The performance and complicated interactions of different classes of travelers on regional
urban networks are presented and analyzed. A new multi-class extension of a regional …

Transportation networks are inherently uncertain due to random disruptions; meanwhile,
real-time information potentially helps travelers adapt to realized traffic conditions and make …

In this paper a new robust optimization (RO) model is proposed for route guidance based on
the advanced traveler information system. The arc travel time is treated as a random …

The roles of learning, inertia and real-time travel information on route choices in a highly
disrupted network are investigated, based on data from a laboratory competitive route …

The purpose of this study is to establish a quantitative relationship between network
congestion and travel-time reduction benefits of a real-time route guidance user service. The …

By providing tripmakers with information about travel options and so allowing them to make
better travel decisions, Advanced Traveler Information Systems (ATIS) promise to enhance …

Intelligent vehicle technologies are opening new possibilities for decentralized vehicle
routing systems, suitable for regulating large traffic networks, and at the same time, capable …

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 …

Routing strategies under the aegis of dynamic traffic assignment have been proposed in the
literature to optimize system performance. However, challenges have persisted in their …

Abstract We propose a Recursive Logit (STD-RL) model for routing policy choice in a
stochastic time-dependent (STD) network, where a routing policy is a mapping from states to …