IATSS Research最新文献

The growing number of vehicles and the evolving behaviour of road users present new and additional challenges to road safety. Study on the variables that influence the frequency of crash occurrences such as road geometry, junction, speed and land use are needed as they have proven effects on the number and severity of crashes. In this paper, we identify and assess the variables, namely road geometry, vehicle speed, traffic volume, land use and junction type, and develop accident frequency prediction models for a main urban transport corridor in São Paulo, Brazil. Crash data was provided by the traffic management company of the city, other datasets were obtained from a mix of primary and secondary sources including roadside cameras, Geographic Information Systems (GIS) and digital mapping tools. The studied road was segmented and the coefficients associated with variables in the segments were obtained using Poisson regression through a stepwise variable selection procedure. Two models with junctions density per type (access/km, T-junction unsignalised/km, T-junction signalised/km and crossroads/km) and junction density per merged type (signalised/km and unsignalised/km) along with land use per type (commercial and residential) are developed. The junction density and land use are found to be significant and positively correlated with crash frequency. The models were evaluated by statistical means for their accuracy of predicting the crashes, and validated with additional information obtained from field observation.

Lane change has a potential significance in road safety. Gap acceptance phenomena serves as a primary and critical phase in lane change maneuver. This study aims to investigate the gap acceptance behaviour of drivers during lane changes on expressways, with a focus on understanding how various factors influence drivers' decisions to change lanes. An extensive dataset collected through various sensors tailored for expressway driving, known as the ‘Expressway Drive: Instrumented Vehicle (EDIV) Dataset’ is utilized. Driving data from 59 drivers covering a distance of around 4000 km was used in the current study. Total 2578 lane changing events are identified through computing lateral deviations measured through 3D LiDAR sensor. Substantial differences are observed within the groups in primary analysis which suggest that lane-change direction significantly affect gap acceptance. To effectively manage both intra- and inter-cluster variances, this study employs two separate three levels mixed-effects linear models. These models account for the interdependence of gap acceptance characteristics within individual drivers and for different directions of lane changes by incorporating random effects. Furthermore, these models examine relationships between lead/ lag gap acceptance and the various influencing factors as fixed effects. It was found that factors such as speed of the subject vehicle, gap position, relative speeds, and surrounding vehicle types had influence on gap acceptance during lane changes on expressways. The insights gained from this study could inform the development of advanced driver assistance systems (ADAS) as well as development of autonomous vehicles, contributing to improved road safety and traffic flow management in high-speed environments.

This paper proposes a method for identifying the bicycle riding environment using only onboard equipment. Initially, a fundamental subsystem is established for identifying the bicycle riding environment, and its functionality is validated. The findings indicate that the subsystem, utilizing an open-source trained model, can detect riding on roadways but not on sidewalks. Consequently, we emphasize the need for transfer learning, specifically using sidewalk viewpoint images, to enable the identification of bicycle riding environments. Subsequently, we conduct bicycle riding environment identification by employing a transfer learning model with manually labeled training data. The results demonstrate that after transfer learning, sidewalk riding detection, which was previously unachievable, becomes feasible. The identification rate was over 80%. Furthermore, we develop four riding environment identification algorithms, including the transfer learning model, and compare their performance across various road environments and riding conditions. Consequently, it is established that the region of interest (ROI) extension identification algorithm exhibits the highest identification performance (93% on average). As a result, this paper contributes valuable insights into the realization of bicycle riding environment identification, particularly in the context of detecting traffic violations within the riding safety support information system.

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.