Automated vehicles and advanced driver-assistance systems require an accurate prediction of future traffic scene states. The tendency in recent years has been to use deep learning …
The significant contribution of human errors, accounting for approximately 94%(with a margin of±2.2%), to road crashes leading to casualties, vehicle damages, and safety …
While autonomous vehicles still struggle to solve challenging situations during on-road driving, humans have long mastered the essence of driving with efficient, transferable, and …
Driver behavior models have been used as input to self-coaching, accident prevention studies, and developing driver-assisting systems. In recent years, driver behavior …
W Ding, J Chen, S Shen - 2019 international conference on …, 2019 - ieeexplore.ieee.org
Anticipating possible behaviors of traffic participants is an essential capability of autonomous vehicles. Many behavior detection and maneuver recognition methods only …
Y Ye, X Zhang, J Sun - Transportation Research Part C: Emerging …, 2019 - Elsevier
Automated vehicles (AVs) are deemed to be the key element for the intelligent transportation system in the future. Many studies have been made to improve AVs' ability of environment …
LG Galvão, MN Huda - Expert Systems with Applications, 2023 - Elsevier
Autonomous vehicles (AV) s have become a trending topic nowadays since they have the potential to solve traffic problems, such as accidents and congestion. Although AV systems …
Innovative technologies and naturalistic driving data sources provide a great potential to develop reliable autonomous driving systems. Understanding the behaviors of surrounding …
Self-driving vehicles need to continuously analyse the driving scene, understand the behavior of other road users and predict their future trajectories in order to plan a safe …