DocumentCode
1891662
Title
Evaluation of Earliest Deadline based schedulers for reduction of traffic congestion in dense urban areas
Author
Ahmed, Arif ; Arshad, Rabia ; Mahmud, Sahibzada Ali ; Khan, Gul Muhammad ; Al-Raweshidy, H.S.
Author_Institution
Dept. of Electr. Eng., Univ. of Eng. & Technol., Peshawar, Pakistan
fYear
2013
fDate
2-6 Dec. 2013
Firstpage
404
Lastpage
409
Abstract
The unwanted delay experienced by priority vehicles as a consequence of traffic congestion is one of the major problems faced while efficiently managing priority traffic. Two adaptive traffic light algorithms namely the Earliest Deadline First (EDF) and Fixed Priority (FP) have been proposed and evaluated in the paper to reduce the traffic congestion experienced by priority vehicles. The performance of the algorithms has been evaluated at isolated intersections and their resulting efficiency has been compared against a static traffic lights control implementation as well. It has been shown and deduced through different performance metrics that the overall performance of EDF is better than the FP in controlling traffic congestion for priority vehicles when evaluated against static control.
Keywords
intelligent transportation systems; road traffic control; traffic engineering computing; EDF algorithms; FP algorithms; adaptive traffic light algorithms; dense urban areas; earliest deadline based schedulers; earliest deadline first algorithms; fixed priority algorithms; priority vehicles; static traffic lights control implementation; traffic congestion reduction; Adaptation models; Algorithm design and analysis; Equations; Mathematical model; Vehicle dynamics; Vehicles; Adaptive Traffic Light Control; Earliest deadline First (EDF); Fixed Priority (FP); Intelligent Transportation System (ITS); Sumo (simulation of urban mobility);
fLanguage
English
Publisher
ieee
Conference_Titel
Connected Vehicles and Expo (ICCVE), 2013 International Conference on
Conference_Location
Las Vegas, NV
Type
conf
DOI
10.1109/ICCVE.2013.6799827
Filename
6799827
Link To Document