithm aiming at the data abnormality of road sensing equipment. In order to achieve the purpose, the invention adopts the following technical scheme that the holographic vehicle track deviation correcting algorithm aiming at the data abnormality of the road sensing equipment comprises the following steps: S1, acquiring position points of each exit lane of a current intersection, and numbering the exit lanes; s2, calculating the current target exit lane of each vehicle according to the existing track of each vehicle in the current intersection; s3, calculating the position relation among the current vehicles in the intersection; and S4, correcting the deviation of the vehicles in the intersection based on the target exit lane sequentially based on the position relation among the vehicles, so as to realize the vehicle track deviation correction. The method comprises the steps of obtaining a target exit lane of a vehicle by utilizing the existing track of each vehicle in the current intersection, and planning a new travel route for the vehicle track with abnormal offset by combining with calculating the position relation among the current vehicles in the intersection. The original track abnormal deviation solution provided by the invention is applied to a holographic digital road, can effectively improve the track reliability and the authenticity of a holographic vehicle, and can be universally applied to various different sensing devices such as millimeter wave radars, video cameras and the like. Preferably, the step S2 further includes: S2.1, acquiring the minimum original track point P 1(lon1,lat1) of the vehicle and the nearest original track point P 2(lon2,lat2 which is far away from the latest original track point D dist m; S2.2, connecting a track point P 1 by taking the track point P 2 as a starting point, and calculating to obtain the slope k and the intercept b of a straight line where the ray in the current target direction of the vehicle is pos