Paper Image

Designing Obstacle Avoidance in Autonomous Vehicles Considering Driver Comfort

Published on:

3 July 2023

Primary Category:

Robotics

Paper Authors:

Weishun Deng,

Fan Yu,

Zhe Wang,

Dengbo He

Bullets

Key Details

Machine learning classifiers link vehicle dynamics and driver subjective ratings

Potential field path planner uses driver models and psychological safety boundaries

Simulations show algorithm avoids obstacles and improves driver comfort

Driver subjective ratings used to tune obstacle avoidance strategy

Algorithm adapts obstacle avoidance to driver risk tolerance

AI generated summary

Designing Obstacle Avoidance in Autonomous Vehicles Considering Driver Comfort

This paper proposes an algorithm for autonomous vehicles to avoid obstacles while improving driver comfort. Machine learning classifiers correlate objective vehicle dynamics with subjective driver ratings. These models inform a potential field path planner that considers psychological safety boundaries. Simulations demonstrate the algorithm's ability to avoid obstacles while enhancing driver confidence.

Answers from this paper

Comments

No comments yet, be the first to start the conversation...

Sign up to comment on this paper

Sign Up