Attitudinal models of modal choice: The multinomial case for selected nonwork trips

Attitudinal multinomial logit models of modal choice are presented for four nonwork activities: major grocery shopping, shopping for odds and ends, shopping for personal goods and visiting friends and acquaintances. Explanatory variables are individuals' beliefs about attributes of four modal alternatives: bus, car, taxi and walking. Factor analysis is employed to identify latent dimensions of perception of the modal alternatives and to eliminate problems of multicollinearities in model estimation. Models are estimated using data obtained for a sample of residents of Buffalo, New York. Planning implications of the methodology are assessed.This author is presently Systems Planner with Applied Resource Integration, Ltd., Boston, Massachusetts.     

An activity-based assessment of the potential impacts of plug-in hybrid electric vehicles on energy and emissions using 1-day travel data

This paper assesses the potential energy profile impacts of plug-in hybrid electric vehicles and estimates gasoline and electricity demand impacts for California of their adoption. The results are based on simulations replicating vehicle usage patterns reported in 1-day activity and travel diaries based on the 2000–2001 California Statewide Household Travel Survey. Four charging scenarios are examined. We find that circuit upgrades to 240 V not only bring faster charging times but also reduce charging time differences between PHEV20 and PHEV60; home charging can potentially service 40–50% of travel distances with electric power for PHEV20 and 70–80% for PHEV60; equipping public parking spaces with charging facilities, can potentially convert 60–70% of mileage from fuel to electricity for PHEV20, and 80–90% for PHEV60; and afternoons are found to be exposed to a higher level of emissions.     

An intersection turning movement estimation procedure based on path flow estimator

Estimation of intersection turning movements is one of the key inputs required for a variety of transportation analysis, including intersection geometric design, signal timing design, traffic impact assessment, and transportation planning. Conventional approaches that use manual techniques for estimation of turning movements are insensitive to congestion. The drawbacks of the manual techniques can be amended by integrating a network traffic model with a computation procedure capable of estimating turning movements from a set of link traffic counts and intersection turning movement counts. This study proposes using the path flow estimator, originally used to estimate path flows (hence origin–destination flows), to derive not only complete link flows, but also turning movements for the whole road network given some counts at selected roads and intersections. Two case studies using actual traffic counts are used to demonstrate the proposed intersection turning movement estimation procedure. Copyright © 2010 John Wiley & Sons, Ltd.