Abstract

A relevant number of collisions between vehicles and pedestrians occur at night because of the reduced capacity of a driver to perceive and react to the presence of pedestrians at crosswalks. To reduce this risk of collision, new smart road technologies have been introduced. This study aims to evaluate the effectiveness of a red LED strip that warns the driver of the presence of pedestrians at unsignalized mid-block crosswalks at night-time. The technology consists of LED strips installed near the crosswalk on the side of oncoming vehicles. The LED is activated when a sensor detects a pedestrian approaching the crosswalk. In this driving simulation experiment, three different urban mid-block crosswalks were evaluated: (i) without an LED strip (baseline), (ii) with a fixed LED strip, and (iii) with a flashing LED strip. Each scenario was tested for three different levels of pedestrian time gap acceptance (PTGA) (i.e., 4, 6, 8 s) and two road sections (i.e., 1 lane vs. 2 lanes). Thirty-six participants took part in a within-subjects’ design. During the experiment, the minimum time to collision (mTTC), the post-encroachment time (PET), maximum vehicle speed, and reaction distance were monitored to quantitatively compare the different levels of vehicle-pedestrian interaction. Compared to the baseline, the LED strip resulted in a safer driver-pedestrian interaction, with an average increase in mTTC of 1.13 s, PET of 0.66 s, and a longer average reaction distance of 7.9 m. However, a slight (albeit not statistically significant) increase in speed was observed following installation of the LED strip. Furthermore, no significant differences were observed between fixed and flashing LED strips. Overall, these results confirm the LED strips effectiveness in alerting the driver to the presence of a pedestrian, thus increasing the safety of their interaction. Further studies should confirm these findings in a more ecological way, e.g., evaluating the safety impact of this technology under different weather and distracted driving conditions.

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