Road Safety Risk Research Articles

Research on safe driving behavior of transportation vehicles based on vehicle network data mining

AbstractIn recent years, with the rapid development of China's economy and the growth of people's travel demand, road transport industry has developed rapidly. However, at the same time, the traffic safety problems caused by the accelerated growth of transport vehicles are becoming more and more serious. Driver's driving behavior is closely related to traffic safety. With the help of data mining technology, we can make full use of the system data collected by road transportation industry to identify the bad driving behavior of transport vehicles and get seven secondary indicators of traffic safety evaluation indicators: overspeed, accelerated, decelerated, fatigue driving, idle preheating, overspeed idling, and flameout taxiing. According to the indicators, the occurrence times and duration are further subdivided into 14 three‐level indicators. Then, by using the analytic hierarchy process, through the construction of comparison judgment matrix and consistency checking, the corresponding weight of each evaluation index is determined with the help of the entropy method, and the formation safety of transport vehicles is evaluated. The results show that drivers with more fatigue driving, acceleration, and deceleration have higher driving risk. Transportation enterprises and relevant departments need to focus on their monitoring. The combination of data mining, data analysis algorithm, and traffic safety field in machine learning provides a demonstration for the study of safe driving behavior of transport vehicles in China and has a guiding significance for the supervision and training of drivers' driving behavior and reducing road safety risks.

Why cities with high bicycling rates are safer for all road users

IntroductionDespite bicycling being considered ten times more dangerous than driving, the evidence suggests that high-bicycling-mode-share cities are not only safer for bicyclists but for all road users. We look to understand what makes these cities safer. Are the safety differences related to ‘safety-in-numbers’ of bicyclists, or can they be better explained by built environment differences or the people that inhabit them? MethodsBased on thirteen years of data from twelve large U.S. cities, we investigated over 17,000 fatalities and 77,000 severe injuries across nearly 8700 block groups via multilevel, longitudinal, negative binomial regression models. We hypothesize three pathways towards better road safety outcomes: i) travel behavior differences (e.g. ‘safety-in-numbers’ or shifts to ‘safer’ modes); ii) built environment differences (e.g. infrastructure that helps promote safer environments); and iii) socio-demographic/socio-economic differences (e.g. some cities may be populated by those with lower road safety risk). ResultsThe results suggest that more bicyclists is not the reason these cities are safer for all road users. Better safety outcomes are instead associated with a greater prevalence of bike facilities – particularly protected and separated bike facilities – at the block group level and, more strongly so, across the overall city. Higher intersection density, which typically corresponds to more compact and lower-speed built environments, was strongly associated with better road safety outcomes for all road users. The variables representing gentrification also accounted for much of our explainable variation in safety outcomes. ConclusionsThis paper provides an evidence-based approach to building safer cities. While the policy implications of this work point to protected and separated bike infrastructure as part of the solution, we need to keep in mind that these approaches are complementary and should not be considered in isolation. Moreover, our results – particularly the safety disparities associated with gentrification – suggest equity issues and the need for future research.

Paper Versus Digital Data Collection for Road Safety Risk Factors: Reliability Comparative Analysis From Three Cities in Low- and Middle-Income Countries.

BackgroundRapid advances in mobile technologies and applications and the continued growth in digital network coverage have the potential to transform data collection in low- and middle-income countries. A common perception is that digital data collection (DDC) is faster and quickly adaptable.ObjectiveThe objective of this study was to test whether DDC is faster and more adaptable in a roadside environment. We conducted a reliability study comparing digital versus paper data collection in 3 cities in Ghana, Vietnam, and Indonesia observing road safety risk factors in real time.MethodsRoadside observation of helmet use among motorcycle passengers, seat belt use among 4-wheeler passengers, and speeding was conducted in Accra, Ghana; Ho Chi Minh City (HCMC), Vietnam; and Bandung, Indonesia. Two independent data collection teams were deployed to the same sites on the same dates and times, one using a paper-based data collection tool and the other using a digital tool. All research assistants were trained on paper-based data collection and DDC. A head-to-head analysis was conducted to compare the volume of observations, as well as the prevalence of each risk factor. Correlations (r) for continuous variables and kappa for categorical variables are reported with their level of statistical significance.ResultsIn Accra, there were 119 observation periods (90-min each) identical by date, time, and location during the helmet and seat belt use risk factor data collection and 118 identical periods observing speeding prevalence. In Bandung, there were 150 observation periods common to digital and paper data collection methods, whereas in HCMC, there were 77 matching observation periods for helmet use, 82 for seat belt use, and 84 for speeding. Data collectors using paper tools were more productive than their DDC counterparts during the study. The highest mean volume per session was recorded for speeding, with Bandung recording over 1000 vehicles on paper (paper: mean 1092 [SD 435]; digital: mean 807 [SD 261]); whereas the lowest volume per session was from HCMC for seat belts (paper: mean 52 [SD 28]; digital: mean 62 [SD 30]). Accra and Bandung showed good-to-high correlation for all 3 risk factors (r=0.52 to 0.96), with higher reliability in speeding and helmet use over seat belt use; HCMC showed high reliability for speeding (r=0.99) but lower reliability for helmet and seat belt use (r=0.08 to 0.32). The reported prevalence of risk factors was comparable in all cities regardless of the data collection method.ConclusionsDDC was convenient and reliable during roadside observational data collection. There was some site-related variability in implementing DDC methods, and generally the productivity was higher using the more familiar paper-based method. Even with low correlations between digital and paper data collection methods, the overall reported population prevalence was similar for all risk factors.

Pattern of road traffic crash hot zones versus probable hot zones in Tunisia: A geospatial analysis

Focusing on how hot zones mapping can predict spatial patterns of crashes and how different mapping approaches compare can help to better inform their application in practice. This study examines the stability of the performance of two spatial autocorrelation measures on the basis of a Road Safety Risk Index (RSRI) through the comparison of the results for three regions (North-West, Center-East, and Center-West) and for three time periods (2002–2005, 2006–2009 and 2010–2013) in Tunisia. Our study differs from others in that it discusses the identification of probable hot zones and enhances the capability to examine a given highway by determining “dangerous probable lengths”, which aims to anticipate the traffic crashes in the future. The identified hot zones and probable hot zones exhibit different regional and temporal characteristics. There are clearly some outstanding spatial clusters of crashes covering specific locations. In both Northwest and Center-West regions, the majority of the identified hot zones and probable hot zones predominantly occur along mainly highways characterized by a dominant rural character. In the Center-East region, both hot zones and probable hot zones are mostly spread northeast and south-west more precisely in NH1 and NH2 where many urban activities are taking place. Spatial autocorrelation indices per region address the diversity within the regions and provide us with useful insights that can be translated into safety policies in Tunisia.

The health and safety risks for people who drive for work in the gig economy

BackgroundVery little research has been conducted into the road safety risks of people who drive in the gig economy (e.g. Uber, Deliveroo). The aim of this study was to explore the experience of risk and its management amongst drivers and their managers engaged in the gig economy. MethodsIn depth interviews and an online survey were carried out among gig economy drivers and their managers. Questions focused on the context in which they work, the extent to which they are aware of, create or experience risks, what they perceived as the roles and responsibilities for safety and how they or their employer managed safety. ResultsIn-depth interviews were carried out with 48 participants and an online survey was completed by 231 respondents. Gig work led some couriers to experience impairment caused by fatigue and pressure to violate speed limits and to use their phones whilst driving. Many admitted to having a collision and experiencing near misses daily. In the online survey 42% said they had been involved in a collision where there vehicle had been damaged and 10% said that someone had been injured, usually themselves. Most respondents (75%) said there had been occasions while working when they have had to take action to avoid a collision. ConclusionsThe emergence of the gig driver could give rise to a perfect storm of risk factors affecting the health and safety not just of the people who work in the economy but for other road users. Pressure from Government should make these service providers more aware of their employment obligations and provide safeguards for people who generate income for them. Recommendations are made to improve the safety of gig workers.

Road safety risk factors for non-motorised vehicle users in a Chinese city: an observational study

ObjectiveThe objective of this study is to describe and analyse the prevalence of speeding, helmet use and red-light running among riders of non-motorised vehicles (NMVs) in Shanghai, China, with a...

Analysis and classification of the road traffic health and safety mobile apps based on the Haddon’s matrix

Background: Road traffic accidents have been one of the main causes of death worldwide. However, most of the crashes are both predictable and preventable. With the widespread use, mobile phone is considered as a major road safety risk. However, varieties of apps have recently been developed for improving the road traffic health and safety. Despite an increasing trend of these apps, there is no comprehensive analysis of their features and no taxonomy or classification of them based on the traffic safety theories or frameworks. The aim of this study was to explore characteristics of available mobile apps on the road traffic health and safety and classify them based on the Haddon’s Matrix. Methods: To conduct this research, a comprehensive and systematic review of the mobile applications developed for the road traffic health and safety was carried out through using the qualitative content analysis. Google Play was searched through using a combination of the keywords to retrieve the road traffic apps. In order to extract the app features, their description was examined, and their content was analyzed. Then they were classified in four main categories including Road Traffic Health & safety, Road Traffic Training, Road traffic Navigation, and Other Road Traffic apps. Finally, the Haddon’s matrix was applied to analyze and classify those mobile apps residing in two main categories of the traffic health & safety, and the traffic training. Haddon’s matrix is a relevant framework for structured analyses of traffic injury events. In the Haddon’s matrix, the contributions of human, vehicle/equipment and environmental factors to the injuries in the three phases pre-crash, crash and post-crash has been presented. Results: In this study, 916 mobile apps met the inclusion criteria and were included in the final analysis.19 subcategories were identified for classifying the included apps based on their features and functionalities. In total, 620 of the mobile apps were grouped on the basis of Haddon’s matrix. About 61.76% of these apps were categorized as the traffic health & safety group. Among the subcategories of the traffic health & safety group, the highest number of apps (194) was the real-time traffic alerting apps. Behavior based feed-backing subcategory was ranked the second among the traffic health and safety apps with 75 apps. When the researchers applied factors and phases of Haddon’s framework for analyzing the apps, it was found that the Haddon’s factors have been taken into account in the apps grouped into two main categories of the apps including traffic training and traffic health & safety applications. The highest percentage of Haddon’s matrix factor considered for the intervention through the apps was related to the physical & social environment (23.69%) in the traffic training category. The features of 259 apps were classified in the Event/ Driving phase of Haddon’s matrix. Most of the apps in this phase was related to the real-time traffic alerting subgroup. These apps performed in real time while driving. The lowest number of the apps in driving phase was observed in the behavior based feed backing subcategory, which inform drivers about their driving behavior in real-time. Sixteen apps had features that categorized them in both Pre-event / Pre-driving and Event / Driving phases. In addition, 20 apps were found to have feature for intervening in both Event / Driving and Post-event / Post –driving phases. All 235 apps in the traffic training category were in pre-event/ pre-driving phase, which requires users to use these apps before driving. Conclusion: Applying Haddon’s matrix on analyzing and classifying the traffic health and safety apps revealed strengths and weaknesses of the existing related mobile apps in terms of the factors that must be considered for intervention toward prevention and reduction of road traffic accidents as the main public health issue.

Assessment of road traffic behavior using Youth Risk Behavior Survey questionnaire among school-going adolescents of Jaipur city, Rajasthan: An observational analysis.

Background:Adolescents are a relatively healthy group, but their developmental stage makes them vulnerable to many risk-taking behaviors. One such major issue is road safety practices and their risk on roads.Objective:To determine road safety risk behavior among school-going adolescents of Jaipur city and factors associated with it.Materials and Methods:An observational, cross-sectional study was conducted from July 2015 to February 2016. A total of 900 school-going adolescents were enrolled from eight schools of Jaipur city and the Youth Risk Behavior Survey (YRBS) questionnaire was administered.Results:Most of the participants (67.56%) were in the age group of 13–16 years. A total of 682 (75%) adolescents were driving one or other type of vehicle to commute. Out of the 682 vehicle-using adolescents, 603 (88%) had risky behavior on roads. Driving under the influence was found more among those using four-wheelers (10%) than two-wheelers (5%). Almost half of drivers used mobile phones while driving a car or two-wheeler. There was statistically significant association between risk on roads with respect to rising education and occupation of parents. A majority (88.41%) of the school-going students were found to be at risk on roads while driving. Safety-belt was not used by 28% of the students while half did not use a helmet. More than 70% of the car drivers and two-wheeler drivers drove without license.Conclusion:Majority of the adolescent drivers are at risk on roads. Driving without license and/or helmet and using mobile phone are the main risk factors.

Road Safety Risk Assessment: An Analysis of Transport Policy and Management for Low-, Middle-, and High-Income Asian Countries

Road safety assessment has played a crucial role in the theory and practice of transport management systems. This paper focuses on risk evaluation in the Asian region by exploring the interaction between road safety risk and influencing factors. In the first stage, a data envelopment analysis (DEA) method is applied to calculate and rank the road safety risk levels of Asian countries. In the second stage, a structural equation model (SEM) with latent variables is applied to analyze the interaction between the road safety risk level and the latent variables, measured by six observed performance indicators, i.e., financial impact, institutional framework, infrastructure and mobility, legislation and policy, vehicular road users, and trauma management. Finally, this paper illustrates the applicability of this DEA-SEM approach for road safety performance analysis.

A resilience-oriented approach for quantitatively assessing recurrent spatial-temporal congestion on urban roads.

Traffic congestion brings not only delay and inconvenience, but other associated national concerns, such as greenhouse gases, air pollutants, road safety issues and risks. Identification, measurement, tracking, and control of urban recurrent congestion are vital for building a livable and smart community. A considerable amount of works has made contributions to tackle the problem. Several methods, such as time-based approaches and level of service, can be effective for characterizing congestion on urban streets. However, studies with systemic perspectives have been minor in congestion quantification. Resilience, on the other hand, is an emerging concept that focuses on comprehensive systemic performance and characterizes the ability of a system to cope with disturbance and to recover its functionality. In this paper, we symbolized recurrent congestion as internal disturbance and proposed a modified metric inspired by the well-applied “R4” resilience-triangle framework. We constructed the metric with generic dimensions from both resilience engineering and transport science to quantify recurrent congestion based on spatial-temporal traffic patterns and made the comparison with other two approaches in freeway and signal-controlled arterial cases. Results showed that the metric can effectively capture congestion patterns in the study area and provides a quantitative benchmark for comparison. Also, it suggested not only a good comparative performance in measuring strength of proposed metric, but also its capability of considering the discharging process in congestion. The sensitivity tests showed that proposed metric possesses robustness against parameter perturbation in Robustness Range (RR), but the number of identified congestion patterns can be influenced by the existence of ϵ. In addition, the Elasticity Threshold (ET) and the spatial dimension of cell-based platform differ the congestion results significantly on both the detected number and intensity. By tackling this conventional problem with emerging concept, our metric provides a systemic alternative approach and enriches the toolbox for congestion assessment. Future work will be conducted on a larger scale with multiplex scenarios in various traffic conditions.

Road Safety Risk Evaluation Using GIS-Based Data Envelopment Analysis—Artificial Neural Networks Approach

Identification of the most significant factors for evaluating road risk level is an important question in road safety research, predominantly for decision-making processes. However, model selection for this specific purpose is the most relevant focus in current research. In this paper, we proposed a new methodological approach for road safety risk evaluation, which is a two-stage framework consisting of data envelopment analysis (DEA) in combination with artificial neural networks (ANNs). In the first phase, the risk level of the road segments under study was calculated by applying DEA, and high-risk segments were identified. Then, the ANNs technique was adopted in the second phase, which appears to be a valuable analytical tool for risk prediction. The practical application of DEA-ANN approach within the Geographical Information System (GIS) environment will be an efficient approach for road safety risk analysis.

From road distraction to safe driving: Evaluating the effects of boredom and gamification on driving behaviour, physiological arousal, and subjective experience

Boredom and low levels of task engagement while driving can pose road safety risks, e.g., inattention during low traffic, routine trips, or semi-automated driving. Digital technology interventions that increase task engagement, e.g., through performance feedback, increased challenge, and incentives (often referred to as ‘gamification’), could therefore offer safety benefits. To explore the impact of such interventions, we conducted experiments in a high-fidelity driving simulator with thirty-two participants. In two counterbalanced conditions (control and intervention), we compared driving behaviour, physiological arousal, and subjective experience. Results indicate that the gamified boredom intervention reduced unsafe coping mechanisms such as speeding while promoting anticipatory driving. We can further infer that the intervention not only increased one's attention and arousal during the intermittent gamification challenges, but that these intermittent stimuli may also help sustain one's attention and arousal in between challenges and throughout a drive. At the same time, the gamified condition led to slower hazard reactions and short off-road glances. Our contributions deepen our understanding of driver boredom and pave the way for engaging interventions for safety critical tasks.

Road safety risk assessment at pedestrian crossings: a case study from Sułkowice

Road safety risk assessment at pedestrian crossings: a case study from Sułkowice

Trends in reports of driving following illicit drug consumption among regular drug users in Australia, 2007–2013: Has random roadside drug testing had a deterrent effect?

IntroductionDriving following illicit drug consumption (‘drug-driving’) is a potential road safety risk. Roadside drug testing (RDT) is conducted across Australia with the dual aims of prosecuting drivers with drugs in their system and deterring drug-driving. We examined trends over time in self-reported past six-month drug-driving among sentinel samples of regular drug users and assessed the impact of experiences of RDT on drug-driving among these participants. MethodsData from 1913 people who inject drugs (PWID) and 3140 regular psychostimulant users (RPU) who were first-time participants in a series of repeat cross-sectional sentinel studies conducted in Australian capital cities from 2007 to 2013 and reported driving in the past six months were analysed. Trends over time were assessed using the χ2 test for trend. Multivariable logistic regressions assessed the relationship between experiences of RDT and recent drug-driving, adjusting for survey year, jurisdiction of residence and socio-demographic and drug use characteristics. ResultsThe percentage of participants reporting recent (past six months) drug-driving decreased significantly over time among both samples (PWID: 83% [2007] vs. 74% [2013], p<0.001; RPU: 72% vs. 56%, p<0.001), but drug-driving remained prevalent. Lifetime experience of RDT increased significantly over time (PWID: 6% [2007] vs. 32% [2013], p<0.001; RPU: 2% vs. 11%, p<0.001). There were no significant associations between experiencing RDT and drug-driving among either PWID or RPU. ConclusionAlthough there is some evidence that drug-driving among key risk groups of regular drug users is declining in Australia, possibly reflecting a general deterrent effect of RDT, experiencing RDT appears to have no specific deterrent effect on drug-driving. Further intervention, with a particular focus on changing attitudes towards drug-driving, may be needed to further reduce this practice among these groups.

Workplace road safety risk management: An investigation into Australian practices

In Australia, more than 30% of the traffic volume can be attributed to work-related vehicles. Although work-related driver safety has been given increasing attention in the scientific literature, it is uncertain how well this knowledge has been translated into practice in industry. It is also unclear how current practice in industry can inform scientific knowledge. The aim of the research was to use a benchmarking tool developed by the National Road Safety Partnership Program to assess industry maturity in relation to risk management practices. A total of 83 managers from a range of small, medium and large organisations were recruited through the Victorian Work Authority. Semi-structured interviews aimed at eliciting information on current organisational practices, as well as policy and procedures around work-related driving were conducted and the data mapped onto the benchmarking tool. Overall, the results demonstrated varying levels of maturity of risk management practices across organisations, highlighting the need to build accountability within organisations, improve communication practices, improve journey management, reduce vehicle-related risk, improve driver competency through an effective workplace road safety management program and review organisational incident and infringement management. The findings of the study have important implications for industry and highlight the need to review current risk management practices.

Gender Effects in Young Road Users on Road Safety Attitudes, Behaviors and Risk Perception

In the present study, we investigated gender-related effects on road safety attitudes in 2681 young drivers (1458 males, 54.4%; aged 18–22) who filled out several scales assessing attitudes toward road safety issues, driving behavior in specific hypothetical situations, accident risk perception, and concerns about such a risk. We focused only on young drivers to better understand the role of gender in road safety attitudes in a period of life in which risky behaviors are widespread for males and females. Indeed, there is still no agreement as to the nature of these gender differences. According to some authors, the effects of gender on being involved in a crash due to driving skills are either non-existent or largely explained by differences in alcohol consumption. In our study, we found gender differences in road safety attitudes (i.e., “negative attitude toward traffic rules and risky driving”; “negative attitude toward drugs and alcohol” and “tolerance toward speeding”) and in driver behavior (i.e., “errors in inattentive driving” and “driving violations”). This result is consistent in all drivers coming from nine different European countries. Our analyses yielded an important finding concerning risk perception. The results indicate that the level of risk perception during driving is the same for males and females. However, these two groups differ in the level of concern about this risk, with males being less concerned about the risk of a road accident. This suggests that the main difference between these two groups is not strictly related to judgment of the perceived risk probability but rather to the level of concern experienced about the consequences of the risk. This difference between risk perception and worry could explain differences in the frequency of car accidents in the two groups. The present findings may provide new insights for the development of gender-based prevention programs.

Examining motorcyclists' postcrash impressions: A qualitative study

ABSTRACTObjective: Motorcycle-related crashes and injuries continue to be of great concern in Iran. This study seeks to explore how motorcyclists' perspectives and impressions of a crash are shaped and influence their future riding behaviors.Methods: This was a qualitative study conducted in 3 major cities in Iran between March 2011 and February 2012. Participants included 31 male motorcyclists, of whom 22 participated in 4 focus groups and 9 in in-depth interviews. Findings were derived through the thematic method of analysis.Results: Six delineated themes suggest different factors that influence riders' postcrash impressions. These include (1) opposing reactions from family and peers postcrash; (2) the motorcyclist's perception of his or her ability to handle risky road situations; (3) risk-taking attributes; (4) perceived responsibility in meeting family needs; (5) the severity of the crash-related injury; and (6) elapsed time from the crash experience.Conclusions: Riders' postcrash impressions were formed by the opposing reactions of their family and peers to the crash experience (i.e., the index crash); the personality of riders, including being overconfident and a risk taker; familial obligations; feeling traumatized by the crash; and passage of time. These formed their perceptions, feelings, attitudes, and thoughts about the index crash.These findings are an important step in understanding how perception and attitudes of motorcyclists are shaped and how these influence their future riding behavior. The needs for interventional studies to assess the effectiveness of road safety risk reduction programs aligned with the riders' degree of postcrash impressions are discussed.

An Engineering or Behavioural Approach? A Study into Employees’ Perceptions Regarding the Effectiveness of Occupational Road Safety Initiatives

Background and Aims: Considerable variation has been documented with fleet safety interventions’ abilities to create lasting behavioural change, and research has neglected to consider employees’ perceptions regarding the effectiveness of fleet interventions. This is a critical oversight as employees’ beliefs and acceptance levels (as well as the perceived organisational commitment to safety) can ultimately influence levels of effectiveness, and this study aimed to examine such perceptions in Australian fleet settings. Method: 679 employees sourced from four Australian organisations completed a safety climate questionnaire as well as provided perspectives about the effectiveness of 35 different safety initiatives. Results: Countermeasures that were perceived as most effective were a mix of human and engineering-based approaches: (a) purchasing safer vehicles; (b) investigating serious vehicle incidents; and (c) practical driver skills training. In contrast, least effective countermeasures were considered to be: (a) signing a promise card; (b) advertising a company’s phone number on the back of cars for complaints and compliments; and (c) communicating cost benefits of road safety to employees. No significant differences in employee perceptions were identified based on age, gender, employees’ self-reported crash involvement or employees’ self-reported traffic infringement history. Perceptions of safety climate were identified to be “moderate” but were not linked to self-reported crash or traffic infringement history. However, higher levels of safety climate were positively correlated with perceived effectiveness of some interventions. Conclusion: Taken together, employees believed occupational road safety risks could best be managed by the employer by implementing a combination of engineering and human resource initiatives to enhance road safety. This paper will further outline the key findings in regards to practice as well as provide direction for future research.

Tool to Manage Road Safety Deficiencies and Risk of Highway Crashes

In order to facilitate the management of the results obtained in the project “Analysis of the relationship between Road Safety Deficiencies, crashes and hazardous sections” financed by Public Works Agency of the Regional Government of Andalusia (AOPJA) and led by the research group TRYSE from University of Granada, a safety management tool has been developed. This application allows safety managers to consult some factors affecting crashes on two-lane rural highways.The main aim of that project was to analyze the influence of some road deficiencies on crashes and hazardous sections in the Complementary Road Network of Andalusia. These deficiencies were defined in a checklist and were identified by a road inspection. Decision Trees (DTs), that are a data mining technique that allows the extraction of Decision Rules (DRs), were used. DRs revealed the relationship between road deficiencies and crashes.The application allows two different analyses. A specific analysis of the Complementary Road Network of Andalusia, in which, particular safety problems can be identified, and the location of roads with those problems can be obtained. A more general analysis in which some characteristics related to road safety can be selected in order to know the combination of factors contributing to traffic crashes. Safety problems are based on data from Complementary Road Network of Andalusia but results can be extrapolated to other rural highways in Spain.

Dynamic and Acoustic Behaviour of Electric Versus Combustion Vehicles

This paper focuses on the methodologies and tools in use to answer the following research question: Is the dynamic and acoustic behaviour of electric vehicles without consequence in terms of a safe integration into current and future road traffic? Our research aims at investigating possible dissimilarities between electric and combustion cars that could reveal potential road safety risks. To this end, vehicle dynamics and acoustic parameters were collected in a field operational trial that was carried out on a dedicated test track, where a professional test driver executed a series of specific driving manoeuvres with three pairs of combustion-electric cars. Preliminary analyses indicate significant differences for the interior acoustics and the external acoustic emissions. Regarding the vehicle dynamics, no direct road safety relevant differences were identified yet.