Advanced vehicle guidance systems use real-time traffic information to route traffic and to
avoid congestion. Unfortunately, these systems can only react upon the presence of traffic …

This paper presents an agent-based approach, called delegate multi-agent systems, for
anticipatory vehicle routing to avoid traffic congestion. In this approach, individual vehicles …

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 …

This paper explores the use of cooperative, distributed multi-agent systems to improve
dynamic routing and traffic management. On the supply-side, real-time control over the …

As urbanization has been spreading across the world for decades, the traffic congestion
problem becomes increasingly serious in most of the major cities. Among the root causes of …

Anticipatory route guidance in traffic networks is based on time-dependent fastest path
calculation requiring forecasts of link travel time over a time horizon. These forecasts would …

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 …

Road congestion results in a huge waste of time and productivity for millions of people. A
possible way to deal with this problem is to have transportation authorities distribute traffic …

This paper reports our experiences with agent-based architectures for intelligent traffic
management systems. We describe and compare integrated TRYS and TRYS autonomous …

Most traffic control systems are centralized, where all the collected data can be analyzed to
make a decision. However, there are problems with computational complexity and, more …