IATSS Research最新文献

The autonomous vehicle (AV) is predicted to reduce the number of accidents and fatalities on the roads caused by human-related error and lessen traffic congestion caused by stop-and-go behavior. The susceptibility of autonomous vehicles (AVs) to potential hacking and data exploitation has generated significant concerns regarding cybersecurity and privacy risks within the domain of perceived safety. This study aimed to empirically test a comprehensive model of perceived safety in AVs, incorporating cognitive safety, emotional safety, and privacy cybersecurity. The responses of 466 participants were analyzed using a structural equation modeling (SEM) approach. The findings indicated that a significant majority of the respondents expressed their intention to utilize high-level autonomous vehicles (AVs) in the future. Specifically, 31.1% of the participants expressed an intention to use a level 2 AV, while 8.8% indicated their preference for a level 5 AV. In terms of perceived safety, privacy cybersecurity emerged as the most influential predictor, followed by emotional safety and cognitive safety. The analysis of causal relationships between the variables further revealed that privacy cybersecurity had the greatest impact on both emotional safety and cognitive safety, highlighting its critical role in shaping the overall perception of safety in AVs. Finally, this study can provide insight into how the drivers perceives AVs safety, which can be useful for government organizations, transportation agencies, and AV developers in shaping AV safety.

This paper summarizes current trends in the research and development of e-Mobility and energy coupled simulation to deal with electric vehicle integration into power systems, optimal charging infrastructure design, and regional energy and environmental impact assessments. Small trials and simulations were introduced as a case study. The car probe and floating population data are input into various electric vehicle dynamic models, in which variable vehicle speed and state-of-charge are precisely considered. Then, the synergic impacts on the mobility and energy sides are evaluated through co-simulation of the road traffic and distributed power system models.

Despite numerous studies on motorcycle safety, especially the compliance of helmet use laws in both developed and developing countries across the globe, little is known about the mediating role of traffic law enforcement and road safety education specifically on the relationship between helmet use influencing factors and helmet usage in general. The aim of this study was to examine the mediating role of traffic law enforcement and road safety education on the relationship between helmet usage influencing factors and motorcycle helmet usage. A total of 358 respondents from a university community that uses a motorcycle on daily bases to and from the community and for other important trip purposes completed a self-reported questionnaire in the Upper West Region of Ghana where motorcycles are predominantly used as a transportation mode. To test for the various hypotheses of this study, we developed a hypothesized single multiple mediated structural equation model and several sub-mediated models using AMOS 26.0. The results showed that the perceived safety of the helmet, weather conditions, and convenience of helmet use have positive significant impacts on helmet use. The study also found a full mediation role of the combined effect of traffic law enforcement and road safety education on the relationship of helmet use influencing factors investigated and helmet use. The study concludes that new traffic law enforcement and road safety education strategies need to be adopted to help improve upon the low prevalence of helmet use within the study area.

For Japan to achieve its targets for carbon neutrality and reduction of carbon dioxide (CO₂) emissions, decarbonization of road transport is essential. Japan regards next-generation vehicles, including hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), battery electric vehicles (BEVs), and fuel cell vehicles, as a key means of reducing carbon emissions from road transport. Four scenarios were proposed to predict the potential carbon emissions reduction of passenger car use in 2030: baseline, business-as-usual, government's target-based, and aggressive scenarios. Economic input–output life cycle assessment was used to evaluate potential CO₂ emissions, acidification, eutrophication, human toxicity, and photochemical oxidation associated with passenger cars. In this study, all environmental impacts were calculated using the multi-regional environmentally extended supply and use/input–output database by applying the CML 2001 impact assessment method. The findings indicate that PHEVs have the lowest CO₂ emissions per km traveled, followed by HEVs and BEVs. The prediction for carbon emissions from passenger cars shows that adopting electrified vehicles, such as HEVs, PHEVs, and BEVs could help decarbonize the passenger car sector. The population of vehicles, vehicle manufacturing, well-to-wheel cycle of fuel, and fuel economy will significantly contribute to CO₂ emissions. Finally, this study recommends policies to steer Japan into achieving its goal of carbon neutrality.

Although the Epworth Sleepiness Scale (ESS) is a scoring system commonly used to assess daytime sleepiness (DS), the association between ESS and motor vehicle accidents (MVAs) remains unclear. Therefore, we conducted a cross-sectional study to examine the association between an increase in the Japanese version of the ESS (JESS) scores and MVAs among Japanese male taxi drivers. The study participants were 1384 Japanese male taxi drivers. DS was assessed using the JESS, and the total JESS scores were categorized into quartile groups. MVA experience during the past five years was assessed using a self-administered questionnaire. A multivariable generalized linear model was used to examine the association between JESS and MVAs after adjusting for age, body mass index, smoking status, snoring, sleep duration, driving experience, driving distance per year, hypertension, and diabetes mellitus.

The proportion of MVAs was 59.7%. The multivariable-adjusted prevalence ratio (95% confidence interval) of MVAs for the highest quartile of the JESS score was 1.16 (1.04–1.29) compared to the lowest quartile, and for continuous JESS score was 1.01 (1.002–1.02). Thus, we found a significant association between an increase in JESS scores and MVAs among Japanese male taxi drivers after adjusting for potential confounders. Stratification by sleep duration and snoring status revealed a significant association among long sleepers and non-snorers. Our findings suggest that ESS evaluation methods be reconsidered in relation to MVA among commercial drivers.

Pedestrian safety is essential to realize a walkable city. This study analyzed the impact of road infrastructure and traffic control on severity of pedestrian–vehicle crashes at intersections and non-intersections. We applied a bias-reduced logistic regression analysis using 86,406 pedestrian–vehicle crashes data including 2636 fatal accidents in Japan. The results of the study indicate that medians increased the severity of crashes at intersections; on the other hand, they decreased the severity at non-intersections. In addition, flashing traffic signals increase the severity while stop signs decrease the severity at intersections.

Estimates of passenger car CO₂ emissions that reflect regional characteristics are useful for predicting the effects of electrification, modal shifts in transport, and urban compactness. To date, differences in emissions have often been estimated based on the regional differences in the number of vehicles owned. Regional differences in mileage were estimated from the counts of the Origin and Destination Surveys in the Road Traffic Census. In this study, by utilizing the mileage data from the vehicle inspection certificate data, it was possible to reflect the differences in mileage per vehicle in detailed regional terms. The higher the population density, the smaller was the mileage per vehicle. Based on this, we calculated the CO₂ emissions from passenger cars by municipality nationwide and estimated the CO₂ emissions and population share by grid population density. In areas of 3000–10,000 persons/km², which accounts for approximately 40% of Japan's population, emissions per person approximated the national average. However, in areas with 1000–3000 persons/km² (approximately 20% of the population), emissions per person were approximately 30% higher; while with 100–1000 persons/km² (approximately 1.5% of the population), they were approximately 70% higher; and with 10,000 persons/km² (approximately 25% of the population), they were approximately 70% lower. A map was produced for use when considering the cities and regions suitable for a decarbonized society as well as policies such as electrification, modal shift, and coordination of urban centers.

The pedestrian crash pattern in the dark-no-streetlight condition is a noteworthy ongoing traffic safety concern. The persistently high percentage of pedestrian fatalities at night in the U.S., as well as in the state of Louisiana, necessitates new research to supplement existing studies. This study utilized 10 years (2010–2019) of pedestrian fatal and severe injury crashes in Louisiana that occurred in the dark without streetlights to identify the associated crash patterns. The methodology is based on Multiple Correspondence Analysis (MCA), an exploratory approach used to discover the association of multiple categorical variables from a crash dataset. The findings suggest that driver characteristics (age, gender, and physical condition), pedestrian action, pedestrian alcohol impairment, and physical settings (posted speed limit, location, and roadway type) have a substantial impact on pedestrian collisions at night without streetlights. Moreover, the obtained combination clouds of MCA reveal associations such as elderly pedestrian (>64 years) alcohol impairment resulting in fatalities, crashes in an open country location with a high posted speed limit, crashes involving pedestrians in dark clothing on high-speed (50–55 mph) roadways, alcohol-impaired driver involvement in crashes on two-way roads without physical separation, severe injury crashes at intersections, male pedestrian crashes on midblock locations during weekends, and young (15–24 years) female driver's involvement in crashes while pedestrians were walking against the traffic. Based on the findings, this research also suggests safety recommendations that can assist highway safety practitioners in determining appropriate countermeasures to reduce pedestrian crashes in the dark-no-streetlight condition.

Background

Low-and middle-income countries (LMICs) have the greatest road traffic crashes burden, with about 93% of global fatalities occurring in such countries. This situation is partly due to the high level of psychosocial work hazards to which professional drivers are exposed. Therefore, this review aims to map evidence on the psychosocial work factors that influence risky driving behaviours and road traffic crashes in LMICs.

Methods

Four main databases (PubMed, Central, Dimensions and JSTOR), in addition to google and google scholar, were searched for records. In all, 6537 records were retrieved and finally, through experts' consultations and a vigorous screening process, 54 studies were included in this review. Included studies sampled 30,272 drivers from 23 LMICs.

Results

The reviewed studies found that job strain, efforts-reward imbalance, payments based on performance, lack of social support from supervisors and co-workers, lack of job control from job autonomy and skill discretion, long driving hours, lonely driving, irregular job schedules like shift work and overtime, work-family conflicts, job insecurity and lack of safety motivation are the main psychosocial work factors influencing risky driving behaviours and road traffic crashes among professional drivers in LMICs.

Conclusion

Though more quality studies are needed to explore the psychosocial work factors of professional drivers in LMICs, there is a need for occupational health and safety policies for improved working conditions like reduction in workload and long driving hours, access to healthcare and improved psychosocial safety climate.