Estimation of the origin-destination trip demand matrix (O-D) plays a key role in travel analysis and transportation planning and operations. Many researchers have developed different O-D matrix estimation methods using traffic counts, which allow simple data collection as opposed to the costly traditional direct estimation methods based on home and roadside interviews. In this paper, a new fuz...

The path choice behavior of battery electric vehicle (BEV) drivers is influenced by the lack of public charging stations, limited battery capacity, range anxiety and long battery charging time. This paper investigates the congestion/flow pattern captured by stochastic user equilibrium (SUE) traffic assignment problem in transportation networks with BEVs, where the BEV paths are restricted by th...

In order to make measurement-based placement, an optimiser must make informed decisions. Currently, it is difficult to assign routes or assign resource commitments to network paths in data centers, as applications do not declare what is carried within each flow. We propose to provide insight into the traffic that traverses each network link, realizing a near real-time map of a data center’s net...

In survivable WDM optical networks, one of the critical issues is route computation. Although there is a possibility to optimize the route computation (together with the wavelength assignment) for static traffic pattern, it is impossible to perform such optimization for incremental and dynamic traffic. The conventional approach first computes the working path and then computes an edge-disjoint ...

There is a growing recognition that discrete choice models are capable of providing a more realistic picture of route choice behavior. In particular, influential factors other than travel time that are found to affect the choice of route trigger the application of random utility models in the route choice literature. This paper focuses on path-based, logit-type stochastic route choice models, i...