Majority Of Crashes Research Articles

Drivers’ Knowledge, Attitude and Practices Towards Traffic Rules and Regulations

Research frequently reports that the majority of crashes (up to 80%), are the fault of drivers. Further, the WHO reports that most fatal crashes occur in low- and middle-income countries (LMIC). In LMIC, including Pakistan, most drivers have low levels of knowledge about traffic rules and regulations, have negative attitudes towards rules and regulations and often violate road safety rules. This study used a structured survey of drivers in Karachi, Pakistan (n=260). Most respondents were aware that helmet use for motorbike riders is compulsory (74.6%), agreed it was important to follow road signs (74.2%) and wear a seat belt (64.6%). However, over half did not know the speed limit in residential areas (54.6%) and almost half considered drug use when driving was not dangerous or were against the penalty or fine for violation of traffic laws (45.4%). In addition, 45.8% of all drivers thought driving licenses were unnecessary. This study suggests there may be low levels of driver knowledge of certain road rules (e.g. speed limit), negative attitudes about certain safe driving practices (drug driving), and low levels of value placed on driving license in Karachi, Pakistan. Analysis suggest that knowledge and attitude affect driver practices in Karachi, Pakistan. Strengthening enforcement and related public communication measures about traffic rules and greater penalties that are sufficiently deterring for the violators of the traffic rules is needed. There must also be a formal mechanism to issue the driving licence after a proper test of the knowledge of road rules and driving following those rules.

Safe Driving Analytics

Abstract: Are you aware that violations of safe driving regulations account for over half of all traffic accidents? However, what if we gave drivers who adhere to those guidelines rewards? It might significantly impact the number of accidents brought on by careless driving. To improve our understanding of how people drive, researchers are also examining how data from automobile cameras may be used. However, the amount of data we collect makes it more difficult to use data science and artificial intelligence to examine it all. In this article, we discuss how we're creating tools to support that analysis and how we might use the data to comprehend the factors that affect people's driving behaviors. We are essentially developing a system that receives video from automobile cameras, interprets it, and then assists us in determining which types of driving pose a risk. To be able to identify dangerous drivers could significantly contribute to making our roads safer for everyone, as driving behavior plays a major role in the majority of crashes. Therefore, improving our understanding of driving behavior could have a revolutionary impact on road safety and the reduction of fatalities and accidents.

The influences of strict and post-strict lockdowns due to the Covid-19 pandemic on crash severity on rural roads: A case study of Khorasan Razavi, Iran

Covid-19 has influenced traffic patterns due to restrictions on travel. During COVID-19 restrictions, many people opted to travel by private cars for their mandatory trips instead of using public transportation, while many non-essential trips were cancelled. The changes in travel restrictions have influenced road safety outcomes. Utilizing decision tree modelling, the current research seeks to evaluate the impact of the COVID-19 pandemic on the severity of road traffic crashes, considering two severity levels: fatal and non-fatal crashes in Iran's Khorasan Razavi province. The analysis considers the time period from May 2019 to October 2021 and includes three main intervals: the pre-COVID-19, strict lockdown period, and post-strict lockdown period. A spatial–temporal analysis of crash data was performed utilizing a data fusion approach with results presented using a Classification and Regression Tree (CART) model. The data fusion approach uses a variety of data sources in order to obtain a thorough overview of the phenomenon being studied. In this study, independent descriptive factors, such as geometric design, weather, temporal variables, driver behavior, crash type, and traffic attributes, were included in the analysis. A similar pattern for crash severity was observed during the pre-COVID-19 and post-strict lockdown phases, with the majority of crashes being non-fatal. However, fatal crashes were more prevalent during the strict lockdown period. Among the independent variables associated with fatalities were traffic volume. In this study we identified that higher traffic volumes resulted in a higher crash frequency, however they were also associated with lower speeds, resulting in a decline in the severity of crashes. Other variables included lack of awareness as a driver behavior and cloudiness as a weather condition.

Evaluation of risk factors for road accidents under mixed traffic: Case study on Indian highways

This paper presents an evaluation of risk factors for highway crashes under mixed traffic conditions. The basis of selecting study sites was abutting land use, roadway, and traffic characteristics. Accordingly, the study selected thirteen segments on the existing highway network in the state of West Bengal of India, covering a wide spectrum of such road attributes. A systematic investigation based on site-specific accident data to capture the highway sections' safety features revealed that the crash rate has steadily increased for years with traffic regardless of roadway category and conditions. A number of risk factors that affect road accidents were identified; they are mid-block access, pavement and shoulder conditions, vehicle involvement, time of day, and road configuration, i.e., two and multi-lane. The empirical observation indicates that the crash rate is relatively lower on multi-lane highways; however, the severity of any crash on such a road is relatively high. Notably, the crash frequencies on such roads are less during daylight hours due to the lane-based unidirectional traffic movement. This is quite the opposite during nighttime when drivers exhibit an inability to meet traffic contingencies, thereby increasing crash risk. The majority of crashes on two-lane highways are, on the other hand, due to unsafe driving manoeuvers. The study also observed that frequent mid-block accesses and poor shoulder conditions reduce scopes to rectify driving errors and increase crash risk as a consequence. The paper subsequently suggests proactive approaches to identify safety deficits at the time of planning and designing.

Stock price crashes in emerging markets

This paper studies large price declines of individual stocks in 22 emerging markets. Using analyst reports as a proxy for information arrivals, we find that majority of crashes in emerging markets are not accompanied by information events, and these crashes are followed by price reversals. Further analyses show that crashes in countries with a better information environment or a lower level of openness are less likely to reverse in the short run, suggesting that factors such as information transparency and market integration may shape the large swings in emerging market stock prices.

Reducing risky driving: Assessing the impacts of an automatically-assigned, targeted web-based instruction program

Introduction: Transportation safety research has consistently shown driver behavior is the primary cause in the majority of crashes. This study evaluated the effectiveness of an automatically-assigned, targeted web-based instruction program to reduce risky driving behavior. Method: This quasi-experiment used a within-subjects, multiple-baseline stepwise ABC design; where “A” was the Phase I baseline, “B” was the Phase II driver awareness of program, and “C” was the Phase III WBI program. Results: A significant reduction in rates of risky driving behaviors coincided with the implementation of the WBI program, even for those drivers who did not receive WBI but were included in the program. More specifically, excessive speeding was significantly reduced by 73.93% from baseline to intervention across all drivers. For those drivers who received WBI, the program coincided with statistically significant reductions in speeding, hard braking, and hard cornering. The first WBI course assigned and completed was the most impactful in reducing at-risk driving behavior. Conclusions: These results show that the automatically-assigned, targeted WBI program was an effective method in reducing risky driving behaviors, not only for those drivers that received training, but for all drivers. The authors hypothesize the reduction in risky driving behaviors was not the result of the WBI, but instead from the implicit feedback of being assigned a training courses, the development of implicit, non-specific goals to reduce risky driving behaviors that result in a WBI course assignment, and the resulting increased driver accountability created by the WBI program. Practical application: Through the use of an automatically-assigned, targeted WBI program, fleets may have fewer crashes and insurance claims. This reduction in crashes and insurance claims may result in lower insurance premiums and may help to prevent injuries and save lives.

Characteristics of fatal road crashes involving unlicensed drivers or riders: Implications for countermeasures

Drivers or riders without a valid license are involved in 10% of fatal road crashes in Norway. This was shown by an analysis of data from all fatal crashes in the period 2005–2014. A literature review shows that unlicensed drivers have a considerably increased crash risk. Such crashes could be prevented by electronic driver authentication, i.e., a technical system for checking that a driver or rider has legal access to a vehicle before driving is permitted. This can be done by requiring the driver/rider to identify themselves with a national identity number and a unique code or biometric information before driving may commence. The vehicle thereafter verifies license availability and vehicle access by communication with a central register. In more than 80% of fatal crashes with unlicensed drivers/riders, speeding and/or drug influence contributed to the crash. This means that a majority of crashes with unlicensed drivers alternatively could be prevented by already available systems, such as alcolock and speed limit dependent speed adapters. These systems will have a wider influence, by preventing crashes also among licensed drivers. Mandatory implementation of alcolock, speed limiter, and electronic driver authentication in all motorized vehicles is estimated to prevent up to 28% of fatal road crashes, depending on effectiveness of the systems.

Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures

Autonomous vehicle (AV) technology has advanced rapidly in recent years with some automated features already available in vehicles on the market. AVs are expected to reduce traffic crashes as the majority of crashes are related to driver errors, fatigue, alcohol, or drugs. However, very little research has been conducted to estimate the safety impact of AVs. This paper aims to investigate the safety impacts of AVs using a simulation-based surrogate safety measure approach. To this end, safety impacts are explored through the number of conflicts extracted from the VISSIM traffic microsimulator using the Surrogate Safety Assessment Model (SSAM). Behaviours of human-driven vehicles (HVs) and AVs (level 4 automation) are modelled within the VISSIM’s car-following model. The safety investigation is conducted for two case studies, that is, a signalised intersection and a roundabout, under various AV penetration rates. Results suggest that AVs improve safety significantly with high penetration rates, even when they travel with shorter headways to improve road capacity and reduce delay. For the signalised intersection, AVs reduce the number of conflicts by 20% to 65% with the AV penetration rates of between 50% and 100% (statistically significant at p<0.05). For the roundabout, the number of conflicts is reduced by 29% to 64% with the 100% AV penetration rate (statistically significant at p<0.05).

Predictors of recovery in cyclists hospitalised for orthopaedic trauma following an on-road crash

BackgroundAs cycling-related injury rates are on the rise, there is a need to understand the long term outcomes of these patients in order to quantify the burden of injury and to inform injury prevention strategies. This study aimed to investigate predictors of return to work and functional recovery in a cohort of cyclists hospitalised for orthopaedic trauma from crashes occurring on-road. MethodsA retrospective analysis of data from the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR) was conducted for patients who were hospitalised for orthopaedic trauma following a cycling crash that occurred on-road between July 2007 and June 2015. ResultsThere were 1787 injured cyclists admitted at the participating hospitals. Most cyclists were male (79%), resided in major cities (89%) and were in the highest socioeconomic quintile (52%). The majority of crashes were either non-collisions (41%) or collisions with a motor vehicle (35%). A smaller proportion of cyclists who collided with motor vehicles had returned to work and had returned to pre-injury functional levels at 12 months post-injury, when compared to collisions with other impact counterparts and non-collisions. Mixed effects logistic regression models revealed that compensable patients demonstrated lower odds of complete functional recovery and return to work when compared with non-compensable patients. ConclusionCyclists who collided with motor vehicles had worse outcomes compared to crashes with other impact counterparts and non-collision events. These findings provide support for reducing the potential for interaction between cyclists and motor vehicles.

Road Traffic Injury on Rural Roads in Tanzania: Measuring the Effectiveness of a Road Safety Program

Objective: Road traffic injuries (RTIs) are a major public health burden, especially in low- and middle-income countries. There is limited data on RTIs in low-volume, rural African settings. This study attempted to survey all individuals living in households within 200 m of two low-volume rural roads in Tanzania and to collect data on RTIs.Methods: Local communities and users of the Bago to Talawanda road (intervention site) and Kikaro to Mihuga road (control site) were targeted and received an intensive program of road safety measures tailored using the crash characteristics of the baseline sample. Demographic data on all household members were collected, and those individuals who suffered an RTI in the previous 3 months had comprehensive information collected about the crash characteristics and the socioeconomic impact. The follow-up data collection occurred nine months after the baseline data were collected.Results: The majority of crashes that caused an RTI involved a motorcycle (71%) and the majority of victims were male (82%) with an average age of 27. Injuries to the legs (55%) were most common and the average length of time away from normal activity was 27 (±33) days. RTI incidence at the intervention site increased during the course of the study (incidence before vs. incidence after) and was unchanged in the community control (incidence before vs. incidence after).Conclusion: The incidence of RTIs in the low-volume rural setting is unacceptably high and most commonly associated with motorcycles. The change in incidence is unreliable due to logistic restraints of the project and more research is needed to quantify the impact of various RTI prevention strategies in this setting. This study provides insight into road traffic injuries on low-volume rural roads, areas where very little research has been captured. Additionally, it provides a replicable study design for those interested in collecting similar data on low-volume rural roads.

The impact of high-risk drivers and benefits of limiting their driving degree of freedom

The perception of drivers regarding risk-taking behaviour is widely varied. High-risk drivers are the segment of drivers who are disproportionately represented in the majority of crashes. This study examines the typologies of drivers in risk-taking behaviour, the common high-risk driving errors (speeding, close following, abrupt lane-changing and impaired driving), their safety consequences and the technological (ITS) devices for their detection and correction. Limiting the driving degree of freedom of high-risk drivers is proposed and its benefits on safety as well as traffic operations are quantified using VISSIM microscopic traffic simulation at various proportions of high-risk drivers; namely, 4%, 8% and 12%. Assessment of the safety benefits was carried out by using the technique of simulated vehicle conflicts which was validated against historic crashes, and reduction in travel time was used to quantify the operational benefits. The findings imply that limiting the freedom of high-risk drivers resulted in a reduction of crashes by 12%, 21% and 27% in congested traffic conditions; 9%, 13% and 18% in lightly congested traffic conditions as well as 9%, 10% and 17% in non-congested traffic conditions for high-risk drivers in proportions of 4%, 8% and 12% respectively. Moreover, the surrogate safety measures indicated that there was a reduction in crash severity levels. The operational benefits amounted to savings of nearly 1% in travel time for all the proportions of high-risk drivers considered. The study concluded that limiting the freedom of high-risk drivers has safety and operational benefits; though there could be social, legal and institutional concerns for its practical implementation.

Understanding Factors Affecting Safety Effects of Indirect Driveway Left-Turn Treatments

This article summarizes research that evaluates the effects of various contributing factors on the safety effects of an important indirect driveway left-turn treatment: using U-turns as alternatives to direct left turns from driveways. Crash data were collected at 140 roadway segments where U-turns are used as alternatives to replace direct left turns from driveways, and 32 three-leg unsignalized intersections where direct left turns from driveways are permitted. It was found that U-turn crashes only account for a very small percentage of crashes related with right turns followed by U-turns (RTUT). U-turn crashes occur very infrequently at median openings and signalized intersections. The majority of crashes related with RTUT occur at the section between driveways and downstream U-turn locations. A crash prediction model was developed to identify the factors that contribute to the crashes related with RTUT at weaving sections (the segments between driveways and downstream U-turn locations). The model shows that the major street average daily traffic (ADT), the location of U-turn bay, and the separation distances between driveway exits and downstream U-turn locations significantly impact the safety of RTUT at weaving sections.

Incidence and characteristics of school bus crashes and injuries

Objective Studies of school bus crashes have focused on the biomechanics of catastrophic collisions, with very few examining crash incidence. Methods Crashes in the state of Iowa were examined from January 2002 through December 2005. School bus crashes were identified through the Iowa Crash Data, a comprehensive database of all reported crashes in the State of Iowa. School bus mileage data were provided by the Iowa Department of Education. School bus crash, fatality, and injury rates were calculated and differences in crash and injury characteristics between school buses and other vehicles were examined. Results The school bus crash, fatality and non-fatal injury rates were 320.7, 0.4 and 13.6 per 100 million bus miles travelled, respectively. School bus crash fatality and injury rates were 3.5 and 5.4 times lower than overall all vehicle crash fatality and injury rates, respectively. Drivers of other vehicles were more likely to have caused the crash than the bus driver ( P < 0.001). Conclusions School buses experience low crash rates, and the majority of crashes do not lead to injury. Buses are among the safest forms of road transportation, and efforts to educate drivers of other vehicles may help reduce crashes with buses.

Motor Vehicle Crashes and Injury among High School and College Aged Drivers. Miami-Dade County, FL 2005

Purpose To describe motor vehicle crashes and injury occurring among high school and college aged drivers in order to guide prevention efforts targeted toward reducing motor vehicle related injuries among the young population. Methods The 2005 crash data used in this study was obtained from the Florida Department of Highway Safety and Motor Vehicles. Data was analyzed using SAS by age, injury severity, alcohol/drug involvement, restraint use, day of week, and time of day. Results There were 16,311 drivers between the ages of 15–24 involved in motor vehicle crashes. Of these, over a 1/3 were injured, 14% were unrestrained, and 1.5% were alcohol and/or drug related. Alcohol and/or drug use among college aged drivers 20–24 years of age was higher than that in other age groups. The majority of crashes (38%) occurred between the hours of 12 PM and 5 PM. Friday and Saturday accounted for 30% of all crashes in this age group. High school and college aged drivers were less likely to use safety restraints compared to all other age groups. Those without restraints were 5 times more likely to suffer severe injuries. Drivers who were using alcohol and/or drugs were twice as likely to be unrestrained and three times more likely to be severely injured. Among those using alcohol and/or drugs 27% were not restrained. Over half of drivers using alcohol and/or drugs crashed between the hours of 12 AM and 5 AM. Conclusion Interventions targeting 15–24 year olds should focus on increasing safety belt use in this age group. Furthermore, college based interventions should also aim to reduce impaired driving due to alcohol and/or drugs. Since the majority of crashes occurred between the hours of 12 PM and 5 PM, intervention campaigns should target students as they leave the school premises for lunch or after class. In addition, localities should make use of readily available data such as the Florida Department of Highway Safety and Motor Vehicles crash database in order to enhance injury surveillance activities and program planning and evaluation.