To reduce life threats and financial losses under hurricane weather and traffic conditions,
stakeholders need to make a sequence of decisions (eg, enforcing traffic control and/or …

While much research has been devoted to analyzing the variation in transportation and land
use model outputs due to uncertainty, little has been done to quantitatively answer the more …

By far the most popular method to account for dependencies in the transportation network
analysis literature is the use of the multivariate normal (MVN) distribution. While in certain …

Several studies have observed an optimistic bias in cost and ridership forecasts for rail
transit projects around the globe, which has led to billions of dollars of public investment in …

The increased participation of the private sector in the delivery of transport infrastructure
projects has increased the emphasis on understanding the accuracy and uncertainty of …

Accurate data are essential for the development of robust and valid travel demand models to
support the planning activities of metropolitan planning organizations (MPOs). The Travel …

A strategic task assigned to large-scale transport models is to forecast the demand for
transport over long periods of time to assess transport projects. However, by modelling …

Sažetak Anticipating uncertainty in short-term traffic flow is crucial for effective traffic
management within intelligent transportation systems. Various methods for predicting …

To better plan and schedule public transportation resources, it is crucial to understand the
travel demand from any location at any time. In this article, we focus on analyzing the …

Budget constraints and competing opportunities demand thoughtful evaluation of projects
before investment. Significant uncertainty surrounds travel choices, demographic futures …