Making Autonomous Intersection Management Backwards-Compatible

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 (Rogers, Flechter, & Langley 1999; Schonberg et al. 1995), and autonomous steering (Pomerleau 1993). 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 (Dresner & Stone 2005). 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.