Numerical Investigation of Sloshing Under Roll Excitation at Shallow Liquid Depths and the Effect of Baffles

Sloshing is relevant in several applications like ship tanks, space and automotive industry and seiching in harbours. Due to the relationship between ship and s...     

Behavioral modeling of on-demand mobility services: general framework and application to sustainable travel incentives

Transportation - This paper presents a systematic way of understanding and modeling traveler behavior in response to on-demand mobility services. We explicitly consider the sequential and yet...     

Integrated population synthesis and workplace assignment using an efficient optimization-based person-household matching method

Transportation - Large scale activity-based simulation models inform a variety of transportation and planning policies using models that often rely on fixed or flexible workplace location in a...     

Non-commitment bias in public opinion on transit usage

Estimation of ridership on a new transit system in an area where no comparable service existed before is a difficult task of transit planning. Traditional modal split models cannot be used in these cases, because no data or basis for developing a new model or adjusting a “borrowed” model are available. One of the techniques which can be used in this type of situation, is to perform a “concept test” based on public opinion. This approach, however, is plagued with the phenomenon of non-commitment bias of interviewees, and tends to overestimate the ridership. A new fixed route and fixed schedule transit service in Johnson City in Tennessee provided a rare opportunity to perform an investigation on the non-commitment bias through “before” and “after” surveys. The analysis of the non-commitment and actual responses of a sample of residents revealed substantial bias. Overall, the non-commitment ridership estimate was about twice (100% greater than) the actual ridership.:It was also observed that the bias was higher for persons owning automobiles, and for work and shopping trips.     

A structural equations analysis of commuters' activity and travel patterns

An exploratory analysis of commuters' activity and travel patterns was carried out using activity-based travel survey data collected in the Washington, DC metropolitan area to investigate and estimate relationships among socio-demographics, activity participation, and travel behavior. Structural equations modeling methodology was adopted to determine the structural relationships among commuters' demographics, activity patterns, trip generation, and trip chaining information. Three types of structural equations model systems were estimated: one that models relationships between travel and activity participation, another that captures trade-offs between in-home and out-of-home activity durations, and a third that models the generation of complex work trip chains. The model estimation results show that strong relationships do exist among commuters' socio-demographic characteristics, activity engagement information, and travel behavior. The finding that significant trade-offs exist between in-home and out-of-home activity participation is noteworthy in the context of in-home vs. out-of-home substitution effects. Virtually all of the results obtained in this paper corroborate earlier findings reported in the literature regarding relationships among time use, activity participation, and travel. This revised version was published online in June 2006 with corrections to the Cover Date.