In-depth approach for identifying crash causation patterns and its implications for pedestrian crash prevention

IntroductionA pedestrian crash occurs due to a series of contributing factors taking effect in an antecedent-consequent order. One specific type of antecedent-consequent order is called a crash causation pattern. Understanding crash causation patterns is important for clarifying the complicated growth of a pedestrian crash, which ultimately helps recommend corresponding countermeasures. However, previous studies lack an in-depth investigation of pedestrian crash cases, and are insufficient to propose a representative picture of causation patterns. Method: In this study, pedestrian crash causation patterns were discerned by using the Driving Reliability and Error Analysis Method (DREAM). One hundred and forty-two pedestrian crashes were investigated, and five pedestrian pre-crash scenarios were extracted. Then, the crash causation patterns in each pre-crash scenario were analyzed; and finally, six distinct patterns were identified. Accordingly, 17 typical situations corresponding to these causation patterns were specified as well. Results: Among these patterns, the pattern related to distracted driving and the pattern related to an unexpected change of pedestrian trajectory contributed to a large portion of the total crashes (i.e., 27% and 24%, respectively). Other patterns also played an important role in inducing a pedestrian crash; these patterns include the pattern related to an obstructed line of sight caused by outside objects (9%), the pattern that involves reduced visibility (13%), and the pattern related to an improper estimation of the gap distance between the vehicle and the pedestrian (10%). The results further demonstrated the inter-heterogeneity of a crash causation pattern, as well as the intra-heterogeneity of pattern features between different pedestrian pre-crash scenarios. Conclusions and practical applications: Essentially, a crash causation pattern might involve different contributing factors by nature or dependent on specific scenarios. Finally, this study proposed suggestions for roadway facility design, roadway safety education and pedestrian crash prevention system development.     

COMPARING THE IMPAIRMENT PROFILES OF OLDER DRIVERS AND NON-DRIVERS: TOWARD THE DEVELOPMENT OF A FITNESS-TO-DRIVE MODEL

The purpose of this research effort was to compare older driver and non-driver functional impairment profiles across some 60 assessment metrics in an initial effort to contribute to the development of fitness-to-drive assessment models. Of the metrics evaluated, 21 showed statistically significant differences, almost all favoring the drivers. Also, it was shown that a logistic regression model comprised of five of the assessment scores could completely and accurately separate the two groups. The results of this study imply that older drivers are far less functionally impaired than non-drivers of similar ages, and that a parsimonious model can accurately assign individuals to either group. With such models, any driver classified or diagnosed as a non-driver would be a strong candidate for further investigation and intervention.     

Associations between driver training, determinants of risky driving behaviour and crash involvement

The core aim of the study is to examine associations between formal and informal practical driver training as well as driving experience on the one hand and young drivers’ safety attitudes, self-assessment of driving ability and self-reported driver behaviour on the other hand. An additional aim is to examine the associations between attitudes, self-assessment and behaviour on the one hand and crash involvement on the other hand. The results are based on a self-completion questionnaire survey conducted among a representative sample of Norwegian drivers aged 18–20 years (n = 1419). The results showed that there were small yet significant associations between driver training, on the one hand and traffic safety attitudes and risky driving behaviour on the other hand. The amount of formal driver training was negatively associated with the respondents’ evaluation of their driving skills; although the amount of lay instruction was positively associated with such self-evaluation. The results also showed that attitudes as well as self-assessment of driving ability were significantly associated with self-reported risk behaviour. This was especially true for attitudes related to rule violations. There was a strong association between crash involvement and exposure (measured as months holding a licence). Young novice drivers’ crash involvement seems stronger associated with driving skills (manifested as self-assessment of driving ability) than safety attitudes and self-reported driver behaviour. The consequences of the results for driver training and accident prevention are discussed.     

Age and gender differences in conviction and crash occurrence subsequent to being directed to Iowa's driver improvement program

Introduction

This paper investigates potential gender and age differences in conviction and crash occurrence subsequent to being directed to attend Iowa's Driver Improvement Program (DIP).

Methods

Binary logit models were developed to investigate the factors that influence conviction occurrence after DIP by gender and age. Because of the low crash occurrence subsequent to DIP, association rules were applied to investigate the factors that influence crash occurrence subsequent to DIP, in lieu of econometric models.

Results

There were statistical significant differences by driver gender, age, and conviction history in the likelihood of subsequent convictions. However, this paper found no association between DIP outcome, crash history, and crash occurrence.

Impact on industry

Evaluating the differences in conviction and crash occurrence subsequent to DIP between female and male drivers, and among different age groups can lead to improvements of the effectiveness of DIPs and help to identify low-cost intervention measures, customized based on drivers’ gender and age, for improving driving behaviors.     

Crash data analysis: collective vs. individual crash level approach

INTRODUCTION: Traffic safety literature has traditionally focused on identification of location profiles where "more crashes are likely to occur" over a period of time. The analysis involves estimation of crash frequency and/or rate (i.e., frequency normalized based on some measure of exposure) with geometric design features (e.g., number of lanes) and traffic characteristics (e.g., Average Annual Daily Traffic [AADT]) of the roadway location. In the recent past, a new category of traffic safety studies has emerged, which attempts to identify locations where a "crash is more likely to occur." The distinction between the two groups of studies is that the latter group of locations would change based on the varying traffic patterns over the course of the day or even within the hour. METHOD: Hence, instead of estimation of crash frequency over a period of time, the objective becomes real-time estimation of crash likelihood. The estimation of real-time crash likelihood has a traffic management component as well. It is a proactive extension to the traditional approach of incident detection, which involves analysis of traffic data recorded immediately after the incident. The units of analysis used in these studies are individual crashes rather than counts of crashes. RESULTS: In this paper, crash data analysis based on the two approaches, collective and at individual crash level, is discussed along with the advantages and shortcomings of the two approaches.     

Alcohol-impaired motorcyclists versus car drivers: A comparison of crash involvement and legal consequence from adjudication data

Introduction: Driving under the influence (DUI) increases the probability of motor-vehicle collisions, especially for motorcycles with less protections. This study aimed to identify commonalities and differences between criminally DUI offenses (i.e., with a blood alcohol concentration (BAC) of 80 mg/dL or higher) committed by motorcyclists and car drivers. Methods: A total of 10,457 motorcycle DUIs and 8,402 car DUIs were compared using a series of logistic regression models, using data extracted from the documents of adjudication decisions by the courts of Jiangsu, China. Results: The results revealed that offenders from the high-BAC group (i.e., 200 mg/dL or higher) accounted for more than 20% of the total DUI offenses, and were more likely to be involved in a crash and punished with a longer detention. Motorcyclists had a higher likelihood of crash involvement, and were also more likely to be responsible for single-vehicle crashes associated with higher odds of injury sustained, compared to alcohol-impaired car drivers. In the verdict, motorcycle offenders were more likely to receive a less severe penalty. Conclusions: Interventions are clearly required to focus on reducing in the high-BAC group of offenders. For alcohol-impaired motorcyclists, their risks of crash and injury against BAC climb more steeply than the risks for car drivers. The factors including frequent occurrences, uncertainty of detection, and short-term sentences may weaken the deterrence effect of the criminalization of motorcycle DUI. Practical Applications: The traffic-related adjudication data support traffic safety analysis. Strategies such as combating motorcycle violations (e.g., unlicensed operators or driving unsafe vehicles), undertaking education and awareness campaigns, are expected for DUI prevention.     

Influence of built environment and roadway characteristics on the frequency of vehicle crashes caused by driver inattention: A comparison between rural roads and urban roads

Introduction: With prevalent and increased attention to driver inattention (DI) behavior, this research provides a comprehensive investigation of the influence of built environment and roadway characteristics on the DI-related vehicle crash frequency per year. Specifically, a comparative analysis between DI-related crash frequency in rural road segments and urban road segments is conducted. Method: Utilizing DI-related crash data collected from North Carolina for the period 2013–2017, three types of models: (1) Poisson/negative binomial (NB) model, (2) Poisson hurdle (HP) model/negative binomial hurdle (HNB) model, and (3) random intercepts Poisson hurdle (RIHP) model/random intercepts negative binomial hurdle (RIHNB) model, are applied to handle excessive zeros and unobserved heterogeneity in the dataset. Results: The results show that RIHP and RIHNB models distinctly outperform other models in terms of goodness-of-fit. The presence of commercial areas is found to increase the probability and frequency of DI-related crashes in both rural and urban regions. Roadway characteristics (such as non-freeways, segments with multiple lanes, and traffic signals) are positively associated with increased DI-related crash counts, whereas state-secondary routes and speed limits (higher than 35 mph) are associated with decreased DI-related crash counts in rural and urban regions. Besides, horizontal curved and longitudinal bottomed segments and segments with double yellow lines/no passing zones are likely to have fewer DI-related crashes in urban areas. Medians in rural road segments are found to be effective to reduce DI-related crashes. Practical Applications: These findings provide a valuable understanding of the DI-related crash frequency for transportation agencies to propose effective countermeasures and safety treatments (e.g., dispatching more police enforcement or surveillance cameras in commercial areas, and setting more medians in rural roads) to mitigate the negative consequences of DI behavior.     

Case-control and cross-sectional methods for estimating crash modification factors: comparisons from roadway lighting and lane and shoulder width safety effect studies

Problem

While observational before-after studies are considered the industry standard for developing crash modification factors (CMFs), there are practical limitations that may preclude their use in highway safety analysis. There is a need to explore alternative methods for estimating CMFs.

Method

This paper employs case-control and cross-sectional analyses to estimate CMFs for fixed roadway lighting and the allocation of lane and shoulder widths.

Results

Based on the case-control method, the CMF for intersection lighting is 0.886, while the cross-sectional study indicates a CMF of 0.881. The CMFs developed for lane and shoulder widths are also similar when comparing the two methods.

Conclusions

This paper suggests that case-control and cross-sectional studies produce consistent results if care is taken in the study design and model development.

Impact on industry

Case-control and cross-sectional studies may provide a viable alternative to estimate CMFs when a before-after study is impractical due to data restrictions.     

Safe speed limits for a safe system: The relationship between speed limit and fatal crash rate for different crash types

Objective: The objective of this article is to provide empirical evidence for safe speed limits that will meet the objectives of the Safe System by examining the relationship between speed limit and injury severity for different crash types, using police-reported crash data.

Method: Police-reported crashes from 2 Australian jurisdictions were used to calculate a fatal crash rate by speed limit and crash type. Example safe speed limits were defined using threshold risk levels.

Results: A positive exponential relationship between speed limit and fatality rate was found. For an example fatality rate threshold of 1 in 100 crashes it was found that safe speed limits are 40 km/h for pedestrian crashes; 50 km/h for head-on crashes; 60 km/h for hit fixed object crashes; 80 km/h for right angle, right turn, and left road/rollover crashes; and 110 km/h or more for rear-end crashes.

Conclusions: The positive exponential relationship between speed limit and fatal crash rate is consistent with prior research into speed and crash risk. The results indicate that speed zones of 100 km/h or more only meet the objectives of the Safe System, with regard to fatal crashes, where all crash types except rear-end crashes are exceedingly rare, such as on a high standard restricted access highway with a safe roadside design.     

Crash analysis and development of safety performance functions for Florida roads in the framework of the context classification system

Introduction: Safety performance functions (SPF) are employed to predict crash counts at the different roadway elements. Several SPFs were developed for the various roadway elements based on different classifications such as functional classification and area type. Since a more detailed classification of roadway elements leads to more accurate crash predictions, multiple states have developed new classification systems to classify roads based on a comprehensive classification. In Florida, the new roadway context classification system incorporates geographic, demographic, and road characteristics information. Method: In this study, SPFs were developed in the framework of the FDOT roadway context classification system at three levels of modeling, context classification (CC-SPFs), area type (AT-SPFs), and statewide (SW-SPF) levels. Crash and traffic data from 2015-2019 were obtained. Road characteristics and road environment information have also been gathered along Florida roads for the SPF development. Results: The developed SPFs showed that there are several variables that influence the frequency of crashes, such as annual average daily traffic (AADT), signalized intersections and access point densities, speed limit, and shoulder width. However, there are other variables that did not have an influence in crash occurrence such as concrete surface and the presence of bicycle slots. CC-SPFs had the best performance among others. Moreover, network screening to determine the most problematic road segments has been accomplished. The results of the network screening indicated that the most problematic roads in Florida are the suburban commercial and the urban general roads. Practical Applications: This research provides a solid reference for decision-makers regarding crash prediction and safety improvement along Florida roads.     

Integration of safety instrumented system with automated HAZOP analysis: An application for continuous biodiesel production

Integration of a human-machine interface (HMI) with hazard and operability (HAZOP) analysis is proposed in this work. This concept can potentially lead to the identification of some unexpected deviations, and radically decreases the time necessary for hazard identification. A continuous biodiesel production was simulated. This can be divided into two cases, covering both conventional and reactive distillation. Soybean oil (trioleic, trilinoleic and tripalmitic) at 1000 kg/h as raw material is converted to 99 wt% pure biodiesel. The HMI was designed to improve these processes by combining automatic HAZOP analysis. With this approach, users can receive sufficient information from the simulation to analyze the optimum operation and safety. Severity levels are also provided to classify the actions in the process. Severity levels 1 and 2 are concerned with operating conditions, which are 58-64 °C, and 50-150 kPa. If the analysis shows severity level 3, the safety instrumented system (SIS) will automatically manage the operation in order to reduce/restrain the amount of damage at this level. This proposed system could minimize the damage and also improve the overall quality of the process.     

起重机在特殊工况下的静刚度与动刚度安全性分析

通过对一台桥式电磁起重机静刚度和动刚度的理论计算,以及对其主梁的探伤检查,分析了桥式起重机在特殊工况下的静刚度和动刚度,指出了在设计时应考虑的安全性问题。     

Pilot sample risk analysis for underground coal mine fires and explosions using MSHA citation data

After three decades of sustained continuous improvement of mine safety performances in the US, mine disasters in 2006 and 2007 compromised an excellent record and presented new challenges and vulnerabilities for the underground coal mining industry. In the aftermath of the incidents, formal investigations and new scrutiny of mine safety by the US Congress and expert study groups followed. The US Congress passed the Mine Improvement and New Emergency Response Act of 2006 (MINER Act), which mandated new laws to address the issues, including those related to mine fires and explosions from which miners must be protected. The National Mining Association-sponsored Mine Safety Technology and Training Commission report highlighted the role of risk analysis and management in identifying and controlling major hazards, such as fires and explosions. In this paper an approach is given for analyzing the risks for fires and explosions based on the Mine Safety and Health Administration citation database. Using 2006 citation data and focusing on subsystem failures, the methodology is applied to a database for a pilot sample of underground coal mines stratified by mine size and state.     

Estimating the effectiveness of ergonomics interventions through case studies: implications for predictive cost-benefit analysis

PROBLEM: Cost-benefit analysis (CBA) can help to justify an investment in ergonomics interventions. A predictive CBA model would allow practitioners to present a cost justification to management during the planning stages, but such a model requires reliable estimates of the benefits of ergonomics interventions. METHOD: Through literature reviews and Internet searches, 250 case studies that reported the benefits of ergonomics programs and control measures were collected and summarized. RESULTS: Commonly reported benefits included reductions in the number of work-related musculoskeletal disorders (WMSDs) or their incidence rate, as well as related lost workdays, restricted workdays, and workers' compensation costs. Additional benefits reported were related to productivity, quality, turnover and absenteeism. DISCUSSION: Benefits reported were largely positive, and payback periods for ergonomics interventions were typically less than one year. SUMMARY: The results of this review could be used to develop predictive CBA models for ergonomics programs and individual control measures. IMPACT ON INDUSTRY: Cost-justifying ergonomics interventions prior to implementation may help to secure management support for proposed changes. Numbers used for the benefits side of a cost-benefit analysis (CBA) need to be based on "real world" data in order to be credible. The data presented in this paper may help in the development of simple cost-benefit models for ergonomics programs and control measures.     

Secondary collisions and injury severity: A joint analysis using structural equation models

Objective: This study aims to investigate the contributing factors to secondary collisions and the effects of secondary collisions on injury severity levels. Manhattan, which is the most densely populated urban area of New York City, is used as a case study. In Manhattan, about 7.5% of crash events become involved with secondary collisions and as high as 9.3% of those secondary collisions lead to incapacitating and fatal injuries.

Methods: Structural equation models (SEMs) are proposed to jointly model the presence of secondary collisions and injury severity levels and adjust for the endogeneity effects. The structural relationship among secondary collisions, injury severity, and contributing factors such as speeding, alcohol, fatigue, brake defects, limited view, and rain are fully explored using SEMs. In addition, to assess the temporal effects, we use time as a moderator in the proposed SEM framework.

Results: Due to its better performance compared with other models, the SEM with no constraint is used to investigate the contributing factors to secondary collisions. Thirteen explanatory variables are found to contribute to the presence of secondary collisions, including alcohol, drugs, inattention, inexperience, sleep, control disregarded, speeding, fatigue, defective brakes, pedestrian involved, defective pavement, limited view, and rain. Regarding the temporal effects, results indicate that it is more likely to sustain secondary collisions and severe injuries at night.

Conclusions: This study fully investigates the contributing factors to secondary collisions and estimates the safety effects of secondary collisions after adjusting for the endogeneity effects and shows the advantage of using SEMs in exploring the structural relationship between risk factors and safety indicators. Understanding the causes and impacts of secondary collisions can help transportation agencies and automobile manufacturers develop effective injury prevention countermeasures.     

Injury severity analysis of rollover crashes for passenger cars and light trucks considering temporal stability: A random parameters logit approach with heterogeneity in mean and variance

Problem: The rollover crash is a serious crash type that often causes higher injury severities. Moreover, factors that contribute to the injury severities of rollover crashes may show instabilities in different vehicle types and time periods, which requires further investigations. This study utilizes the rollover crash data in North Carolina from Highway Safety Information System (HSIS) to study the effect instabilities of factors in vehicle type and time periods in rollover crashes. Methods: The injury severities of drivers are estimated using the random parameters logit (RPL) model with heterogeneity in means and variances. Available factors in HSIS have been categorized into three groups, which are drivers, road, and environment, respectively. This study also justifies the segmentations through transferability tests. The effects of identified significant factors are evaluated using marginal effects. Results: Factors such as FWP (farm, wood, and pasture areas), unhealthy physical condition, impaired physical condition, road adverse, and so forth have shown instabilities in marginal effects among vehicle types and time periods. Practical Applications: The finding of this research could provide important references for policy makers and automobile manufactures to help mitigate the injury severity of rollover crashes.     

Experimental data and CFD performance for cloud dispersion analysis: The USP-UPC project

Forecasting the behaviour of a flammable or toxic cloud is a critical challenge in quantitative risk analysis. Recent literature shows that empirical and integral models are unable to model complex dispersion scenarios, like those occurring in semi-confined spaces or with the presence of physical barriers. Although CFD simulators are promising tools in this regard, they still need to be fully validated with comprehensive datasets coming from experimental campaigns designed ad-hoc. In this paper, we present an experimental campaign carried out by a joint venture between University of São Paulo and Universitat Politècnica de Catalunya to investigate CFD tools performance when used to analyse clouds dispersion. The experiments consisted on propane cloud dispersion field tests (unobstructed and with the presence of a fence obstructing the flow) of releases up to 0.5 kg s⁻¹ of 40 s of duration in a discharge area of 700 m². We provide a full 1-s averaged propane concentration evolution dataset of two experiments, extracted from 29 points located at different positions within the cloud, with which we have tested FLACS^® CFD-software performance. FLACS reproduces successfully the presence of complex geometry, showing realistic concentration decreases due to cloud dispersion obstruction by the existence of a fence. However, simulated clouds have not represented the whole complex accumulation dynamics due to wind variation.     

Risk analysis for road and rail transport of hazardous materials: a simplified approach

A simplified approach to transportation risk analysis for road and rail transport of dangerous goods is proposed, which is based on the use of a product databank, containing the impact areas for a number of pre-selected accidental scenarios, and on the selection of a few typical average values of the involved parameters, relevant to the type of transport activity and to the route. Such an approach enables also a non-specialist to very rapidly perform a transportation risk analysis, obtaining both individual and societal risk measures for the study case(s): the results may be used to support a decision making process, and/or as a basis for a more in deep analysis.     

Cross-sectional study of road accidents and related law enforcement efficiency for 10 countries: A gap coherence analysis

Objective: Road crashes are considered as the eighth leading causes of death. There is a wide disparity in crash severity and law enforcement efficiency among low-, medium-, and high-income countries. It would be helpful to review the crash severity trends in these countries, identify the vulnerable road users, and understand the law enforcement effectiveness in devising efficient road safety improvement strategies.

Method: The crash severity, fatality rate among various age groups, and law enforcement strategies of 10 countries representing low-income (i.e., India and Morocco), medium-income (i.e. Argentina, South Korea, and Greece), and high-income (i.e., Australia, Canada, France, the UK, and the United States) are studied and compared for a period of 5 years (i.e., 2008 to 2012). The critical parameters affecting road safety are identified and correlated with education, culture, and basic compliance with traffic safety laws. In the process, possible road safety improvement strategies are identified for low-income countries.

Results: The number of registered vehicles shows an increasing trend for low-income countries as do the crash rate and crash severity. Compliance related to seat belt and helmet laws is high in high-income countries. In addition, recent seat belt– and helmet-related safety programs in middle-income countries helped to curb fatalities. Noncompliance with safety laws in low-income countries is attributed to education, culture, and inefficient law enforcement.

Conclusion: Efficient law enforcement and effective safety education taking into account cultural diversity are the key aspects to reduce traffic-related injuries and fatalities in low-income countries like India.     

Risk analysis for road and rail transport of hazardous materials: a GIS approach

An approach to transportation risk analysis for road and rail transport of dangerous goods is proposed, which is based on the use of geographic information systems (GIS) to manage territorial information, coupled with a product data bank in a risk evaluation tool. Such an approach enables to accurately take into account the local data affecting risk analysis, such as population, accident rate, and weather conditions along all the route, by means of a system which can be easily updated. The resulting risk evaluation tool assists in the step of route identification and allows to rapidly perform an accurate transportation risk analysis, for a single transportation event as well as for multiple substances, trips and itineraries.