Non-motorized travel modes, including bicycling and walking, have the potential for reducing environmental damage. SANDAG promotes a bicycle and pedestrian friendly environment to resolve issues, such as traffic congestion, air quality, and public health. The San Diego regional transportation plan (RTP), for the first time, identifies an active transportation (AT) network (bicycle and pedestrian network), similar to how highway and transit networks are identified.
As an enhancement to the ABM, SANDAG recently developed an active transportation model that serves as a quantitative tool for evaluating the impact of bicycle and pedestrian projects. Estimation of non-motorized impedances is an important component because its impact perpetuates throughout the modeling sequence, in both ABM and AT models. This paper, based on an empirical study, is to investigate the impact of using an all street network on model results and quality.
First, this paper describes two scenarios, before and after the AT model. In the before scenario, a coarse straight line-based calculation is used to estimate walk and bike distances. In the after scenario, a path finding procedure based on an all street network is used to estimate walk and bike distances. The path finding is a custom made procedure that maximizes a path utility function, sensitive to distances and elevation gains. We keep all other model inputs and parameters constant to isolate the impact of the impedance estimation procedures.
Second, this paper describes and compares the results from the two scenarios. More specifically, statistical analysis is conducted on number of walk accessible zones, number of walk accessible transit stops, shares of bicycle, walk, and walk to transit mode, walk and bike trip length distributions, walk to transit leg trip length distributions, and physical activity hours spent on walking, biking, and walking to transit. The analyses are conducted on both regional and sub-regional levels, focusing on urbanized areas with denser road networks.
Finally, this paper discusses the findings of the impact of using all street network in modeling non-motorized travel modes, in the context of regional long range transportation planning and how the analysis may assist policymakers in their decision making process.