Self-Driving like a Human driver instead of a Robocar: Personalized comfortable driving experience for autonomous vehicles

TL;DR

This paper presents a personalized control system for autonomous vehicles that mimics human driving preferences, enhancing comfort by adjusting acceleration and jerk within user-defined limits.

Contribution

It introduces an Occupant's Preference Metric and a control framework that enables autonomous vehicles to adopt human-like driving styles based on individual preferences.

Findings

Successfully tracks user-defined acceleration and jerk limits

Provides a human-like driving experience in simulations and experiments

Enhances passenger comfort through personalized control strategies

Abstract

This paper issues an integrated control system of self-driving autonomous vehicles based on the personal driving preference to provide personalized comfortable driving experience to autonomous vehicle users. We propose an Occupant's Preference Metric (OPM) which is defining a preferred lateral and longitudinal acceleration region with maximum allowable jerk for users. Moreover, we propose a vehicle controller based on control parameters enabling integrated lateral and longitudinal control via preference-aware maneuvering of autonomous vehicles. The proposed system not only provides the criteria for the occupant's driving preference, but also provides a personalized autonomous self-driving style like a human driver instead of a Robocar. The simulation and experimental results demonstrated that the proposed system can maneuver the self-driving vehicle like a human driver by tracking the specified criterion of admissible acceleration and jerk.