Assessment of an Adaptive Traffic Signal System Based on Vehicle-Pedestrian Conflicts at Intersections with High Vehicular and Pedestrian Demand (#1469)
Read ArticleDate of Conference
July 15-17, 2026
Published In
"Engineering without Borders: Artificial Intelligence, Knowledge, Innovation, and Alliances for a Future from the Americas"
Location of Conference
Santiago (Chile)
Authors
Pérez, Alexander
Zevallos, Luisa Maria
Silvera, Manuel
Campos, Fernando
Palacios-Alonso, Daniel
Abstract
At urban intersections with high vehicular and pedestrian demand, vehicle-pedestrian conflicts represent a recurring problem for road safety and operational efficiency, necessitating the evaluation of new traffic control strategies that prioritize both mobility and the protection of vulnerable users. This study analyzes the effectiveness of different traffic signal systems at urban intersections with high vehicular and pedestrian demand, focusing on conflicts between vehicles and pedestrians. Three approaches were compared: fixed-time signalization, adaptive signalization based on traffic flow, and adaptive signalization based on vehicle–pedestrian conflict detection. The methodology included detailed modeling of the intersection using PTV VISSIM, control logic implementation in VISVAP, and safety analysis through SSAM. Data collection was conducted using RPA footage and field observations, allowing a realistic representation of traffic behavior. Results showed that the conflict-based adaptive system achieved a 50.9% reduction in total conflicts, recording 1081 interactions compared to 2204 in the fixed-time system It also maintained an average crossing time of 7.96 seconds, slightly higher than conventional adaptive traffic lights (7.86 s), but lower than the fixed system (8.26 s). In terms of operational performance, it reached a traffic flow of 1996 vehicles per lane per hour, a value comparable to that of the traditional adaptive model (2080 veh/lane/h). This strategy proves to be an effective and replicable solution for complex urban intersections.