Intelligent Vehicle Trajectory Planning Based on Spatio-temporal Risk Fields

doi:10.3969/j.issn.1004-132X.2025.10.036

Abstract

Abstract:

Aming to describe and avoid different dimensions of risks faced by intelligent vehicles， a two-layer trajectory planning method was proposed based on spatio-temporal risk fields. Traffic elements were divided into abstract elements and concrete elements， the spatial-temporal risk fields of abstract elements based on Gaussian distribution function and concrete elements based on spatial vector were established respectively to represent the environmental risks faced by intelligent vehicles in three dimensions： vertical， horizontal and temporal. Additionally， the trajectory planning problem of intelligent vehicles was divided into path and speed dual planning problem. The longitudinal-lateral dimension risk and longitudinal-temporal dimension risk were accordingly applied to dynamic planning cost function. Then， the path and speed with the comprehensive lowest cost were calculated， and combined with quadratic programming algorithm， the path and velocity were further optimized to obtain the final trajectory. Simulation results demonstrate that the proposed methodology may effectively characterize spatio-temporal driving risks across diverse scenarios while generating constraint-satisfying trajectories， thereby significantly enhance road driving safety.

Key words: intelligent vehicle, spatio-temporal risk field, trajectory planning, dynamic planning

摘要：

为描述及规避智能车辆行驶时面临的不同维度风险，提出了一种基于时空风险场的双层轨迹规划方法。将交通要素划分为抽象要素和具象要素，分别建立基于高斯分布函数的抽象要素时空风险场和基于空间向量的具象要素时空风险场，以表征智能车辆在纵向、横向和时间三个维度面临的环境风险。将智能车辆的轨迹规划问题划分为路径和速度双层规划问题，分别考虑纵向-横向维度和纵向-时间维度的风险构建动态规划的代价函数，获取综合代价最低的路径和速度。结合二次规划算法对路径和速度进一步优化得到最终轨迹。仿真结果表明，所提出的方法在不同的驾驶场景下能够有效表征时空风险并规划出满足各项约束条件的行驶轨迹，从而提高道路驾驶的安全性。

关键词: 智能车辆, 时空风险场, 轨迹规划, 动态规划

CLC Number:

U461

Huifang KONG, Chenshun WANG, Qian ZHANG, Tiankuo LIU. Intelligent Vehicle Trajectory Planning Based on Spatio-temporal Risk Fields[J]. China Mechanical Engineering, 2025, 36(10): 2463-2471.

孔慧芳, 王晨顺, 张倩, 刘田阔. 基于时空风险场的智能车辆轨迹规划[J]. 中国机械工程, 2025, 36(10): 2463-2471.

Figures/Tables 20

Fig.1 Trajectory planning architecture based on spatio-temporal risk field

Fig.2 Schematic method of spatio-temporal risk field modeling of abstract elements

Fig.3 Spatio-temporal risk field of abstract elements

Fig.4 Plots spatio-temporal trajectories

Fig. 5 Tangent vector and projection rendering of spatio-temporal trajectory

Fig.6 θ angle acquisition

Fig.7 Spatio-temporal risk field of concrete elements

Fig.8 Schematic diagram of spatio-temporal risk field

Fig.9 Intersection scene

Fig.10 ST risk map generation

Fig.11 Driving scene on a straight road

Fig.12 Spatio-temporal risk of straight-line driving scenario

Fig.13 Three-dimensional view， s-l view and s-t view of trajectory planning（scene 1）

Fig.14 Velocity result curves（scene 1）

Fig.15 Acceleration result curves（scene 1）

Fig.16 Driving scene at an intersection without traffic lights

Fig.17 Spatio-temporal risk distribution of intersection scenes

Fig.18 Three-dimensional view， s-l view and s-t view of trajectory planning（scene 2）

Fig.19 Velocity result curves（scene 2）

Fig.20 Acceleration result curves（scene 2）

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