Traveler Response Architecture using Novel Signaling for Network Efficiency in Transportation
The projects in ARPA-E’s Traveler Response Architecture using Novel Signaling for Network Efficiency in Transportation (TRANSNET) program aim to minimize energy consumption in personal transportation, without having to improve current infrastructure or vehicle efficiency. TRANSNET project teams are developing new network control architectures, coupled with incentive strategies, to encourage individual travelers to take specific energy-relevant actions. These actions could, for example, contribute to reductions in miles traveled and increased occupancy rates for all modes. Project teams will design two interacting computer models: a system model that dynamically simulates the entire transportation network, including roadways, public transit, and other modes of travel, and calculates energy use at an individual level; and a control architecture, which quantifies the impacts of incentives and signals on real-time energy reductions. Operating together, these modules will measure changes to energy use in response to controls. If successful, these systems will allow the optimization of control strategies, which could increase the efficiency in a transportation network.
Annually, more than 25% of all the energy consumed in the U.S. is used in transportation, and this energy is derived substantially from imports and contributes to harmful energy emissions. In personal transportation, energy is not used as efficiently as possible due to idling in traffic, the predominance of single-occupancy vehicles, and variability in personal driving styles. To date, efforts to improve transportation efficiency have focused on vehicle characteristics and expanding use and availability of public transit. Historically, such improvements have required significant time and financial investment in new infrastructure. However, even with such large investments, travelers may perceive the quality of service to be lower and thus not choose alternate transportation options. Network optimization approaches, combined with personalized incentives, that employ sensors and communication networks to acquire, interpret, and share data might be used to signal and guide individual travelers to improve the energy efficiency of the transportation system. The tools needed to implement this mechanism are already present: low-cost, mobile sensors in vehicles and cell phones are commonplace and could be purposed to measure energy use, and wireless communications already facilitate sharing of this data, as well as information about traffic, mass transit schedules, and changes to transportation networks, such as lane closures. Yet, mechanisms that predict and influence travel routes are generally impersonal, designed to meet a generic traveler’s needs and preferences. Further, collecting or inferring data on energy use at the level of the individual traveler is technically challenging. An ideal solution must overcome these limitations to data measurement, accuracy, interpretation, and integration, as well as provide incentives to travelers to tackle the inherent challenge of selecting more energy-efficient options for their travel needs.
If successful, innovations developed through the TRANSNET program could be utilized by regional planners, transportation providers, and individual travelers to improve the energy efficiency and quality of service in personal transportation networks.
Network technologies can facilitate energy conservation in transportation and reduce demand for imported oil.
More efficient transportation networks will result in improved air quality in urban areas and lower greenhouse gas emissions.
TRANSNET projects can reduce congestion, which will help individual drivers save time and fuel and improve the overall productivity within a regional transportation network.
• Massachusetts Institute of Technology (MIT) - Sustainable Travel Incentives with Prediction, Optimization and Personalization (TRIPOD)
• National Renewable Energy Laboratory (NREL) - The Connected Traveler: A Framework to Reduce Energy Use in Transportation
• Palo Alto Research Center (PARC) - Collaborative Optimization and Planning for Transportation Energy Reduction (COPTER)
• University of Maryland (UMD) - Traveler Information and Incentive Technology