Autonomous vehicles (AVs) have now drawn significant attentions in academic and
industrial research because of various advantages such as safety improvement, lower …

In this paper the various driving style analysis solutions are investigated. An in-depth
investigation is performed to identify the relevant machine learning and artificial intelligence …

Driver behavior monitoring system as Intelligent Transportation Systems (ITS) have been
widely exploited to reduce the traffic accidents risk. Most previous methods for monitoring …

Accurately discovering hazards and issuing appropriate warnings to drivers in advance or
performing autonomous control is the core of the Collision Avoidance (CA) system used to …

Poor driving habits such as not using turn signals when changing lanes present a major
challenge to advanced driver assistance systems that rely on turn signals. To address this …

Autonomous vehicles have to share the road with human-driven ones for a prolonged period
in the near future. Thus, they should have the ability to understand the lane changing …

In complex lane change (LC) scenarios, semantic interpretation and safety analysis of
dynamic interaction pattern are necessary for autonomous vehicles to make appropriate …

Modelling, predicting and analysing driver behaviours are essential to advanced driver
assistance systems (ADAS) and the comprehensive understanding of complex driving …

Accurately predicting and inferring a driver's decision to brake is critical for designing
warning systems and avoiding collisions. In this paper, we focus on predicting a driver's …

In a mixed-traffic scenario where both autonomous vehicles and human-driving vehicles
exist, a timely prediction of driving intentions of nearby human-driving vehicles is essential …