Abstract
The need for travel demand models is growing worldwide. Obtaining reasonably accurate level of service (LOS) attributes of different travel modes such as travel time and cost representing the performance of transportation system is not a trivial task, especially in growing cities of developing countries. This study investigates the sensitivity of results of a travel mode choice model to different specifications of network-based LOS attributes using a mixed logit model. The study also looks at the possibilities of correcting some of the inaccuracies in network-based LOS attributes. Further, the study also explores the effects of different specifications of LOS data on implied values of time and aggregation forecasting. The findings indicate that the implied values of time are very sensitive to specification of data and model implying that utmost care must be taken if the purpose of the model is to estimate values of time. Models estimated on all specifications of LOS-data perform well in prediction, likely suggesting that the extra expense on developing a more detailed and accurate network models so as to derive more precise LOS attributes is unnecessary for impact analyses of some policies.
Highlights
The need for travel demand models is growing due to rising travel activities in response to increasing incomes and urban population in large cities in many developing countries in Asia and Africa
This study investigates the sensitivity of results of a travel mode choice model to different specifications of network-based level of service (LOS) attributes using a mixed logit model
The study in this paper examines the effects of using network LOS attributes measured at different levels of accuracy on relative magnitudes of the coefficients, a value of time implied by travel demand models, and aggregate forecasting
Summary
Detailed and accurate data relating to land use, transportation systems and their performance, and people’s travel behavior including their socioeconomic characteristics are needed to estimate the travel demand models. Such detailed data are not often collected routinely in most developing countries. Data on travel behavior and socioeconomic characteristics are obtained from travel surveys while the data relating to transportation level of service (LOS) attributes are mostly obtained from the zonal-based network models. Many rapidly growing cities in Asia and Africa usually lack appropriate network models and LOS attributes which seriously constrain modeling travel demand. Some of the errors can be known, for example, missing toll, which can be corrected later, while others are unknown and cannot be corrected
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