Title :
Earliest-Deadline-Based Scheduling to Reduce Urban Traffic Congestion
Author :
Ahmad, Ayaz ; Arshad, Rabia ; Mahmud, Sahibzada Ali ; Khan, Gul Muhammad ; Al-Raweshidy, H.S.
Author_Institution :
Dept. of Electr. Eng., NWFP Univ. of Eng. & Technol., Peshawar, Pakistan
Abstract :
One of the major problems, caused by traffic congestion, owes its existence to the unwanted delay experienced by the priority vehicles. The evaluation of two scheduling algorithms as adaptive traffic control algorithms has been proposed here to reduce this unwanted delay. One of these algorithms is the earliest deadline first (EDF) algorithm, whereas the other is the fixed priority (FP) algorithm. The performance of both algorithms as adaptive traffic light control algorithms is evaluated for isolated traffic intersections. A comparative study is performed here, where the performance of these algorithms is compared against a fixed static traffic light controller. Moreover, their performance is also compared against each other. Conclusive results from the simulation of the algorithms reveal that the number of stops, average delay, and mean trip time of the priority vehicles is significantly reduced by the implementation of these algorithms. Furthermore, it has been shown that the overall performance of EDF is much better than FP in terms of improvement of different performance measures for congestion reduction of priority vehicles.
Keywords :
adaptive control; road traffic control; scheduling; EDF; FP; adaptive traffic light control algorithms; congestion reduction; earliest deadline first algorithm; earliest-deadline-based scheduling; fixed priority algorithm; mean trip time; priority vehicles; scheduling algorithms; static traffic light controller; unwanted delay; urban traffic congestion reduction; Delays; Mathematical model; Sensors; Switches; Vehicles; Wireless sensor networks; Adaptive traffic light control (TLC); earliest deadline first (EDF); fixed priority (FP); intelligent transportation system (ITS); simulation of urban mobility (SUMO);
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
DOI :
10.1109/TITS.2014.2300693