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Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

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PUBLISHED
01.03.2024
DOI
https://doi.org/10.7307/ptt.v36i1.288
ISSUE
2024 (Vol 36), Issue 1
LICENSE
Copyright (c) 2024 Shaojie Liu, Wei Fan, Shuaiyang Jiao, Aizeng Li
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This work is licensed under a
Creative Commons Attribution-NonCommercial-
NoDerivatives 4.0 International License.

The Performance of Connected and Autonomous Vehicles with Trajectory Planning in a Fixed Signal Controlled Intersection

Authors:Shaojie Liu, Wei Fan, Shuaiyang Jiao, Aizeng Li

Abstract

Connected and autonomous vehicles (CAVs) are recognised as a technology trend in the transportation engineering arena. As one of the most popular capabilities of CAVs, trajectory planning attracts extensive attention and interest from both academia and the industry. Segmented trajectory planning is gaining popularity for its simplicity and robustness in computation and deployment. Constructive recommendations and guidelines can be provided by exploring the effects of segmented trajectories in different settings of CAVs and intersections. This research proposes a control strategy for segmented trajectory planning in a fixed signal timing environment. To test the effects of this control strategy, this research designs simplified fixed signalised intersection scenarios and implements segmented trajectory planning features of CAVs with different traffic demand scenarios, distances and speed limits. The results show that the proposed control strategy has stable superior performances in different traffic scenarios especially when the traffic volume is near capacity.

Keywords:connected and autonomous vehicles, trajectory planning, fixed signal-controlled intersection, virtual platoon

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