Human factors are a primary cause of vehicle accidents. Driver monitoring systems, utilizing
a range of sensors and techniques, offer an effective method to monitor and alert drivers to …

Pedestrians are a vulnerable road user group, and their crashes are generally spread
across the network rather than in a concentrated location. As such, understanding and …

Safety decisions for vehicles at an intersection rely on real-time, objective and continuous
assessment of risks in vehicle–pedestrian interactions. Existing surrogate safety models …

Facilitating proactive pedestrian safety management, the application of extreme value theory
(EVT) models has gained popularity due to its extrapolation capabilities of estimating …

Vehicle-pedestrian crashes are generally severe due to the vulnerability of pedestrians
compared to the occupants of vehicles. However, the estimation of pedestrian crash risk by …

Intersections are among the most hazardous roadway spaces due to the complex and
conflicting road users' movements. Spatio-temporal modeling of conflict risks among road …

Sample size plays a critical role in an Extreme Value Theory (EVT) model for estimating
crash risks from traffic conflicts. Many studies have raised concerns regarding sample size …

Crash risk measures (CRMs) are widely used in safety analysis to complement crash
reports. However, none of the existing CRMs are specifically developed for modeling the risk …

The combined contributions to mountain freeway safety of pavement performance, weather
conditions, and traffic condition indicators have not been thoroughly investigated due to the …

Accurately identifying the risk of traffic accidents in real time for specific road sections is
crucial for implementing proactive traffic control strategies. The existing studies have …