Microsimulation-Based Evaluation of Fixed-Time and Vehicle-Actuated Traffic Signal Control Strategies Using PTV Vissim in an Urban Corridor

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Authors: Veranda Syla, Algenti Lala
Cited by: 2

Abstract

Urban traffic congestion at signalized intersections can be mitigated by enhanced signal control strategies.This paper presents a microsimulation-based comparative analysis of two strategies applied to a heavilycongested corridor in Tirana, Albania. Scenario 1 implements conventional fixed-time traffic signals, andScenario 2 deploys fully vehicle-actuated signals. Four intersections along Tirana’s main ring road weremodeled in PTV Vissim under morning peak-hour conditions. The simulation uses a 50-run Monte Carloapproach, and the model was calibrated to field-measured volumes and queues for realism. A customVehicle Actuated Programming (VAP) logic with inductive-loop detectors was developed to emulate realcontroller behavior. Key performance metrics (queue lengths, vehicle delay, and network throughput) wereevaluated for each scenario. The results show that vehicle-actuated control yields significant reductions inqueue lengths and delays compared to the fixed-time plan. For example, at the most congested approach,fixed-time control caused over 2200 s/vehicle average delay (37 min), whereas actuated control reducedthis by about 39% to 1346 s/vehicle. Similarly, queue lengths on major approaches dropped by up to 70%during the first peak hour under actuated control. Network-wide, the actuated strategy improved averagetravel speed by 33% and reduced total travel time by 25% relative to fixed timings. These findings underscorethe effectiveness of vehicle-actuated signals in dynamically allocating green time based on real-timedemand, thereby improving intersection throughput and reducing congestion. The paper further examinesimplementation considerations such as detector placement and maintenance. The adaptive Scenario 2 isfound to be highly beneficial for urban traffic management in a growing city like Tirana.

Fields of Study & Subjects

Traffic control and management Traffic Prediction and Management Techniques Transportation Planning and Optimization

Publication details

Journal / source
Informatica
Publisher
Slovenian Association Informatika
Volume
50
Issue
5
Publication date
2 February 2026