Adaptive route selection support system based on road traffic information

Rahman, Shafin; Yeasmin, Nilufar; Ahmmed, Mahtab Uddin; Kaiser, M. Shamim

doi:10.1109/iceeict.2015.7307526

Cited by 5 publications

(6 citation statements)

References 4 publications

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“…Based on field measurement they provide a regression analysis which measures the accuracy of traffic models considering the traffic scenario of Dhaka City [22]. The work of [23] presents a traffic information based adaptive route selection support system by offering a model that helps to calculate the minimum delay for a particular source to destination according to the google map.…”

Section: Related Workmentioning

confidence: 99%

“…In this paper, we use the proposed model scheme of [23] for more realistic modeling of FNN based route selection support system for Dhaka, Bangladesh.…”

Section: Related Workmentioning

confidence: 99%

“…The cross section delay is the time that a vehicle takes to cross a crossingpoint intersection. The signal point delay is the time which is required at a signalized junction [23] [24] [25]. It also considers road type and traffic flow calculation used in FNN controller.…”

Section: Data Pre-processingmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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FNN based Adaptive Route Selection Support System

Rahman¹,

Kaiser²,

Ahmmed³

2016

ijacsa

Self Cite

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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.

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Section: Related Workmentioning

confidence: 99%

“…In this paper, we use the proposed model scheme of [23] for more realistic modeling of FNN based route selection support system for Dhaka, Bangladesh.…”

Section: Related Workmentioning

confidence: 99%

Section: Data Pre-processingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

FNN based Adaptive Route Selection Support System

Rahman¹,

Kaiser²,

Ahmmed³

2016

ijacsa

Self Cite

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show abstract

“…According to road network attributes, the shortest route selection problem can be divided into the following two types: static shortest route selection and dynamic shortest route selection [22][23][24][25]. The selection of the static shortest route generally does not consider time characteristics, and it takes the shortest route as the evaluation performance to determine the shortest driving route.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Dynamic Route Optimization Based on Predictive Control Principle

Wang

2022

IEEE Access

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The principle of predictive control is applied to research on real-time dynamic route optimization of traffic travel, and a real-time dynamic route optimization model based on predictive control is proposed. Taking the driving time as the controlled variable, the driving speed as the manipulated variable, some traffic conditions as disturbance factors, the shortest driving time as the set value, the static shortest route as the reference route of the control system, and the objective function with the shortest driving time, which is defined as the control performance is established. According to the change in the road network state and the optimal solution result of the objective function, the real-time dynamic route selection based on the shortest driving time is realized by switching among different static shortest routes, and the rolling optimization and combination of dynamic and static routes are implemented in the process. A unique method is also used to obtain the optimal solution of the objective function in this study, which is scientific, reasonable, fast, and convenient. The optimization model overcomes the shortcomings of determining the dynamic shortest route by depending on traffic flow prediction and speed prediction. The simulation results and case study prove that the predictive control model algorithm of real-time dynamic route optimization is correct and better. The most important feature of the model algorithm is that it takes the static driving route and desired driving time as the control goals, and it can achieve the global optimal solution of the shortest path and shortest time. The proposed model algorithm has good innovation and practical applications.

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Optimal Charging Strategy for Spatially Distributed Electric Vehicles in Power System by Remote Analyser

Venkataswamy

Joseph

2019

Lecture Notes in Networks and Systems

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Adaptive route selection support system based on road traffic information

Cited by 5 publications

References 4 publications

FNN based Adaptive Route Selection Support System

FNN based Adaptive Route Selection Support System

Real-Time Dynamic Route Optimization Based on Predictive Control Principle

Optimal Charging Strategy for Spatially Distributed Electric Vehicles in Power System by Remote Analyser

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