Objectives: Both the National Vital Statistics System (NVSS) and the Fatality Analysis Reporting System (FARS) can be used to examine motor vehicle crash (MVC) deaths. These 2 data systems operate independently, using different methods to collect and code information about the type of vehicle (e.g., car, truck, bus) and road user (e.g., occupant, motorcyclist, pedestrian) involved in an MVC. A substantial proportion of MVC deaths in NVSS are coded as “unspecified” road user, which reduces the utility of the NVSS data for describing burden and identifying prevention measures. This study aimed to describe characteristics of unspecified road user deaths in NVSS to further our understanding of how these groups may be similar to occupant road user deaths.
Methods: Using data from 1999 to 2015, we compared NVSS and FARS MVC death counts by road user type, overall and by age group, gender, and year. In addition, we examined factors associated with the categorization of an MVC death as unspecified road user such as state of residence of decedent, type of medical death investigation system, and place of death.
Results: The number of MVC occupant deaths in NVSS was smaller than that in FARS in each year and the number of unspecified road user deaths in NVSS was greater than that in FARS. The sum of the number of occupant and unspecified road user deaths in NVSS, however, was approximately equal to the number of FARS occupant deaths. Age group and gender distributions were roughly equivalent for NVSS and FARS occupants and NVSS unspecified road users. Within NVSS, the number of MVC deaths listed as unspecified road user varied across states and over time. Other categories of road users (motorcyclists, pedal cyclists, and pedestrians) were consistent when comparing NVSS and FARS.
Conclusions: Our findings suggest that the unspecified road user MVC deaths in NVSS look similar to those of MVC occupants according to selected characteristics. Additional study is needed to identify documentation and reporting challenges in individual states and over time and to identify opportunities for improvement in the coding of road user type in NVSS. 相似文献
Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.
Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).
Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.
Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy. 相似文献
Objective: The purpose of this study was to identify and better understand the features of fatal injuries in cyclists aged 75 years and over involved in collisions with either hood- or van-type vehicles.
Methods: This study investigated the fatal injuries of cyclists aged 75 years old and over by analyzing accident data. We focused on the body regions to which the fatal injury occurred using vehicle–bicycle accident data from the Institute for Traffic Accident Research and Data Analysis (ITARDA) in Japan. Using data from 2009 to 2013, we examined the frequency of fatally injured body region by gender, age, and actual vehicle travel speed. We investigated any significant differences in distributions of fatal injuries by body region for cyclists aged 75 years and over using chi-square tests to compare with cyclists in other age groups. We also investigated the cause of fatal head injuries, such as impact with a road surface or vehicle.
Results: The results indicated that head injuries were the most common cause of fatalities among the study group. At low vehicle travel speeds for both hood- and van-type vehicles, fatalities were most likely to be the result of head impacts against the road surface.
The percentage of fatalities following hip injuries was significantly higher for cyclists aged 75 years and over than for those aged 65–74 or 13–59 in impacts with hood-type vehicles. It was also higher for women than men in the over-75 age group in impacts with these vehicles.
Conclusions: For cyclists aged 75 years and over, wearing a helmet may be helpful to prevent head injuries in vehicle-to-cyclist accidents. It may also be helpful to introduce some safety measures to prevent hip injuries, given the higher level of fatalities following hip injury among all cyclists aged 75 and over, particularly women. 相似文献
Introduction: This study performed a path analysis to uncover the behavioral pathways (from contributing factors, pre-crash actions to injury severities) in bicycle-motor vehicle crashes. Method: The analysis investigated more than 7,000 bicycle-motor vehicle crashes in North Carolina between 2007 and 2014. Pre-crash actions discussed in this study are actions of cyclists and motorists prior to the event of a crash, including “bicyclist failed to yield,” “motorist failed to yield,” “bicyclist overtaking motorist,” and “motorist overtaking bicyclist.” Results: Model results show significant correlates of pre-crash actions and bicyclist injury severity. For example, young bicyclists (18 years old or younger) are 23.5% more likely to fail to yield to motor traffic prior to the event of a crash than elder bicyclists. The “bicyclist failed to yield” action is associated with increased bicyclist injury severity than other actions, as this behavior is associated with an increase of 5.88 percentage points in probability of a bicyclist being at least evidently injured. The path analysis can highlight contributing factors related to risky pre-crash actions that lead to severe injuries. For example, bicyclists traveling on regular vehicle travel lanes are found to be more likely to involve the “bicyclist failed to yield” action, which resulted in a total 44.38% (7.04% direct effect + 37.34% indirect effect) higher likelihood of evident or severe injuries. The path analysis can also identify factors (e.g., intersection) that are not directly but indirectly correlated with injury severity through pre-crash actions. Practical Applications: This study offers a methodological framework to quantify the behavioral pathways in bicycle-motor vehicle crashes. The findings are useful for cycling safety improvements from the perspective of bicyclist behavior, such as the educational program for cyclists. 相似文献
Introduction: Using connected vehicle technologies, pedestrian to vehicle (P2V) communication applications can be installed on smart devices allowing pedestrians to communicate with drivers by broadcasting discrete safety messages, received by drivers in-vehicle, as an alternative to expensive fixed-location physical safety infrastructure. Method: This study consists of designing, developing, and deploying an entirely cyber-physical P2V communication system within the cellular vehicle to everything (C-V2X) environment at a mid-block crosswalk to analyze drivers’ reactions to in-vehicle advanced warning messages, the impacts of the advanced warning messages on driver awareness, and drivers’ acceptance of this technology. Results: In testing human subjects with, and without, advanced warning messages upon approaching a mid-block crosswalk, driver reaction, acceptance, speed, eye tracking data, and demographic data were collected. Through an odds ratio comparison, it was found that drivers were at least 2.44 times more likely to stop for the pedestrian with the warning than without during the day, and at least 1.79 times more likely during the night. Furthermore, through binary logistic regression analysis, it was found that driver age, time of the day, and the presence of the advanced warning message all had strong, significant impacts with a confidence value of at least 98% (p < 0.02) on the rate at which drivers stopped for the pedestrian. Conclusions: The results from this study indicate that the advanced warning message sent within the C-V2X had a strong, positive impact on driver behavior and understanding of pedestrian intent. Practical Applications: Pedestrian crashes and fatality rates at mid-block crossings continue to increase over the years. Connected vehicle technology utilizing smart devices can be used as a means for communications between pedestrians and drivers to deliver safety messages. State and local city planners should consider geofencing designated mid-block crossings at which this technology operates to increase pedestrian safety and driver awareness. 相似文献
Objective: This article estimates the safety potential of a current commercially available connected vehicle technology in real-world crashes.Method: Data from the Centre for Automotive Safety Research's at-scene in-depth crash investigations in South Australia were used to simulate the circumstances of real-world crashes. A total of 89 crashes were selected for inclusion in the study. The crashes were selected as representative of the most prevalent crash types for injury or fatal crashes and had potential to be mitigated by connected vehicle technology. The trajectory, speeds, braking, and impact configuration of the selected in-depth cases were replicated in a software package and converted to a file format allowing “replay” of the scenario in real time as input to 2 Cohda Wireless MK2 onboard units. The Cohda Wireless onboard units are a mature connected vehicle technology that has been used in both the German simTD field trial and the U.S. Department of Transport's Safety Pilot project and have been tuned for low false alarm rates when used in the real world. The crash replay was achieved by replacing each of the onboard unit Global Positioning System (GPS) inputs with the simulated data of each of the involved vehicles. The time at which the Cohda Wireless threat detection software issued an elevated warning was used to calculate a new impact speed using 3 different reaction scenarios and 2 levels of braking.Results: It was found that between 37 and 86% of the simulated crashes could be avoided, with highest percentage due a fully autonomous system braking at 0.7 g. The same system also reduced the impact speed relative to the actual crash in all cases. Even when a human reaction time of 1.2 s and moderate braking of 0.4 g was assumed, the impact speed was reduced in 78% of the crashes. Crash types that proved difficult for the threat detection engine were head-on crashes where the approach angle was low and right turn–opposite crashes.Conclusions: These results indicate that connected vehicle technology can be greatly beneficial in real-world crash scenarios and that this benefit would be maximized by having the vehicle intervene autonomously with heavy braking. The crash types that proved difficult for the connected vehicle technology could be better addressed if controller area network (CAN) information is available, such as steering wheel angle, so that driver intent can be inferred sooner. More accurate positioning in the real world (e.g., combining satellite positioning and accelerometer data) would allow the technology to be more effective for near-collinear head-on and rear-end crashes, because the low approach angles that are common in such crashes are currently ignored in order to minimize false alarms due to positioning uncertainty. 相似文献