A Before-and-After Study of a Collision Risk Detecting and Warning System on Local Roads

Abstract

Local roads have numerous blind spots caused by complex geometry, obstacles, and narrow width. Thus, conventional proactive countermeasures, such as passive traffic signs and convex mirrors, have not always been effective in preventing local road collisions. In this paper, we present a novel proactive two-step approach for traffic safety on local roads, comprised of detection of pedestrian-to-vehicle and vehicle-to-vehicle collision risks and warning systems. First, using video surveillance and radars to eliminate blind spots, the system detects road objects, predicts their trajectories and reachable areas, and identifies a potential risk situation. Second, it provides road users such as vehicles and pedestrians with warnings through LED variable message signs, which allows them to react effectively in risky situations. We have applied the system to two local road sites in South Korea, including a university campus in Seoul City and an apartment complex in Daejeon City. The detecting system has been validated using a confusion matrix. We have assessed the warning effect through a before-and-after study and found that the proposed system contributed to the improvement of traffic safety at the case study site in that traffic conflicts decreased by 55–62%.

Examining Car Accident Prediction Techniques and Road Traffic Congestion: A Comparative Analysis of Road Safety and Prevention of World Challenges in Low-Income and High-Income Countries

“…A study was conducted using a before-and-after methodology, comparing the number of collisions after the installation of the system. Te results showed a signifcant reduction in the number of collisions after the system was installed, suggesting that the system is efective in reducing collision risks on local roads [57]. Auclair [58] highlighted the negative impact of road trafc congestion, rating it at 54.5% in major cities worldwide.…”