Connected Automated Vehicle Highway System (Gen 1)

The Connected and Automated Vehicle Highway (CAVH) system is an automated driving system that utilizes both the automated vehicle and intelligent roadside infrastructure to efficiently achieve high levels of automated driving. The CAVH system (vehicles, infrastructures) performs sensing, prediction, decision-making, and control efficiently and cooperatively to form a new generation of ITS. The CAVH approach emphasizes the automation of road infrastructure and transportation system integration. The CAVH approach aims to cover all the major elements of transportation systems in a multidimensional perspective. Figure1 shows a three-dimension view of it: Connectivity, Vehicle Automation, and System Integration.

The three dimensions in Figure 1 can be defined using different levels, similar to the SAE vehicle automation levels:

  • Vehicle automation. This dimension represents the intelligence of vehicles, and levels are from the SAE vehicle automation level definitions;
  • Connectivity. The dimension of connectivity is to present information flows, measured in terms of volume and content. Specifically, five levels are defined:
    • C0: No connectivity. Both vehicles and travelers do not have access to any traffic information;
    • C1: Information assistance. Vehicles and travelers can only access aggregated traffic information of certain accuracy, resolution, and noticeable delays, such as average traffic speed at the downstream traffic detection station five minutes ago;
    • C2: Limited connected sensing. Vehicles and travelers can access live traffic information of high accuracy and unnoticeable delay, through connection with roadside units, other vehicles, and other information providers. However, the information may not be complete;
    • C3: Redundant information sharing. Vehicles and travelers are provided with information of adequate accuracy and almost in real time from multiple sources. The information available is complete but redundant with different formats due to the various sources;
    • C4: Optimized connectivity. Information from various sources is integrated, completed, and unified before provided to vehicles and travelers.
  • Transportation System Integration. This dimension represents the scale of system coordination and optimization. Specifically, six levels are defined:
    • S0: No integration. There is no traffic control and management measures for coordination or optimization, such as pre-timed traffic signals.
    • S1: Key point system integration. Traffic control measures are covering a small area such as actualized signals at intersections and ramp metering, and those measures are only for the major travel mode, such as passenger cars;
    • S2: Segment system integration. The measures are extended to a short road segment such as a freeway segment between two ramp access points, and for most of the travel modes, such as passenger cars and buses;
    • S3: Corridor system integration. The measures are extended to a corridor with connecting roads and ramps, and for all coexisting traffic modes, such as integrated corridor management;
    • S4: Regional system integration. The scale of coordination and optimization now covers a city or urban area for both normal conditions and under emergency or incident; and
    • S5: Macroscopic system integration. The scale of coordination and optimization now covers several regions and inter-regional traffic.

The CAVH system aims to redistribute the driving task and utilized both the automated vehicle and intelligent roadside infrastructure instead of relying solely on vehicles’ capabilities. Here we define all roadside units and traffic control/management centers as an Intelligent Road Infrastructure System (IRIS), which is a subsystem under CAVH. Under our CAVH system, the IRIS Subsystem and Vehicle Subsystem jointly cover all the driving tasks. Figure 2 shows an exemplary distribution of driving tasks of CAVH. The two subsystems both have sensing and telecommunication capabilities to facilitate those driving tasks, and the two subsystems are highly integrated to work together through the two types of capabilities. The integration and collaboration of the vehicle and IRIS subsystems also provide redundant backup for each other, which increases the overall safety and reliability.

One way to look at the CAVH approach is through the analogy of a client-server relationship, with vehicles as the clients and infrastructure as the server. The vehicle-based approach aims at developing super smart vehicles with limited consideration and requirements for the road infrastructure and other transportation system components. In other words, the vehicle-based approach is designed to be a fat client–thin server mode. The CAVH approach, however, can facilitate the thin client–fat server mode, as shown in Figure 3, in which the vehicles receive and follow detailed instructions from the IRIS, similar to a railway system.

To realize this thin client–fat server mode, a well-instrumented infrastructure would be needed. One design is shown in Figure 4

Figure 3. CAVH server-client model

, in which: 1) roadside units (RSUs) are deployed on the roadside to monitor the vehicles and communicate with them, and 2) traffic control units (TCUs) and traffic control centers (TCCs) do the heavy lifting to generate real-time instructions for vehicles.

Figure 4. CAVH managing a corridor