Developing smart cities is vital for ensuring sustainable development and improving human
well-being. One critical aspect of building smart cities is designing intelligent methods to …

Traffic management by applying congestion pricing is a measure for mitigating congestion in
protected city corridors. As a promising tool, pricing improves the level of service in a …

A learning optimization is proposed to enhance overall resilience of interdependent traffic
systems with hazardous materials (hazmat) transportation under uncertainty. To this end …

Modern urban centers have one of the most critical challenges of congestion. Traditional
electronic toll collection systems attempt to mitigate this issue through pre-defined static …

A knowledge-assisted reinforcement learning evolution optimization (KARLEO) is presented
for a road network under uncertain demand and capacity. In order to hedge against …

This study examines the potential of an iterative and interactive approach to learn network
traffic dynamics and optimise tolling strategies considering time-varying stochastic traffic. A …

Express lanes (ELs) implementation is a proven strategy to deal with freeway traffic
congestion. Dynamic toll pricing schemes effectively achieve reliable travel time on ELs. The …

This study formulates the joint decisions of commuters on departure time and parking
location choices in a morning commute problem where the commuters travel with …

Congestion pricing is one of the efficient travel demand management strategies. Many
existing researches focus on dealing with the toll optimization problem for a single area …

Objective This research investigates the problem of dynamic pricing in rail transportation
systems using advanced deep reinforcement learning techniques. The main goal is to …