Methodology to Gather Multimodal Trip Generation Data in Smart-Growth Areas

Abstract

This study presents a method to quantify multimodal trip generation for developments in smart-growth areas. The technique combines door counts and intercept surveys to classify trips by mode, and it has several advantages over existing methods that use automated technologies to count automobiles entering and exiting access points to developments. These advantages are particularly important in urban areas with mixed-use developments, mixed-use buildings, and a variety of parking arrangements. First, door counts quantify the total number of trips generated by all modes. Second, door counts quantify all people traveling to and from particular land uses, even if a targeted use is part of a larger, mixed-use building. Third, intercept surveys differentiate between people who are walking for an entire trip and people who are walking as a secondary mode to or from parking or transit. The method was applied at 30 smart-growth study locations in California. Multimodal person trips and vehicle trips were documented at 24 of the study locations during the morning peak hour and at 27 study locations during the afternoon peak hour. Weighted averages from these locations show that suburban-based ITE peak hour vehicle trip estimates were 2.3 times higher than actual vehicle trips in the morning and 2.4 times higher than those in the afternoon. Total person trip generation at the smart-growth study locations was similar to the total person trips estimated from ITE data; however, larger shares of person trips at the smart-growth locations were made by walking, bicycling, or public transit.