Traffic Accident Database Research Articles

Data mining combined to the multicriteria decision analysis for the improvement of road safety: case of France

IntroductionThe problem studied in this paper is the road insecurity, which is manifested by the big number of injuries and deaths recorded annually around the world. These victims of road accidents worry the whole community, hence the duty and the need to find solutions for reducing the number of victims and material damage. The overall purpose of this case study is to treat the problem of corporeal accidents known in France.Case descriptionThe case study presented in this paper is intended to help decision-makers to find and understand the all significant relationships and correlations that exist between the conditions that led to these corporeal accidents. In fact, the two French ministries of interior and transport have jointly created a unique database on corporeal accidents, called BAAC “Accident Analysis Bulletin Corporal”, with the aim of allowing different exploitations of this database by different concerned administrations and research organizations. Our intervention consists to adopt a hybrid approach based on data mining techniques combined to the multicriteria decision methods. This approach allows to extract the most relevant association rules. The results thus obtained can be easily exploited by the decision-makers to choose the appropriate policies in the perspective of improving road safety.Discussion and evaluationThe proposed approach ranks all association rules in order of importance for several quality measures of association rules. The alternatives at the top of the ranking are the results to retaining for the analysis. The approach is applied to the BAAC database of 2016, which led to the selection of three association rules. These association rules reveal that there are narrow correlations between the following elements: Driver with Pedestrian, Normal Surface of Road with Normal Atmospheric Condition and the Pavement with Pedestrian. These correlations can be justified by excess speed and carelessness of the drivers.ConclusionThe improvement of the road safety needs mainly to work more intensively on the behavioral side of the road users. For future work, it is planned to apply the proposed approach to the French traffic accident database, containing all the data on road accidents collected over several years. In addition, other measures will be used in the ranking of the association rules.

교통사고-인체상해 데이터베이스 기반 차량 탑승자 상해 중증도 영향요인 분석

본 연구는 교통사고-인체상해 데이터베이스에 저장된 교통사고, 차량파손 자료 및 사고차량 탑승자의 심층 의료기록을 이용하여 사고 당시 탑승자가 중증 외상을 입었지만 생존하는 경우 대비 중증 외상 후 사망한 경우를 비교한 후, 탑승자의 생존 여부에 영향을 미치는 유의미한 요인들을 분석하였다. 이를 위하여 본 연구는 Sequential Logistic Regression모형의 두 포맷을 사용하여 외상 중증도를 예측하였고 Receiver Operation Characteristic 커브의 넓이를 비교하여 더 우수한 포맷을 선택하였다. 그 결과, Sequential Logistic Regression모형의 Forward 포맷이Backward 포맷보다 우수한 성능을 보였다. 특히, 병원 전 응급의료서비스 시간이 24분이 초과될 경우에 중증 외상 후 생존 대비 사망 확률을 약 540% 증가시키는 것으로 나타났다. 또한, 교통사고의 주 원인이 졸음이나 기기조작과 같은 운전자의 부주의일 경우, 중증 외상 후 생존 대비 사망 확률을 약 380% 증가시키는 것으로 나타났다. 이와 같은 결과를 근거로 본 연구는 응급의료 구급차의 개수, 응급의료 처치 인력 및 장비 증가, 긴급차량 우선신호 시스템 운영, 럼블스트립 혹은 고속도로 졸음쉼터 증설, 운전 중 스마트 폰 기기 제한 법제화 및 관련 캠페인, 운전자 교육과 같은 대안이 필요함을 제시하였다. 본 연구결과를 기반으로 사고장소의 위치정보를 추가적으로 통합하여 GIS공간 클러스터링으로 발전시킨다면 안전향상대책 시행의 우선순위 지역을 선정하는 근거로도 본 연구의 활용가치가 높을 것이다.

Accident severity levels and traffic signs interactions in state roads: a seemingly unrelated regression model in unbalanced panel data approach

This study intended to investigate the interactions between accident severity levels and traffic signs in state roads located in Croatia, and explore the correlation within accident severity levels and heterogeneity attributed to unobserved factors. The data from 410 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia Ministry of the Interior. To address the correlation and heterogeneity, a seemingly unrelated regression (SUR) model in unbalanced panel data approach was proposed, in which the seemingly unrelated model addressed the correlation of residuals, while the panel data model accommodated the heterogeneity due to unobserved factors. By comparing the pooled, fixed-effects and random-effects SUR models, the random-effects SUR model showed priority to the other two. Results revealed that (1) low visibility and the number of invalid traffic signs per km increased the accident rate of material damage, death or injured; (2) average speed limit exhibited a high accident rate of death or injured; (3) the number of mandatory signs was more likely to reduce the accident rate of material damage, while the number of warning signs was significant for accident rate of death or injured.

Investigation into Interactions between Accident Consequences and Traffic Signs: A Bayesian Bivariate Tobit Quantile Regression Approach

This study intended to investigate the interactions between accident severity levels and traffic signs in state roads located in Croatia and explore the correlation between accident severity levels and heterogeneity attributed to unobserved factors. The data from 460 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia Ministry of the Interior. To address the correlation and heterogeneity, Bayesian bivariate Tobit quantile regression models were proposed, in which the bivariate framework addressed the correlation of residuals with Bayesian approach, while the Tobit quantile regression model accommodated the heterogeneity due to unobserved factors. By comparing the Bayesian bivariate Tobit quantile and mean regression models, the proposed quantile models showed priority to mean model. Results revealed that (1) low visibility and the number of invalid traffic signs per km increased the accident rate of material damage, death, or injury; (2) average speed limit exhibited a close relation with accident rate; and (3) the number of mandatory signs was more likely to reduce the accident rate of material damage, while the number of warning signs was significant for accident rate of death or injury.

PC-Crash와 교통사고 데이터베이스를 이용한 레이더각도에 따른 AEBS 적용성에 관한 연구

PC-Crash와 교통사고 데이터베이스를 이용한 레이더각도에 따른 AEBS 적용성에 관한 연구

Effectiveness and acceptability of milled rumble strips on rural two-lane roads in Sweden

PurposeThe study sought to estimate the effects of centreline milled rumble strips on rural two-lane roads in Sweden in a wide perspective. Traffic safety effects (i.e., fewer crashes and injuries), driver experience, and driver opinions of centreline milled rumble strip usage on rural roads are investigated.MethodsTo evaluate the traffic safety effects, an Empirical Bayes study comparing the outcome before and-after the introduction of rumble strips was conducted. This study is based on data from 2003–2012 from the Swedish national traffic accident database, STRADA. To capture driver experience and opinions about milled centreline rumble strips, focus groups and road-side interviews were performed.ResultsThe results indicate a significant decrease in all types of severe injury crashes, a 20% (±13%) reduction in the number of fatalities and seriously injured people (all crash types) and a 27% (±18%) reduction in the number of fatalities and severely injured people in single-vehicle crashes. Participants in focus groups and road-side interviews generally favoured centreline rumble strips on rural roads, and up to 90% of the interviewed motorcyclists and commuters stated that the rumble strips would help improve traffic safety.ConclusionsRumble strips in the centre of two-lane rural roads are a countermeasure to help drivers who are unintentionally about to leave the lane, for example, due to sleepiness or inattention. Based on the results of this study, installing centreline milled rumble strips on two-lane rural roads 8–10 meters wide is a measure to consider to increase safety.

Integrasi Sistem Data Kecelakaan Lalu Lintas di Kabupaten Jember

The rapid development of technology can help people solve their problems faced every day. One of them is the problem in transportation sector related traffic accident data often occur in Jember. Many agencies and institutions that play a role, making the existing data to be different. Traffic accident report from police and patient report in emergency room from hospital is collected from 2012 to 2014. The result of this research is a good integration traffic accident database system between police and hospital using PostgreSQL, an information system about traffic accident recording with the location can be presented in digital map using Microsoft Visual Basic 6.0, and a recommendations to improve the accuracy of existing traffic accident data.

The effectiveness of lane departure warning systems—A reduction in real-world passenger car injury crashes

ABSTRACTObjective: The objective of this study was to estimate the safety benefits of in vehicle lane departure warning (LDW) and lane keeping aid (LKA) systems in reducing relevant real-world passenger car injury crashes.Methods: The study used an induced exposure method, where LDW/LKA-sensitive and nonsensitive crashes were compared for Volvo passenger cars equipped with and without LDW/LKA systems. These crashes were matched by car make, model, model year, and technical equipment; that is, low-speed autonomous emergency braking (AEB) called City Safety (CS). The data were extracted from the Swedish Traffic Accident Data Acquisition database (STRADA) and consisted of 1,853 driver injury crashes that involved 146 LDW-equipped cars, 11 LKA-equipped cars, and 1,696 cars without LDW/LKA systems.Results: The analysis showed a positive effect of the LDW/LKA systems in reducing lane departure crashes. The LDW/LKA systems were estimated to reduce head-on and single-vehicle injury crashes on Swedish roads with speed limits between 70 and 120 km/h and with dry or wet road surfaces (i.e., not covered by ice or snow) by 53% with a lower limit of 11% (95% confidence interval [CI]). This reduction corresponded to a reduction of 30% with a lower limit of 6% (95% CI) for all head-on and single-vehicle driver injury crashes (including all speed limits and all road surface conditions).Conclusions: LDW/LKA systems were estimated to lower the driver injury risk in crash types that the systems are designed to prevent; that is, head-on and single-vehicle crashes. Though these are important findings, they were based on a small data set. Therefore, further research is desirable to evaluate the effectiveness of LDW/LKA systems under real-world conditions and to differentiate the effectiveness between technical solutions (i.e., LDW and LKA) proposed by different manufacturers.

Severity of pedestrian injuries due to traffic crashes at signalized intersections in Hong Kong: a Bayesian spatial logit model

SummaryThe present study intended to (1) investigate the injury risk of pedestrian casualties involved in traffic crashes at signalized intersections in Hong Kong; (2) determine the effect of pedestrian volumes on the severity levels of pedestrian injuries; and (3) explore the role of spatial correlation in econometric crash‐severity models. The data from 1889 pedestrian‐related crashes at 318 signalized intersections between 2008 and 2012 were elaborately collected from the Traffic Accident Database System maintained by the Hong Kong Transport Department. To account for the cross‐intersection heterogeneity, a Bayesian hierarchical logit model with uncorrelated and spatially correlated random effects was developed. An intrinsic conditional autoregressive prior was specified for the spatial correlation term. Results revealed that (1) signalized intersections with greater pedestrian volumes generally exhibited a lower injury risk; (2) ignoring the spatial correlation potentially results in reduced model goodness‐of‐fit, an underestimation of variability and standard error of parameter estimates, as well as inconsistent, biased, and erroneous inference; (3) special attention should be paid to the following factors, which led to a significantly higher probability of pedestrians being killed or sustaining severe injury: pedestrian age greater than 65 years, casualties with head injuries, crashes that occurred on footpaths that were not obstructed/overcrowded, heedless or inattentive crossing, crashes on the two‐way carriageway, and those that occurred near tram or light‐rail transit stops. Copyright © 2017 John Wiley & Sons, Ltd.

How Expressway Geometry Factors Contribute to Accident Occurrence? A Binary Logistic Regression Study

Logistic regression and statistical method are combined to analyze accident data from “Traffic Accident Database System” (TADS) in order to find the relationship between expressway geometric factors and accident rate. A total of 2004 observations are used to illustrate the proposed model. A new concept mean angle of deflection (MAD) is also introduced to evaluate the effect of horizontal alignment. Accident rate (the dependent variable) in this study is a dichotomous variable, so a binary logistic regression is found suitable. Totally sixteen variables are proposed and fourteen are used in the model. Eight variables are found significantly associated with accident rate at the 0.05 significance. Each variable is interpreted with the results of SPSS 19.0 and the results provide the references for identifying unsafe locations and taking appropriate counteractive measures for expressways in mountainous areas.

The effect of natural and built environmental characteristics on pedestrian-vehicle crash severity in Ghana

Despite the benefits of walking as a means of travelling, walking can be quite hazardous. Pedestrian-vehicle crashes remain a major concern in Ghana as they account for the highest percentage of fatalities. The objective of this study is to determine the effect of both natural and built environmental features on pedestrian-vehicle crash severity in Ghana. The study is based on an extensive pedestrian-vehicle crash dataset extracted from the National Road Traffic Accident Database at the Building and Road Research Institute (BRRI) of the Council for Scientific and Industrial Research (CSIR), Ghana. Using a multinomial logit modelling framework, possible determinants of pedestrian-vehicle crash severity were identified. The study found that fatal crashes are likely to occur during unclear weather conditions, on weekends, at night time where there are no lights, on curved and inclined roads, on untarred roads, at mid-blocks and on wider roads. The developed model and its interpretations will make important contributions to road crash analysis and prevention in Ghana with the possibility of extension to other developing countries. These contributing factors could inform policy makers on road design and operational improvements.

Usefulness of overnight pulse oximeter as the sleep assessment tool to assess the 6-year risk of road traffic collision: evidence from the Taiwan Bus Driver Cohort Study.

In order to support health service organizations in arranging a system for prevention of road traffic collisions (RTC), it is important to study the usefulness of sleep assessment tools. A cohort study was used to evaluate the effectiveness of subjective and objective sleep assessment tools to assess for the 6-year risk of both first RTC event only and recurrent RTC events. The Taiwan Bus Driver Cohort Study (TBDCS) recruited 1650 professional drivers from a large bus company in Taiwan in 2005. The subjects were interviewed in person, completed the sleep assessment questionnaires and had an overnight pulse oximeter survey. Moreover, this cohort of drivers was linked to the National Traffic Accident Database (NTAD) and researchers found 139 new RTC events from 2005 to 2010. Primary outcomes were traffic collisions from NTAD, nocturnal oxygen desaturation index (ODI) from pulse oximeter, Pittsburg sleeping quality score, Epworth daytime sleepiness score, Snore Outcomes Survey score and working patterns from questionnaires. A Cox proportional hazards model and an extended Cox regression model for repeated events were performed to estimate the hazard ratio for RTC. The RTC drivers had increased ODI4 levels (5.77 ± 4.72 vs 4.99 ± 6.68 events/h; P = 0.008) and ODI3 levels (8.68 ± 6.79 vs 7.42 ± 7.94 events/h; P = 0.007) in comparison with non-RTC drivers. These results were consistent regardless of whether ODI was evaluated as a continuous or a categorical variable. ODI4 and ODI3 levels increased the 6-year RTC risks among professional drivers even after adjusting for age, education, history of cardiovascular disease, caffeine intake, sleeping pills used, bus driving experience and shift modes. Moreover, there was an increased trend for ODI between the stratification of the number of RTCs in comparison with the non-RTC group. In the extended Cox regression models for repeated RTC events with the Anderson and Gill intensity model and Prentice-Williams-Petersen model, measurement of ODI increased hazards of the subsequent RTC events. This study showed that an increase in the 6-year risk of RTC was associated with objective measurement of ODI for a sign of sleep-disordered breathing (SDB), but was not associated with self-reported sleeping quality or daytime sleepiness. Therefore, the overnight pulse oximeter is an effective sleep assessment tool for assessing the risk of RTC. Further research should be conducted regarding measures to prevent against SDB among professional drivers.

Missing value imputation for the analysis of incomplete traffic accident data

Death, injury and disability resulting from road traffic crashes continue to be a major global public health problem. Recent data suggest that the number of fatalities from traffic crashes is in excess of 1.25 million people each year with non-fatal injuries affecting a further 20–50 million people. It is predicted that by 2030 road traffic accidents will have progressed to be the 5th leading cause of death and that the number of people who will die annually from traffic accidents will have doubled from current levels. Both developed and developing countries suffer from the consequences of increase in human population, and therefore, vehicle population. Therefore, methods to reduce accident severity are of great interest to traffic agencies and the public at large. To analyse traffic accident factors effectively we need a complete traffic accident historical database. Any missing data in the database could prevent the discovery of important environmental and road accident factors and lead to invalid conclusions. In this paper, we present a novel imputation method that exploits the within-record and between-record correlations to impute missing data of numerical or categorical values. In addition, our algorithm accounts for uncertainty in real world data by sampling from a list of potential imputed values according to their affinity degree. We evaluated our algorithm using four publicly available traffic accident databases from the United States, the first of which is the largest open federal database (explore.data.gov) in the United States, and the second is based on the National Incident Based Reporting System (NIBRS) of the city and county of Denver (data.opencolorado.org). The other two are from New York's open data portal (Motor Vehicle Crashes-case information: 2011 and Motor Vehicle Crashes-individual information: 2011, data.ny.gov). We compare our algorithm with four state-of-the-art imputation methods using missing value imputation accuracy and RMSE. Our results indicate that the proposed method performs significantly better than the existing algorithms we compared.

Traffic accidents involving fatigue driving and their extent of casualties

The rapid progress of motorization has increased the number of traffic-related casualties. Although fatigue driving is a major cause of traffic accidents, the public remains not rather aware of its potential harmfulness. Fatigue driving has been termed as a “silent killer.” Thus, a thorough study of traffic accidents and the risk factors associated with fatigue-related casualties is of utmost importance. In this study, we analyze traffic accident data for the period 2006–2010 in Guangdong Province, China. The study data were extracted from the traffic accident database of China's Public Security Department. A logistic regression model is used to assess the effect of driver characteristics, type of vehicles, road conditions, and environmental factors on fatigue-related traffic accident occurrence and severity. On the one hand, male drivers, trucks, driving during midnight to dawn, and morning rush hours are identified as risk factors of fatigue-related crashes but do not necessarily result in severe casualties. Driving at night without street-lights contributes to fatigue-related crashes and severe casualties. On the other hand, while factors such as less experienced drivers, unsafe vehicle status, slippery roads, driving at night with street-lights, and weekends do not have significant effect on fatigue-related crashes, yet accidents associated with these factors are likely to have severe casualties. The empirical results of the present study have important policy implications on the reduction of fatigue-related crashes as well as their severity.

GBD-2010 overestimates deaths from road injuries in OECD countries: new methods perform poorly.

We assessed the quality of Global Burden of Disease-2010 (GBD-2010) estimates of road injury deaths by comparing with government statistics for Organisation for Economic Co-operation and Development (OECD) countries that report to the International Road Traffic Accident Database (IRTAD). We obtained tabulated data for 25 OECD countries that report to IRTAD and also report vital registration (VR) data to WHO. We collated VR deaths corresponding to the GBD-2010 road injury definition and estimated 'traffic', 'non-traffic' and 'unspecified whether traffic or non-traffic' components. We estimated national road injury deaths by redistributing partially specified causes of death, as was done by GBD until this was replaced by more complex methods in GBD-2010. GBD-2010 estimates of road injury deaths exceeded IRTAD by 45% overall. IRTAD values fell below the GBD-2010 95% uncertainty interval in all but three countries. Mismatch of conceptual scope accounted for about 8% of this discrepancy, 5% was because GBD-2010 included cases other than road traffic and 3% because GBD-2010 (unlike IRTAD) includes deaths >30 days after injury. Pro rata distribution of partially specified causes in VR data gave estimates that were 18% higher than IRTAD but closer than GBD-2010 estimates for all but two countries. Cases in VR data specified as road injury gave estimates closer to IRTAD. GBD-2010 road injury mortality estimates are substantially higher than the road death toll in OECD countries. The discrepancy is not explained by wider scope of the GBD road injury construct nor by undercounting by IRTAD. GBD-2010 likely attributed substantially more deaths with partially specified causes to road injuries than is appropriate.

Increasing Road Traffic Throughput through Dynamic Traffic Accident Risk Mitigation

The introduction of vehicular ad-hoc networks (VANETs) leads to the possibility to re-evaluate many traditional functions and views of road traffic networks. The ability for vehicles and infrastructure to communicate and collaborate will enable many novel solutions for problems as diverse as collision avoidance and traffic management with the view of reducing traffic congestion, increasing the effectiveness of logistics systems etc. In this paper we introduce a novel framework that utilises VANET information to share information about risk factors among road occupants and infrastructure. We introduce the concept of risk limits as a means of traffic accident risk mitigation, whereby vehicles need to adjust their behaviour to maintain a given level of risk. We discuss determination of risk values and detail this process using the NSW traffic accident database. We show how the effects on risk of particular vehicular behaviours such as speed and headway can be calculated and use these results to modify vehicle behaviour in real time to maintain a predefined risk limit. Experiments are carried out using the Paramics Microsimulator. Our results show that it is possible to reduce the accident rate among vehicles while at the same time increasing road network throughput by exploiting the variation in risk between vehicles.

Main stumbling blocks for a good traffic accident database system - evidences from Brazil

Research on road safety requires, as one of its main assets, a good accident database system (ADS). This work proposes to identify the requirements for such a system, as well as the main stumbling blocks in the path of its creation in Brazil. Results show that each municipality makes its own partnership with the police, database maintenance is irregular and dependent upon political change, and no municipality has information from hospitals. The information varies from municipality to municipality; the level of reported accidents also varies. Therefore, we propose that developing countries could design accident recording systems from a spatial data infrastructure (SDI) perspective. Accident data can then comprise a uniform dataset, potentially hosted by several different institutions, to be made readily and freely available through the country's spatial data infrastructure.

Quantifying the influence of safe road systems and legal licensing age on road mortality among young adolescents: Steps towards system thinking

Based on existing literature, a system thinking approach was used to set up a conceptual model on the interrelationships among the components influencing adolescent road mortality, distinguishing between components at the individual level and at the system level. At the individual level the role of risk behaviour (sometimes deliberate and sometimes from inexperience or other non-deliberate causes) in adolescent road mortality is well documented. However, little is known about the extent to which the ‘road system’ itself may also have an impact on younger adolescents’ road mortality. This, by providing a safe or unsafe road environment for all road users (System-induced exposure) and by allowing access to high-risk vehicles at a young or older age through the legal licensing age. This study seeks to explore these relationships by analysing the extent to which the road mortality of 10 to 17 year olds in various jurisdictions can be predicted from the System-induced Exposure (SiE) in a jurisdiction and from its legal licensing age to drive motor vehicles. SiE was operationalized as the number of road fatalities per 105 inhabitants/all ages together, but excluding the 10 to 17 year olds. Data on road fatalities during the years 2001 through 2008 were obtained from the OECD International Road Traffic Accident Database (IRTAD) and from the USA NHTSA's Fatality Analysis Reporting System (FARS) database for 29 early and 10 late licensing jurisdictions. Linear mixed models were fitted with annual ‘Adolescent road mortality per capita’ for 2001 through 2008 as the dependent variable, and time-dependent ‘SiE’ and time-independent ‘Licensing system’ as predictor variables. To control for different levels of motorisation, the time-dependent variable ‘Annual per capita vehicle distance travelled’ was used as a covariate. Licensing system of a jurisdiction was entered as a categorical predictor variable with late licensing countries as a baseline group. The study found support for the protective effects of SiE on adolescent safety. If SiE increased by one unit, the mortality rate of 10 to 17 year olds increased by 0.487 units. No support was found for a protective effect of late licensing for this age group. Thus, compared to young adolescents who are allowed to drive motor vehicles in early licensing jurisdictions, late licensing does not provide extra protection for pre-license adolescents. This finding is probably the result of the high risks associated with alternative transport modes, such as moped riding and bicycling. Also, the fact that the study only included risks to young adolescents themselves and did not include the risks they might pose to other road users and passengers may have contributed to this finding, because such risks are greater when driving a motor vehicle than riding a moped or a bicycle. Therefore, to advance our understanding of the impact of licensing systems, more study is needed into the benefits of early or late licensing, thereby considering these wider effects as well.

The effect of sun glare on traffic accidents in Chiba Prefecture, Japan

This study aims to clarify the effect of sun glare on traffic accident occurrence. Analyses of traffic accidents were carried out to calculate the position of the sun relative to the first vehicle concerned (i.e., the vehicle most responsible for causing the accident) at the accident time and location by using the traffic accident database of Chiba Prefecture, Japan. The traffic accident rate was found to increase when the viewing angle decreased to less than 90 degrees. When the sun was in front of the first vehicle concerned, there was a higher occurrence of pedestrian accidents, bicycle accidents and accidents at intersections, and a slightly higher occurrence of right-turning accidents and accidents in winter. However, the tendency for vehicle drivers to be affected adversely by sun glare was not observed to increase with increases in vehicle speed. Traffic safety measures against such kinds of accidents are needed. Language: en

An Assessment of the Effects of Passenger Vehicle Weight and Size on Accident and Fatality Risk Based on Data for 1991 through 2007 Model Year Vehicles

Quantifying the independent effects of vehicle weight and size on overall vehicle safety is necessary in order to assess the risks and benefits of vehicle weight reduction. This paper describes the results of one-stage and two-stage logistic regression analyses of the effects of passenger vehicle weight, wheelbase, track, and footprint on fatalities per accident, accidents per exposure (e.g., vehicle-miles-traveled), and fatalities per exposure using national and multi-state traffic accident and exposure databases. The analyses were accomplished in two phases. The first phase used 1995 though 2000 calendar year data for 1991 through 1999 model year vehicles. The second phase used 2002 through 2008 calendar year data for 2000 through 2007 model year vehicles. The overall fatalities per exposure results tend to confirm the one-stage results previously reported by NHTSA, however the new two-stage results provide additional insight into the independent effects of weight reduction and size reduction on vehicle crash involvement, crashworthiness and crash compatibility. The sensitivity of the results to various databases, variables, and assumptions was also investigated. The results from both phases indicated that the estimated overall effects of passenger vehicle weight reduction (while holding vehicle size constant) on fatalities are small in comparison to other variables and may not be statistically significant depending on various key assumptions (e.g., controlling for changes in wheelbase and track versus changes in footprint, and the type of induced-exposure data that are used), and this is due to small or opposing effects of these variables on crash involvement, crashworthiness and crash compatibility. Language: en