Active Obstacle Avoidance Path Planning for Multi-scenario Autonomous Vehicles Under Icy and Snowy Road Conditions

doi:10.12068/j.issn.1005-3026.2025.20239039

Abstract

Abstract:

Addressing the issue of autonomous vehicles’ instability on icy and snowy roads， an improved rapidly-exploring random tree （RRT） path planning algorithm is proposed. Firstly， a dynamic model introducing road adhesion coefficient on icy and snowy roads is established. Secondly， the global target deflection sampling combined with the front pointing and steering angle of the vehicle， combined with the collision avoidance detection and the maximum curvature constraint under the velocity-adhesion coefficient， is used to improve the traditional RRT algorithm problem.Finally， a double quintic polynomial is used for path smoothing to ensure stability， brake constraints， and comfort. The performance of the improved algorithm RRT is compared with that of the traditional algorithm under multi-scenario conditions through the joint simulation of MATLAB-Simulink and CarSim. The experiments show that the improved RRT algorithm significantly improves the path smoothness， reduces the curvature mutation， has short time， high success rate and good stability when driving on ice and snow.

Key words: autonomous vehicle, path planning, rapidly-exploring random tree, ice and snow roads, multi-scenario

CLC Number:

U 495

Yu-long PEI, Shuang-zhu ZHAI. Active Obstacle Avoidance Path Planning for Multi-scenario Autonomous Vehicles Under Icy and Snowy Road Conditions[J]. Journal of Northeastern University(Natural Science), 2025, 46(3): 1-11.

Figures/Tables 15

Fig.1 Simplified two-degree of freedom vehicle dynamical model

Fig.2 Input and output variables of magic formula tire model

Fig.3 Flow chart of collision detection

Fig.4 Schematic diagram of the curvature- constrained pruning strategy

Fig.5 Schematic diagram of the curvature-constrained branching strategy

Fig.6 Static lane changing scenario

Fig.7 Static turning scenario

Fig.8 Static U-turn scenario

Fig.9 Dynamics simulation parameters of vehicle in lane change scenario 1

Fig.10 Dynamics simulation parameters of vehicle in lane change scenario 2

Fig.11 Dynamics simulation parameters of vehicle in turning scenario 1

Fig.12 Dynamics simulation parameters of vehicle in turning scenario 2

Fig.13 Dynamics simulation parameters of vehicle in U-turn scenario

Fig.14 Simulation results of dynamic path planning

Fig.15 Changes of dynamics simulation parameters of vehicle in a dynamic scenario

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