Intelligent Transportation System For Lane Change Assistance Using Freeway Lane Selection Algorithm

Ketkee V. Deshpande, Prof. S. D. Zade, Prof.C.U. Chauhan

Abstract


:- In todays era the traffic situations are going critical. So in such cases changing of lane becomes more critical task. This system not only helps a driver for lane departure but also warns unsafe distances. For a driver to change a lane by considering all the traffic conditions becomes more challenging thus there exists a need of perfect lane allocation system .

This paper proposes lane change allocation system. It guides the drivers for making required lane moves. It uses the parameters such as vehicles position, speed, distances along vehicles, space etc [15]. These parameters are present into the vehicles database [17]. The freeway lane selection algorithm helps to take correct and instant decision for a lane allocation.

Two main classifiers that are used for in the system are Bayes classifier and decision tree. Bayes classifier and decision-tree methods were applied to filter the lane allocation decision. These two classifiers are used to differentiate the merging & non merging acts. The best results were obtained when both Bayes and decision-tree approaches are used. This paper also proposes the use of freeway lane selection algorithm, which is considered to be the best traffic simulation algorithm. The earlier accuracy was 94.3% for non merging and 79.3% for merging category. Thus by using the freeway lane selection algorithm we have improved the accuracy of lane merging up to some higher level.

Index terms: Total number of lanes, target lane, merging lane, position, Freeway lane selection algorithm, Bayes classifier, decision tree.


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