IATSS Research最新文献

Adaptive Cruise Control (ACC) is a technology that can reduce traffic. However, its availability in Iran is relatively limited compared to more developed countries. This research examines the acceptance and willingness to pay for ACC among Iranian drivers. Data from an online survey of 453 respondents were analyzed using an ordered logit model and a structural equation model. The results of modelings show that perceived ease of use and perceived usefulness affect attitudes towards using ACC, which in turn influence behavioural intentions. In addition, drivers who find ACC easy to use and user-friendly, own expensive vehicles, and female drivers who have experience with cruise control are more likely to pay for ACC. To enhance the adoption of ACC in Iran, it is recommended to target early adopters, especially women and capitalists, who can influence others with their positive feedback. The benefits of ACC for traffic safety and environmental sustainability should also be emphasized. Furthermore, future studies would better concentrate on public perceptions and assessing the necessary infrastructure for ACC in Iran.

Until early 2000s, modern roundabouts (RABs) were poorly understood in Japan and were not fully recognized as a form of at-grade intersections. The RAB research projects of the International Association of Traffic and Safety Sciences (IATSS), which began in 2009, started with examining the applicability of RABs in Japan and have steadily progressed to various stages of field experiments, social implementation, and dissemination promotion activities. These RAB research projects, which lasted for approximately seven years, are considered to have played a significant role in the practical application of RAB in Japan. This paper provides a chronological overview of the history, content, and development status of these projects and records and discusses the role that IATSS research projects played in the early days of RABs in Japan.

Modelling traffic characteristics is the foundation for resolving various traffic and transportation issues. Among them, traffic speed has a significant impact on roadway crashes at blackspot (BS) locations. Speed is a random variable; several studies have recommended normal distribution to characterize the distribution of traffic speed for uninterrupted flow. However, a mixed-traffic situation causes heterogeneity, and the distribution of speeds deviates from the normal distribution. The present study investigates the distributions of traffic speeds for uninterrupted flow at 18 blackspot locations and individual vehicle types in mixed-traffic environments. Seven distribution models, namely Normal, Lognormal, Gamma, Logistic, Weibull, Burr, and Generalized Extreme Value (GEV), are considered to determine the speed characteristics. Different parametric distribution models are fitted to the vehicular speeds using maximum likelihood estimation (MLE) methods. Kolmogorov-Smirnov (KS), Anderson-Darling (AD), and two penalized criteria, i.e., Akaike and Bayesian Information Criteria (AIC and BIC), are used as goodness-of-fit (GoF) measures to find the best-fitting distribution. The overall suitability of each predicted distribution is also determined using a novel ranking method. The test findings suggest that GEV and Burr are the most suitable empirical speed distributions, with GEV fitting best above 96%. When the heavy vehicle composition (truck, bus, and tractor) is below 10%, 10–14%, 15–20%, and above 20%, it follows the Weibull, Gamma, GEV, and Burr distributions, respectively, in a mixed traffic environment.

Following behavior, an integral part of driving, is vital in describing the longitudinal interaction among vehicles. The traffic composition of the stream influences the following behavior. Several studies have concentrated on developing the following behavioral models; however, very few have addressed the sophistication needed to cater to the pragmatic needs of the present day, inducing the real, naturalistic sense of traffic movement. This study endeavors to review the previous following behavior studies in a different aspect and to find the research gaps accordingly. The study disintegrates the following behavioral models based on three levels of heterogeneous traffic conditions: (1) Homogenous Regular Vehicle (Hom-RV); (2) Heterogenous Regular Vehicle (Het-RV); (3) Heterogenous Connected Automated Vehicles (Het-CAV) (4) Heterogenous Regular Vehicle with Connected Autonomous Vehicles (Het-RV-CAV). The categories mentioned above have been explored in terms of the generalized following behavioral model structure having uniform notations to study input-output variables and their inter-relations, data collected and performance measures of the parameters for different traffic conditions. The in-depth review reveals that incorporating human psychological variables, and intelligent vision-based sensors, thereby upgrading the existing dataset and adding more studies considering Het-RV-CAV, can fill the potential gaps in the current knowledge domain.

Sleep-related breathing disorders (SRBD), characterized by episodes of apnea and hypopnea during sleep, are highly prevalent worldwide. Although adherence to continuous positive airway pressure (CPAP) therapy improves quality of life and reduces symptoms in patients with obstructive sleep apnea (OSA), and OSA treatment is well established, the vast majority of individuals with OSA who might benefit from treatment remain undiagnosed. This is attributed to the high-cost of undergoing polysomnography, which is the gold standard test for OSA, and requires special equipment and experts, limiting the number of facilities that can perform this test. SRBD is a risk factor for traffic accidents and lifestyle diseases because it causes daytime/waking sleepiness. Traffic accidents caused by commercial drivers have a serious impact on social safety. Furthermore, obesity and overweight status, which is a main risk factor for SRBD, is more prevalent among commercial drivers than among the general population. Thus, the promotion and awareness of SRBD screening among commercial drivers are urgently required. In this overview, we provide an assessment of the present status and challenges related to SRBD screening in Japan. Our insights are drawn from the outcomes of our project titled “Interdisciplinary research on the dissemination and promotion of screening for sleep disorders”, which received funding from the International Association of Traffic and Safety Sciences from 2012 to 2014. The project focused on exploring the association between SRBD and traffic accidents among commercial drivers in Japan. The findings of our project suggest the importance of early detection and treatment of SRBD through screening using objective measurements for all commercial drivers.

Distracted driving poses one of the most significant risks to road safety. The current study aims to provide a deeper understanding of the factors affecting the severity of distracted driving crashes in New York City and to explore the temporal stability in the effects of different variables on crash outcomes in 2016 to 2019 period by adopting a post-crash perspective. The police-reported data of single-vehicle distraction-related crashes of private cars on urban roads of New York City was used for this study. Three injury categories were considered: no injury, minor injury, and severe injury. To investigate crash severities and identify unobserved heterogeneities, a random parameters logit model was conducted. The results revealed that a wide variety of variables including driver traits, vehicle and temporal characteristics, and crash attributes were found to be significant in explaining distracted-related crash severities. Furthermore, a series of likelihood ratio tests were conducted to identify the temporal shifts of estimated variables during the period. The results of the temporal analysis showed that the estimated variables of the random parameters model were unstable during the 4-year period, which may be the result of shifting trends such as the development of in-vehicle technologies, and new sources of distraction. However, the complex nature of distracted-related crashes and changes in driver behavior should be considered for further interpretation. This research provides a set of policy implications for planners and policymakers, aiming at facing factors contributing to a higher level of injury severity in distracted driving crashes. This includes providing targeted information on distracted driving to high-risk groups, such as younger drivers, and also combining education, awareness programs, higher penalties, and intense patrolling. Engineering measures such as enhanced roadside illumination and audible edge lines can be effective, especially in reducing late-night distracted driving crashes.

Mountainous areas pose unique challenges to transportation safety, with their complex terrain and harsh weather conditions. The presence of steep terrain can lead to winding roads with a high degree of azimuth change per mile, thereby increasing the potential for hazardous driving conditions. Additionally, steep terrain is often associated with fog formation, which can obscure roads by clouds. Thus, there is a need to study weather-related crashes and identify associated risk factors in mountainous areas. To address this issue, the Tobit, latent class Tobit (LCT), and two-part truncated log normal (TPTLN) models were employed to investigate the potential interactions between topography and weather-related crash rates, while accounting for the censored nature of crash data. Data from the western region of North Carolina, which is home to numerous mountains experiencing a wide range of weather conditions was used for this purpose. This region comprises a 3570-mile road network across seven cities, with elevations ranging from 1000 ft. to >6158 ft. above mean sea level. Crash data from 2015 to 2017 was obtained from the Highway Safety Information System (HSIS). The results revealed that topography significantly affect weather-related crashes in mountainous areas. Higher elevations and steeper slopes are associated with lower crash rates. Also, the study highlights the importance of considering topography when assessing transportation safety in mountainous areas. The findings help develop transportation safety policies and interventions aimed at improving safety in these areas.

Traffic enforcement is one of the 3E's of traffic safety measures. Traffic enforcement has been reported to reduce traffic accidents worldwide; however, significant regional differences exist in its effectiveness. This study summarizes the history of the effects of traffic enforcement on reducing traffic accidents in Japan. In particular, scientific approaches and more efficient enforcement since 2000 have been described in the research results. Although the implementation of data-based PDCA (Plan-Do-Check-Action) has steadily reduced the number of traffic fatalities, further reductions are expected through the use of new technologies such as artificial intelligence.

This study was conducted in 2007–2009 as the IATSS Research Project to consider the comfort and safety of city centers in the automobile age from the perspective of “parking places.”

We focused on four elements related to parking places, that is, 3D & M (density, disposition, design, and management) and proposed changes to parking policy in Japan by comparing and analyzing the actual conditions of parking lots or facilities in different city centers and legal systems in several counties, including Japan, the United States of America, the United Kingdom, and Germany.

The key concept of our proposal is that we should shift the policy of parking from equipment-duty car-parking “on-site” to parking installation”in-area,“good management, and smart operation.

The findings of this project were widely shared through open symposium with non-members of the IATSS as well as book publication and led to many system revisions in the Japanese parking policies.

Introduction-Motorized Two-Wheeler (MTW) is a convenient and affordable mode of transportation despite being highly vulnerable to rollover crashes. The possible fact may be that MTW is a single-track vehicle and thus lack longitudinal stability, particularly on horizontal curves (H_C). This stability depends on external factors such as curve geometrics and contact surface properties. Therefore, this research aims to identify the impact of pavement surface conditions and roadway geometrics on MTW run-off road crashes on H_C. Method-To consider the temporal effect of pavement surface conditions, this study analyzed different combinations of light and surface moisture conditions for pre- and post-pavement surfacing conditions. Thus, Generalized Estimating Equation (GEE) linked with the log function was used to account for repeated observations. Sample data were collected bi-annually from 76 H_C for two years of pre- and post-resurfacing. Pavement surface condition parameter includes skid resistance, rut depth, and international roughness index (IRI). However, to restrain the impact of pavement surface conditions, a separate analysis was carried out to investigate the impact of geometrical design attributes. Results-The analysis concluded that surface moisture condition, light condition, rut depth, and their interactions with AADT were found significant for pre-resurfacing. For post-resurfacing, surface moisture condition, and light condition, IRI and its interaction with AADT were found significant. Similarly, roadway geometrics such as curve radius and their interaction with the presence of sight distance, public activity centre and cross-slope were found significant. Conclusion-Overall, the study insights and confirms how and to what extent pavement surface properties and geometric attributes impact the subject crashes. The results will enhance the understanding of roadway architecture and may help highway designers to implement, either at the intervention or treatment level, to improve safety and comfort.