Abstract
This paper presents Fuzzy Neural Network (FNN) based Adaptive Route Selection Support System (ARSSS) for assisting drivers of vehicles. The aim of the proposed ARSSS system is to select path based on shortest possible time. The proposed system intakes traffic information, such as volume to capacity ratio, traffic flow, vehicle queue length and green cycle length, passenger car unit etc using different types of sensor nodes, remote servers, CCTVs and the road information such as path length, signalized junctions, intersection points between source-destination pair are captured using GPS service. A FNN has been employed to select an optimal path having shortest time. The input parameters of FNN are distance, signal point delay, road type and traffic flow whereas the output parameter is path selection probability which paves the way to identify the best suitable path. The simulation result revels that FNN based ARSSS outperforms more accurate than that of other route selection support system (webster delay model) and artificial neural network (ANN) in estimating path delay.
Highlights
With the increase of metropolitan cities, traffic scenario has become more complex and heavily congested
It is a universal truth that people always want to reach their destination in shortest possible time. This human nature introduces the need of an Adaptive Route Selection (ARS) technique, which allows to discover the optimal route between a source-destination pair
Fuzzy Neural Network (FNN) controller takes distance denoted as Djm, signal point delay denoted as, Sij, traffic flow denoted as ∆fjm and road type φjm as input parameters and performs fuzification-defuzification calculation and generates the best suitable route between a source-destination pair
Summary
With the increase of metropolitan cities, traffic scenario has become more complex and heavily congested. As metropolitan cities include heterogeneous traffic environment, FNN is more applicable for traffic delay estimation and optimal route selection between a source-destination pair due to it’s nature of adaptivity and flexibility. It supports different types of transportation with low traffic capacity and unstructured road map [4] Under such circumstances of the city Dhaka, FNN based route selection support system can make its people capable of traveling between a sourcedestination pair in shortest possible time. The motivation of the proposed work is to represent a concurrent ARSSS system which is well suited for heterogeneous traffic environment for Dhaka [23] It intakes route map and traffic information dynamically, delivers optimal possible routes to its user between a source-destination pair.
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