Abstract
An adaptive potential field is designed to adapt the acceleration/deceleration and mass of the obstacle. The potential fields are established in a transformed road coordinate system to improve the feasibility and robustness. A path planning method is proposed based on the designed adaptive potential field to improve the driving safety and the ride comfort of autonomous vehicles in complex driving scenarios, which including the cut-in, emergency braking, obstacle sudden accelerating during overtaking and the curve road driving scenarios. The effectiveness of the proposed method is validated by simulations with constructed and real data, respectively. The $TTC\text{s}$ (Time-to-Collision) and the maximum lateral accelerations are used to evaluate the improvements on safety and ride comfort. The results show that both the driving safety and ride comfort are efficiently improved by using the proposed approach in emergency braking and accelerating scenarios. Meanwhile, the proposed method can be well applied in a curve road driving environment.
Highlights
Various algorithms have been developed for path planning according to the application scenarios [2], e.g. RRT methods for structured [3] and unstructured driving scenarios [4], A∗ algorithm for off-line path planning [5] [6], polynomial interpolation approaches for real-time motion planning [7], etc
Uk,t = uk−1,t + ∆uk,t where Q and R are the weights of the cost terms, k represents the prediction of kth step ahead of t; Ad and Bd are the discrete matrices of the state-equation based on Euler method [33]; Cd denotes the output matrix, ytd+esk,t represents the reference path generated by adaptive potential field (ADPF)-PP; yt+k,t is the realtime position of the ego vehicle
An improved potential field-based path planning (IPF-PP) method [35] and the classical conventional potential fieldbased path planning (CPF-PP) method are used for comparison with the proposed approach in this study
Summary
P ATH planning as an important component of autonomous driving techniques has been widely researched in recent years [1]. Considering the improvements on driving safety during obstacle avoidance, the potential fieldbased approaches have been popularly used for path planning of autonomous vehicles (AVs) [9]. According to the definition of safety field, the PF values around the obstacles are used to declare the risk degree of collision [17] These applications of the PF are based on the assumption that the shape of the PFs are symmetric distribution [18], and the PFs are only constructed and applied in a straight road environment. 2) The ADPF-based path planning (ADPF-PP) is proposed to improve the driving safety and ride comfort of the autonomous vehicles in various scenarios including emergency braking, fast cut-in, and sudden acceleration of the obstacle vehicle. To the best of our knowledge, this is one of the first attempts to apply innovatively proposed potential fieldbased methods in curve road scenarios
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