Autonomous vehicles currently suffer from a time-inefficient driving style caused by
uncertainty about human behavior in traffic interactions. Accurate and reliable prediction …

Gap acceptance analysis is crucial for determining capacity and delay at uncontrolled
intersections. The probability of a driver accepting an adequate gap changes over time, and …

This paper proposes a reinforcement learning-based framework for mandatory lane
changing of automated vehicles in a non-cooperative environment. The objective is to create …

To better prepare and guide both intersection planning and operations under different
market penetration rates (MPRs) of connected and autonomous vehicles (CAVs) and traffic …

Motion prediction for intelligent vehicles typically focuses on estimating the most probable
future evolutions of a traffic scenario. Estimating the gap acceptance, ie, whether a vehicle …

The efficiency of the entire transportation system depends on the capacity of the individual
elements that make up the given network. Point-type elements of the road and street network …

Autonomous vehicles currently suffer from a time-inefficient driving style caused by
uncertainty about human behavior in traffic interactions. Accurate and reliable prediction …

Uncontrolled intersections are the most common type of intersections in a transportation
network. The study modeled minor road driver's decision of accepting or rejecting a gap at …

This study calibrated the HCM roundabout capacity models to incorporate local Louisiana
driver behavior at single-lane roundabouts, using gap acceptance parameters measured …

In light of the traffic congestion and traffic environment problems around schools that are
caused by students commuting by car, this paper explores an efficient and feasible student …