Generating <i>G</i> <sup>2</sup> Continuity Reference Paths for Autonomous Vehicles at Roundabouts

Planning paths for Frenet-based autonomous vehicles (AVs) at roundabouts is difficult without complete and smooth reference paths. In such situations, the interpolating curve planner is often used to create segmented reference paths from simplified geometric roundabout data. While this method ensures curvature continuity within each curve segment, the continuity at the junctions of these segments is poor. Additionally, the determination of merging and diverging point positions at roundabouts has not been thoroughly explored. This paper introduces a novel approach using 5th-order Bézier curves to plan piecewise reference paths for AVs at roundabouts. The proposed method enhances endpoint curvature continuity of the Bézier curves and improves adaptability to non-standard roundabouts. A well-designed objective function is created to optimize both the geometric continuity parameters of the Bézier curves and the positions of merging and diverging points in the circulatory roadway. This function takes into account key factors, including path length and smoothness. Case studies validate the feasibility of maintaining curvature continuity at the endpoints and the method’s ability to generalize across various scenarios, proving its effectiveness for different roundabout structures. The results also confirm the method’s efficacy in generating paths from original geometric roundabout data. Lastly, the acceptable transverse deviations between real-world trajectories and reference paths demonstrate the rationality and practical applicability of this method.

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Publication Details

Journal
IEEE Transactions on Intelligent Transportation Systems
Published
2025-07-14
DOI
https://doi.org/10.1109/tits.2025.3585504
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
0.00

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article

Generating G 2 Continuity Reference Paths for Autonomous Vehicles at Roundabouts

Chenhui Yin, Haobin Jiang, Marco Cecotti, Qingyuan Shen et al.
IEEE Transactions on Intelligent Transportation Systems
Autonomous Vehicle Technology and Safety
article

Generating G 2 Continuity Reference Paths for Autonomous Vehicles at Roundabouts

Chenhui Yin, Haobin Jiang, Marco Cecotti, Qingyuan Shen, Aoxue Li, You Gong
article en

Abstract

Planning paths for Frenet-based autonomous vehicles (AVs) at roundabouts is difficult without complete and smooth reference paths. In such situations, the interpolating curve planner is often used to create segmented reference paths from simplified geometric roundabout data. While this method ensures curvature continuity within each curve segment, the continuity at the junctions of these segments is poor. Additionally, the determination of merging and diverging point positions at roundabouts has not been thoroughly explored. This paper introduces a novel approach using 5th-order Bézier curves to plan piecewise reference paths for AVs at roundabouts. The proposed method enhances endpoint curvature continuity of the Bézier curves and improves adaptability to non-standard roundabouts. A well-designed objective function is created to optimize both the geometric continuity parameters of the Bézier curves and the positions of merging and diverging points in the circulatory roadway. This function takes into account key factors, including path length and smoothness. Case studies validate the feasibility of maintaining curvature continuity at the endpoints and the method’s ability to generalize across various scenarios, proving its effectiveness for different roundabout structures. The results also confirm the method’s efficacy in generating paths from original geometric roundabout data. Lastly, the acceptable transverse deviations between real-world trajectories and reference paths demonstrate the rationality and practical applicability of this method.

IEEE Transactions on Intelligent Transportation SystemsVol. 26(9)
Jiangsu University (CN), Xiamen University of Technology (CN), Cranfield University (GB)
National Natural Science Foundation of China
Openalex Percentile: Top 83%
Autonomous Vehicle Technology and Safety
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