Studying vehicle characteristics and determining service levels at road intersections (Case study: Ruwaifa Al-Ansari intersection, Al-Jabal Al-Akhdar Municipality, State of Libya)

Abstract

The aim of this study was to investigate vehicle characteristics and determine the Level of Service (LOS) at the signalized intersection in Al-Jabal Al-Akhdar (Ruwaifa Al-Ansari intersection). Traffic data was collected using video cameras and a field survey using a special logbook during different time periods: morning and evening peak hours. The SIDRA software package, developed by the Australian Road Research Council, was used to assess and determine the level of service and average delay at the intersection. SIDRA operates according to the American Highway Capacity Manual and utilizes artificial intelligence tools on a model of the study, including sensors and traffic lights. The data analysis revealed that traffic flow is heterogeneous and not lane-dependent, with private vehicles accounting for more than 50% of the traffic compared to other vehicles. The results also showed that the intersection had a service level of F, the worst level, and an average delay of 183.4 vehicles/second. Finally, alternatives were proposed, including eliminating left-turn traffic in arms (NB) and (EB), as these are the busiest traffic flows. A change in service level from (F) to (E) was observed, as well as a decrease in average delay from 183.4 sec/veh to 68.6 sec/veh. Furthermore, proposed solutions involved developing an intelligent control model using traffic signals and sensors. This model utilizes artificial intelligence algorithms to determine the optimal timing for improving and reducing traffic congestion at intersections, employing a traffic signal and sensor system, as illustrated in the study model.