Coordinated small changes in individual travel behavior (such as route choice, departure time, and travel mode) have the potential to produce significant reductions in regional transportation energy use. The Tripod (Travel Incentives with Prediction, Optimization and Personalization) project aims to design, test, and optimize a decentralized mobility market and information system to influence travelers’ behavior and nudge it towards system-optimized energy, emissions and mobility performance. This project comprises a control architecture and a system model. The control architecture combines sensing, modeling, prediction and control methodologies that implement our vision of a mobility market and related services. This steers the system towards an optimum in two ways: it provides users with more concrete information on the time and monetary costs of their travel decisions, and it creates an incentive scheme to better align users’ individual goals with the system optimum. The system model is our laboratory, representing the real world for the purposes of development and testing, ultimately towards actual deployment. The base for this model is an integrated agent-based activity-based travel demand model linked to an energy estimation model. This combined system model will have the capability to dynamically calculate the energy used by each traveler at any given time as changes occur in travelers’ choices and in the network.
TripEnergy : The TripEnergy tool developed by the Trancik Lab provides the energy estimates used to optimize traveler rewards in the control architecture as well as well as to establish baseline energy consumption and evaluate Tripod’s performance in the system model. TripEnergy works by using a database of high resolution GPS vehicle trajectories to probabilistically link simulated driving patterns to realistic ones observed in the real world. It captures impact on energy consumption of different driving styles, traffic conditions, and weather patterns on a large number of vehicles, including alternative powertrain types such as hybrid- and battery-electric vehicles.
- McNerney J, Needell Z, Chang MT, Miotti M, Trancik JE, TripEnergy: Estimating personal vehicle energy consumption given limited travel survey data, Transportation Research Record: Journal of the Transportation Research Board, forthcoming.