In order to control for censoring and the integer nature of trip demand, the use of count data models in travel cost analysis is attractive. Two such models, the Poisson and negative binomial, are discussed. Robust estimation techniques that loosen potentially stringent distributional assumptions are also reviewed. For illustrative purposes, several count data models are used to estimate a coun...

Rapid urban growth is resulting into increase in travel demand and private vehicle ownership in urban areas. In the present scenario the existing infrastructure has failed to match the demand that leads to traffic congestion, vehicular pollution and accidents. With traffic congestion augmentation on the road, delay of commuters has increased and reliability of road network has decreased. Four s...

Introducing electric vehicles (EVs) into urban transportation network brings higher requirement on travel time reliability and charging reliability. Specifically, it is believed that travel time reliability is a key factor influencing travelers' route choice. Meanwhile, due to the limited cruising range, EV drivers need to better learn about the required energy for the whole trip to make decisi...

This paper addresses the importance of travel forecasting, the general direction of emerging forecasting methods, the importance of integrating land use and transportation forecasting, and this committee’s relationship to other committees at the Transportation Research Board (TRB). In particular, the movement from trip-based to activity-pattern or activity-scheduling methods of modeling is emph...

One of the important problems studied in the area of travel behavior analysis is travel mode choice which is one of the four crucial steps in transportation demand estimation for urban planning. State of the art models in travel demand modelling can be classified as trip based; tour based; and activity based. In trip based approach, each individual trips is modelled as independent and isolated ...