Journal of Jilin University(Engineering and Technology Edition) ›› 2024, Vol. 54 ›› Issue (8): 2378-2384.doi: 10.13229/j.cnki.jdxbgxb.20230345

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Vehicle trajectory holographic perception method based on laser range sensors

Hui ZHANG(),Xin WEN,Hai-yu CHEN,Shi-chun HUANG   

  1. School of Intelligent Systems Engineering，Sun Yat-sen University，Shenzhen 518107，China
  • Received:2023-04-12 Online:2024-08-01 Published:2024-08-30

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Abstract:

To achieve real-time holographic perception of vehicle trajectories on all sections of highways， this paper aims to explore a cost-effective and easily deployable method for holographic perception of vehicle trajectories. Initially， perception devices composed of laser range sensors， distributed along the roadside， are used to collect discrete trajectory profile information of vehicles in real time. Subsequently， by conditional matching， the information from adjacent detection profiles is matched and associated to obtain the sequence of trajectory points for each vehicle. Finally， cubic spline interpolation is used to reconstruct the complete trajectory of the vehicles. Verification shows that the reconstructed vehicle trajectories are fundamentally consistent with their actual trajectories， demonstrating the feasibility of this method in theory.

Key words: vehicle trajectory holographic perception, laser range sensor, trajectory reconstruction, roadside perception devices

CLC Number: 

  • U417.9

Fig.1

Schematic diagram of equipment deployment of holographic perception system"

Fig.2

Schematic diagram of the variation of the relative distance waveform of the detection section"

Fig.3

Scatter plot of velocity versus acceleration for 01 segment data of the HighD dataset"

Fig.4

Relationship between speed and ultimate acceleration"

Table 1

Vehicle operating conditions correspond to matching priority levels"

车辆运行工况优先等级
正常行驶（无换道）一级
正常行驶（有换道）二级
紧急制动（无换道）三级
紧急制动（有换道）四级

Fig.5

Evolution of accuracy with section interval"

Fig.6

Evolution of accuracy rates with section interval by different traffic volumes"

Fig.7

Reconstructed trajectories of vehicles"

Fig.8

Statistics on the average error of multi-vehicle trajectories （HighD-56 Segment）"

Fig.9

Evolution of mean error of multi-vehicle trajectories with section interval"

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