Intelligent Transportation System Technologies
New technologies at the driver-, vehicle-, and transportation system-level are attracting more research attention for their potential to improve the energy efficiency and environmental impact of current transportation systems. These intelligent transportation system technologies are enabled by connectivity, including vehicle-to-vehicle and vehicle-to-infrastructure communication and by the mobile devices that most travelers carry in their pockets.
Connected and Automated Vehicles (CAVs)
Connected vehicle technology enables vehicles, roads, and other infrastructure, as well as smartphones to communicate and share vital transportation information through advanced wireless communication technology. Connected vehicles could dramatically reduce the number of fatalities and serious injuries caused by accidents on our roads and highways. The U.S. Department of Transportation is collaborating with public and private partners, including state and local governments, vehicle and device manufacturers, and academia, to advance connected vehicle development and implementation. Automated vehicle technologies use hardware and software to perform some or all driving tasks on a sustained basis. SAE International has defined six levels of driving automation, ranging from no driving automation (level 0) to full driving automation (level 5). With level 5 automation, a vehicle can operate on all mapped roads in the United States that are navigable by a human driver. CAVs may have a range of potential effects on vehicle miles traveled, vehicle fuel efficiency, and costs to consumers.
Automated Mobility Districts
An Automated Mobility District (AMD) is a campus-scale implementation of automated/connected vehicle technology. AMDs are characterized by driverless, on-demand transit that provides direct origin-to-destination service to either individuals or small groups within a set boundary such as a college campus or business park. Personal vehicles may or may not be prohibited, but the area is designed to be most efficiently accessed using the automated mobility services provided. An AMD has the potential to reduce total system fuel consumption, but the amount is largely dependent on operating and ridership assumptions.
Transportation on Demand
While transportation network companies (TNCs) like Uber and Lyft provide a for-hire transportation mode like taxis, their on-demand service with real-time observability through map-based monitoring and mobile phone-friendly payment methods are priced lower than traditional taxi services. The emerging impacts of ride-hailing, including impacts upon congestion and parking revenues, have become an increased area of city attention and research. The rise of ride-hailing has implications for transportation, energy use, parking revenues, and future infrastructure.
Green routing is a connected vehicle strategy under which drivers receive information about the most fuel-efficient route before departing for a given destination. Routing applications such as Google Maps Directions provide route options for any origin/destination pair by considering typical real-world traffic conditions. The API routes are conveniently obtained, and the routes are reliable due to the commercial maturity of the technology and its supporting high-quality road network and real-time traffic data. A study using a large-scale, high-resolution data set from the California Household Travel Survey indicates that 31% of actual routes have fuel savings potential, and among these routes the cumulative fuel savings could reach 12%. The Connected Traveler project is designed to boost the energy efficiency of personal trips and the overall transportation system by maximizing the accuracy of predicted traveler behavior in response to real-time feedback and incentives.