We address the problem of maritime traffic management in busy waterways to increase the safety of navigation by reducing congestion. We model maritime traffic as a large multiagent systems with individual vessels as agents, and VTS authority as the regulatory agent. We develop a maritime traffic simulator based on historical traffic data that incorporates realistic domain constraints such as uncertain and asynchronous movement of vessels. We also develop a traffic coordination approach that provides speed recommendation to vessels in different zones. We exploit the nature of collective interactions among agents to develop a scalable policy gradient approach that can scale up to real world problems. Empirical results on synthetic and real world problems show that our approach can significantly reduce congestion while keeping the traffic throughput high.

This paper proposes a multi agent based timetable scheduling algorithm for railway system which handles the in−between time delay of the newly introduced train. The delay management indeed optimizes the total journey time, hence increases the total utility of the whole railway system as well.Here we show that schedule generated by our proposed algorithm is the most optimized schedule. It is done by using the notion of DCOP(Distributed Constraint Optimization Problem), where we define some metric to analyze the system to achieve our goals. We use JADE(Java Agent DEvelopment Framework) platforms to simulate our work and test it using a small network. We also take a small case study to compare our proposed work with the existing one and the results are therefore presented.

No abstract

No abstract