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Article

Dilemma Zone: Modeling Drivers’ Decision at Signalized Intersections against Aggressiveness and Other Factors Using UAV Technology

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Laboratory of Transportation Engineering, School of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
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Laboratory of Transportation Planning, Transportation Engineering & Highway Engineering, School of Rural & Surveying Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
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Author to whom correspondence should be addressed.
Received: 16 November 2020 / Revised: 16 January 2021 / Accepted: 23 January 2021 / Published: 3 February 2021
(This article belongs to the Special Issue Transportation System Design)
Intersection safety and drivers’ behavior are strongly interrelated, especially when the latter are located in dilemma zone. This paper explores, among others, the main factors affecting driver behavior, such as distance to stop line, approaching speed and acceleration/deceleration, and two additional factors, namely, driver’s aggressiveness and driver’s relative position at the onset of the yellow signal. Field data were collected using unmanned aerial vehicle (UAV) technology. Two binary choice models were developed, the first relying on observed data and the latter enriched by the latent factor drivers’ aggressiveness and the vehicles’ relative position. Drivers were classified to aggressive and non-aggressive ones using a latent class model that combined approaching speed and acceleration/deceleration data. Drivers were further grouped according to their expected reaction/decision to stop or cross the intersection in relation to their relative position. Both models equally explain drivers’ decisions adequately, but the second one offers additional explanatory power attributed to aggressiveness. Being able to identify the level of aggressiveness among the drivers enables the calculation of the probability that drivers will cross the intersection even if caught in a dilemma zone or in a zone in which the obvious decision is to stop. Such findings can be valuable when designing a signalized intersection and the traffic time settings, as well as the posted speed limit. View Full-Text
Keywords: UAV video-observed vehicle trajectory data; driver behavior; signalized intersection; dilemma zone; choice model; latent class model; acceleration/deceleration; drivers’ aggressiveness UAV video-observed vehicle trajectory data; driver behavior; signalized intersection; dilemma zone; choice model; latent class model; acceleration/deceleration; drivers’ aggressiveness
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MDPI and ACS Style

Papaioannou, P.; Papadopoulos, E.; Nikolaidou, A.; Politis, I.; Basbas, S.; Kountouri, E. Dilemma Zone: Modeling Drivers’ Decision at Signalized Intersections against Aggressiveness and Other Factors Using UAV Technology. Safety 2021, 7, 11. https://0-doi-org.brum.beds.ac.uk/10.3390/safety7010011

AMA Style

Papaioannou P, Papadopoulos E, Nikolaidou A, Politis I, Basbas S, Kountouri E. Dilemma Zone: Modeling Drivers’ Decision at Signalized Intersections against Aggressiveness and Other Factors Using UAV Technology. Safety. 2021; 7(1):11. https://0-doi-org.brum.beds.ac.uk/10.3390/safety7010011

Chicago/Turabian Style

Papaioannou, Panagiotis, Efthymis Papadopoulos, Anastasia Nikolaidou, Ioannis Politis, Socrates Basbas, and Eleni Kountouri. 2021. "Dilemma Zone: Modeling Drivers’ Decision at Signalized Intersections against Aggressiveness and Other Factors Using UAV Technology" Safety 7, no. 1: 11. https://0-doi-org.brum.beds.ac.uk/10.3390/safety7010011

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