Browsing by Author "Schneider, Robert James"
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Item Local environment characteristics associated with walking and taking transit to shopping districts(Journal of Transport and Land Use, 2015) Schneider, Robert JamesMixed logit modeling was used to identify local environment characteristics associated with walking and taking public transit to and from shopping districts. The analysis was based on 388 intercept survey responses and local environment data from 20 San Francisco Bay Area shopping districts. This study makes methodological advances by 1) evaluating an extensive set of explanatory variables (travel time and cost, socioeconomic characteristics, attitudes, perceptions, and local environment characteristics) within the same modeling process and 2) analyzing shopping mode choice within a tour-based framework. Travel time, travel cost, and respondent socioeconomic characteristics had expected relationships with mode choice. Walking to and from shopping districts was associated with shorter trip distances (i.e., shorter travel time relative to other modes). Transit use was associated with shopping district population density and proximity to a transit station. Automobile use was discouraged by higher employment densities and smaller parking lots. The results support strategies such as developing high-density, mixed-use activity hubs; reducing surface parking; and increasing the price of on-street parking to increase walking and taking transit to shopping districts.Item Measuring transportation at a human scale: An intercept survey approach to capture pedestrian activity(Journal of Transport and Land Use, 2013) Schneider, Robert JamesPedestrian travel data are critical for measuring and analyzing sustainable transportation systems. However, traditional household travel surveys and analysis methods often ignore secondary modes, such as walking from a street parking space to a store entrance or walking from a bus stop to home. New data collection and analysis techniques are needed, especially in areas where walking is common. This paper describes an intercept survey methodology used to measure retail pharmacy customer travel to, from, and within 20 shopping districts in the San Francisco Bay Area. Of the 1003 respondents, 959 (96 percent) reported all modes of travel used from leaving home until returning home, including secondary modes. Walking was the primary travel mode on 21 percent of respondent tours, but an analysis of secondary modes found that 52 percent of tours included some walking. Pedestrian travel was particularly common within shopping districts, accounting for 65 percent of all trips within 804 meters (0.5 miles) of survey stores. Detailed walking path data from the survey showed that respondents in denser, more mixed-use shopping districts tended to walk along the main commercial street as well as other streets connecting to the core shopping area, while respondent pedestrian movements in automobile-oriented shopping districts tended to be contained within specific shopping complexes.Item Method to adjust Institute of Transportation Engineers vehicle trip-generation estimates in smart-growth areas(Journal of Transport and Land Use, 2015) Schneider, Robert James; Shafizadeh, Kevan; Handy, Susan L.This paper describes a practical method of adjusting existing Institute of Transportation Engineers (ITE) estimates to produce more accurate estimates of motor-vehicle trip-generation at developments in smart-growth areas. Two linear regression equations, one for an A.M. peak-hour adjustment and one for a P.M. peak-hour adjustment, were developed using vehicle trip counts and easily measured site and surrounding area context variables from a sample of 50 smart-growth sites in California. Many of the contextual variables that were associated with lower vehicle trip generation at the smart-growth study sites were correlated. Therefore, variables representing characteristics such as residential population density, employment density, transit service, metered on-street parking, and building setback distance from the sidewalk were combined into a single “smart-growth factor” that was used in the linear regression equations. The A.M. peak-hour and P.M. peak-hour adjustment equations are only appropriate for planning-level analysis at sites in smart-growth areas. In addition, the method is only appropriate for single land uses in several common categories, such as office, mid- to high-density residential, restaurant, and coffee/donut shop. The method uses data from California, but the methodological approach could provide a framework for adjusting ITE trip-generation estimates in smart-growth areas throughout the United States.