Drivers’ behavioral responses to combined speed and red light cameras

Drivers’ behavioral responses to combined speed and red light cameras

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Article ID: iaor201527279
Volume: 81
Issue: 2
Start Page Number: 153
End Page Number: 166
Publication Date: Aug 2015
Journal: Accident Analysis and Prevention
Authors: , , , , , , ,
Keywords: accident, government, simulation, behaviour
Abstract:

The results of the on‐site observation study reveal decreases in the number of red and yellow light violations, a shift (i.e., closer to the stop line) in the dilemma zone and a time headway reduction after the installation of the SRLC. Based on the driving simulator data, the odds of rear‐end collisions (compared to the control condition) for the conditions with SRLC and SRLC+warning sign is 6.42 and 4.01, respectively. The real‐world and driving simulator observations indicate that the risk of rear‐end collisions increases when SRLCs are installed. However, this risk might decrease when a warning sign is placed upstream. Numerous signalized intersections worldwide have been equipped with enforcement cameras in order to tackle red light running and often also to enforce speed limits. However, various impact evaluation studies of red light cameras (RLCs) showed an increase of rear‐end collisions (up to 44%). The principal objective of this study is to provide a better insight in possible explaining factors for the increase in rear‐end collisions that is caused by placing combined speed and red light cameras (SRLCs). Real‐world observations and driving simulator‐based observations are combined. Video recordings at two signalized intersections where SRLCs were about to be installed are used to analyze rear‐end conflicts, interactions and driver behavior in two conditions (i.e., with and without SRLC). Furthermore, one of these intersections was rebuilt in a driving simulator equipped with an eye tracking system. At this location, two test conditions (i.e., SRLC and SRLC with a warning sign) and one control condition (i.e., no SRLC) are examined. The data of 63 participants were used to estimate the risk of rear‐end collisions by means of a Monte Carlo Simulation.

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