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, and 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. 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 roads in the United States that are navigable by a human driver.

CAVs provide the opportunity to transform the logic, operations, and performance of traffic signal control, thereby reducing congestion and increasing transportation system efficiency. The potential impacts of CAVs on vehicle miles traveled, vehicle fuel efficiency, and costs to consumers are unknown. They could substantially increase vehicle miles traveled by allowing riders to do other, productive activities while they spend time in a vehicle. Conversely, they could facilitate increased rideshare, thereby promoting greater vehicle operating efficiency.

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. In addition, the U.S. Department of Energy’s (DOE) Energy Efficient Mobility Systems (EEMS) program has investigated the energy, technology, and usage implications of vehicle connectivity and automation and identified efficient CAV solutions. For example, EEMS research demonstrated that cooperative adaptive cruise control, which allows vehicles to communicate with each other to optimize their adaptive cruise control systems, could generate significant fuel savings.

Automated Mobility Districts

An Automated Mobility District (AMD) is the implementation of CAV technology across a focused area, such as a campus for a university, medical facility, or business. AMDs are characterized by driverless, on-demand, low-speed shuttles that provide direct origin-to-destination service to either individuals or small groups. 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 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 typically 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

Green routing is a connected vehicle strategy under which drivers receive information about the most fuel-efficient route before departing for a given destination. A study using a large-scale, high-resolution dataset 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.

Traffic Signal Control

Advances in CAV technologies provide an opportunity to transform how traffic signals are controlled to reduce delay, conserve energy, and enhance safety at intersections. Currently, traffic signals use sensing and control to safely coordinate the flow of vehicles, pedestrians, bikes, and scooters, while also prioritizing safe and efficient public transportation. However, modern control systems are limited by the information provided to them from sensors.

Many traffic signals are controlled by software within signal cabinets that run simple pretimed sequences for particular times of day and days of the week. Some can respond to changes in demand, varying their timing in response to feedback from infrastructure sensors. At best, such signals only offer a partial picture of the state of traffic, leaving out details about the location and velocity of all vehicles.

Improvements are possible by pairing CAVs with more sophisticated infrastructure-based sensing that provides the location and speed of all vehicles (and possibly pedestrians, cyclists, and other moving objects) to optimize movement in intersections. DOE’s EEMS program is investigating the potential to reduce delay, conserve energy, and enhance safety with an advanced signal control network (either through vehicles or at the intersection) and control at signalized intersections in the SMART Mobility Urban Science Capstone Report.