Abstract:It is widely recognized that new vehicle and fuel technologies are necessary but not sufficient to meet deep greenhouse gas reduction goals in the United States. Demand management strategies, such as land use, transit, and auto pricing policies, are also needed. These measures, however, have historically faced political challenges and have been difficult to implement. Emerging ridesharing systems now suggest the possibility of a new demand management strategy that may be more politically palatable and reduce the number of vehicle miles traveled (VMT). To date, however, little research has evaluated their potential travel effects, especially on a regional scale. This study used the San Francisco, California, Bay Area activity-based travel demand model to simulate business-as-usual, transit-oriented development, and auto pricing scenarios with and without high, medium, and low ridesharing participation levels. The analysis suggests that relatively large VMT reductions are possible from moderate and high participation levels, but at low participation levels, VMT reductions are negligible. Moderate dynamic ridesharing alone compares favorably, with a 9% reduction in VMT, to transit-oriented development and auto pricing scenarios. The analysis also suggests a potentially promising policy combination: a moderately used regional dynamic ridesharing system with a 10- to 30-cent increase in the per mile cost of auto travel, which together may reduce VMT on the order of 11% to 19%.