In The 2005 IEEE Intelligent Vehicles Symposium (IV 2005), Las Vegas, Nevada, USA, June 2005. Turning the Corner: Improved Intersection Control for Autonomous Vehicles Kurt Dresner and Peter Stone University of Texas at Austin Department of Computer Sciences Austin, TX 78712 USA {kdresner, pstone}@cs.utexas.edu Abstract— Traffic congestion is one of the leading causes of lost productivity and decreased standard of living in urban settings. Recent advances in artificial intelligence suggest vehicle navigation by autonomous agents will be possible in the near future. In a previous paper, we proposed a reservation-based system for alleviating traffic congestion, specifically at intersec- tions. This paper extends our prototype implementation in several ways with the aim of making it more implementable in the real world. In particular, we 1) add the ability of vehicles to turn, 2) enable them to accelerate while in the intersection, 3) give a better sensor model and communication-efficient heuristic to our driver agent, and 4) augment their interaction capabilities with a detailed protocol such that the vehicles do not need to know anything about the intersection control policy. The use of this protocol limits the interaction of the driver agent and the intersection manager to the extent that it is a reasonable approximation of reliable wireless communication. We then use this protocol to implement a new control policy: the stop sign. All three improvements are fully implemented and tested, and we present detailed empirical results validating their effectiveness. I. I NTRODUCTION Traffic congestion is one of the leading causes of lost productivity and decreased standard of living in urban settings. According to a recent study of 85 U.S. cities [1], annual time spent waiting in traffic has increased from 16 hours per capita to 46 hours per capita since 1982. In the same period, the annual financial cost of traffic congestion has swollen from $14 billion to more than $63 billion (in 2002 US dollars). Each year, Americans burn approximately 5.6 billion gallons of fuel while idling in heavy traffic. Recent advances in artificial intelligence suggest that autonomous vehicle navigation will be possible in the near future. Individual cars can now be equipped with features of autonomy such as cruise control, GPS-based route planning [2], and autonomous steering [3]. Once individual cars become autonomous, it is inevitable that before long many of the cars on the road will have such capabilities, thus opening up the possibility of autonomous interactions among multiple vehicles. Multiagent Systems (MAS) is the subfield of AI that aims to provide both principles for construction of complex systems involving multiple agents and mechanisms for coordination of independent agents’ behaviors [4]. In an earlier paper, we proposed an MAS-based approach to alleviating traffic congestion, specifically at intersections [5]. In this paper, we describe several ways in which we have transformed that system into a more realistic and implementable system. Current methods for enabling traffic to flow through in- tersections include building overpasses and installing traffic lights. However, the former is very expensive and forbids turning, while the latter can be quite inefficient, often requiring cars to remain stopped even when no cars are present on the intersecting road. At this time, it is possible to create a small-scale system in which all cars are piloted by a central computer. Consider, for example, the task of controlling ten vehicles on an open factory floor. However, growing such a system to handle an in- tersection in which a city’s worth of cars might turn up would involve prohibitively expensive and inefficient communication and control infrastructure. Here we aim to maximize the efficiency of moving cars through intersections with minimal centralized infrastructure. We assume that intersections can be outfitted with a simple wireless communication system and a protocol (which we introduce here) for communicating with oncoming traffic and giving permission for cars to pass. In our system, vehicles must traverse intersections according to a set of parameters agreed upon by the vehicle and the in- tersection manager (as they do today by obeying red and green lights), but otherwise are free to decide for themselves how to drive. Each car is an autonomous agent, and in particular need not surrender control to any centralized decision maker. Given the above assumptions, we have proposed a novel reservation-based system by which cars request and receive time slots from the intersection during which they may pass [5]. While this system showed the potential for a reservation-based system to drastically improve the efficiency of intersections, it required driving agents to maintain a constant velocity in the intersection and forbade turning (a very important part of intersections). Furthermore, it did not adequately specify how they should interact. In this paper, we take three large steps towards making the system imple- mentable in the real world. First, we augment it to allow turning. Second, we make acceleration in the intersection possible, which allows us to subsume the stop sign policy within the reservation framework. Third, we devise a protocol to govern the interactions of the vehicles and the intersection such that the vehicles do not need to know anything about the intersection control policy. The use of this protocol limits the interaction of the driver agent and the intersection manager