The role of the built environment in explaining relationships between perceived and actual pedestrian and bicyclist safety

While the conventional approach to safety planning has emphasized crash analysis with police-reported crash information, transportation professionals increasingly recognize the importance of proactively identifying potential crash risk and considering environmental characteristics. In a proactive approach, individuals’ perception of crash risk provides important information in identifying potential crash risk. As built environment characteristics influence the levels of pedestrian and bicycle safety, this study examined how perceived and actual crash risk are related with each other and with respect to built environmental characteristics. Our results showed that residents who live in low density-single residential neighborhoods are more likely to perceive their neighborhood as dangerous relative to residents of compact, mixed-use neighborhoods even though the latter exhibited higher actual crash rates. The results of path analyses confirmed that a simultaneous but opposite relationship exists between perceived and actual crash risks. Our results indicate that higher actual crash risk increases perceived crash risk, while higher perceived crash risk is negatively associated to actual crash rates. Consequently, low density and non-mixed land uses increase individuals perception of crash risk, and increased perception of risk and unfriendly environment for pedestrian and bikers reduces actual crash rates as a result of behavioral changes. From a policy standpoint, more attention and proactive interventions are desirable in suburban areas beyond the areas with high crash rates, as some of these areas have high-perceived risks.     

Characteristics of traffic crashes in Maryland (1996-1998): differences among the youngest drivers

Motor vehicle crashes (MVCs) are the leading cause of death among teenagers in the US. The present study examines how crash rates and crash characteristics differed among drivers aged 16-21 in the state of Maryland from 1996 to 1998. The results show that, based on police reports. the youngest drivers have the highest rate of MVCs per licensed driver and per annual miles driven. Furthermore, crash characteristics suggest that inexperience rather than risky driving may account for the differing rates. Drivers closer to the age of 16 had their crashes under the safest conditions: during the day in clear weather while drinking less.     

Accident involvement and crash injury rates: An investigation by make, model and year of car

Accident involvement and crash injury rates per million miles of vehicle travel are estimated by make, model and year of car. The accident and injury information was obtained from the North Carolina accident files, while exposure data were derived from paired odometer readings recorded on a statewide sample of motor vehicle inspection receipts.

The resulting estimates show a steady decrease in annual mileage with vehicle age. For the newer model years, large cars have generally higher annual mileages than small cars, and station wagons higher mileages than sedans or hardtops. The accident involvement and injury rates decline for the newer model cars, especially for larger-sized cars. Full-sized cars have the lowest overall accident and injury rates. Among standard-sized cars, two-door cars have higher accident and injury rates than four-door cars, and hardtops higher than sedans or station wagons.     

Surface condition and safety at signalised intersections

The study reported herein focuses on assessing the effects and contributions of pavement surface condition parameters including roughness, rut depth and skid resistance on crash frequencies and rates at signalised intersections. The assessment has been performed using graphical trend analysis and negative binomial regression. For each signalised intersection in the sample, condition data are collected for the year before and after the year of surface treatment. Crash data, however, are collected for a minimum of 3 and maximum of 5 years before and after treatment years. Analyses results show that before treatment, light condition (day/night), road surface moisture condition (wet/dry) and skid resistance are the significant contributors to crash occurrence. For after-treatment; light condition, road surface moisture condition and the interaction between roughness and traffic volume are the significant contributors. The study aim and approach are presented herein together with a discussion of the main findings.     

Highway accident rates and rural travel densities

Rural highway injury accident rates should theoretically increase with an increase in travel densities. Regression analyses of cross-sectional data on U.S. Primary and Secondary highways show a moderate positive association, but on the Interstate this association appears to be invariant. Fatal accident rates, on the other hand, are negatively associated with travel densities. Explanations for these results may be found in variables associated with travel densities, such as speed, speed variability, types of crash, and accessibility to emergency medical services. Changes in travel densities, between 1976 and 1979. on the major rural highway systems have been accommodated with no apparent effect on average accident rates.     

列车追尾事故的故障树分析兼谈复杂系统安全

温州动车组追尾事故是我国铁路大发展时期发生的特别重大事故.为更深入了解事故的可能原因,以列车追尾事故为顶事件,开展故障树分析,探讨事故的各种发生模式,剖析造成事故的各种事件,并从宏观的角度讨论了复杂安全关键系统的安全要素和策略,给出了一些建议.     

Overtaking, rear-end, and door crashes involving bicycles: an empirical investigation

Recent emphasis on bicycling as an alternative to automobile transportation has underscored the need for research efforts directed at bicycle safety when sharing roadways with motorised vehicles. Much of the research attention is focused on junction accidents where motorists tend to infringe upon bicycles’ right of way. Non-junction accidents where a motorist strikes a bicycle while overtaking it, or crashes into the rear of the bicycle, have been less frequently researched. Another common crash type is a door crash that involves a bicycle striking an open door of an automobile. Using British Stats19 accident data, the present study estimates a mixed multinomial model to predict the likelihood of a non-junction crash being of a certain crash type (out of three possible types). The methodological approach adopted allows for the individuals within the observations to have different parameter estimates (as opposed to a single parameter representing all observations). Main findings include that buses/coaches as collision partners were associated with overtaking crashes; and bicycles’ traversing manoeuvres were associated with overtaking and rear-end collisions. Given a crash where a bicycle collides with a motorcycle/taxi, it is more likely a rear-end crash and a door crash, respectively. Implications of the research findings, the concluding remarks, and recommendations for future research are finally provided.     

Refined-scale panel data crash rate analysis using random-effects tobit model

Random effects tobit models are developed in predicting hourly crash rates with refined-scale panel data structure in both temporal and spatial domains. The proposed models address left-censoring effects of crash rates data while accounting for unobserved heterogeneity across groups and serial correlations within group in the meantime. The utilization of panel data in both refined temporal and spatial scales (hourly record and 1-mile roadway segments on average) exhibits strong potential on capturing the nature of time-varying and spatially varying contributing variables that is usually ignored in traditional aggregated traffic accident modeling. 1-year accident data and detailed traffic, environment, road geometry and surface condition data from a segment of I-25 in Colorado are adopted to demonstrate the proposed methodology. To better understand significantly different characteristics of crashes, two separate models, one for daytime and another for nighttime, have been developed. The results show major difference in contributing factors towards crash rate between daytime and nighttime models, implying considerable needs to investigate daytime and nighttime crashes separately using refined-scale data. After the models are developed, a comprehensive review of various contributing factors is made, followed by discussions on some interesting findings.     

Evaluation of rear-end crash risk at work zone using work zone traffic data

This paper aims to evaluate the rear-end crash risk at work zone activity area and merging area, as well as analyze the impacts of contributing factors by using work zone traffic data. Here, the rear-end crash risk is referred to as the probability that a vehicle is involved in a rear-end crash accident. The deceleration rate to avoid the crash (DRAC) is used in measuring rear-end crash risk. Based on work zone traffic data in Singapore, three rear-end crash risk models are developed to examine the relationship between rear-end crash risk at activity area and its contributing factors. The fourth rear-end crash risk model is developed to examine the effects of merging behavior on crash risk at merging area. The ANOVA results show that the rear-end crash risk at work zone activity area is statistically different from lane positions. Model results indicate that rear-end crash risk at work zone activity area increases with heavy vehicle percentage and lane traffic flow rate. An interesting finding is that the lane closer to work zone is strongly associated with higher rear-end crash risk. A truck has much higher probability involving in a rear-end accident than a car. Further, the expressway work zone activity area is found to have much larger crash risk than arterial work zone activity area. The merging choice has the dominated effect on risk reduction, suggesting that encouraging vehicles to merge early may be the most effective method to reduce rear-end crash risk at work zone merging area.     

Safety impacts of platform tram stops on pedestrians in mixed traffic operation: A comparison group before–after crash study

Tram stops in mixed traffic environments present a variety of safety, accessibility and transport efficiency challenges. In Melbourne, Australia the hundred year-old electric tram system is progressively being modernized to improve passenger accessibility. Platform stops, incorporating raised platforms for level entry into low floor trams, are being retro-fitted system-wide to replace older design stops. The aim of this study was to investigate the safety impacts of platform stops over older design stops (i.e. Melbourne safety zone tram stops) on pedestrians in the context of mixed traffic tram operation in Melbourne, using an advanced before–after crash analysis approach, the comparison group (CG) method. The CG method evaluates safety impacts by taking into account the general trends in safety and the unobserved factors at treatment and comparison sites that can alter the outcomes of a simple before–after analysis. The results showed that pedestrian-involved all injury crashes reduced by 43% after platform stop installation. This paper also explores a concern that the conventional CG method might underestimate safety impacts as a result of large differences in passenger stop use between treatment and comparison sites, suggesting differences in crash risk exposure. To adjust for this, a modified analysis explored crash rates (crash counts per 10,000 stop passengers) for each site. The adjusted results suggested greater reductions in pedestrian-involved crashes after platform stop installation: an 81% reduction in pedestrian-involved all injury crashes and 86% reduction in pedestrian-involved FSI crashes, both are significant at the 95% level. Overall, the results suggest that platform stops have considerable safety benefits for pedestrians. Implications for policy and areas for future research are explored.     

Identifying repeat DUI crash factors using state crash records

The objective of this study is to identify high risk factors that are closely related to repeat DUI crashes using readily available information from the state crash records. Survival analysis was used and a Cox proportional hazards model was developed using the police-reported crash records in the state of Louisiana. A variety of variables were found to be significant in predicting repeat DUI crashes. The factors included the characteristics of the drivers (gender, race, and age), the types of the vehicle (light truck/pick up truck or other), the characteristics of the crash (hit-and-run, driver violations, and whether the driver is arrested), the type of location (residential area or other), and the characteristics of the roadway (highway type and roadway type). This study provides a comprehensive picture of the repeat DUI crashes. The model can quantitatively predict the relative hazards of repeat DUI crashes. It can be used to identify the characteristics of the crash-involved DUI drivers who are at greatest risk of being involved in a subsequent DUI crash, allowing to apply appropriate remedial measures to reduce the risk.     

Validity of using linked hospital and police traffic crash records to analyse motorcycle injury crash characteristics

Linking hospital discharge and police traffic crash records has been used to provide information on causes and outcomes for hospitalised traffic crash cases. Motorcyclists are particularly vulnerable to injury in a traffic crash, but no published linkage studies have reported in detail on this road user group. The present study examined motorcycle traffic crash injury cases in New Zealand in 2000–2004 by probabilistically linking national hospital discharge records with police traffic crash reports. Injury cases had to have spent at least one night in hospital before being discharged and were defined as serious or moderate based on their International Classification of Disease Injury Severity Scores (ICISS). Despite a robust linkage process, only 46% of cases could be linked to a police record; 60% of the serious injuries and 41% of the moderate. The low linkage was most likely due to under-reporting of crashes to or by the police. While moderate injury cases were expected to be under-reported, the level of under-reporting of cases with serious threat-to-life injuries is concerning. To assess whether the linked dataset could provide valid information on the crash circumstances and injury outcomes of hospitalised motorcycle crash cases, the characteristics of the linked and unlinked hospital discharge cases were compared using chi-square tests and multivariate logistic regression. Serious injury cases were less likely to be linked if only one vehicle was involved, or the injured riders and passengers were younger than 20 years or spent less than one week in hospital. For moderate injury cases, there were also differences in linkage by injured body region and crash month. While these discrepancies need to taken into consideration when interpreting results, the linked hospital-police dataset has the potential to provide insights into motorcycle crash circumstances and outcomes not otherwise obtainable.     

Analyzing the influence of median cross-section design on highway safety using vehicle dynamics simulations

Although vehicle dynamics simulations have long been used in vehicle design and crash reconstruction, their use for highway design is rare. This paper investigates the safety of highway medians through iterative simulations of off-road median encroachments. The commercially available software CarSim was used to simulate over one hundred thousand encroachments, representing the entire passenger vehicle fleet and a wide range of encroachment angles, departure speeds, steering inputs, and braking inputs. Each individual simulation output was then weighted using data from previous studies to reflect the probability of each specific accident scenario occurring in a real-life median encroachment. Results of this analysis illustrate the relative influence of median cross-section geometry on the resulting accident outcomes. The simulations indicate that the overall safety of a highway median depends on the occurrence of both vehicle rollover and median crossover events, and the cross-section shape, slope, and width are all shown to greatly affect each of these incidents. An evaluation of the simulation results was conducted with vehicle trajectories from previous experimental crash tests. Further assessment of the aggregate simulation results to actual crash data was achieved through comparison with several databases of crash statistics. Both efforts showed a strong agreement between the simulations and the real-life crash data.     

A multinomial logit model-Bayesian network hybrid approach for driver injury severity analyses in rear-end crashes

Rear-end crash is one of the most common types of traffic crashes in the U.S. A good understanding of its characteristics and contributing factors is of practical importance. Previously, both multinomial Logit models and Bayesian network methods have been used in crash modeling and analysis, respectively, although each of them has its own application restrictions and limitations. In this study, a hybrid approach is developed to combine multinomial logit models and Bayesian network methods for comprehensively analyzing driver injury severities in rear-end crashes based on state-wide crash data collected in New Mexico from 2010 to 2011. A multinomial logit model is developed to investigate and identify significant contributing factors for rear-end crash driver injury severities classified into three categories: no injury, injury, and fatality. Then, the identified significant factors are utilized to establish a Bayesian network to explicitly formulate statistical associations between injury severity outcomes and explanatory attributes, including driver behavior, demographic features, vehicle factors, geometric and environmental characteristics, etc. The test results demonstrate that the proposed hybrid approach performs reasonably well. The Bayesian network reference analyses indicate that the factors including truck-involvement, inferior lighting conditions, windy weather conditions, the number of vehicles involved, etc. could significantly increase driver injury severities in rear-end crashes. The developed methodology and estimation results provide insights for developing effective countermeasures to reduce rear-end crash injury severities and improve traffic system safety performance.     

Analysis of work zone rear-end crash risk for different vehicle-following patterns

This study evaluates rear-end crash risk associated with work zone operations for four different vehicle-following patterns: car–car, car–truck, truck–car and truck–truck. The deceleration rate to avoid the crash (DRAC) is adopted to measure work zone rear-end crash risk. Results show that the car–truck following pattern has the largest rear-end crash risk, followed by truck–truck, truck–car and car–car patterns. This implies that it is more likely for a car which is following a truck to be involved in a rear-end crash accident. The statistical test results further confirm that rear-end crash risk is statistically different between any two of the four patterns. We therefore develop a rear-end crash risk model for each vehicle-following pattern in order to examine the relationship between rear-end crash risk and its influencing factors, including lane position, the heavy vehicle percentage, lane traffic flow and work intensity which can be characterized by the number of lane reductions, the number of workers and the amount of equipment at the work zone site. The model results show that, for each pattern, there will be a greater rear-end crash risk in the following situations: (i) heavy work intensity; (ii) the lane adjacent to work zone; (iii) a higher proportion of heavy vehicles and (iv) greater traffic flow. However, the effects of these factors on rear-end crash risk are found to vary according to the vehicle-following patterns. Compared with the car–car pattern, lane position has less effect on rear-end crash risk in the car–truck pattern. The effect of work intensity on rear-end crash risk is also reduced in the truck–car pattern.     

Why have fatality rates among older drivers declined? The relative contributions of changes in survivability and crash involvement

ObjectivesThis study examined the trend in fatality rates per vehicle miles traveled (VMT) among older drivers relative to middle-aged drivers and quantified the contributions of changes in crash involvement and survivability to this trend.MethodsUsing U.S. national databases, changes in driver deaths per crash involvement (marker of death risk when involved in a crash) and crash involvements per VMT (marker of crash risk) from 1995–1998 to 2005–2008 among older drivers aged 70 and over relative to changes among middle-aged drivers aged 35–54 were computed. The contributions of these components to the relative changes in older drivers’ fatality rates per VMT were calculated using the decomposition methodology.ResultsFatality rates per VMT declined more among older drivers than among middle-aged drivers over the study period. Relative to middle-aged drivers, drivers aged 75 and older experienced large declines in crash risk and modest declines in death risk. Relative declines in crash risk accounted for 68–74% of the larger decline in fatalities per VMT among drivers aged 75 and older compared with middle-aged drivers. Drivers aged 70–74 experienced modest relative declines in crash risk and death risk. Declines in death risk among drivers aged 75 and older relative to middle-aged drivers were much larger in side-impact crashes; improvements in crash survivability accounted for nearly half of the relative decline in fatality rates in these crashes. Relative survivability did not change significantly in frontal impacts. Higher death risk was more important than higher crash risk in explaining older drivers’ elevated fatality rates per VMT relative to middle-aged drivers during 1995–1998, and the contribution of heightened death risk was even greater during 2005–2008.ConclusionsMany factors may have reduced crash involvements among drivers 75 and older, including changes in travel patterns, health, and roadway design. In side impacts, side airbags and reduced passenger vehicle incompatibility may have improved survivability for older drivers. Because excess fragility now makes an even larger contribution to older drivers’ elevated fatality rates, future countermeasures that improve survivability can likely provide large benefits.     

Economic development's effect on road transport-related mortality among different types of road users: a cross-sectional international study

The relationship between a country's stage of economic development and its motor vehicle crash (MVC) mortality rate is not defined for different road users. This paper presents a cross-sectional regression analysis of recent national mortality in 44 countries using death certificate data provided by the World Health Organization. For five types of road users, MVC mortality is expressed as deaths per 100,000 people and per 1000 motor vehicles. Economic development is measured as gross national income (GNI) per capita in U.S. dollars and as motor vehicles per 1000 people. Results showed overall MVC mortality peaked among low-income countries at about US$ 2000 GNI per capita and at about 100 motor vehicles per 1000 people. Overall mortality declined at higher national incomes up to about US$ 24,000. Most changes in MVC mortality associated with economic development were explained by changes in rates among nonmotorized travelers, especially pedestrians. Overall MVC rates were lowest when pedestrian exposure was low because there were few motor vehicles or few pedestrians, and were highest during a critical transition to motorized travel, when many pedestrians and other vulnerable road users vied for use of the roadways with many motor vehicles.     

Older drivers do not have a high crash risk--a replication of low mileage bias

The widespread claim that older drivers are overly involved in crashes has apparent support from crash data, especially when distance travelled is used as the exposure measure. However, independent of age, drivers travelling more kilometres will typically have lower crash rates per kilometre than those driving fewer kilometres. This paper uses Dutch travel survey data from a large sample of respondents to confirm previous research findings concerning the association between annual mileages driven and crash involvement. When the crash rates of drivers of different ages were compared after being matched for yearly driving distance, most drivers aged 75 years and above were indicatively safer than all other drivers. Only older drivers travelling less than 3000 km per year (just over 10% of all older drivers in the survey) gave any indication of elevated crash rates.     

Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation

There is a high potential of severe injury outcomes in traffic crashes on rural interstate highways due to the significant amount of high speed traffic on these corridors. Hierarchical Bayesian models are capable of incorporating between-crash variance and within-crash correlations into traffic crash data analysis and are increasingly utilized in traffic crash severity analysis. This paper applies a hierarchical Bayesian logistic model to examine the significant factors at crash and vehicle/driver levels and their heterogeneous impacts on driver injury severity in rural interstate highway crashes. Analysis results indicate that the majority of the total variance is induced by the between-crash variance, showing the appropriateness of the utilized hierarchical modeling approach. Three crash-level variables and six vehicle/driver-level variables are found significant in predicting driver injury severities: road curve, maximum vehicle damage in a crash, number of vehicles in a crash, wet road surface, vehicle type, driver age, driver gender, driver seatbelt use and driver alcohol or drug involvement. Among these variables, road curve, functional and disabled vehicle damage in crash, single-vehicle crashes, female drivers, senior drivers, motorcycles and driver alcohol or drug involvement tend to increase the odds of drivers being incapably injured or killed in rural interstate crashes, while wet road surface, male drivers and driver seatbelt use are more likely to decrease the probability of severe driver injuries. The developed methodology and estimation results provide insightful understanding of the internal mechanism of rural interstate crashes and beneficial references for developing effective countermeasures for rural interstate crash prevention.