Kurt Dresner

AAMAS Conference 2008 Conference Paper

Mitigating Catastrophic Failure at Intersections of Autonomous Vehicles

• Kurt Dresner
• Peter Stone

Fully autonomous vehicles promise enormous gains in safety, efficiency, and economy. Before such gains can be realized, safety and reliability concerns must be addressed. We have previously introduced a system for managing such vehicles at intersections that is capable of handling more vehicles and causing fewer delays than traffic lights and stop signs [2]. While the system is safe under normal operating conditions, we have not discussed the possibility or implications of unforeseen mechanical failures. Because the system orchestrates such precarious “close calls” the tolerance for such errors is small. In this paper, we introduce safety features of the system designed to deal with these types of failures, and perform a basic failure mode analysis, demonstrating that without these features, the system is unsuitable for deployment due to a propensity for catastrophic failure modes.

AAMAS Conference 2008 Conference Paper

Replacing the Stop Sign: Unmanaged Intersection Control for Autonomous Vehicles

• Mark Van Middlesworth
• Kurt Dresner
• Peter Stone

As computers replace humans as the drivers of automobiles, our current traffic management mechanisms will give way to hyper-efficient protocols designed to exploit the capabilities of fully autonomous vehicles. We have introduced such a system for coordinating large numbers of autonomous vehicles at intersections [2, 3]. Our experiments suggest that this system could alleviate many of the dangers and delays associated with intersections by allowing vehicles to “call ahead” to an agent stationed at the intersection and reserve time and space for their traversal. Unfortunately, such a system is not cost-effective at small intersections. In this paper, we propose an intersection control mechanism for autonomous vehicles designed specifically for low-traffic intersections where the previous system would not be practical. Our mechanism is based on purely peer-to-peer communication and thus requires no infrastructure at the intersection. We present experimental results demonstrating that our system, while not suited to large, busy intersections, can significantly outperform traditional stop signs at small intersections.

IJCAI Conference 2007 Conference Paper

• Kurt Dresner
• Peter Stone

In modern urban settings, automobile traffic and collisions lead to endless frustration as well as significant loss of life, property, and productivity. Recent advances in artificial intelligence suggest that autonomous vehicle navigation may soon be a reality. In previous work, we have demonstrated that a reservation-based approach can efficiently and safely govern interactions of multiple autonomous vehicles at intersections. Such an approach alleviates many traditional problems associated with intersections, in terms of both safety and efficiency. However, the system relies on all vehicles being equipped with the requisite technology - a restriction that would make implementing such a system in the real world extremely difficult. In this paper, we extend this system to allow for incremental deployability. The modified system is able to accommodate traditional human-operated vehicles using existing infrastructure. Furthermore, we show that as the number of autonomous vehicles on the road increases, traffic delays decrease monotonically toward the levels exhibited in our previous work. Finally, we develop a method for switching between various human-usable configurations while the system is running, in order to facilitate an even smoother transition. The work is fully implemented and tested in our custom simulator, and we present detailed experimental results attesting to its effectiveness.

AAAI Conference 2006 Short Paper

Making Autonomous Intersection Management Backwards-Compatible

• Kurt Dresner

Traffic congestion and automobile accidents are two of the leading causes of decreased standard of living and lost productivity in urban settings. 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 adaptive cruise control, GPS-based route planning, and autonomous steering. Once individual cars become autonomous, many of the cars on the road will have such capabilities, thus opening up the possibility of autonomous interactions among multiple vehicles. In earlier work, we proposed a novel Multiagent Systems–based approach to alleviating traffic congestion and collisions, specifically at intersections. In this work, we make three further contributions. First, we augment our existing intersection control mechanism to allow use by human drivers with minimal additional infrastructure. Second, we show that this hybrid mechanism offers performance and safety benefits over traditional traffic light systems. Finally, we show that at each stage, there exists an incentive to use autonomous vehicles over traditional vehicles. All work is fully implemented and tested in our custom simulator and we present experimental results to support its effectiveness.

AAAI Conference 2006 Conference Paper

Traffic Intersections of the Future

• Kurt Dresner

Few concepts embody the goals of artificial intelligence as well as fully autonomous robots. Countless films and stories have been made that focus on a future filled with autonomous agents that complete menial tasks or run errands that humans do not want or are too busy to carry out. One such task is driving automobiles. In this paper, we summarize the work we have done towards a future of fully-autonomous vehicles, specifically coordinating such vehicles safely and efficiently at intersections. We then discuss the implications this work has for other areas of AI, including planning, multiagent learning, and computer vision.

AAMAS Conference 2005 Conference Paper

Multiagent Traffic Management: An Improved Control Mechanism

• Kurt Dresner
• Peter Stone

AAMAS Conference 2004 Conference Paper

Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism

• Kurt Dresner
• Peter Stone