To reduce the false detection rate of vehicle targets caused by occlusion, an improved
method of vehicle detection in different traffic scenarios based on an improved YOLO v5 …

This paper explores deep learning (DL) methods that are used or have the potential to be
used for traffic video analysis, emphasising driving safety for both autonomous vehicles and …

Transportation safety studies have been mostly focused on using crash data that are rare
events. Alternatively, conflict estimation can be used to assess safety. This has been proven …

The primary objective of this study is to investigate the relationship between field-measured
conflicts and simulated conflicts estimated from the surrogate safety assessment model …

This paper proposes a new framework to evaluate pedestrian safety at non-signalized
crosswalk locations. In the proposed framework, the yielding maneuver of a driver in …

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

This study aims to propose a new algorithm to evaluate the rear-end collision risk under fog
conditions considering reduced visibility. The proposed algorithm compares the safe …

Proactive safety management has gained increasing attention for its potential to mitigate
crash risk. This study aims to leverage massive vehicle trajectory data for proactive safety …

Surrogate measures of safety (SMoS) aims at road safety evaluation without depending on
historical crash data. Existing studies have evaluated SMoS in traffic conditions having good …

This work contributes to study the application of extreme value theory (EVT) in road safety
analysis, estimating the risk of being involved in an entering–circulating collision in single …