Connected vehicles (CVs), be they autonomous vehicles or a fleet of cargo carriers or Uber,
are a matter of when they become a reality and not if. It is not unreasonable to think that CV …

In this paper, the Bush–Mosteller (BM) reinforcement learning (RL) scheme is introduced to
model the route choice behaviors of the travelers in traffic networks, who aim to seek the …

A critical issue of constrained optimization evolutionary algorithms (COEAs) is how to
balance the minimization of the objective function and the reduction of the constraint …

Static traffic assignment models are still widely applied for strategic transport planning
purposes in spite of the fact that such models produce implausible traffic flows that exceed …

Genetic algorithm is a heuristic population-based search method that incorporates three
primary operators: crossover, mutation and selection. Selection operator plays a crucial role …

A link-based elastic demand equilibrium model with explicit link-exit capacities and explicit
bottleneck or queuing delays is specified. The model, which is at the borderline between …

A major objective of the practical implemented cordon-based congestion pricing schemes is
to maintain the traffic conditions within the cordon area, which is rarely considered in most of …

Recent studies show that energy consumption of battery electric vehicles (BEVs) increases
in traffic congestion. Therefore, it is important to consider the effect of link flow on BEV …

Congestion pricing is seen as an effective policy to address traffic congestion. In such
policies where money, people and authorities are involved, the success generally hinges …

In the literature, networks are usually assumed to operate at their steady states in static traffic
assignment models. Given a set of demand management and supply regulation strategies …