A temporal assessment of distracted driving injury severities using alternate unobserved-heterogeneity modeling approaches

Alnawmasi, Nawaf; Mannering, Fred

doi:10.1016/j.amar.2022.100216

Cited by 29 publications

(4 citation statements)

References 86 publications

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“…With the use of the simulation, Alogaili and Mannering 78 found that pedestrian-vehicle crashes in the daytime would cause as much as 16.45% less severe injuries compared to the crashes at nighttime, given both crash times having the same other associated factors. Additionally, the application of this simulation has also been adopted by numerous recent crash severity studies to gain a better overview understanding of how two or more crash conditions are different in influencing injury severities 38 , 40 , 80 , 90 . Likewise, this study also adopted this simulation for predictive comparison between restrained and unrestrained driver-injury severities and investigating how injury severity distribution changed over time.…”

Section: Resultsmentioning

confidence: 99%

“…In this regard, the model can be more flexible in uncovering the unobserved heterogeneity by allowing the interaction effect between non-random parameters with the mean and variance of the random parameters on the injury-severity probability. Following the previous studies 32 , 80 , 83 , 84 , 86 , let be a vector of estimable parameters that vary across crash observations, which is derived as: where is a mean parameter estimateed across all crashes 90 , 91 , denotes a vector of the variables that capture heterogeneity in the mean that influences injury severity n, with parameter vector 86 , is a vector of variables that captures heterogeneity in the standard deviation with the corresponding vector 86 , and is a disturbance term.…”

Section: Methodsmentioning

confidence: 99%

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Temporal instability and differences in injury severity between restrained and unrestrained drivers in speeding-related crashes

Champahom

Wisutwattanasak

et al. 2023

Sci Rep

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Upon detecting a crash impact, the vehicle restraint system locks the driver in place. However, external factors such as speeding, crash mechanisms, roadway attributes, vehicle type, and the surrounding environment typically contribute to the driver being jostled within the vehicle. As a result, it is crucial to model unrestrained and restrained drivers separately to reveal the true impact of the restraint system and other factors on driver injury severities. This paper aims to explore the differences in factors affecting injury severity for seatbelt-restrained and unrestrained drivers involved in speeding-related crashes while accounting for temporal instability in the investigation. Utilizing crash data from Thailand between 2012 and 2017, mixed logit models with heterogeneity in means and variances were employed to account for multi-layered unobserved heterogeneity. For restrained drivers, the risk of fatal or severe crashes was positively associated with factors such as male drivers, alcohol influence, flush/barrier median roadways, sloped roadways, vans, running off the roadway without roadside guardrails, and nighttime on unlit or lit roads. For unrestrained drivers, the likelihood of fatal or severe injuries increased in crashes involving older drivers, alcohol influence, raised or depressed median roadways, four-lane roadways, passenger cars, running off the roadway without roadside guardrails, and crashes occurring in rainy conditions. The out-of-sample prediction simulation results are particularly significant, as they show the maximum safety benefits achievable solely by using a vehicle's seatbelt system. Likelihood ratio test and predictive comparison findings highlight the considerable combined impact of temporal instability and the non-transferability of restrained and unrestrained driver injury severities across the periods studied. This finding also demonstrates a potential reduction in severe and fatal injury rates by simply replicating restrained driver conditions. The findings should be of value to policymakers, decision-makers, and highway engineers when developing potential countermeasures to improve driver safety and reduce the frequency of severe and fatal speeding-related single-vehicle crashes.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Temporal instability and differences in injury severity between restrained and unrestrained drivers in speeding-related crashes

Champahom

Wisutwattanasak

et al. 2023

Sci Rep

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“…We reviewed past studies on crash severity heterogeneity to determine the randomness of the parameters. Te basis for decision-making was the signifcance of the standard deviation of each random parameter [67].…”

Section: Methodsmentioning

confidence: 99%

Modeling the Motorcycle Crash Severity on Nonintersection Urban Roadways in the Australian State of Victoria Using a Random Parameters Logit Model

Seyfi

Aghabayk

Mamaghan

et al. 2023

Journal of Advanced Transportation

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Due to a lack of physical protection and balance, motorcycle riders are one of the most vulnerable road users and are more likely to suffer severe injuries than motorists. Between 2009 and 2020, about 60% of motorcycle crashes occurred on nonintersection urban roadways in Victoria, Australia. While considerable research on intersections and their influence on the severity of motorcycle crashes has been conducted, there are limited studies on motorcycle crashes on nonintersection roadways. Since gathering all information from every motorcycle crash may not be possible, heterogeneity can arise from unobserved factors and cause problems in developing reliable crash severity models. Therefore, this study aims to investigate the factors contributing to motorcycle crash severity on Victorian nonintersection urban roadways while considering the heterogeneity of factors. A total of 10,897 nonintersection motorcycles crash data from the beginning of 2009 to November 2020 in the State of Victoria, Australia, were analyzed. A random parameters (mixed) logit model (RPL) was used for evaluating motorcycle crashes. The severity of motorcycle crashes was divided into three categories: fatal injury, serious injury, and minor injury. Also, marginal effects were calculated to see how each parameter estimate affects crash severity outcomes. The RPL model results showed that some factors increased the likelihood of fatal injuries. These factors included not wearing a helmet, being in the older rider age group, riding during the early morning or midnight hours, weekend motorcycle use, riding in the early morning or midnight hours (00:00–6:29 A.M), and insufficient lighting (dark and dusk/dawn). Also, the following factors enhanced the probability of serious injuries: having a pillion passenger, having a motorcycle age of more than 7 years, riding at higher speed limits (more than 50 km/h) or during peak hours in the morning (6:30−8:59 A.M), and being in the younger age group (less than 26 years old). The findings from this study are valuable resources for road safety policy managers to develop effective strategies for improving motorcyclists’ safety at nonintersections. This may include improving the light conditions at nonintersection, encouraging the motorcyclist to maintain motorcycles regularly, and educating the motorcyclist to wear a helmet, avoid distractions, and ride responsibly on the weekends.

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“…Although most of these studies have used survey and interview-based approaches, these methods have certain limitations in capturing the external factors such as weather conditions and traffic/roadway characteristics that could lead to distracted driving. Several studies have used driving simulators and behavioral models to understand the impact of these external factors and how these distractions affect the driver's behavior [15][16][17][18][19].…”

Section: Distracted Driving Literaturementioning

confidence: 99%

Reducing Distracted Driving and Improving Consistency with Brine Truck Automation

Mahlberg,

Mathew,

Desai

et al. 2024

Electronics

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Salt brine is routinely used by transportation agencies to pre-treat critical infrastructure such as bridges, ramps, and underpasses in advance of winter storms. This requires an operator turning on and off brine controls while driving at highway speeds, introducing driver distraction and consistency challenges. In urban areas, such as Indianapolis, a 5500-gallon tractor trailer with a gross vehicle weight of 80,000 pounds is typically used and the driver may have 1200 on/off activations while covering 318 miles during a pre-treatment shift. This study conducted in collaboration with Indiana Department of Transportation has worked with their truck upfitters to adapt geo-fenced agriculture spraying controls to seven trucks that use the Global Positioning System (GPS) position of the truck to activate the sprayer valves when the trucks enter and exit geo-fenced areas that require pre-treatment. This automated brine system enhances safety, reduces driver workload, and ensures the consistent application of brine in designated areas. Furthermore, as additional environmental constraints and reporting requirements evolve, this system has the capability of reducing application rates in sensitive areas and provides a comprehensive geo-coded application history. The Indiana Department of Transportation has scaled deployment for treating interstates and major arterials with brine. This deployment on 5500-gallon tankers, used on I-64/65/69/70/74, and 465, eliminates over 10,000 driver distraction events during every statewide pre-treatment event.

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A temporal assessment of distracted driving injury severities using alternate unobserved-heterogeneity modeling approaches

Cited by 29 publications

References 86 publications

Temporal instability and differences in injury severity between restrained and unrestrained drivers in speeding-related crashes

Temporal instability and differences in injury severity between restrained and unrestrained drivers in speeding-related crashes

Modeling the Motorcycle Crash Severity on Nonintersection Urban Roadways in the Australian State of Victoria Using a Random Parameters Logit Model

Reducing Distracted Driving and Improving Consistency with Brine Truck Automation

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