Artificial Intelligence-Based Trajectory Planning for Driverless Vehicles—A Review

Aathira G. Menon*, S. Bindu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationRecent Advances in Hybrid and Electric Automotive Technologies - Select Proceedings of HEAT 2021
EditorsV. Krishna, K.N. Seetharamu, Yogendra Kumar Joshi
PublisherSpringer Science and Business Media Deutschland GmbH
Pages167-183
Number of pages17
ISBN (Print)9789811920929
DOIs
Publication statusPublished - 2022
Event1st Biennial International Conference on Hybrid and Electric Automotive Technologies, HEAT 2021 - Bangalore, India
Duration: 29-10-202130-10-2021

Publication series

NameLecture Notes in Mechanical Engineering
ISSN (Print)2195-4356
ISSN (Electronic)2195-4364

Conference

Conference1st Biennial International Conference on Hybrid and Electric Automotive Technologies, HEAT 2021
Country/TerritoryIndia
CityBangalore
Period29-10-2130-10-21

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes

Fingerprint

Dive into the research topics of 'Artificial Intelligence-Based Trajectory Planning for Driverless Vehicles—A Review'. Together they form a unique fingerprint.

Cite this