Risk measures are often used by decision makers (DMs) as a scalar risk characterization by integrating the statistical characteristics of risk as well as the DMs’ risk strategy towards uncertainty. A good risk measure typically needs to have a risk preference control mechanism, a complete...

Travel demand forecasting is subject to great uncertainties. A systematic uncertainty analysis can provide insights into the level of confidence on the model outputs, and also identify critical sources of uncertainty for enhancing the robustness of the travel demand model. In this paper, we...

Paradox in the transportation literature is about improving an existing link or adding a new link can actually increase network-wide travel costs or travel costs of each traveler. In this paper, we investigate the stochastic assignment paradox using the multinomial weibit (MNW) model, a new...

This paper proposes an alternate formulation for the combined distribution and assignment (CDA) problem, which seeks to determine consistent level-of-service and flow values of the trip distribution and traffic assignment steps. The CDA problem is modeled as a hierarchical travel choice problem...

This study provides an unconstrained minimization program as an alternative formulation for the multinomial weibit (MNW) stochastic user equilibrium (SUE) model that explicitly considers the heterogeneous perception variances with respect to different trip lengths under congested conditions....

Travel time, travel time reliability and monetary cost have been empirically identified as the most important criteria influencing route choice behaviour. We concentrate on travel time and travel time reliability and review two prominent user equilibrium models incorporating these two factors....

In this paper, we extend the α-reliable mean-excess traffic equilibrium (METE) model of Chen and Zhou (Transportation Research Part B 44(4), 2010, 493–513) by explicitly modeling the stochastic perception errors within the travelers’ route choice decision processes. In the METE model, each...

This paper proposes a generalized model to estimate the peak hour origin–destination (OD) traffic demand variation from day-to-day hourly traffic counts throughout the whole year. Different from the conventional OD estimation methods, the proposed modeling approach aims to estimate not only...

The uncertainty of an origin–destination (O–D) trip table estimate is affected by two factors: (i) the multiplicity of solutions due to the underspecified nature of the problem, and (ii) the errors of traffic counts. In this paper, a confidence interval estimation procedure for path flow...

Path flow estimator (PFE) is a one-stage network observer proposed to estimate path flows and hence origin-destination (O-D) flows from traffic counts in a transportation network. Although PFE does not require traffic counts to be collected on all network links when inferring unmeasured traffic...