This study develops a model of a person's day activity schedule that can be used to forecast urban travel demand. It is motivated by the notion that travel outcomes are part of an activity scheduling decision, and uses discrete choice models to address the basic modeling problem-capturing...

This final report describes an advanced traffic surveillance technique based on pattern recognition and the use of current inductive loop technology. The focus of the investigation was a study of the feasibility of using inductive loop signatures for obtaining vehicle classification information...

The focus of this project was to examine the potential travel, emissions, and consumer benefits of advanced freeway automation and travel demand management measures. The Sacramento Regional Travel Demand model (SACMET 95) was used to simulate the travel effects of travel demand management...

In this paper, we conduct an empirical comparison of travel time estimation methods based on single-loop detector data. The methods of concern are the regression method based on an intuitive stochastic model as proposed by Petty et al. in [7], and the conventional method of using an identity...

This paper develops an improved algorithm for estimating velocity from isolated loop detector data. Unlike preceding works, the algorithm is simple enough that it can be implemented using existing controller hardware. The discussion shows how the benefits of this work extend to automated tests...

This research presents a model to predict the influence of demand and capacity on the running speed of signalized arterials in Montgomery County, Maryland. The model separates the changes to link running speed due to same-direction traffic and intersection approach delay from cross traffic. It...