Auction-Based Traffic Management: Towards Effective Concurrent Utilization of Road Intersections
CECANDEEE '08 Proceedings of the 2008 10th IEEE Conference on E-Commerce Technology and the Fifth IEEE Conference on Enterprise Computing, E-Commerce and E-Services
GreenWave distributed traffic intersection control
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
A multiagent approach to autonomous intersection management
Journal of Artificial Intelligence Research
iCO2: multi-user eco-driving training environment based on distributed constraint optimization
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
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Traffic causes pollution and demands fuel. When it comes to vehicle traffic, intersections tend to be a main bottleneck. Traditional approaches to control traffic at intersections have not been designed to optimize any environmental criterion. Our objective is to design mechanisms for intersection control which minimize fuel consumption. This is difficult because it requires a specialized infrastructure: It must allow vehicles and intersections to communicate, e.g., vehicles send their dynamic characteristics (position, speed etc.) to the intersection more or less continuously so that it can estimate the fuel consumption. In this context, the use of software agents supports the driver by reducing the necessary degree of direct interaction with the intersection. In this paper, we quantify the fuel consumption with existing agent-based approaches for intersection control. Further, we propose a new, agent-based mechanism for intersection control, with minimization of fuel consumption as an explicit design objective. It reduces fuel consumption by up to 26% and waiting time by up to 98%, compared to traffic lights. Thus, agent-based mechanisms for intersection control may reduce fuel consumption in a way that is substantial.