Abstract
The convergence of mechanical, electrical, and advanced ICT technologies, driven by artificial intelligence and 5G vehicle-to-everything (5G-V2X) connectivity, will help to develop high-performance autonomous driving vehicles and services that are usable and convenient for self-driving passengers. Despite widespread research on self-driving, user acceptance remains an essential part of successful market penetration; this forms the motivation behind studies on human factors associated with autonomous shuttle services. We address this by providing a comfortable driving experience while not compromising safety. We focus on the accelerations and jerks of vehicles to reduce the risk of motion sickness and to improve the driving experience for passengers. Furthermore, this study proposes a time-optimal velocity planning method for guaranteeing comfort criteria when an explicit reference path is given. The overall controller and planning method were verified using real-time, software-in-the-loop (SIL) environments for a real-time vehicle dynamics simulation; the performance was then compared with a typical planning approach. The proposed optimized planning shows a relatively better performance and enables a comfortable passenger experience in a self-driving shuttle bus according to the recommended criteria.
Highlights
Autonomous driving vehicles are expected to achieve outstanding results in decreasing traffic accidents, improving traffic flow, and improving fuel efficiency
The overall controller and planning method were verified using real-time, software-in-the-loop (SIL) environments for a real-time vehicle dynamics simulation; the performance was compared with a typical planning approach
The proposed optimized planning shows a relatively better performance and enables a comfortable passenger experience in a self-driving shuttle bus according to the recommended criteria
Summary
Autonomous driving vehicles are expected to achieve outstanding results in decreasing traffic accidents, improving traffic flow, and improving fuel efficiency. Autonomous vehicles are convenient for humans as they free humans from the driving workload. Riding in a self-driving vehicle can be accomplished without paying attention to the roadway environment. User acceptance is of fundamental importance for achieving successful market penetration; this has motivated research on the study of human factors in harmony with the development of self-driving vehicles. Remarkable achievements have been published in recent decades regarding the development of an autonomous vehicle control system [1,2,3], there remains a lack of investigation on the control strategy in terms of self-driving service operations in accordance with comfortable driving factors for passengers. It is difficult to define “ride convenience” because it is highly related to personal preference and individual tastes, driving comfort for autonomous car users has been studied with respect to human–machine interface (HMI) [5,6,7]
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