Use of Real-Time Traffic and Signal Timing Data in Modeling Occupant Injury Severity at Signalized Intersections

Abstract

This study explored the use of real-time traffic events and signal timing data to determine the factors influencing the injury severity of vehicle occupants at intersections. The analysis was based on 3 years (2017–2019) of crash and high-resolution traffic data. The best fit regression was first identified by comparing the conventional regression model and logistic models with random effect. The logistic model with a heavy-tailed distribution random effect best fitted the data set, and it was used in the variable assessment. The model results revealed that about 13.6% of the unobserved heterogeneity comes from site-specific variations, which underlines the need to use the logistic model with a random effect. Among the real-time traffic events and signal-based variables, approach delay and platoon ratio significantly influenced the injury severity of vehicle occupants at 90% Bayesian credible interval. Additionally, the manner of a collision, occupant seat position, number of vehicles involved in a crash, gender, age, lighting condition, and day of the week significantly affected the vehicle occupant injury. The study findings are anticipated to provide valuable insights to transportation agencies for developing countermeasures to mitigate the crash severity risk proactively.

The Analysis of Spatial Patterns and Significant Factors Associated with Young-Driver-Involved Crashes in Florida

“…Fifty percent of crashes involving young drivers were also found to be due to intentional risky behavior and decisions [5]. Young drivers' beliefs, perceptions, and decision-making processes that may determine their willingness to engage in risky driving behaviors have also been examined in the literature [23,28]. This excessive risk-taking among young drivers was mainly due to failing to perceive hazardous situations compared to more experienced drivers [29].…”

Investigating the Probability of Potential Actions Performed by Drivers Experiencing Daytime Sun Glare-Induced Blindness

“…Intersection collision avoidance technologies including, but not limited to, automated traffic signal performance measure ( 45 ), cooperative intersection collision avoidance system for violations ( 46 ), and autonomous emergency brake on forward collision warning systems ( 47 ) can be helpful. These infrastructure-to-vehicle- and vehicle-to-vehicle communication systems are able to improve the safety condition of the locations prone to this hazard particularly during apparent sunrise and sunset.…”

Calibrated confidence learning for large-scale real-time crash and severity prediction

“…Some efforts to assess the viability of spatial and temporal transferability of real-time crash likelihood prediction models 30 or propose a workflow for real-time crash likelihood prediction, quantification, and classification 39 were also found. Real-time crash severity-related studies have evolved in the literature since 2010, and these studies are conducted in the USA 11,[40][41][42][43][44][45][46][47][48][49] , China 50,51 , France 52 , Greece 53 , and Iran 54 . Most of these studies are conducted on Freeways/Expressways/Toll Roads.…”

“…Most of these studies are conducted on Freeways/Expressways/Toll Roads. Some of them also considered using data collected from arterials 48,49,53 . The length of the roadway section considered in those studies ranged from very low, i.e., 7.7 miles 49 , to sufficiently large, i.e., 111 miles 47 .…”

“…Some of them also considered using data collected from arterials 48,49,53 . The length of the roadway section considered in those studies ranged from very low, i.e., 7.7 miles 49 , to sufficiently large, i.e., 111 miles 47 . The real-time data study period used for modeling or analyses in those studies ranged from 1 year 40,43,46 to 5 years 53,54 .…”