Rear-end Accidents Research Articles

Analysis of following vehicle driver injury severity in rear-end collision on straight road based on LightGBM and SHAP

Rear-end accidents, as one of the common accident types, may cause serious injuries to the driver and passengers. There are mutual coupling effects among causal features of rear-end accidents, and traditional analytical methods may lead to modeling distortion due to assumption constraints. In this study, the Light Gradient Boosting Machine (LightGBM), a machine learning algorithm, is used to model the injury severity of the following vehicle driver in a rear-end crash accident on a straight road, based on the data from the China In-depth Accident Study data. The Shapley Additive Explanations (SHAP) method was used to interpret the results of the LightGBM model and to analyze the relationship between factors and driver injury severity. The results show that location familiarity, willingness to take risks, and driving time have a significant impact on the injury severity for following vehicle drivers involved in rear-end crashes. Cloudy conditions increase a driver’s risk of being involved in a fatal or injured rear-end collision. In rain, snow, hail, and foggy conditions, have a higher propensity to cause driver fatalities in the crash event. The rear-end crash of passenger cars resulted in a higher death probability of the following vehicle driver compared to sedan and truck, and female drivers are more likely to be involved in uninjured accidents compared to males. These results are informative for preventing rear-end accidents and reducing the extent of accidental injuries.

Driver Injury from Vehicle Side Impacts When Automatic Emergency Braking and Active Seat Belts Are Used.

As an advanced driver assistance system, automatic emergency braking (AEB) can effectively reduce accidents by using high-precision and high-coverage sensors. In particular, it has a significant advantage in reducing front-end collisions and rear-end accidents. Unfortunately, avoiding side collisions is a challenging problem for AEB. To tackle these challenges, we propose active seat belt pretensioning on driver injury in vehicles equipped with AEB in unavoidable side crashes. Firstly, records of impact cases from China's National Automobile Accident In-Depth Investigation System were used to investigate a scenario in which a vehicle is impacted by an oncoming car after the vehicle's AEB system is triggered. The scenario was created using PreScan software. Then, the simulated vehicles in the side impact were devised using a finite element model of the Toyota Yaris and a moving barrier. These were constructed in HyperMesh software along with models of the driver's side seatbelt, side airbag, and side curtain airbag. Moreover, the models were verified, and driver out-of-position instances and injuries were evaluated in simulations with different AEB intensities up to 0.7 g for three typical side impact angles. Last but not least, the optimal combination of seatbelt pretensioning and the timing thereof for minimizing driver injury at each side impact angle was identified using orthogonal tests; immediate (at 0 ms) pretensioning at 80 N was applied. Our experiments show that our active seatbelt with the above parameters reduced the weighted injury criterion by 5.94%, 22.05%, and 20.37% at impact angles of 90°, 105°, and 120°, respectively, compared to that of a conventional seatbelt. The results of the experiment can be used as a reference to appropriately set the collision parameters of active seat belts for vehicles with AEB.

Research on Minimum Non-Collision Distance and Protection Strategy for Normal Train to Avoid Rear-End Accidents With Braking-Fault Train

Generally, a train adopts the method of emergency stop to avoid risks if there is any fault in the railway system. However, for braking system faults in a train, the relevant documents and specifications don’t provide a theoretical basis or solutions to ensure the parking safety of the breaking-fault train. For the tracking scenario, when a braking-fault train tracks the normal train running ahead, a calculation model of the tracking operation between trains with a failure coefficient is proposed. By detecting the braking-fault train information and the operation parameters of the train ahead, the model can calculate the minimum non-collision distance or predict the collision speed and position of these two trains. Considering the Yumen station of the Lanzhou-Xinjiang high-speed railway as an example, a series of experimental analyses are conducted under multiple fault scenarios, and the operation schemes that can avoid collision accidents are investigated. The experimental results show that the actual distance between the faulty and the front trains and the maximum acceleration that the front train could achieve are the two most critical factors. Finally, based on the information obtained from the above model results, the process of calculating the anti-collision scheme of the front train is summarized, and a protection strategy is designed, which provides the calculation basis and overall execution framework for the dispatching system to ensure the safety of these two trains.

Incorporating real-time weather conditions into analyzing clearance time of freeway accidents: A grouped random parameters hazard-based duration model with time-varying covariates

To minimize non-recurrent congestion, a better understanding of the factors that affect accident clearance time is crucial, in order to optimize incident management strategies. A number of methods have been developed to predict incident clearance duration, but few of those have considered the time-varying nature of certain observed factors. In addressing this gap in the literature, this study developed a grouped random parameters hazard-based duration model with time-varying covariates, while accounting for unobserved heterogeneity. Data on accidents, traffic, road inventory, and real-time weather condition were compiled for the Kaiyang freeway in 2014. Comparison of candidate models shows that the proposed model with Weibull distribution exhibits the best fit performance. The results suggest that the effects of rear-end accident, involvements of trucks or other vehicles, evening hours, and shoulder blockage on the hazard function are heterogeneous across observations. Other variables such as angle accident, injury severity, traffic volume and composition, morning or pre-dawn hours, and blockage of overtaking lane were also found to have significant but homogenous effects on accident clearance time. More importantly, the results also reveal the significant effects of the time-varying covariates (wind speed, temperature, and humidity). Accordingly, the viability and superiority of the proposed model in analyzing accident clearance time are confirmed. Overall, the results of this study are expected not only to improve traffic incident management by allowing government agencies to better understand factors affecting accident clearance times, but also to facilitate incident clearance through the recognition of time-varying pattern.

Cellphone laws and rear-end accidents

In an attempt to reduce accident frequency caused by distraction involving cellphone use, the state of California enacted two sets of laws banning cellphone use while driving. We examine the relationship between laws to ban cellphone use while driving and rear-end accident frequency in California. Using a panel data set that groups accidents by geographic location, we find evidence that the association between California’s handheld cellphone ban and the number of rear-end accidents is negative and statistically significant. In robustness testing, we find this result is unaltered when we use a broader definition of “collision accident.” These results have implications for public safety and transportation, automobile insurance markets and insurance regulation.

Study of the Risk of Truck Rear-End Collision in a Continuous Downhill Section of an Expressway

To improve the safety of truck traffic on continuous downhill sections of highways, optimize traffic safety management and the design of traffic safety facilities, study in-depth the risk of truck rear-end accidents on continuous downhill sections of highways, based on actual measurement data, this paper puts forward the evaluation index of rear-end risk considering the speed difference and headway time distance called the Collision Deceleration Rate (CDR). First, the principle of risk of truck rear-end accidents on long downhill road sections was analyzed, and the data of trucks travelling on long downhill road sections in a special control area of a western motorway were used to determine the risk-influencing factors as speed difference and headway time distance; then, the distribution law of effective CDR data was analyzed and calculated through a fitting distribution test, and the 85% quantile value of its distribution was taken as the threshold value of dangerous CDR; finally, the collision potential index (CPI) is combined with the concept (CPI) to establish a CDR-based continuous downhill truck rear-end risk probability model. Based on the tailgating accident data in the special control area of the motorway, the CDR-based continuous downhill truck tailgating risk probability model was applied and tested, and the results showed that: in the fitted distribution test, the CDR samples of the studied continuous downhill section obeyed lognormal distribution, and the threshold value of hazardous CDR is 0.4916 m/s2. There are more significant differences in the tailgating probability risk at different measurement points, while the tailgating risk are different. The correlation coefficient between the accident rate data and the probability risk data is r(X,Y)=94.5%, which is a strong correlation, i.e. the trend of the accident rate data and the probability risk data is consistent, indicating that the CDR-based probability model of tailgating accident risk can provide a scientific assessment basis for the risk study of continuous downhill sections of highways, and the research method can be used as a reference for other sections of highways.

Laryngeal Trauma, Its Types, and Management.

Laryngotracheal wounds are rare; however, they have a significant mortality rate. These wounds can be blunt or penetrating. Usually, the larynx is protected from blunt trauma by the sternum and jaw. A "clothesline" injury happens when the exposed neck is struck by a hard object, such as a wall wire or tree branch, or when an attack is intended to damage the larynx. Additionally, injuries may occur when the neck is stressed due to damage, such as in a rear-end accident that causes a whiplash-like injury or when the larynx is intentionally targeted for harm. Penetrating neck trauma may result in injury to the larynx. Assume a patient has suffered a penetrating or severe neck injury. It is usually evident from their medical history or a quick trauma evaluation in that case. However, it is recommended to be cautious for anterior neck injuries in general and to have a low threshold for establishing a surgical airway. The priority is securing an airway when a patient with a laryngeal injury arrives in the emergency room. The operating surgeon may request any flexible laryngoscopy, computed tomography (CT), esophagram, and chest X-ray for additional examination, depending on the nature of the damage and the patient's health. After the examination, the initial step in treating laryngeal injuries should be to locate and secure the airway. According to the evaluation and management based on the Schaefer classification system for laryngeal injury, the patient is treated based on whether the patient has impending airway obstruction or a stable airway. Medical management or observation and surgical management depend on the site and severity of the injury, patient condition, and type of injury. There are several complications related to laryngotracheal trauma, which can be minor or even fatal. Following successful treatment, postoperative and rehabilitative care, vocal rest, speech therapy, and swallowing therapy may be necessary.

Knowledge of state-recommended following-distance rules

Rear-end accidents are often attributed to the following vehicle not allowing sufficient headway to react in the event of a sudden change in velocity by the lead vehicle. Accordingly, most U.S. state DMVs offer seconds-based guidelines for safe following distances such as a ‘three-second rule’. However, studies have demonstrated that headways shorter than those recommendations are common. While numerous explanations can account for these observations, fundamentally, drivers must be aware of following distance recommendations in order to follow them. Here, we tested drivers’ knowledge of the following-distance rule (FDR). Results demonstrated that only 55.2% of survey respondents knew their state had an FDR, only 13.4% knew that it was based off of a seconds method, and only 2.4% accurately identified their state’s specific FDR. Factors associated with FDR knowledge included number of years of licensure and self-reported knowledge of driving rules.

The Real-World Effects of Route Familiarity on Drivers' Eye Fixations at Urban Intersections in Changsha, China.

A crucial factor, route familiarity, can affect traffic safety. Nevertheless, focus on the influence of route familiarity on drivers’ eye fixations at urban intersections has received less attention. Identifying the real-world effect of route familiarity on drivers’ eye fixations at urban intersections in Changsha, China, was the objective of this study. Their visual fixation indicators were recorded while unfamiliar drivers and familiar drivers drove a 9 km-long route with nine intersections in an urban environment, but their effectiveness was indicated by the data collected 150 m before the lane stop and 50 m after the lane stop at these intersections. From the analysis of the extracted data, the results indicated that route familiarity could influence drivers’ processing times in the left window (LW) and other areas (OT). Compared with familiar drivers, unfamiliar drivers had longer processing times and higher mental workloads for the right front (RF). For the vehicle’s front (RF, FL, FR), the sampling rates and mental workloads of unfamiliar drivers were higher than those of familiar drivers, but it was the opposite for the driver’s sides (LW, RW) and rear (LM, RM, ReM). It was also indicated that the phenomenon said to increase familiarity with the route and make drivers more likely to be distracted in urban intersections had not been found. From the present findings, the effect of route familiarity on drivers’ eye fixations at urban intersections was confirmed. The high accident risk of familiar drivers could be partly explained by the decrement in drivers’ eye fixation strategies. However, the strategies could not account for the phenomenon that more familiar drivers are involved in rear-end accidents. Therefore, the reason can be investigated based on drivers’ visual scanning strategies, their physiological signals and driving behavior in the future.

Impact Energy Absorbtion by Active Braking

Abstract Due to urbanization and the significantly increasing number of vehicles, urban roads are becoming more congested day by day, with the result that the rear-end collision has become the third most common type of collision. By developing and integrating active and passive safety systems, car manufacturers are working to prevent accidents and reduce the consequences of an accident. The present study examines a braking procedure and its applicability based on the integration of a passive and active safety system and provides development guidelines for the reduction of personal injuries and property damage in the event of a rear-end accident.

Variance-based global sensitivity analysis for rear-end crash investigation using deep learning

Traffic accidents are rare events with inconsistent spatial and temporal dimensions; thus, accident injury severity (INJ-S) analysis faces a significant challenge in its classification and data stability. While classical statistical models have limitations in accurately modeling INJ-S, advanced machine learning methods have no apparent equations to prioritize/analyze different contributing factors to predict INJ-S levels. Also, the intercorrelations among the input factors could make the results of a typical sensitivity analysis misleading. Rear-end accidents constitute the most frequent type of traffic accidents; and therefore, their associated INJ-S need more insight investigations. To resolve all these issues, this study presents a sophisticated approach based on a deep learning paradigm combined with a Variance-Based Globa1 Sensitivity Analysis (VB/GSA). The methodology proposes a deep residual neural networks structure that utilizes residual shortcuts (i.e., connections), unlike other neural network architectures. The connections allow the DRNNs to bypass a few layers in the deep network architecture, circumventing the regular training with high accuracy problems. The Monte Carlo simulation with the aid of the trained DRNNs model was conducted to investigate the impact of each explanatory factor on the INJ-S levels based on the VB/GSA. The developed methodology was used to analyze all rear-end accidents in North Carolina from 2010 to 2017. The performance of the developed methodology was evaluated utilizing some selected representative indicators and then compared with the well-known ordered logistic regression (OLR) model. The developed methodology was found to achieve an overall accuracy of 83% and attained a superior performance, as compared with the OLR model. Furthermore, the VB/GSA analysis could identify the most significant attributes to rear-end crashes INJ-S level.

The impact of CCT on driving safety in the normal and accident situation: A VR-based experimental study

Correlated color temperature (CCT) of the light source inside the road tunnel plays a crucial role in ensuring driving safety, which is demonstrated by previous studies that CCT influences not only visual effects but also non-visual effects. Although conventional laboratory experiments could simulate the CCT environment inside the tunnel to some extent, they fail to restore driving experience, let alone simulate driving behavior in the accident situation. It has largely remained unclear whether and how CCT would influence visual/non-visual performance of the subjects who are performing driving tasks, especially in the accident situation. Motivated by this gap, a virtual-reality-based framework for assessing the influence of CCT on the visual and non/visual performance in normal driving situation and in accident situation was proposed. In this study, tunnel models under seven different CCTs were created and a rear-end accident was designed in the tunnel. By integrating analog driving equipment, all participants were required to perform virtual driving tasks both in the normal situation and in the accident situation. The non-visual performance (driving fatigue) and the visual performance (reaction time) of the participants were collected and analyzed. Results show that the CCT of light source inside the tunnel was significant on the driving fatigue of the driver who was performing driving task, and it also had a significant impact on the visual performance when the driver was faced with a rear-end accident. Detailed experimental methodology, behavioral explanations underlying these findings, validity of results and practical implications are also discussed in the paper.

Exploring relationships between microscopic kinetic parameters of tires under normal driving conditions, road characteristics and accident types

IntroductionFreeway accidents are a leading cause of death in China, which also triggers substantial economic loss and an emotional burden to society. However, the internal mechanism of how microscopic kinetic parameters of vehicles influenced by road characteristics determine the occurrence of different types of accidents has not been explicitly studied. This research aimed to explore the “link role” of tire microscopic kinetic parameters in road characteristic variables and traffic accidents to aid in facilitating the traffic design and management, and thus to prevent traffic accident. Method: A mountain freeway in Zhejiang Province, China was used as the research object and the data used in this paper were obtained through a real-time vehicle experiment. Multiple estimation models, including the standard ordered logit (SOL) model, fixed parameters logit (FPL) model, and random parameters logit (RPL) model were established. Results: The findings show that road characteristics will affect the longitudinal kinetic characteristics of the vehicle and, consequently, map the level of risk of rear-end accidents. Driving compensation effects were also identified in this paper (i.e., the drivers tend to be more cautious in complicated driving circumstances). Another finding relating to the mountain freeway is that different tunnel characteristics (e.g., tunnel entrance and tunnel exit) have different effects on different types of traffic accidents. Practical Applications: The framework proposed in this article can provide new insight for researchers to enlarge the research subjects of both explanatory and outcome variables in accident analysis. Future research could be implemented to consider more driving conditions.

The crash injury severity prediction of traffic accident using an improved wrappers feature selection algorithm

The crash injury severity prediction of traffic accident is the prerequisite for driving decisions under dangerous conditions. This paper puts forward a new wrapper feature selection algorithm to improve the prediction accuracy of the injury severity. Firstly, based on Gini index and Mutual information, the importance of factors is analyzed by the comprehensive evaluation criteria, according to the importance score, the factors were selected by sequential backward selection. Secondly, three models, that is RF (Random Forest), C4.5 (C4.5 Decision Tree) and SVM (Support Vector Machine) are established to verify the prediction accuracy of selected subsets. In order to verify the proposed algorithm, based on the FARS(Fatality Analysis Reporting System) in the NHTSA(National Highway Traffic Safety Administration), a total of 6,295 rear-end accidents including 23 candidate factors were screened, the results demonstrate that the accuracy of the three models increases with the elimination of redundant variables, among them the SVM model has better predictive performance, the significant factors are obtained which include seat belts, airbag, the relative speed, vehicle weight, etc. finally the sensitivity analysis of significant factors is implemented and some suggestions are given to improve traffic safety.

Suggestions on Over-the-horizon Cloud Warning System for Collision Avoidance of Two Intersections

As the highway transportation network expands and modern technologies in the automobile industry develops, automobiles contribute a lot to human life, which have also led to many problems such as traffic accidents, traffic jams, environmental pollution, and energy waste. Take traffic accidents as an example. According to the China’s website of the State Administration of Work Safety, in 2011, about 211,000 people died or injured in traffic accidents, with the death toll hitting 62,000. Among all those accidents, rear-end collisions account for a large proportion, as the freeway rear-end accidents was about 33.4% of the total accidents in China and 24% in America. These traffic accidents have not only resulted in huge economic losses, but have also made highways more congested and occupied medical resources.

Effects of Traffic Calming Measures on Mobility, Road Safety and Pavement Conditions on Abuakwa-Bibiani Highway

Traffic calming measures (TCMs) have been widely adopted as the major speed control devices in Ghana. While initial evaluations have underscored their effectiveness, little research has been conducted to assess their characteristics relative to design guidelines and the negative externalities associated with their misapplications. The objectives of this research were to; i) establish the characteristics of TCMs, and their implications on mobility; ii) to establish essential speed parameters in communities where TCMs are deployed iii) to establish pavement conditions abutting traffic calming measures and; iv) to analyse the accident typology on the Abuakwa-Bibiani road. Method: Firstly, a radar gun and android speed measuring device were used to unobtrusively measure vehicles’ spot speeds and profiles respectively at different locations relative to the TCMs. Also, visual inspections were carried out to assess the pavement conditions surrounding the TCMs while a geodetic laser levelling instrument and a surveying staff were used to obtain the crown heights of the TCMs. Further, the accident typology on the candidate road were analysed to establish how the TCMs are affecting road crashes. Results: Vehicle speeds were generally lower than the posted speed limits in settlements which have TCMs. Nevertheless, the proportion of accident casualties being pedestrians despite lower speeds in settlements remains unacceptably high. Further, the collision typology on this highway were predominantly loss control and rear-end accidents suggesting that the TCMs are playing insidious roles in some of the crash types on this road. Pavement distresses such as depressions, cracks, rutting, ravelling, potholes and deposit of debris were common in the vicinity of the TCMs. Conclusion: Our findings suggest that awareness creation among communities along the highway may be amenable to improving pedestrians’ safety than relying on only engineering countermeasures. The predominant collision types; loss control and rear-end implies that the TCMs are inadvertently contributing to some accident types. For a long term and sustainable speed control, bypassing settlements, use of active dynamic speed bumps (smart or intelligent speed bumps); and a deterrence-based electronic enforcement such as the Automatic Number Plate Recognition System which uses the demerit points offer better alternatives on the highways.

Optimizing Speed Limits Upstream of Freeway Reconstruction and Expansion Work Zones Based on Driver Characteristics

AbstractTraffic incidents occurring in freeway work zones mainly include rear-end accidents and roadside accidents, as well as collisions between vehicles and traffic facilities and construction pe...

Simulating the relative influence of tire, vehicle and driver factors on forward collision accident rates

Introduction: There is currently a strong focus within the automotive industry centered on traffic safety, with topics such as distracted driving, accident avoidance technologies, and autonomous vehicles. These papers tend to focus on the possible improvements from a single factor. However, there are many factors that are present in each accident, and it is important to understand the influence of each factor on the relative accident risk in order to identify the most effective approaches for improving driver safety. Rear-end accidents tend to be the most common accident type with approximately 1.8 M cases, or 31% of all accidents, in 2012, according to NHTSA. Of the rear-end accident scenarios, approximately 18–23% occur on wet surfaces. Method: A Monte Carlo Forward Collision Simulation models the conditions of a wet rear-end accident and estimates the relative impact of various vehicle collision parameters. The model takes distributions of these parameters as inputs, and outputs a risk of collision relative to a known reference case. The parameters that can be studied include: tire grip level, road grip level, vehicle velocity, following distances, and the presence of vehicle technologies (ABS, FCW & AEB). Distributions of some of these parameters have been improved thanks to Naturalistic Driving Study data from SHRP2. Results: This study shows that these vehicle systems have a large impact on safety and can change the amount of influence attributed to other parameters such as tire grip levels. As the use of automated vehicle systems expands, so will the influence of tire grip performance levels on collision risks. Practical Applications: It is more important than ever for consumers and auto manufacturers to consider tire performance levels. Therefore, the tire industry should continue to focus on wet grip as a key performance related to safety and should strive to continue to improve tire performance.

Mobile Phone Use in a Car-Following Situation: Impact on Time Headway and Effectiveness of Driver's Rear-End Risk Compensation Behavior via a Driving Simulator Study.

Mobile phone use while driving has become one of the leading causes of traffic accidents and poses a significant threat to public health. This study investigated the impact of speech-based texting and handheld texting (two difficulty levels in each task) on car-following performance in terms of time headway and collision avoidance capability; and further examined the relationship between time headway increase strategy and the corresponding accident frequency. Fifty-three participants completed the car-following experiment in a driving simulator. A Generalized Estimating Equation method was applied to develop the linear regression model for time headway and the binary logistic regression model for accident probability. The results of the model for time headway indicated that drivers adopted compensation behavior to offset the increased workload by increasing their time headway by 0.41 and 0.59 s while conducting speech-based texting and handheld texting, respectively. The model results for the rear-end accident probability showed that the accident probability increased by 2.34 and 3.56 times, respectively, during the use of speech-based texting and handheld texting tasks. Additionally, the greater the deceleration of the lead vehicle, the higher the probability of a rear-end accident. Further, the relationship between time headway increase patterns and the corresponding accident frequencies showed that all drivers’ compensation behaviors were different, and only a few drivers increased their time headway by 60% or more, which could completely offset the increased accident risk associated with mobile phone distraction. The findings provide a theoretical reference for the formulation of traffic regulations related to mobile phone use, driver safety education programs, and road safety public awareness campaigns. Moreover, the developed accident risk models may contribute to the development of a driving safety warning system.

Performance properties of health-related measurement instruments in whiplash: systematic review protocol

BackgroundWhiplash is a common traumatic cervical injury which is most often a consequence of rear-end motor vehicle accidents. It has been estimated that up to 50% of the whiplash patients suffer from chronic symptoms, resulting in extensive individual and societal burden. Several measurement instruments are used for initial assessment of whiplash and evaluation of response to treatment. However, a comprehensive assessment of the performance of these measures is lacking. Furthermore, there is no consensus on the most relevant outcome domains and their corresponding measurement instruments of choice. This systematic review aims to identify, describe, and critically appraise the performance properties of health-related measurement instruments in whiplash population.MethodsThe following literature databases will be searched from their date of establishment: PubMed, Embase®, MEDLINE, CINAHL Complete, PsycINFO, and HAPI. All original articles evaluating the reliability, validity, responsiveness, and feasibility of health-related measurement instruments in whiplash will be included, without additional restriction on their intended use, source of data, and structure. Risk of bias will be assessed using the COSMIN Risk of Bias checklist. Findings of the studies will be judged against the criteria for good measurement properties, and results from all studies will be qualitatively summarized to generate an overall quality of findings. Overall quality of evidence will be determined using a modified GRADE approach, which will be used in conjunction with the overall quality of results for generation of recommendations. Two reviewers will perform all steps of the review independently. Discrepancies will be discussed between the reviewers, and in case of remaining disagreement, the senior reviewer will make the final decision.DiscussionThis systematic review will summarize the body of literature on health-related measurement instruments in whiplash, aiming to facilitate the selection of high-quality measurement instrument for researchers and physicians. Findings of this study will guide the ongoing efforts for development of a core outcome set.Systematic review registrationPROSPERO reference number CRD42018070901