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2-dimensional human-like driver model for autonomous vehicles in mixed traffic

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journal contribution
posted on 18.03.2021, 11:40 authored by MN Sharath, NR Velaga, Mohammed Quddus
© The Institution of Engineering and Technology 2020. Classical artificial potential approach of motion planning is extended for emulating human driving behaviour in two dimensions. Different stimulus parameters including type of ego-vehicle, type of obstacles, relative velocity, relative acceleration, and lane offset are used. All the surrounding vehicles are considered to influence drivers' decisions. No emphasis is laid on vehicle control; instead, an ego vehicle is assumed to reach the desired state. The study is on human-like driving behaviour modelling. The developed motion planning algorithm formulates repulsive and attractive potentials in a data-driven way in contrast to the classical arbitrary formulation. Interaction between the stimulus parameters is explicitly considered by using multivariate cumulative distribution functions. Comparison of two-dimensional (lateral and longitudinal) performance indicators with a baseline model and generative adversarial networks indicate the effectiveness and suitability of the developed motion planning algorithm in the mixed traffic environment.

History

School

  • Architecture, Building and Civil Engineering

Published in

IET Intelligent Transport Systems

Volume

14

Issue

13

Pages

1913 - 1922

Publisher

WILEY

Version

AM (Accepted Manuscript)

Rights holder

© 2020 The Institution of Engineering and Technology

Publisher statement

This paper was accepted for publication in the journal IET Intelligent Transport Systems and the definitive published version is available at https://doi.org/10.1049/iet-its.2020.0297

Acceptance date

09/12/2020

Publication date

2021-01-13

Copyright date

2020

ISSN

1751-956X

eISSN

1751-9578

Language

en

Depositor

Prof Mohammed Quddus. Deposit date: 16 March 2021