In this review paper, the integration of Machine Learning (ML) and Model Predictive Control
(MPC) in Automotive Control System (ACS) applications are discussed. ACS can be divided …

An internal combustion engine (ICE) is a highly nonlinear dynamic and complex
engineering system whose operation is constrained by operational limits, including …

This comprehensive review focuses on the Autonomous Driving System (ADS), which aims
to reduce human errors that are the reason for about 95% of car accidents. The ADS …

The autonomous vehicle is widely applied in various ground operations, in which motion
planning and tracking control are becoming the key technologies to achieve autonomous …

Emergency vehicle transportation is important for responding to and transporting individuals
during emergencies. This type of transportation faces several issues, such as road safety …

This article addresses a common issue in the design of battery electric vehicles (BEVs) by
introducing a comprehensive methodology for the modeling and simulation of BEVs …

Driver models play a vital role in developing and verifying autonomous vehicles (AVs).
Previously, they were mainly applied in traffic flow simulation to model driver behavior. With …

A core issue inherent to decision‐making and path‐planning tasks is managing the
uncertainties in the motion of dynamic obstacles. Therefore, this article proposes a new …

Planning the optimal trajectory of emergency avoidance maneuvers for highly automated
vehicles is a complex task with many challenges. The algorithm needs to decrease accident …

To improve the path tracking accuracy and yaw stability of distributed drive autonomous
vehicles (DDAVs) under extreme working conditions, a cooperative lateral motion control …