Highly Dynamic and Scalable VANET Routing for Avoiding Traffic ...

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Sep 10, 2007 - Sebastian Lehnhoff. School of ... sebastian[email protected]. Bernhard van ... Traffic Jam Avoidance, Nature Inspired Routing, VANETs. 1.
Highly Dynamic and Scalable VANET Routing for Avoiding Traffic Congestions Horst F. Wedde

Sebastian Lehnhoff

Bernhard van Bonn

School of Computer Science University of Dortmund Germany ++49-231-755-5321

School of Computer Science University of Dortmund Germany ++49-231-755-2768

Fraunhofer-Institute Dortmund Germany ++49-231-9743-369

[email protected]

[email protected]

[email protected]

Categories and Subject Descriptors C.2.2 [Computer Protocols

Communication

Networks]:

Routing

General Terms Algorithms, Performance, Experimentation

Keywords Traffic Jam Avoidance, Nature Inspired Routing, VANETs

1. INTRODUCTION Traffic congestions have become a major problem in metropolitan areas world-wide, within and between cities, in particular due to the highly dynamic character of congestion building and dissolving. Our earlier work on the novel multi-agent BeeHive routing algorithms [1,2,3] derived from the honey bee behavior exhibits high adaptability and flexibility, high throughput and fault tolerance at a so far unsurpassed degree. Part of the algorithm is concerned with dynamically updating the quality weights of the communication links which at the key feature for the probabilistic routing decisions. We integrated these algorithms into a distributed traffic control model where vehicles are directed under decentralized control at each road intersection. The result is the BeeJamA system.

2. QUALITY RATING FUNCTION 4-lane-freeways

street’s vehicle density and the traffic quality (in terms of congestion) for various high- and freeway types. Figure 1 shows the progression of an approximated density/speed dependency for 4-lane-freeways and its classification into 3 traffic state sections (congestion free, transition, congestion). We defined an approximating ρ-v-curve with three functions over three separate intervals, where α and β specify the vehicle densities at which the transitions between the three different states can be observed. A and B are used as parameters specifying the average speeds at which the three sections meet. The functions are: 0

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