TY - GEN
T1 - Traffic Light Control System for Four-Way Intersection and T-Crossing Using Fuzzy Logic
AU - Firdous, Maheen
AU - Din Iqbal, Fasih Ud
AU - Ghafoor, Nouman
AU - Qureshi, Nauman Khalid
AU - Naseer, Noman
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/3
Y1 - 2019/3
N2 - Traffic signals are vital for traffic management. It is essential to increase the efficiency of the traffic controller to alleviate traffic congestion. In this paper, the traffic light control system using fuzzy logic is designed to minimize queue count (QC) and waiting time (WT) for vehicles at the intersection. Real-time traffic is generated and a fuzzy logic controller is implemented to control the traffic light system. In the proposed fuzzy logic controller, trapezoidal membership functions are combined with the rules to generate green light time for input QC and WT. The improvement in QC, WT, and tailback is witnessed by using Static Phase Scheduling Traffic Light System (SPSTLS) as a benchmark to measure the performance of the proposed controller. The performance comparison records a significant improvement of 81.68% in QC, 87.04% in average WT and 18.05% in the tailback. The results show that fuzzy logic controlled Dynamic Phase Scheduling Traffic Light System (DPSTLS) has the potential to resolve the problem of QC, WT, travel cost, accident, and traffic congestion.
AB - Traffic signals are vital for traffic management. It is essential to increase the efficiency of the traffic controller to alleviate traffic congestion. In this paper, the traffic light control system using fuzzy logic is designed to minimize queue count (QC) and waiting time (WT) for vehicles at the intersection. Real-time traffic is generated and a fuzzy logic controller is implemented to control the traffic light system. In the proposed fuzzy logic controller, trapezoidal membership functions are combined with the rules to generate green light time for input QC and WT. The improvement in QC, WT, and tailback is witnessed by using Static Phase Scheduling Traffic Light System (SPSTLS) as a benchmark to measure the performance of the proposed controller. The performance comparison records a significant improvement of 81.68% in QC, 87.04% in average WT and 18.05% in the tailback. The results show that fuzzy logic controlled Dynamic Phase Scheduling Traffic Light System (DPSTLS) has the potential to resolve the problem of QC, WT, travel cost, accident, and traffic congestion.
KW - DPSTLS
KW - Fuzzy Logic Controller
KW - SPSTLS
KW - Traffic Light Control
UR - http://www.scopus.com/inward/record.url?scp=85074384733&partnerID=8YFLogxK
U2 - 10.1109/ICAICA.2019.8873518
DO - 10.1109/ICAICA.2019.8873518
M3 - Conference contribution
AN - SCOPUS:85074384733
T3 - Proceedings of 2019 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2019
SP - 178
EP - 182
BT - Proceedings of 2019 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2019
Y2 - 29 March 2019 through 31 March 2019
ER -