IATSS Research最新文献

In Asian megacities, behind wide streets accessible by car, there are areas of narrow streets that are inaccessible by bus or car. This study investigates measures to improve access to bus stops in Hanoi from the perspective of the neighborhood environment of these residents. These results are expected to contribute to solving similar problems in Asian megacities. The survey divided residents into two groups, one group living on wide streets and the other group living on narrow streets in Hanoi, then obtained and analyzed data on their attitudes towards walking to bus stops through a questionnaire survey. The results revealed the following. The distance to the bus stop was accessible for both groups. Between the two groups, the attitude towards walking to the bus stop is more influenced by the location factor than the occupation (employee or student). Factors such as the benefits of walking, infrastructure, and security conditions play an important role in the decision to walk to the bus stop during the daily commute.

The most well-known benefits of heavy commercial vehicle (HCV) platooning include fuel savings and emission reductions. In addition, HCV platooning under SAE automation level 4 or 5 can mitigate the truck driver shortage in North America by eliminating the driver from one or more HCVs in a platoon. This study investigates the passing sight distance (PSD) required to overtake a truck platoon or long combination vehicle (LCV). The PSD is one of the most important highway geometric design parameters. This study modified the 2018 AASHTO's PSD model for HCV platooning and long combination vehicles (LCVs). A micro-simulation model is used to validate the outcomes of the modified AASHTO model. The estimated PSDs suggest that it may be possible to operate two-HCV platoons on two-lane highways that already allow LCV operation if appropriate passing lanes are installed. The study's approach and findings are expected to help transportation engineers and government agencies prioritize two-lane highway sections for possible HCV platooning operation.

In our three-year project, the team set the final goal as a proposal for future cities and public transportation linkages in the context of cultural and creative activities in cities. As the project leader, the author first introduces a basic discussion of cities and urban public transport modes, followed by an analysis of subjective accessibility related to well-being. Second, the author introduces field surveys in New York, London, and Wien as advanced cities with excellent cultural and creative activities, as well as Toyama City in Japan, where the importance of public space redesign related to quality public transport in conjunction with cultural and creative activities is identified. Finally, the author summarizes the conclusion of the research project, including the proposal as “Yoin City” (city or district where aftertaste of any cultural and creative activities is highly respected mainly with excellent design of urban public spaces and public transport services) with “new local” concept primarily for middle-sized cities in Japan.

In this study, we conducted bicycle riding experiments that focus on the method of information presentation by an automated system to cyclists, with the intent to design an information system related to bicycle safety information. In an evaluation of information presentation, we confirmed that auditory presentation was the most effective from the viewpoints of both recognition and comprehension. In addition, information presented using the auditory method was more likely to be recognized than information presented using the visual and tactile method combined. The results of the analysis of variance for recognition showed that the visual presentation method had no significant effect. In addition, the experiments involved behavioral observation using the system and a questionnaire survey on changes in behavior before and after experiencing the system. The results showed that information was correctly conveyed by the system using a combination of auditory, tactile, and visual presentation methods, regardless of the users' degree of awareness of the system. Two weeks after the experiment, a survey was conducted to investigate the changes in the participants' awareness and behavior regarding risky or illegal riding. The results showed an improvement in the awareness of risky or illegal riding in daily life and an increase in right behavior, confirming the effectiveness of this system. Consequently, the results demonstrate the effectiveness of the system and provide knowledge for realizing a bicycle riding safety support information system.

This study aims to examine the differentiated impacts of frontage-lane, main-lane, and standard-lane motorcycle collisions on rider injury severity in Thailand. Using comprehensive crash data from 2016 to 2019, a random parameters model accommodating heterogeneity in means and variances is applied. Predictive comparisons between out-of-sample and within-sample predictions uncover differences between collision location sub-models. For frontage-lane collisions, severe or fatal injuries are positively associated with male riders, truck involvement, and speeding. In main-lane collisions, increased severe/fatal injury risk is associated with nighttime, holidays, weekends, single-motorcycle crashes, and collisions with trucks or pickups. In standard-lane collisions, positive severe/fatal injury associations include male riders, nighttime, non-peak hours, speeding, truck/pickup involvement, and pillion presence. Predictive comparisons show reorienting crashes to the frontage lane could reduce fatal injury probability by 0.1199 and 0.2233 versus the main and standard lanes respectively, preventing many fatalities. This research underscores accounting for unobserved heterogeneity and predictive simulation insights. The findings inform effective countermeasures and aid safety professionals, instructors, policymakers, law enforcement, and designers in motorcycle safety efforts.

Overtaking is one of the most complex maneuvers on the two-lane two-way (TLTW) roads, where the follower vehicles use the opposing lane to bypass the leader slower vehicles. Overtaking becomes more riskier with the presence of oncoming vehicles from the opposite direction. This paper presents the development of an overtaking model for the Egyptian TLTW roads under mixed traffic conditions. About 20-h of videotaped data from 6 different TLTW roads, located in the Delta region in Egypt are studied to develop the proposed model. This model considers key factors affecting model performance that are not considered in most international state-of-the-art models. These factors include (a) acceleration of the follower vehicle (FV) during all phases of overtaking, (b) deceleration of the leader vehicle (LV), (c) length of the LV, and (d) speed change of the LV during overtaking. The proposed overtaking model is divided into two parts. The first part includes two conditions as criteria for acceptance/rejection decision of overtaking while the second part computes the overtaking duration and the corresponding distance for successful overtakes. The model is calibrated for 4 sites and validated on the remaining 2 sites. The results show that the proposed overtaking model matches closely the observed accepted and rejected overtakes by 96.45% and 95.90%, respectively. Furthermore, the results showed that the proposed model was consistent with the observed overtaking distances and times. In addition, the results are compared with other international models such as the Ghods, Tang, TWO-PAS, and Cirianni models.

Vehicle-pedestrian hit-and-run crashes have grave consequences as the pedestrian casualty is left at the crash scene, leading to delays in emergency response. Research indicates that prevailing weather conditions are pivotal in influencing these crashes. Nonetheless, there exists a substantial gap in understanding the diverse associations of contributing factors that impact the severity of pedestrian injuries in vehicle-pedestrian hit-and-run crashes under varying weather conditions. This paper extensively examines the intricate patterns of critical factor associations influencing the pedestrian casualty injury severity in vehicle-pedestrian hit-and-run collisions in Ghana, differentiating between clear and inclement weather conditions. Leveraging historical crash data, this research employs the robust Association Rule Mining tool to unveil the relationships between key crash factors and their outcomes. The association rules extracted from the data reveal that specific factors consistently influence injury outcomes in vehicle-pedestrian hit-and-run crashes, regardless of weather conditions. However, there are distinct patterns of factors contributing to fatal and severe injuries in these crashes that vary depending on the prevailing weather conditions. Hit-and-run crashes resulting in fatal and severe pedestrian injuries are primarily associated with males and are notably correlated with factors like pedestrian crossings, late and early morning hours, the absence of traffic control measures on median-separated motorways, and good urban roads, regardless of prevailing weather conditions. During clear weather conditions, fatal/severe injuries tend to occur in daylight conditions, primarily on roadways devoid of shoulders, and involve older pedestrians crossing the road. Conversely, for inclement weather conditions, these crashes are more prone to occur during nighttime hours on unlit roads, often involving younger pedestrians walking along the road's edge. The reduction of fatal/severe injury hit-and-run crashes involving vehicles and pedestrians can be effectively tackled by eliminating or improving the critical factors pinpointed in the extracted rules. The study underscores the urgency of policy recommendations to mitigate fatalities resulting from vehicle-pedestrian hit-and-run crashes, emphasising the need for stricter legislation, heightened enforcement measures, increased awareness of pedestrian safety, enhanced driver training, and infrastructure upgrades. By acting on these insights, a significant stride can be made in curbing the alarming rates of vehicle-pedestrian hit-and-run fatalities.

Run-Off-Road (ROR) crashes are frequent and pose a significant risk of injury and fatality. Given the complexity of their mechanisms and the interaction of multiple factors, this study aims to comprehensively investigate the factors influencing the severity of ROR crashes, which have been understudied. Furthermore, addressing the current methodological challenge in machine learning (ML) crash modeling, this study proposes an approach to tackle unobserved heterogeneity in ML. An interpretable ML joint with prior latent class clustering is implemented. The significant risk factors and interactions are interpreted using SHAP (SHapley Additive exPlanations) method across clusters. This study utilizes ROR crash records, traffic, and geometric data from main suburban freeways in Iran collected over a 5-year period. The key interacting factors associated with severe ROR during adverse weather (cluster 1) are: co-occurrence of low congestion and higher speed variation; low congestion, nighttime darkness and rollover; roadway departure by buses and mini-buses and rollover occurrence; vehicle departure and collision with fixed objects. Moreover, the critical interactions for nighttime condition (cluster 2) are: curve sections combined with longitudinal slope; inside shoulder width <1.5 m and a hit median concrete NewJersey barrier. The risky interactions for crashes occurred in curves (cluster 3) are: departing in two-lane sections in low congestion conditions; vehicles collisions with the median concrete NewJersey barriers. The findings of this study enhance comprehension of the significant effects of interactions under various conditions, offering valuable insights for policymakers. Additionally, recommendations are offered to mitigate the risk of severe ROR crashes.

As part of a research project of the International Association for Traffic and Safety Sciences (IATSS), a series of surveys were conducted on the behavior of cyclists and the countermeasures. This paper outlines the mechanisms of bicycle accidents in Japan and their countermeasures. According to accident statistics, the two target groups for the prevention of bicycle accidents include the child population of elementary, junior high, and high school students, and the older population aged 65 years and over. Questionnaires and behavioral observation surveys of junior high school students revealed tendencies for students to violate rules, such as not stopping temporarily, not searching left and right at crossings, riding alongside, and looking aside when riding. A field experiment with junior high school students using gyro sensors revealed that their level of searching for safety was extremely low. Furthermore, clear differences existed in the manner in which each individual searched. Based on these results, several educational and practical activities were performed. In addition, a study was conducted with older cyclists at a driving school to measure behavioral characteristics, such as searching behavior at crossings and riding (walking) position. The license status factor significantly impacted the safety aspects of the behavior of older cyclists, with unlicensed cyclists lacking safety searching behavior when passing through intersections and crossing the road and having lower riding position scores.

The first edition of the Highway Safety Manual (HSM) contains a simplistic version of the crash prediction model for two-way stop-controlled intersections (TWSC) on rural two-lane highways. This model considers AADT on major and minor roads, with the base conditions defined as no intersection skewness, no turning lanes, and no lighting. A crash modification factor (CMF) will be applied if an intersection has conditions different from the base condition. However, the HSM model does not take account of curvature. It is well known that curved TWSC intersections are less safe than non-curved ones, particularly on rural two-lane roadways. This paper presents the development of crash prediction models incorporating intersection geometrics for TWSC intersections on rural two-lane highways in Louisiana. Then, it compares the results from the developed model with the calibrated HSM model. The negative binomial model was used with 5126 TWSC intersections verified one by one, including both three- and four-leg intersections from all parishes (counties). The estimation results indicate that AADT, curve radius, and intersection skewness angle significantly impact expected crash frequency for both three- and four-leg intersections. This research utilizes cumulative residual plots, mean absolute error, and root mean square error for comparative analysis of HSM models, HSM models with calibration, and Louisiana-specific models. The results show that Louisiana-specific SPFs outperformed the calibrated SPFs with superior reliability. Calibration factors of 0.58 for three-leg intersections and 0.46 for four-leg intersections are estimated, suggesting that the original HSM model overpredicts crashes in Louisiana.