Analyzing traffic conflicts and the behavior of motorcyclists at unsignalized three-legged and four-legged intersections in Cartagena, Colombia

Ospina-Mateus, Holman; Quintana, Leonardo; López‐Valdés, Francisco J.

doi:10.1016/j.aap.2023.107222

Cited by 7 publications

(1 citation statement)

References 35 publications

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“…In [7,12], detailed loss time values were provided, advocating for safer infrastructure. Meanwhile, in Indonesia, where motorcycles constitute a significant portion of the traffic, a study exposed shortcomings in existing traffic models and introduced a novel approach to determine saturation flow based on motorcycle behavior, aiming to improve traffic management at signalized intersections [13]. In [14], factors influencing motorcycle riders' stopping choices at signalized urban intersections were identified utilizing Unmanned Aerial Vehicles (UAVs) to collect data and employing multinomial logistic regression to identify key factors that account for nearly 50% of the variation in motorcycle riders' stopping behavior [15].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Motorcycle Positioning on Start-Up Lost Time: The Empirical Case Study of Signalized Intersections in Marrakech using VISSIM

Charef,

Jarir,

Quafafou

2024

Eng. Technol. Appl. Sci. Res.

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This study explores the influence of a high percentage of motorcycles on the traffic flow and congestion in Marrakech by examining the impact of motorcycle positioning in shaping urban traffic dynamics, in particular, the start-up lost time at signalized intersections. Different motorcycle positioning strategies are analyzed to improve intersection efficiency and safety. A twofold approach was followed to achieve this objective. First, empirical data were collected using computer vision techniques. Second, different strategies were simulated in VISSIM based on the collected data. The approach adopted for data collection was based on mobile phone video recording at a representative signalized intersection in Marrakech, capturing traffic behaviors during four distinct time periods. Then the YOLOv8 algorithm was employed for real-time object detection and analysis, allowing precise monitoring of motorcycle positioning and examining its influence on the start-up lost time. Afterwards, VISSIM simulations were implemented, on the basis of the collected data, to explore various scenarios, such as motorcycles sharing lanes with cars or dedicated motorcycle lanes. The results reveal a compelling correlation between motorcycle proximity to cars and traffic congestion, with closer positioning leading to increased congestion, longer travel times, reduced average vehicle speeds, and extended queue lengths at intersections. On the contrary, scenarios with dedicated motorcycle lanes consistently show reduced congestion and smoother traffic flow.

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