Surrogate safety measure for evaluating rear-end collision risk related to kinematic waves near freeway recurrent bottlenecks

This study presents a surrogate safety measure for evaluating the rear-end collision risk related to kinematic waves near freeway recurrent bottlenecks using aggregated traffic data from ordinary loop detectors. The attributes of kinematic waves that accompany rear-end collisions and the traffic conditions at detector stations spanning the collision locations were examined to develop the rear-end collision risk index (RCRI). Together with RCRI, standard deviations in occupancy were used to develop a logistic regression model for estimating rear-end collision likelihood near freeway recurrent bottlenecks in real-time. The parameters in the logistic regression models were calibrated using collision data gathered from the 6-mile study site between 2006 and 2007. Findings indicated that an additional unit increase in RCRI results in increasing the odds of rear-end collision by 21.1%, a unit increase in standard deviation of upstream occupancy increases the odds by 19.5%, and a unit increase in standard deviation of downstream occupancy increases the odds by 18.7%. The likelihood of rear-end collisions is highest when the traffic approaching from upstream is near capacity state while downstream traffic is highly congested. The paper also reports on the findings from comparing the predicted number of rear-end collisions at the study site using the proposed model with the observed traffic collision data from 2008. The proposed model's true positive rates were higher than those of existing real-time crash prediction models.     

The impact of young drivers’ lifestyle on their road traffic accident risk in greater Athens area

Young drivers (18–24) both in Greece and elsewhere appear to have high rates of road traffic accidents. Many factors contribute to the creation of these high road traffic accidents rates. It has been suggested that lifestyle is an important one. The main objective of this study is to find out and clarify the (potential) relationship between young drivers’ lifestyle and the road traffic accident risk they face. Moreover, to examine if all the youngsters have the same elevated risk on the road or not. The sample consisted of 241 young Greek drivers of both sexes. The statistical analysis included factor analysis and logistic regression analysis. Through the principal component analysis a ten factor scale was created which included the basic lifestyle traits of young Greek drivers. The logistic regression analysis showed that the young drivers whose dominant lifestyle trait is alcohol consumption or drive without destination have high accident risk, while these whose dominant lifestyle trait is culture, face low accident risk. Furthermore, young drivers who are religious in one way or another seem to have low accident risk. Finally, some preliminary observations on how health promotion should be put into practice are discussed.     

Characteristics,cycling patterns,and crash and injury experiences at baseline of a cohort of transport and recreational cyclists in New South Wales,Australia

This paper examines self-reported retrospective data for a 12 month period from 2038 adult cyclists from New South Wales (Australia), and compares cyclists according to whether they self-identify as riding mainly for transport or mainly for recreation. Statistically significant differences were found in the demographic characteristics, cycling patterns, and crash experiences between these two groups of cyclists. Transport cyclists tended to be younger, travel more days per week, and within morning and evening peak hours than recreational cyclists; recreational cyclists were more likely to identify fitness as a purpose for cycling. The proportion of cyclists experiencing a crash or crash-related injury in the previous 12 months was similar for transport and recreational cyclists, but there were differences in crash types and location which likely reflect different cycling environments. Heterogeneity within transport and recreational cyclists was also found, based on self-reported riding intensity. An understanding of the different cycling patterns and experiences of various types of cyclists is useful to inform road safety, transport and health promotion policy.     

Risk factors for causing road crashes involving cyclists: An application of a quasi-induced exposure method

A quasi-induced exposure approach was applied to the Spanish Register of Traffic Crashes to identify driver- and vehicle-related factors associated with the risk of causing a road crash involving a cyclist in Spain from 1993 to 2009. We analyzed 19,007 collisions between a bicycle and another vehicle in which only one of the drivers committed an infraction, and 13,540 records that included the group of non-infractor cyclists in the above collisions plus cyclists involved in single-bicycle crashes. Adjusted odds ratios were calculated for being responsible for each type of crash for each factor considered. Age from 10 to 19 years, male sex, alcohol or drug consumption and non-helmet use were cyclist-related variables associated with a higher risk of crash, whereas cycling more than 1 h increased only the risk of single crashes. Bicycles with brake defects and ridden by two occupants were also at higher risk of involvement in a crash, whereas light defects were associated only with collisions with another vehicle. For drivers of the other vehicle, age more than 60 years, alcohol, not using safety devices and nonprofessional drivers were at higher risk. The risk of colliding with a bicycle was higher for mopeds than for passenger cars.     

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.     

The use of Functional Resonance Analysis Method (FRAM) in a mid-air collision to understand some characteristics of the air traffic management system resilience

The Functional Resonance Analysis Model (FRAM) defines a systemic framework to model complex systems for accident analysis purposes. We use FRAM in the mid-air collision between flight GLO1907, a commercial aircraft Boeing 737-800, and flight N600XL, an executive jet EMBRAER E-145, to investigate key resilience characteristics of the Air Traffic Management System (ATM). This ATM system related accident occurred at 16:56 Brazilian time on September 29, 2006 in the Amazonian sky. FRAM analysis of flight monitoring functions showed system constraints (equipment, training, time, and supervision) that produce variability in system behavior, creating demand resources mismatches in an attempt to perceive and control the developing situation. This variability also included control and coordination breakdowns and automation surprises (TCAS functioning). The analysis showed that under normal variability conditions (without catastrophic failures) the ATM system (pilots, controllers, supervisors, and equipment) was not able to close the control loops of the flight monitoring functions using feedback or feedforward strategies to achieve an adequate control of an aircraft flying in the controlled air space. Our findings shed some light on the resilience of Brazilian ATM system operation and indicated that there is a need of a deeper understanding on how the system is actually functioning.     

A statistical law in the perception of risks and physical quantities in traffic

This paper suggests that a universal psychophysical law influences the perception of risks and physical quantities in traffic. This law states that there will be a tendency to overestimate low probabilities or small quantities, while high probabilities or large quantities may be underestimated. Studies of the perception of risk and physical quantities in traffic have found a highly consistent pattern, which shows that:

• 1.Pedestrians intending to cross the road overestimate the stopping distance of cars travelling at low speed and underestimate the stopping distance of cars travelling at high speed.
• 2.Car drivers intending to overtake overestimate the distance needed at low speed, but underestimate it at high speed.
• 3.Car drivers asked to accelerate from standstill to a given speed overshoot the target speed; when asked to slow down to a stated speed, drivers also overshoot the target speed.
• 4.When asked what speed to choose to save a given amount of time on a trip of given length, drivers overestimate target speed when initial speed is low and underestimate it when initial speed is high.
• 5.Drivers overestimate the increase in risk associated with a small increase in speed and underestimate the increase in risk associated with a larger increase in speed.
• 6.Drivers overestimate the risk of apprehension for traffic offences when it is low and underestimate it when it is high.
• 7.Road users overestimate the risk associated with comparatively safe modes of transport and underestimate the risk associated with comparatively hazardous modes of transport.

The paper gives examples of all these misperceptions of physical quantities and risk.     

Bayesian networks for maritime traffic accident prevention: Benefits and challenges

Bayesian networks are quantitative modeling tools whose applications to the maritime traffic safety context are becoming more popular. This paper discusses the utilization of Bayesian networks in maritime safety modeling. Based on literature and the author's own experiences, the paper studies what Bayesian networks can offer to maritime accident prevention and safety modeling and discusses a few challenges in their application to this context. It is argued that the capability of representing rather complex, not necessarily causal but uncertain relationships makes Bayesian networks an attractive modeling tool for the maritime safety and accidents. Furthermore, as the maritime accident and safety data is still rather scarce and has some quality problems, the possibility to combine data with expert knowledge and the easy way of updating the model after acquiring more evidence further enhance their feasibility. However, eliciting the probabilities from the maritime experts might be challenging and the model validation can be tricky. It is concluded that with the utilization of several data sources, Bayesian updating, dynamic modeling, and hidden nodes for latent variables, Bayesian networks are rather well-suited tools for the maritime safety management and decision-making.     

Prediction of traffic fatalities and prospects for mobility becoming sustainable-safe

The macroscopic trend of road traffic fatalities in any motorized country is described and predicted by the product of rather well fitting functions of time for the exponential decay of fatality risk per unit of traffic volume and the S-shaped Gompertz function of traffic volume growth. This product defines a single-peaked development of road traffic deaths, where its peak reaches earlier the sooner and faster a nation or region motorizes massively. Since in developing countries long series of traffic volume data are absent, another model for the fit and prediction of road traffic fatalities for developing countries is used, based on the relationships of income level per capita with road traffic mortality. Also this model implies that at some point in time road traffic deaths will start declining for ever, also worldwide. After empirically derived corrections for missing or incomplete data and police under-reporting, it is estimated that 1·2 million deaths and almost 8 million serious injuries are caused by road traffic worldwide in 2000. Using realistic income level predictions the new income-dependent model predicts markedly later and higher fatality peaks than the verified time-dependent model. It might be assumed that the developing countries could learn faster to increase their road safety by knowledge transfer from developed countries. Four prediction scenarios are specified for modified income-dependent models of road traffic death and serious injury developments up to 2050. Depending on the scenario the world total of road fatalities begins to reduce soon or only after 2035 with a global peak of about 1·8 million road traffic deaths, where the national fatality reduction starts later the lower the national income per capita is. Without the potentially achievable learning scenario the road fatality reductions in developed countries may not be enough to compensate the road fatality increases in developing countries, while road fatality increases may even occur after 2060 in countries with the lowest levels of income per capita.     

Road mobility and the risk of road traffic accident as a driver. The impact of medical conditions and life events

STUDY OBJECTIVE: We conducted a longitudinal investigation of the impact of self-reported life events and medical conditions on changes in road mobility on the wheel between 2000 and 2002 in order to assess whether these changes would affect the risk of road traffic accident (RTA). METHODS: Data are from a cohort of workers and retirees from the French national gas and electricity companies (the Gazel cohort). In the present study, 10,483 participants were included (7843 men aged 51-61 years and 2640 women aged 46-61 years, in 2000). The link between mobility and the risk of RTA was approximated using data on RTA number during lifetime and reported mobility in 2000. We then compared changes in road mobility between 2000 and 2002 resulting from life events and medical conditions reported to have occurred in the year 2001 or changed when compared to year 2000. We also compared road mobilities in 2000 in order to assess any pre-existing differences before life events and medical conditions. This led to estimation of the effect of road mobility changes on the risk of RTA. RESULTS: Changes in road mobility associated with life events and medical conditions were only found among men. These changes in road mobility were minimal. Ensuing changes in the risk of RTA were estimated to be small (odds-ratios ranged from 0.94 to 1.01). The only life events found to be associated with increased road mobility was an important purchase. Hospitalization, serious RTA, and retiring were associated with reduced road mobility. Concerning medical conditions, men who reported cataract, angina pectoris, diabetes, anxiety and stress, sleep disorder, and depression decreased their road mobility. CONCLUSION: We found no or moderate changes in road mobility resulting from life events and medical conditions, suggesting that results from previous published studies that assessed the impact of life events or medical conditions on RTA were not jeopardized by improper adjustment for road mobility.     

Effect of wheelchair headrest use on pediatric head and neck injury risk outcomes during rear impact

Comparative risks or benefits to wheelchair-seated pediatric occupants in motor vehicles associated with wheelchair headrest use during rear impact were evaluated using pediatric head and neck injury outcome measures. A Hybrid III 6-year-old anthropomorphic test device (ATD), seated in identical WC19-compliant pediatric manual wheelchairs, was used to measure head and neck response during a 25 km/h (16 mph), 11 g rear impact. ATD responses were evaluated across two test scenarios: three sled tests conducted without headrests, and three with slightly modified commercial headrests. Head and neck injury outcomes measures included: linear head acceleration, head injury criteria (HIC) values, neck injury criteria (N(ij)) values, and combined rotational head velocity and acceleration. Neck and head injury outcome measures improved by 34-70% in sled tests conducted with headrests compared to tests without headrests. Headrest use reduced N(ij) values and the likelihood of concussion from values above established injury thresholds to values below injury thresholds. Injury measure outcome reductions suggest lower head and neck injury risks for wheelchair-seated children using wheelchair-mounted headrests as compared to non-headrest users in rear impact. Use of relative comparisons across two test scenarios served to minimize effects of ATD biofidelity limitations.     

Car occupant safety in frontal crashes: a parameter study of vehicle mass, impact speed, and inherent vehicle protection

A new mathematical model was developed to estimate average injury and fatality rates in frontal car-to-car crashes for changes in vehicle fleet mass, impact speed distribution, and inherent vehicle protection. The estimates were calculated from injury/fatality risk data, delta-V distribution and collision probability of two vehicles, where delta-V depends on impact speed and mass of the colliding vehicles. The impact speed distribution was assumed to be unaffected by a change in fleet mass distribution.

The results showed that safety in frontal crashes would improve 27–35% by a 10% increase in fatality risk parameters, which reflected substantial improvement in inherent vehicle protection. A 40% safety improvement was attained by a 10% impact speed reduction. Consequences of vehicle fleet mass were not as strong, but depended on the average mass ratio of the fleet. A reduction in mass range would be the most beneficial, while a uniform mass reduction of 20% would increase the fatality rate by 5.4%. The model estimates trends in traffic safety and may help to identify priorities in active and passive safety.     

金温线武义江桥列车走行性与行车安全指标研究

运用列车脱轨能量随机分析理论分析了金温线武义江桥列车走行性。计算结果表明尽管该桥横向振幅超过《检规》行车安全限值,但列车走行安全性、平稳性与舒适性有保障,在现行行车条件下,不需要对该桥采取加固或限速措施。对比超限桥梁横向振幅与《检规》行车安全限值可知,现有的桥梁横向振幅行车安全限值过于严格。基于列车脱轨能量随机分析理论,提出了铁路桥梁行车安全指标分析方法。具体内容为：确定桥梁跨中横向振幅作为梁墩系统行车安全判别参数,计算找出保证列车安全、平稳及舒适运行的临界梁墩系统,计算出临界梁墩系统跨中横向振幅作为桥梁行车安全限值。算出了金温线武义江32 m 预应力混凝土T形梁桥横向振幅行车安全限值为L/6200,研究成果已被金温铁路公司采纳。     

The impact of autonomous vehicle technologies on product recall risk

Complex Advanced Driving Assistance Systems (ADAS) and Autonomous Vehicle (AV) technology are increasing the number of vehicle recalls. At the same time, financial risks resulting from extensive product recall events can severely affect vehicle manufacturers and their suppliers, exposing the automotive supply chain to business continuity, legal and reputational risk. However, these risk implications are under-appreciated by large segments of the supply chain. This study shows that product recall events are increasing in general but recall events associated with ADAS/AV technology form an increasingly large percentage of these recall events. Based on this analysis, we describe ADAS/AV-specific aspects of risk mitigation and present a multidimensional approach, combining production-centric risk mitigation avenues in the automotive supply chain with the transfer of residual financial risks via insurance. We find that this comprehensive risk mitigation approach benefits in higher transparency of total production costs and increased resilience of the automotive supply chain. Against the background of an increasing product recall risk resulting from the increasing automation and interconnectedness of modern vehicles, we therefore suggest a closer, more strategic cooperation between insurance companies, car manufacturers and automotive suppliers for the benefit of all parties.     

An empirical tool to evaluate the safety of cyclists: Community based,macro-level collision prediction models using negative binomial regression

Today, North American governments are more willing to consider compact neighborhoods with increased use of sustainable transportation modes. Bicycling, one of the most effective modes for short trips with distances less than 5 km is being encouraged. However, as vulnerable road users (VRUs), cyclists are more likely to be injured when involved in collisions. In order to create a safe road environment for them, evaluating cyclists’ road safety at a macro level in a proactive way is necessary. In this paper, different generalized linear regression methods for collision prediction model (CPM) development are reviewed and previous studies on micro-level and macro-level bicycle-related CPMs are summarized. On the basis of insights gained in the exploration stage, this paper also reports on efforts to develop negative binomial models for bicycle–auto collisions at a community-based, macro-level. Data came from the Central Okanagan Regional District (CORD), of British Columbia, Canada. The model results revealed two types of statistical associations between collisions and each explanatory variable: (1) An increase in bicycle–auto collisions is associated with an increase in total lane kilometers (TLKM), bicycle lane kilometers (BLKM), bus stops (BS), traffic signals (SIG), intersection density (INTD), and arterial–local intersection percentage (IALP). (2) A decrease in bicycle collisions was found to be associated with an increase in the number of drive commuters (DRIVE), and in the percentage of drive commuters (DRP). These results support our hypothesis that in North America, with its current low levels of bicycle use (<4%), we can initially expect to see an increase in bicycle collisions as cycle mode share increases. However, as bicycle mode share increases beyond some unknown ‘critical’ level, our hypothesis also predicts a net safety improvement. To test this hypothesis and to further explore the statistical relationships between bicycle mode split and overall road safety, future research needs to pursue further development and application of community-based, macro-level CPMs.     

ADHD and relative risk of accidents in road traffic: A meta-analysis

The present meta-analysis is based on 16 studies comprising 32 results. These studies provide sufficient data to estimate relative accident risks of drivers with ADHD. The overall estimate of relative risk for drivers with ADHD is 1.36 (95% CI: 1.18; 1.57) without control for exposure, 1.29 (1.12; 1.49) when correcting for publication bias, and 1.23 (1.04; 1.46) when controlling for exposure. A relative risk (RR) of 1.23 is exactly the same as found for drivers with cardiovascular diseases. The long-lasting assertion that “ADHD-drivers have an almost fourfold risk of accident compared to non-ADHD-drivers”, which originated from Barkley et al.’s study of 1993, is rebutted. That estimate was associated with comorbid Oppositional Defiant Disorder (ODD) and/or Conduct Disorder (CD), not with ADHD, but the assertion has incorrectly been maintained for two decades. The present study provides some support for the hypothesis that the relative accident risk of ADHD-drivers with comorbid ODD, CD and/or other conduct problems, is higher than that of ADHD-drivers without these comorbidities. The estimated RRs were 1.86 (1.27; 2.75) in a sample of ADHD-drivers in which a majority had comorbid ODD and/or CD compared to 1.31 (0.96; 1.81) in a sample of ADHD-drivers with no comorbidity. Given that ADHD-drivers most often seem to drive more than controls, and the fact that a majority of the present studies lack information about exposure, it seems more probable that the true RR is lower rather than higher than 1.23. Also the assertion that ADHD-drivers violate traffic laws more often than other drivers should be modified: ADHD-drivers do have more speeding violations, but no more drunk or reckless driving citations than drivers without ADHD. All accident studies included in the meta-analysis fail to acknowledge the distinction between deliberate violations and driving errors. The former are known to be associated with accidents, the latter are not. A hypothesis that ADHD-drivers speed more frequently than controls because it stimulates attention and reaction time is suggested.     

Noise abatement and traffic safety: The trade-off of quieter engines and pavements on vehicle detection

Road traffic sounds are a major source of noise pollution in urban areas. But recent developments such as low noise pavements and hybrid/electric engine vehicles cast an optimistic outlook over such an environmental problem. However, it can be argued that engine, tire, and road noise could be relevant sources of information to avoid road traffic conflicts and accidents. In this paper, we analyze the potential trade-offs of traffic-noise abatement approaches in an experimental study, focusing for the first time on the impact and interaction of relevant factors such as pavement type, vehicle type, listener's age, and background noise, on vehicle detection levels. Results reveal that vehicle and pavement type significantly affect vehicle detection. Age is a significant factor, as both younger and older people exhibit lower detection levels of incoming vehicles. Low noise pavements combined with all-electric and hybrid vehicles might pose a severe threat to the safety of vulnerable road users. All factors interact simultaneously, and vehicle detection is best predicted by the loudness signal-to-noise ratio.     

Social impacts of road traffic: perceptions and priorities of local residents

The assessment of the social impacts of road traffic is usually based on objective indicators or on expert judgement, without input from the affected communities. This paper considers the perceptions and priorities of local residents about traffic impacts and possible mitigation measures, using as a case study a rural area that will be affected by traffic associated with the construction of a nuclear power station. The study consisted of a qualitative phase followed by a stated preference survey. Econometric models were used to measure the relative priority of different impacts and mitigation measures. The most impactful aspects were noise, vibration and increased car or bus travel times. The most preferred measures were night-time restrictions to HGVs, parking restrictions and safety measures for pedestrians and cyclists. There were significant differences in preferences according to residence location, gender, employment status and household composition. The results provide information about aspects that tend to be aggregated in existing assessment frameworks, separating the reduction in the utility of some activities (like walking and driving) and the suppression of those activities.     

Sustainable supply chains for supply chain sustainability: impact of sustainability efforts on supply chain risk

Supply chain managers across the globe are finding it difficult to manage the increasingly complex supply chains despite adopting a variety of risk mitigation strategies. Firms on the other hand have also been adopting various kinds of environmental and social sustainability practices in recent times to reduce carbon footprint and improve their image on the social front. However, very few studies in the extant literature have examined the impact of sustainability practices on supply chain risk. We address this important gap in literature by empirically testing this relationship, using primary data from six manufacturing sectors and 21 different countries including developed as well as emerging markets across the globe. Our findings indicate that risk mitigation strategies do not always reduce the actual supply chain risk experienced by firms, whereas sustainability efforts help reduce supply chain risk, especially in emerging market contexts. In addition, we find that, while reactive risk mitigation strategies on their own fail to reduce supply chain risk, they are effective when used in conjunction with sustainability efforts. We also find that preventive risk mitigation efforts are only effective in mature supply chains such as the OECD countries.