The unavoidable travel time variability in transportation networks, resulted from the
widespread supply-side and demand-side uncertainties, makes travel time reliability (TTR) …

The new era of sharing information and “big data” has raised our expectations to make
mobility more predictable and controllable through a better utilization of data and existing …

Existing fixed-time traffic signal optimization methods mainly use traffic volumes collected by
infrastructure-based detectors (eg, loop detectors). These infrastructure-based detectors …

The incorporation of disruptive innovations into the transportation industry will inevitably
cause major upheavals in the transportation sector. However, existing research lacks …

Urban travel time information is of great importance for many levels of traffic management
and operation. This paper develops a tensor-based Bayesian probabilistic model for …

This work focuses on traffic parameters estimation based on trajectory data in an arterial
corridor with multiple signalized intersections. We develop a general framework that can …

This paper proposes a framework to combine shockwave analysis (SA) with Bayesian
Network (BN) for traffic flow parameters estimation at signalized intersections using vehicle …

With the increasing uncertainties in freight transportation, truck loans are playing a crucial
role in the stability and development of the logistics industry. A pivotal problem to truck loan …

In urban transportation network, the formation of traffic congestion is often caused by link
capacity constraints, which is often accompanied by physical queuing phenomena. This …

The decision making of travelers for route choice and departure time choice depends on the
expected travel time and its reliability. A common understanding of reliability is that it is …