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Driving through intersections can be potentially dangerous because nearly 23 percent of the total automotive related fatalities and almost 1 million injury-causing crashes occur at or within intersections every year [1]. The impact of traffic intersections on trip delays also leads to waste of human and natural resources. Our goal is to increase the safety and throughput of traffic intersections using co-operative driving. In earlier work [2], we have proposed a family of vehicular network protocols, which use Dedicated Short Range Communications (DSRC) and Wireless Access in Vehicular Environment (WAVE) technologies to manage a vehicle's movement at intersections Specifically, we have provided a collision detection algorithm at intersections (CDAI) to avoid potential crashes at or near intersections and improve safety. We have shown that vehicle-to-vehicle (V2V) communications can be used to significantly decrease the trip delays introduced by traffic lights and stop signs.

Autonomous vehicle (AV) developers test extensively on public roads, potentially putting other road users at risk. A safety case for human supervision of road testing could improve safety transparency. A credible safety case should include: (1) the supervisor must be alert and able to respond to an autonomy failure in a timely manner, (2) the supervisor must adequately manage autonomy failures, and (3) the autonomy failure profile must be compatible with effective human supervision. Human supervisors and autonomous test vehicles form a combined human-autonomy system, with the total rate of observed failures including the product of the autonomy failure rate and the rate of unsuccessful failure mitigation by the supervisor. A difficulty is that human ability varies in a nonlinear way with autonomy failure rates, counter-intuitively making it more difficult for a supervisor to assure safety as autonomy maturity improves.

A substantial fraction of automotive collisions occur at intersections. Statistics collected by the Federal Highway Administration (FHWA) show that more than 2.8 million intersection-related crashes occur in the United States each year, with such crashes constituting more than 44 percent of all reported crashes [12]. In addition, there is a desire to increase throughput at intersections by reducing the delay introduced by stop signs and traffic signals. In the future, when dealing with autonomous vehicles, some form of co-operative driving is also necessary at intersections to address safety and throughput concerns. In this paper, we investigate the use of vehicle-to-vehicle (V2V) communications to enable the navigation of traffic intersections, to mitigate collision risks, and to increase intersection throughput significantly.