Influence of Demand Uncertainty and Correlations on Traffic Predictions and Decisions

Abstract

Decisions to improve a regional transportation network are often based on predictions of future link flows that assume future travel demand is a deterministic matrix. Despite broad awareness of the uncertainties inherent in forecasts, rarely are uncertainties considered explicitly within the methodological framework due at least in part to a lack of knowledge as to how uncertainties affect the optimality of decisions. This article seeks to address this issue by presenting a new method for evaluating future travel demand uncertainty and finding an efficient technique for generating multiple realizations of demand. The proposed method employs Hypersphere Decomposition, Cholesky Decomposition, and user equilibrium traffic assignment. Numerical results suggest that neglecting correlations between the future demands of travel zone pairs can lead to improvement decisions that are less robust and could frequently rank improvements improperly. Of the six sampling techniques employed, Antithetic sampling generated travel demand realizations with the least relative bias and error.

Consistent formulation of network equilibrium with stochastic flows

“…Furthermore, we assumed independent drivers, and hence independent demand, but as the work of Duthie et al (2011) implies, neglecting the correlation among demands may lead to a mis-estimation. Considering correlated demands and identifying the demand distributions from the actual day-to-day data are therefore also important areas for future work.…”

Robust Optimization Strategy for the Shortest Path Problem under Uncertain Link Travel Cost Distribution

“…Duthie et al (), Ng and Waller (), and Papola and Marzano () focus on traveler perception of uncertain capacity and costs respectively in network assignment models. Minimizing risk associated with travel cost and incorporating the reliability measures have been studied in the context of hazardous materials transportation (Kang et al., 2014a, b; Xie and Waller, ).…”

A network traffic assignment model for autonomous vehicles with parking choices

“…One methodological approach through which the network traffic pattern can be examined is the traffic assignment under the user equilibrium (UE) principle, which is also recognized as the network equilibrium. In the area of traffic assignment, the notion of UE was initially proposed by Wardrop (), followed by intensive research efforts in transport network modeling (Ban, Liu, Lu, & Ferris, ; Bar‐Gera, ; Duthie, Unnikrishnan, & Waller, ; Evans, ; Friesz, ; Ferguson, Duthie, & Waller, ; Hamdouch, Marcotte, & Nguyen, ; Jiang, Xie, & Waller, ; Meng, Liu, & Wang, ; Patriksson, ; Unnikrishnan, Valsaraj, Damnjanovic, & Waller, ; Xie, Wu, & Boyles, ; Yang, Ban, & Ma, ; Zhang & Waller, ). The Wardropian UE principle holds the selfish route‐choice assumption, which states that every traveler minimizes his or her own travel cost, and no one can further reduce the individual cost by unilaterally changing their routes at equilibrium.…”