Long-combination vehicles (LCVs) have significant potential to increase economic productivity for shippers and carriers by decreasing the number of truck trips, thus reducing costs. However, size and weight regulations, triggered by safety concerns and, in some cases, infrastructure investment concerns, have prevented large-scale adoption of such vehicles. Information on actual crash performance is needed. To this end, this work uses standard and heteroskedastic ordered probit models, along with the United States’ Large Truck Crash Causation Study, General Estimates System, and Vehicle Inventory and Use Survey data sets, to study the impact of vehicle, occupant, driver, and environmental characteristics on injury outcomes for those involved in crashes with heavy-duty trucks. Results suggest that the likelihood of fatalities and severe injury is estimated to rise with the number of trailers, but fall with the truck length and gross vehicle weight rating (GVWR). While findings suggest that fatality likelihood for two-trailer LCVs is higher than that of single-trailer non-LCVs and other trucks, controlling for exposure risk suggest that total crash costs of LCVs are lower (per vehicle-mile traveled) than those of other trucks.

Analysis of Large-Truck Crash Severity Using Heteroscedastic Ordered Probit Models

You are given vehicle accident data from 337 rural interstate road sections in the state of Indiana for a 5-year period (1995 to 1999). The use of accidents per vehiclemiles traveled has an intuitive appeal in highway safety – providing a standardized measure of the relative safety of roadway segments that is more easily interpreted than the number of accidents per some time period. Because accident rates on specific highway segments are assessed over some finite time period, there is the likelihood that many highway segments will have no accidents reported during the analysis period. Thus, modeling accident rates by standard OLS would result in biased and inconsistent parameter estimates. The solution to this is to consider accident rates as a censored dependent variable (censored at zero) and apply a tobit model. For the accident-rate considered, the data will be left-censored with a clustering at zero (zero accidents per 100-million vehicle miles traveled) because accidents may not be observed on all roadway segments during the period of observation. For model estimation, the accident rate (number of accidents per 100-million VMT) was calculated as:

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Statistical and Econometric Methods for Transportation Data Analysis

Road safety research in the context of low- and middle-income countries: Macro-scale literature analyses, trends, knowledge gaps and challenges

Although the Occupational Safety and Health Administration (OSHA) has played a key role in decreasing safety accidents on construction sites, such reduction is not well perceived among the ...

Determining Critical Combinations of Safety Fatality Causes Using Spectral Clustering and Computational Data Mining Algorithms

Understanding the factors that contribute to traffic crashes can help provide a fundamental basis to plan and develop appropriate countermeasures for road safety issues emerging in particular on two-lane rural roads. However, most of the studies have focused on urban roadways and freeway systems, and few studies have investigated the issue of heterogeneity on two-lane rural roads. The purpose of this study is to uncover the risk factors influencing crash severity on two-lane rural roads in China. A sample of 1490 traffic crashes occurring on two-lane rural roads between 2012 and 2017 was collected from the Mouding County Highway Bureau in Yunnan, China. A random-parameter ordered probit model was estimated using these data to capture underlying unobserved characteristics in personal traits, vehicle attributes, roadway conditions, environmental factors, and crash attribute. To better understand the effect of critical factors on crash severity outcome probability, an elasticity analysis was then introduced. The results show that six factors such as driver’s attribution, illegal driving behaviour, access segment, day of week, vehicle type, and crash form have a significant impact on the injury severity, and the impacts of driving behaviours, access segment, and vehicle-fixed object crashes had significant variation across observations. Besides, the correlations between critical factors and the probability of serious injury sustained in traffic crashes are identified and discussed. The local driver indicator has more positive impact on the crash severity than nonlocal driver, and nonaccess segment appears a higher probability of serious or vicious collisions. It is worth mentioning that motorcycle-involved crashes do show an obvious correlation with crash injury severity. As for crash forms, vehicle-vehicle crashes are more likely to lead to severe crash injury. Besides, high-risk driving behaviour (e.g., fatigue driving, speeding, and converse driving), weekends, and holidays are found to have significant contribution to increasing the probability of traffic crash injuries and fatalities on two-lane rural roads.

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Exploring Risk Factors with Crash Severity on China Two-Lane Rural Roads Using a Random-Parameter Ordered Probit Model

Analysis of Traffic Accident Characteristic and Difference in Two-Lane Plateau Mountain Highways

The invention relates to a mountainous area double-lane highway hidden danger road section traffic conflict risk dynamic evaluation method, which comprises the following steps: firstly, obtaining vehicle driving track data and traffic flow data of a current implementation road section, calculating according to the track data to obtain a serious conflict discrimination threshold, and extracting thetraffic flow data 5 minutes before the occurrence moment of a serious traffic conflict; selecting mountainous area double-lane road traffic conflict risk dynamic possibility evaluation indexes and conflict severity evaluation indexes, establishing a road conflict risk evaluation model, and determining conflict risk possibility and conflict severity grades; and combining conflict risk possibilitygrading and conflict severity grading to construct a mountainous area double-lane highway traffic conflict risk dynamic evaluation comprehensive matrix, and determining the conflict risk grade of eachtraffic conflict of the current implementation road section. According to the method, the collected high-precision space-time trajectory data and traffic flow data are used for dynamically evaluatingthe traffic conflict risk of the mountainous area double-lane road, the data are easy to obtain, and the constructed model has relatively good prediction precision.

Shikun Xie

Papers

Exploring Risk Factors with Crash Severity on China Two-Lane Rural Roads Using a Random-Parameter Ordered Probit Model

Analysis of Traffic Accident Characteristic and Difference in Two-Lane Plateau Mountain Highways

Mountainous area double-lane highway hidden danger section traffic conflict risk dynamic evaluation method

A Thermal Assessment for High-Speed Angular Contact Ball Bearings Considering the Oil-Air Separation and Structural Constraint Effect