Development of pre-time intersection isolated signal using a fuzzy logic model

• Published in: MATEC Web of Conferences Vol. 270; p. 3002
• Main Authors: Studyana, Moch D., Sjafruddin, Ade, Kusumantoro, Iwan P., Soeharyadi, Yudi
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Les Ulis EDP Sciences 2019
• Subjects: Confidence intervals; Fuzzy logic; Fuzzy systems; Intersections; Motorcycles; Operating systems; Queues; Traffic models; Traffic signals; Traffic surveys; Indonesia
• ISSN: 2261-236X; 2274-7214; 2261-236X
• DOI: 10.1051/matecconf/201927003002

We investigate the development of pre-time signal intersection operating systems for isolated intersections using Fuzzy Logic models. The traffic signal system setting in Indonesia has been using the Indonesia Road Capacity Manual model 1997, for example it is installed at the intersection in large cities in Indonesia. The development of the Fuzzy Logic model is focused on improving the performance of the signaled intersection, using a combination of numerical variable analysis used by IRCM 1997, and the linguistic or traffic behavior variable as the basis of the Fuzzy Logic model study. The combination of the two variables in the Fuzzy Logic model analysis is expected to improve the intersection performance. The Fuzzy Logic model process involves the Membership Function theory as the basis for the confidence level of the traffic variable to be surveyed, and the Fuzzy Inference Engine to measure the choice of combinations of variables that will be selected to make the best performance of the intersection. The geometric of intersection must be control as it involves the input of research data, especially on the condition of the intersection legs and markers of motor cycle-special stopping places, which is a potential of a traffic violation by traveller. The model is verified with fuzzified data from 2017 traffic research survey in Bandung. As an illustration of the majority of intersection setting with an isolated pre-time operating system, there are 60 intersection points or 85% of the total 71 intersections available. This would be a potentially major problem when performance improvements is not carried out. The final analysis shows that the number of vehicles queues decreases while the traffic flows passing through the intersection increases, therefore fuzzy logic model is expected to contribute and to give alternative handling for intersection performance with pre-time operational.