Abstract
Navigation in a traffic congested city can prove to be a difficult task. Often a path that may appear to be the fastest option is much slower due to congestion. If we can predict the effects of congestion, it may be possible to develop a better route that allows us to reach our destination more quickly. This paper studies the possibility of using a centralized real-time traffic information system containing travel time data collected from each road user. These data are made available to all users, such that they may be able to learn and predict the effects of congestion for building a route adaptively. This method is further enhanced by combining the traffic information system data with previous routing experiences to determine the fastest route with less exploration. We test our method using a multi-agent simulation, demonstrating that this method produces a lower total route time for all vehicles than when using either a centralized traffic information system or direct experience alone.
Highlights
When a driver attempts to navigate in a modern urban environment, they must overcome many obstacles to reach their destination, e.g., poor weather, road construction and accidents; while these problems may occur with varying degrees of frequency, traffic congestion is one which is encountered daily
We ran experiments in which we simulated vehicles traveling in a city road network grid, each directed by an agent
We found that each method reduced the total route times of all agents when compared to routing by selecting the fastest route based on map data alone
Summary
When a driver attempts to navigate in a modern urban environment, they must overcome many obstacles to reach their destination, e.g., poor weather, road construction and accidents; while these problems may occur with varying degrees of frequency, traffic congestion is one which is encountered daily. Delays on the morning and evening commute to and from work are familiar to many who regularly travel in a city. Delays due to traffic congestion can be the cause of many problems. Drivers experience increased stress as delays may cause them to miss appointments or arrive late for work. Environmental damage is a concern, as traffic delays require vehicles to operate for longer periods than may otherwise be necessary, resulting in increased pollution due to automotive exhaust. Economic damage can occur as worker productivity is reduced due to increased stress and work time lost in travel [1]
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