Understanding how drivers behave at stop-controlled intersection is of critical importance for
the control and management of an urban traffic system. It is also a critical element of …

Driving behavior is considered as a unique driving habit of each driver and has a significant
impact on road safety. This study proposed a novel data-driven Machine Learning …

This report describes an experimental investigation performed at live intersections to gather
infrastructure-based naturalistic driver approach behavior data. This data was collected and …

In the contemporary era, modern public buses are equipped with multiple built-in cameras,
offering real-time or recorded monitoring capabilities through centralized systems. This …

Safely passing through unsignalized intersections (USI) in urban area is challenging for
autonomous vehicles due to high uncertainties of surrounding engaged human-driven …

Movement-specific vehicle classification and counting at traffic intersections is a crucial
component of various traffic management activities. In this context, with recent …

Introduction: Although stop signs are popular in North America, they have become
controversial in cities like Montreal, Canada where they are often installed to reduce …

A methodology for assessing crash risk using vehicle driving trajectories based on data
mining techniques was developed in this study. A variety of safety indicators reflecting the …

The advent of autonomous driving technology offers transformative potential in mitigating
traffic congestion and enhancing road safety. A particularly challenging aspect of traffic …

Semantic understanding of multi-vehicle interaction patterns at intersections play a pivotal
role in proper decision-making of autonomous vehicles. This paper presents a flexible …