In this paper, we present a comprehensive, in-depth survey of the literature on reinforcement
learning approaches to decision optimization problems in a typical ridesharing system …

Transportation is the backbone of the economy and urban development. Improving the
efficiency, sustainability, resilience, and intelligence of transportation systems is critical and …

Reducing traffic delay is of crucial importance for the development of sustainable
transportation systems, which is a challenging task in the studies of stochastic shortest path …

This paper aims to develop a paradigm that models the learning behavior of intelligent
agents (including but not limited to autonomous vehicles, connected and automated …

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 …

Travel information has the potential to influence travellers choices, in order to steer travellers
to less congested routes and alleviate congestion. This paper investigates, on the one hand …

Road congestion induces significant costs across the world, and road network disturbances,
such as traffic accidents, can cause highly congested traffic patterns. If a planner had control …

Trip information and navigation systems are expected to become key components of future
traffic management strategies, which, if properly exploited, may contribute to the mitigation of …

Route choice models are a vital tool for evaluating the impact of transportation policies and
infrastructure improvements, such as the addition of new roads, tolls, or congestion charges …

Real-time information (RTI) is defined as any up-to-date information collected which is
immediately made available for the users. RTI is often used in transportation such as …