Predicting the exact number of tours during a full day: A case study

The escalating travel demands in recent years have led to higher levels of vehicle miles traveled, resulting in adverse effects such as greenhouse gas emissions, increased traffic congestion, and increased energy consumption. To address these challenges, transportation planners and policymakers play a crucial role in controlling and managing travel patterns through trip chaining and tour-based analysis. Trip chaining involves combining multiple trips into one tour, reducing vehicle miles traveled. This study aims to estimate the impact of socioeconomic variables and some of the Daily Activity Pattern model outputs on the number of tours individuals take for seven distinct tour purposes. Utilizing data from the ۲۰۰۷-۲۰۰۸ Washington region origin-destination survey, this research employs a multinomial logit model to analyze the number of tours taken by individuals. The study explores various socio-economic factors, including person type, age group, gender, household composition, income, and accessibility logsum variables. Results indicate that accessibility variables have a substantial influence on tour frequency, suggesting that individuals residing in areas conducive to multiple tours tend to engage in more activities during the day. This study contributes to the understanding of tour-based analysis and its importance in modeling travel behavior. It emphasizes the need for comprehensive travel surveys and data collection in developing economies to inform transportation policies and address complex transportation challenges.

کلیدواژه ها:

Multinomial Logit ، Accessibility ، Tour Frequency ، Activity-Based ، Trip Chain