One of the hurdles in implementing self-driving automobiles is their precise decision-making in uncertain traffic conditions. The paper reviews various Artificial Intelligence-based trajectory planning algorithms addressing this issue. The review focuses on lane changing, trajectory selection, and safety to model a Level-5 autonomous vehicle. The prominent algorithms are discussed in terms of their features, status, and scope. The algorithms are analysed in the increasing order of levels of automation. As the trajectory planning algorithm mimics human intelligence, it is more probable to develop the characteristics of a trustworthy self-driving vehicle capable of making accurate decisions in extreme road or traffic circumstances. In addition to the major traffic elements, pedestrian interaction, vehicle dynamics, and the usage of an adaptive controller can ensure more promising results to achieve safe lane changing/selection.
Artificial Intelligence-Based Trajectory Planning for Driverless Vehicles—A Review
Lect.Notes Mechanical Engineering
Recent Advances in Hybrid and Electric Automotive Technologies ; Chapter : 14 ; 167-183
2022-08-02
17 pages
Article/Chapter (Book)
Electronic Resource
English
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