Bicyclist injury severities in bicycle-motor vehicle accidents

This research explores the factors contributing to the injury severity of bicyclists in bicycle-motor vehicle accidents using a multinomial logit model. The model predicts the probability of four injury severity outcomes: fatal, incapacitating, non-incapacitating, and possible or no injury. The analysis is based on police-reported accident data between 1997 and 2002 from North Carolina, USA. The results show several factors which more than double the probability of a bicyclist suffering a fatal injury in an accident, all other things being kept constant. Notably, inclement weather, darkness with no streetlights, a.m. peak (06:00 a.m. to 09:59 a.m.), head-on collision, speeding-involved, vehicle speeds above 48.3 km/h (30 mph), truck involved, intoxicated driver, bicyclist age 55 or over, and intoxicated bicyclist. The largest effect is caused when estimated vehicle speed prior to impact is greater than 80.5 km/h (50 mph), where the probability of fatal injury increases more than 16-fold. Speed also shows a threshold effect at 32.2 km/h (20 mph), which supports the commonly used 30km/h speed limit in residential neighborhoods. The results also imply that bicyclist fault is more closely correlated with greater bicyclist injury severity than driver fault.     

Factors influencing injury severity of motor vehicle-crossing pedestrian crashes in rural Connecticut

The ordered probit model was used to evaluate the effect of roadway and area type features on injury severity of pedestrian crashes in rural Connecticut. Injury severity was coded on the KABCO scale and crashes were limited to those in which the pedestrians were attempting to cross two-lane highways that were controlled by neither stop signs nor traffic signals. Variables that significantly influenced pedestrian injury severity were clear roadway width (the distance across the road including lane widths and shoulders, but excluding the area occupied by on-street parking), vehicle type, driver alcohol involvement, pedestrian age 65 years or older, and pedestrian alcohol involvement. Seven area types were identified: downtown, compact residential, village, downtown fringe, medium-density commercial, low-density commercial, and low-density residential. Two groups of these area types were found to experience significantly different injury severities. Downtown, compact residential, and medium- and low-density commercial areas generally experienced lower pedestrian injury severity than village, downtown fringe, and low-density residential areas.     

A multinomial logit analysis of risk factors influencing road traffic injury severities in the Erzurum and Kars Provinces of Turkey

A retrospective cross-sectional study is conducted analysing 11,771 traffic accidents reported by the police between January 2008 and December 2013 which are classified into three injury severity categories: fatal, injury, and no injury. Based on this classification, a multinomial logit analysis is performed to determine the risk factors affecting the severity of traffic injuries. The estimation results reveal that the following factors increase the probability of fatal injuries: drivers over the age of 65; primary-educated drivers; single-vehicle accidents; accidents occurring on state routes, highways or provincial roads; and the presence of pedestrian crosswalks. The results also indicate that accidents involving cars or private vehicles or those occurring during the evening peak, under clear weather conditions, on local city streets or in the presence of traffic lights decrease the probability of fatal injuries. This study comprises the most comprehensive database ever created for a Turkish sample. This study is also the first attempt to use an unordered response model to determine risk factors influencing the severity of traffic injuries in Turkey.     

A note on modeling pedestrian-injury severity in motor-vehicle crashes with the mixed logit model

Pedestrian-injury severity has been traditionally modeled with approaches that have assumed that the effect of each variable is fixed across injury observations. This assumption ignores possible unobserved heterogeneity which is likely to be particularly important in pedestrian injuries because unobserved physical health, strength, and behavior may significantly affect the pedestrians’ ability to absorb collision forces. To address such unobserved heterogeneity, this research applies a mixed logit model to analyze pedestrian-injury severity in pedestrian-vehicle crashes. Using police-reported collision data from 1997 through 2000 from North Carolina, several factors were found to more than double the average probability of fatal injury for pedestrians in motor-vehicle crashes including: darkness without streetlights (400% increase in fatality probability), vehicle is a truck (370% increase), freeway (330% increase), speeding involved (360% increase), and collisions involving a motorist who had been drinking (250% increase). It was also found that the effect of pedestrian age was normally distributed across observations, and that as pedestrians became older the probability of fatal injury increased substantially. Heterogeneity in the mean of the random parameters for the freeway and pedestrian-solely-at-fault collision indicators was related to pedestrian gender, and heterogeneity in the mean of the random parameters for the traffic-sign and motorist-back-up indicators was related to pedestrian age.     

Pedestrians’ injury patterns in Ghana

Objective

To establish the associations between pedestrian injury and explanatory variables such as vehicular characteristics, temporal trends, and road environment.

Methods

A retrospective analysis of de-identified pedestrian crash data between 2002 and 2006 was conducted using the Building & Road Research Institute's crash data bank. We estimated the odds ratios associated with casualty fatalities using a multinomial logistic regression.

Results

There were 812 pedestrian casualties reported, out of which 33% were fatal, 45% sustained serious injuries requiring hospitalization, and 22% were slightly injured but were not hospitalized. Crossing the roadway accounted for over 70% of all pedestrians’ deaths. Whereas fatalities in 2002 and 2003 were statistically indistinguishable from those of 2004 (p > 0.05), in comparison with 2004, there were significantly fewer fatalities in 2005 and 2006 (78% and 65% reduction respectively). According to police report, the probability that a pedestrian fatality occurring in Ghana attributable to excessive speeding is 65%. The adjusted odds ratio of pedestrian fatality associated with speeding compared with driver inattentiveness was 3.6 (95% CI: 2.5-5.2). It was also observed that generally, lighter vehicular masses were associated with lower pedestrian fatalities. Compared with buses, pedestrians were less likely to die when struck by private cars (52%), pick-up trucks (57%), and motorcycles (86%).

Conclusion

Pedestrian death remains the leading cause of fatality among urban road users in Ghana. Risk factors associated with pedestrian fatality include being hit by heavy vehicles, speeding, and roadside activities such as street hawking, jaywalking and nighttime walking. Steps which may contribute to reducing pedestrian fatalities include measures to reduce vehicles speeds in settlements, providing traffic medians and lighting streets in settlements, and discouraging street and roadside activities such as hawking.     

Analyzing fault in pedestrian–motor vehicle crashes in North Carolina

Crashes between pedestrians and motor vehicles are an important traffic safety concern. This paper explores the assignment of fault in such crashes, where observed factors are associated with pedestrian at fault, driver at fault, or both at fault. The analysis is based on police reported crash data for 1997 through 2000 in North Carolina, U.S.A.The results show that pedestrians are found at fault in 59% of the crashes, drivers in 32%, and both are found at fault in 9%. The results indicate drivers need to take greater notice of pedestrians when drivers are turning, merging, and backing up as these are some of the prime factors associated with the driver being found at fault in a crash.Pedestrians must apply greater caution when crossing streets, waiting to cross, and when walking along roads, as these are correlated with pedestrians being found at fault. The results suggest a need for campaigns focused on positively affecting pedestrian street-crossing behavior in combination with added jaywalking enforcement. The results also indicate that campaigns to increase the use of pedestrian visibility improvements at night can have a significant positive impact on traffic safety. Intoxication is a concern and the results show that it is not only driver intoxication that is affecting safety, but also pedestrian intoxication.The findings show in combination with other research in the field, that results from traffic safety studies are not necessarily transferable between distant geographic locations, and that location-specific safety research needs to take place. It is also important to further study the specific effects of the design of the pedestrian environment on safety, e.g. crosswalk spacing, signal timings, etc., which together may affect pedestrian safety and pedestrian behavior.     

Diagnostic analysis of the logistic model for pedestrian injury severity in traffic crashes

This study attempts to evaluate the injury risk of pedestrian casualties in traffic crashes and to explore the factors that contribute to mortality and severe injury, using the comprehensive historical crash record that is maintained by the Hong Kong Transport Department. The injury, demographic, crash, environmental, geometric, and traffic characteristics of 73,746 pedestrian casualties that were involved in traffic crashes from 1991 to 2004 are considered. Binary logistic regression is used to determine the associations between the probability of fatality and severe injury and all contributory factors. A consideration of the influence of implicit attributes on the trend of pedestrian injury risk, temporal confounding, and interaction effects is progressively incorporated into the predictive model. To verify the goodness-of-fit of the proposed model, the Hosmer–Lemeshow test and logistic regression diagnostics are conducted. It is revealed that there is a decreasing trend in pedestrian injury risk, controlling for the influences of demographic, road environment, and other risk factors. In addition, the influences of pedestrian behavior, traffic congestion, and junction type on pedestrian injury risk are subject to temporal variation.     

Factors contributing to hit-and-run in fatal crashes

Hit-and-run in a collision is a punishable offence as it delays crash notification thereby delaying emergency response which increases the likelihood of traffic fatality. To obtain a better understanding of hit-and-run behavior, a logistic regression model has been applied in this study to identify the factors that might affect the occurrence of hit-and-run in fatal crashes in California, USA. Our results show that roadway functional class, routes, traffic flow, types of roadway section, speed limit, traffic control device, functioning of traffic control device, lighting condition, roadway alignment and roadway profile are important determinants that engineers can target to reduce hit-and-run in fatal crashes. In addition, targeted traffic enforcement should be performed on weekends and nighttime.     

Factors influential in making an injury severity difference to older drivers involved in fixed object-passenger car crashes

To identify factors influencing severity of injury to older drivers in fixed object-passenger car crashes, two sets of sequential binary logistic regression models were developed. The dependent variable in one set of models was driver injury severity, whereas for the other it was the crash severity (most severe injury in the crash). For each set of models, crash or injury severity was varied from the least severity level (no injury) to the highest severity level (fatality) and vice versa. The source of data was police crash reports from the state of Florida. The model with the best fitting and highest predictive capability was used to identify the influence of roadway, environmental, vehicle, and driver related factors on severity. Travel speed, restraint device usage, point of impact, use of alcohol and drugs, personal condition, gender, whether the driver is at fault, urban/rural nature and grade/curve existence at the crash location were identified as the important factors for making an injury severity difference to older drivers involved in single vehicle crashes.     

Exploring the impacts of factors contributing to tram-involved serious injury crashes on Melbourne tram routes

Previous research is limited regarding factors influencing tram-involved serious injury crashes. The aim of this study is to identify key vehicle, road, environment and driver related factors associated with tram-involved serious injury crashes. Using a binary logistic regression modelling approach, the following factors were identified to be significant in influencing tram-involved fatal crashes in Melbourne: tram floor height, tram age, season, traffic volume, tram lane priority and tram travel speed. Low floor trams, older trams, tram priority lanes and higher tram travelling speeds are more likely to increase tram-involved fatal crashes. Higher traffic volume decreases the likelihood of serious crashes. Fatal crashes are more likely to occur during spring and summer. Findings from this study may offer ideas for future research in the area of tram safety and help to develop countermeasures to prevent specific fatality types from occurring.     

Analyzing pedestrian crash injury severity at signalized and non-signalized locations

This study identifies and compares the significant factors affecting pedestrian crash injury severity at signalized and unsignalized intersections. The factors explored include geometric predictors (e.g., presence and type of crosswalk and presence of pedestrian refuge area), traffic predictors (e.g., annual average daily traffic (AADT), speed limit, and percentage of trucks), road user variables (e.g., pedestrian age and pedestrian maneuver before crash), environmental predictors (e.g., weather and lighting conditions), and vehicle-related predictors (e.g., vehicle type). The analysis was conducted using the mixed logit model, which allows the parameter estimates to randomly vary across the observations. The study used three years of pedestrian crash data from Florida. Police reports were reviewed in detail to have a better understanding of how each pedestrian crash occurred. Additionally, information that is unavailable in the crash records, such as at-fault road user and pedestrian maneuver, was collected. At signalized intersections, higher AADT, speed limit, and percentage of trucks; very old pedestrians; at-fault pedestrians; rainy weather; and dark lighting condition were associated with higher pedestrian severity risk. For example, a one-percent higher truck percentage increases the probability of severe injuries by 1.37%. A one-mile-per-hour higher speed limit increases the probability of severe injuries by 1.22%. At unsignalized intersections, pedestrian walking along roadway, middle and very old pedestrians, at-fault pedestrians, vans, dark lighting condition, and higher speed limit were associated with higher pedestrian severity risk. On the other hand, standard crosswalks were associated with 1.36% reduction in pedestrian severe injuries. Several countermeasures to reduce pedestrian injury severity are recommended.     

Driver fatalities versus car mass using a new exposure approach

A new approach to estimating exposure is presented and applied to determining relations between car mass and driver fatality likelihood. The new approach considers two groups of fatal crashes in the FARS files. The first group contains crashes in which car drivers are killed in single car crashes or in crashes with trucks. These are both examples of non-two car crashes. It is hypothesized that the likelihood of a car driver fatality in such crashes depends on car mass. The second group of fatal crashes contains crashes in which either pedestrians or motorcyclists are killed in crashes with cars. It is hypothesized that the likelihood of the pedestrian or motorcyclist being killed in such crashes is independent of the mass of the car. The new exposure approach implies that the ratio of the number of people killed in the mass dependent crash to those killed in the mass independent crash gives an estimate of how car mass affects the likelihood of a driver fatality. The approach further implies that the estimate obtained is an estimate of the physical effect of mass, essentially independent of driver behavior. It is found that the new exposure approach yields relationships between driver fatality likelihood and car mass that are more precise and consistent than can normally be obtained in accident research. The effects found, which are attributed to the physical properties of the vehicle, essentially independent of driver behavior, are larger (for example, a driver of a 900 kg car is 2.6 times as likely to be killed as is a driver of a 1800kg car) than those based on fatalities per car.     

Logistic regression analysis of pedestrian casualty risk in passenger vehicle collisions in China

A large number of pedestrian fatalities were reported in China since the 1990s, however the exposure of pedestrians in public traffic has never been measured quantitatively using in-depth accident data. This study aimed to investigate the association between the impact speed and risk of pedestrian casualties in passenger vehicle collisions based on real-world accident cases in China. The cases were selected from a database of in-depth investigation of vehicle accidents in Changsha-IVAC. The sampling criteria were defined as (1) the accident was a frontal impact that occurred between 2003 and 2009; (2) the pedestrian age was above 14; (3) the injury according to the Abbreviated Injury Scale (AIS) was 1+; (4) the accident involved passenger cars, SUVs, or MPVs; and (5) the vehicle impact speed can be determined. The selected IVAC data set, which included 104 pedestrian accident cases, was weighted based on the national traffic accident data. The logistical regression models of the risks for pedestrian fatalities and AIS 3+ injuries were developed in terms of vehicle impact speed using the unweighted and weighted data sets. A multiple logistic regression model on the risk of pedestrian AIS 3+ injury was developed considering the age and impact speed as two variables. It was found that the risk of pedestrian fatality is 26% at 50 km/h, 50% at 58 km/h, and 82% at 70 km/h. At an impact speed of 80 km/h, the pedestrian rarely survives. The weighted risk curves indicated that the risks of pedestrian fatality and injury in China were higher than that in other high-income countries, whereas the risks of pedestrian casualty was lower than in these countries 30 years ago. The findings could have a contribution to better understanding of the exposures of pedestrians in urban traffic in China, and provide background knowledge for the development of strategies for pedestrian protection.     

Pedestrian-vehicle crashes and analytical techniques for stratified contingency tables

In 1999 there were 450 fatalities due to road crashes in Riyadh, the capital of Saudi Arabia, of which 130 were pedestrians. Hence, every fourth person killed on the roads is a pedestrian. The aim of this study is to investigate pedestrian-vehicle crashes in this fast-growing city with two objectives in mind: to analyze pedestrian collisions with regard to their causes, characteristics, location of injury on the victim's body, and most common patterns and to determine the potential for use of the odds ratio technique in the analysis of stratified contingency tables. Data from 638 pedestrian-vehicle crashes reported by police, during the period 1997-1999, were used. A systematic sampling technique was followed in which every third record was used. The analysis showed that the pedestrian fatality rate per 10(5) population is 2.8. The rates were relatively high within the childhood (1-9 years) and young adult (10-19 years) groups, and the old-age groups (60 - > 80 years), which indicate that young as well as the elderly people in this city are more likely to be involved in fatal accidents of this type than are those in other age groups. The analysis revealed that 77.1% of pedestrians were probably struck while crossing a roadway either not in a crosswalk or where no crosswalk existed. In addition, the distribution of injuries on the victims' bodies was determined from hospital records. More than one-third of the fatal injuries were located on the head and chest. An attempt was made to conduct an association analysis between crash severity (i.e. injury or fatal) and some of the study variables using chi-square and odds ratio techniques. The categorical nature of the data helped in using these analytical techniques.     

A cellular automaton simulation model for pedestrian and vehicle interaction behaviors at unsignalized mid-block crosswalks

At unsignalized crosswalks, interactions between pedestrians and vehicles often lead to traffic safety hazards due to absence of traffic control and unclear right-of-ways. To address this safety problem, there is a need to understand the interaction behaviors of pedestrians and vehicles that are complicated by a variety of traffic and roadway attributes. The prime objective of this study is to establish a reliable simulation model to represent the vehicle yielding and pedestrian crossing behaviors at unsignalized crosswalks in a realistic way. The model is calibrated with detailed behavioral data collected and extracted from field observations. The capability of the calibrated model in predicting the pedestrian-interaction events as well as estimating the driver yielding rate and pedestrian delay are also tested and demonstrated. Meanwhile, the traffic dynamics in the vicinity of the crosswalk can be meaningfully represented with simulation results based on the model. Moreover, with the definitions of the vehicle-pedestrian conflicts, the proposed model is capable to evaluate the pedestrian safety. Thereby, the simulation model has the potential to serve as a useful tool for assessing safety performance and traffic operations at existing facilities. Furthermore, the model can enable the evaluation of policy effectiveness and the selection of engineering treatments at unsignalized crosswalks to improve safety and efficiency of pedestrian crossing.     

Comprehensive analysis of vehicle-pedestrian crashes at intersections in Florida

This study analyzes vehicle-pedestrian crashes at intersections in Florida over 4 years, 1999-2002. The study identifies the group of drivers and pedestrians, and traffic and environmental characteristics that are correlated with high pedestrian crashes using log-linear models. The study also estimates the likelihood of pedestrian injury severity when pedestrians are involved in crashes using an ordered probit model. To better reflect pedestrian crash risk, a logical measure of exposure is developed using the information on individual walking trips in the household travel survey. Lastly, the impact of average traffic volume on pedestrian crashes is examined. As a result of the analysis, it was found that pedestrian and driver demographic factors, and road geometric, traffic and environment conditions are closely related to the frequency and injury severity of pedestrian crashes. Higher average traffic volume at intersections increases the number of pedestrian crashes; however, the rate of increase is steeper at lower values of average traffic volume. Based on the findings in the analysis, some countermeasures are recommended to improve pedestrian safety.     

Paediatric slow-speed non-traffic fatalities: Victoria, Australia, 1985–1995

An important group of fatal incidents are slow-speed pedestrian non-traffic incidents to children, which account for 14% of accidental deaths from all causes in Victorian children under 5 years of age between 1985 and 1995, and 12% of pedestrian deaths of all ages. In Victoria, Australia, the database of the state Consultative Council on Obstetric and Paediatric Morbidity and Mortality was utilised to identify paediatric slow-speed pedestrian non-traffic-accident deaths in the local population. Additional data relating to the car and its driver, the child, and the circumstances of the incident were abstracted from records kept by the State Coroner and the Victorian compulsory third party traffic injury insurance organisation. Twenty eight Victorian children were identified who had died in one of three types of incident (driverless cars, child interacting with the vehicle and driver, and drivers who were unaware of the child's proximity). These incidents were more common in rural areas compared with urban, usually occurring at the child's home. The child was with or near an adult on all occasions. The vehicle was usually being driven by a relative, and was reversing in a higher proportion of ‘unaware’ incidents compared with the ‘interactive’ type. The association of ‘off-road’ family vehicles and trucks with these incidents appears to be increasing, especially in recent years. These findings suggest some countermeasures, including the separation of vehicle driveways from children's play areas, and object vicinity ultrasonic warning devices for vehicles.     

An assessment of the effect of driver age on traffic accident involvement using log-linear models

Statistical models were developed to help understand the relationship between the driver age and several important accident-related factors and circumstances such as injury severity, collision types, average daily traffic (ADT), roadway character, speed ratio, alcohol involvement, and accident location. By using techniques of categorical analysis on the 1994 and 1995 Florida accident database, four log-linear models with three variables in each model with all possible two-way interactions were developed. In order to compare the differences in response between the age groups and a particular accident-related variable, odds multipliers were computed. The effects of age and accident-related factors were examined, and interactions among them were considered. The results indicated significant relationships between the driver age and ADT, injury severity, manner of collision, speed, alcohol involvement, and roadway character. The findings' contribution to the understanding of the effect of age on accident involvement is addressed. A discussion of how log-linear and logit modeling with estimation of `odds multipliers' may contribute to traffic safety studies is also provided.     

The influence of alcohol, age and number of passengers on the night-time risk of driver fatal injury in New Zealand

Breath alcohol measurements and other data collected at randomly selected roadside sites were combined with data on fatally injured drivers in crashes occurring on the same weekdays and times (Friday and Saturday nights) at locations matched by the size of the nearest town. A logistic model was fitted to these data for the years 1995-2000 to estimate the effects of alcohol, driver's age and the influence of passengers carried on the risk of driver fatal injury in New Zealand. The estimated risks increased steeply with increasing blood alcohol concentration (BAC), closely following an exponential curve at levels below about 200mg/dl (i.e. 0.2%) and increasing less than exponentially thereon. The model fitted to data for drivers under 200mg/dl showed that risks at all BAC levels were statistically significantly higher for drivers aged under 20 (over five times) and for drivers aged 20-29 (three times) than for drivers aged 30 and over. Further, controlling for age and BAC level, driving with a single passenger was associated with approximately half the night-time risk of driver fatal injury relative to driving either solo or with two or more passengers. According to a recent travel survey, the types of passengers carried at the times of night and days of week studied appear to differ significantly from the types of passengers carried generally, which may lead to different passenger effects on driver behaviour. The high relative risk of teenage drivers means that they reach high risk levels commonly regarded as unacceptable in the field of road safety even at their current legal limit of 30mg/dl, particularly when more than one passenger is carried in the car.