Active Transportation Demand Management (ATDM) aims to influence people’s travel behavior. Over the past few decades, a variety of traditional TDM programs have been implemented, such as flexible work hours, teleworking, vanpooling, ridesharing, transit, etc., with limited impact on travel mode shift from driving alone. A more drastic type of TDM strategy receiving increasing attention is value pricing, which aims to influence travelers’ behavior by imposing additional monetary charges during peak travel periods. On the other hand, a “carrot” approach using a combination of positive incentives or reward programs has shown to be an effective strategy to trigger and anchor behavior change in the areas of energy use and health. Currently there is no effective incentive program to help auto drivers - accounting for 85% of Vehicle Miles Traveled (VMT) for most metro areas - to make a smarter travel decisions to benefit themselves and the entire system as a whole.
A new ADM strategy aiming to influence and incentivize auto drivers’ departure times and route choices has been developed for several cities such as Austin, Tucson, New York City and Los Angeles. This strategy utilizes advanced algorithms and coordinating technology to determine which departure times and routes have available capacity, while offering drivers varying levels of incentives for using less congested departure times and routes. Based on past demonstration projects, travel time savings by drivers ranged from 10% to 40%, with the highest savings occurring when program participants changed both their departure time and route. In addition to traveler information, the crowd sourced data provided by the users creates new opportunities to enhance planning and analysis activities undertaken by various agencies such as:
-Origin-Destination travel patterns analysis
-Corridor travel times
-Activity history and patterns
-Reliability monitoring programs and measures
-User Based Insurance Programs
The presentation will highlight results from a recent pilot study and the potential applications pertaining to the data collected via the ADM platform.