Red-Light-Running Crashes’ Classification, Comparison, and Risk Analysis Based on General Estimates System (GES) Crash Database

Abstract

Red-light running (RLR) has been identified as one of the prominent contributing factors involved in signalized intersection crashes. In order to reduce RLR crashes, primarily, a better understanding of RLR behavior and crashes is needed. In this study, three RLR crash types were extracted from the general estimates system (GES), including go-straight (GS) RLR vehicle colliding with go-straight non-RLR vehicle, go-straight RLR vehicle colliding with left-turn (LT) non-RLR vehicle, and left-turn RLR vehicle colliding with go-straight non-RLR vehicle. Then, crash features within each crash type scenario were compared, and risk analyses of GS RLR and LT RLR were also conducted. The results indicated that for the GS RLR driver, the speed limit displayed the highest effects on the percentages of GS RLR collision scenarios. For the LT RLR driver, the number of lanes displayed the highest effects on the percentages of LT RLR collision scenarios. Additionally, the drivers who were older than 50 years, distracted, and had a limited view were more likely to be involved in LT RLR accidents. Furthermore, the speeding drivers were more likely to be involved in GS RLR accidents. These findings could give a comprehensive understanding of RLR crash features and propensities for each RLR crash type.

The Dilemma of Road Safety in the Eastern Province of Saudi Arabia: Consequences and Prevention Strategies

“…The highest chances of fatality among these variables were for hitting a pedestrian barrier, which had a coefficient value β of 1.865, followed by hit pedestrian crashes, having a β value of 1.289. It is interesting to note from Table 6 that although the variable of violating red signal was significant, it had a negative coefficient (β = −1.572), indicating that the chance of fatality was low for such instances, which seems counter-intuitive compared to previous studies [47][48][49][50]. This anomaly could be attributed to the fact that red-light cameras accompany the majority of signalized intersections in Saudi Arabia.…”

An Edge-Based Framework for Enhanced Road Safety of Connected Cars

“…As depicted in Figure 1, one or more base stations provide connectivity over the geographical area and ensure data communication with passingby vehicles, which are equipped with On Board Units (OBU). Note that intersections may be unregulated or regulated by traffic lights: in both cases our solution is effective, since, as reported in [20]- [22], it is unfortunately quite frequent that drivers do not obey traffic light signals. Furthermore, as reported in a study conducted by NHTSA (National Highway Traffic Safety Administration), more than 50% of the total intersection-related crashes occur at intersections that are regulated by traffic lights [23].…”

A Review on Drivers’ Red Light Running Behavior Predictions and Technology Based Countermeasures

“…Intersection crashes represent a significant portion of these fatalities and lifethreatening injuries, with the USA, for instance, reporting 45% of severe injuries and 22% of fatal crashes occurring at intersections [3]. The major factors of signalised intersection crashes are identified to be a failure to break immediately at the red light onset, miscalculating turning angles and distances of other vehicles, and deliberately running the red light [4]. At signalised intersections, drivers are often faced with such judgement errors during the onset of yellow or amber signals and may become confused and accelerate through the amber light or brake hard, potentially resulting in a rear end or right angle collision and or serious injury outcomes [5,6].…”