Asian Transport Studies最新文献

The limited road space and overlapping driving decisions may cause frequent speed and lane changes in the downstream area of expressway toll stations, which easily cause high accident risks. In this paper, micro vehicle trajectory data in the Huai'an South Toll Station was automatically extracted from aerial videos using the novel YSKT algorithm framework to analyze traffic flow characteristics. To further evaluate vehicle collision risks, the Extended Time-To-Collision (ETTC) and Post Encroachment Time (PET) indicators were employed. The results demonstrated that the longitudinal and lateral velocity and acceleration, the distribution of lane-changing points, lane-changing times, and travel time varied with road sections and vehicle types. Notably, the ETC vehicles had a higher risk of traffic accidents compared to MTC vehicles since their greater initial speed. The findings could provide valuable references for traffic managers to comprehensively understand traffic characteristics and evaluate traffic safety of similar complex road nodes.

In response to escalating climatic threats, this research innovatively integrates flood risk assessment with road network dynamics to formulate optimized evacuation strategies in flood-susceptible regions. Employing a path-based traffic model and flood risk index, our method significantly decreases travel durations by 25% and vehicle hours by 20% compared to traditional frameworks. Complexities arise in intricate evacuation systems. Zone 4 was a critical node due to a 15% rise in vehicular inflow and unique flood risks, emphasizing the necessity for tailored evacuation plans considering variable traffic and flood risks. Our approach enhanced evacuation efficiency and also resulted in a 10% increase in fuel consumption while highlighting areas for further optimization. This study proposes a refined, sustainable evacuation model that harmonizes flood risks and traffic dynamics and offers insights for resilient urban development amid climatic uncertainties.

Since floods caused by overflowing rivers are increasing in Southeast Asia cities, reducing urban mobility, adaptation measures are required to cope with this situation. One possible measure would be to develop transportation facilities to make them passable even during flooding conditions. Another measure is to encourage people to relocate from high-risk areas to low-risk areas. Implementing an appropriate combination of these two different adaptation measures is necessary. However, there is limited research to assess the impacts of adaptation measures on flood risk and urban activity. Therefore, this study developed an urban adaptation model that could assess mobility and land use for Ubon Ratchathani, Thailand, and analyzed to what extent the decrease in urban mobility can be alleviated by combining these adaptation measures. It showed that a combination of both adaptation measures could ensure mobility under flood conditions, with benefits from travel time reduction estimated at up to 230.44 million baht (6.36 million USD) over 20 years.

Understanding driver behavior is crucial for introducing roundabouts. This study focuses on calibrating the parameters of the car-following model using naturalistic data and analyzing the appropriateness of different car-following models on the roundabout. We utilize rounD trajectory dataset. This dataset allows for the precise definition of lead and follow vehicles, enabling the calibration of model parameters accordingly. We compared the calibration results for roundabouts with those obtained for signalized intersections from CitySim. Our results show that the Krauss and intelligent driver models (IDM) achieve mean absolute percentage errors of 10.09% and 23.21%, respectively. Furthermore, IDM exhibited higher errors in the circulation segment of the roundabout, while in the exit segment, the Krauss model showed elevated errors. It contrasted with the homogenous results obtained in the signalized intersection. These findings provide valuable insights into driver's behavior on roundabouts.

This study aims to investigate the relationship between the numbers of pedestrian-vehicle crashes (PVCs) and the traffic and built environments from a macroscopic perspective. A binomial distribution model has been developed to represent the occurrence of PVCs. To calibrate the model, Bayesian analysis using the Markov chain Monte Carlo method has been employed. The results identify thirteen variables representing urban activities and traffic conditions, including land uses, degrees of mixed use, points of interest, various passage widths, and street hierarchy that significantly impact PVCs. Additionally, the study unveils the spatial distribution of PVC probabilities and exposures. This research contributes to the field by developing an analytical framework for comprehending PVCs from a macroscopic viewpoint, introducing innovative methods for uncovering latent variables, integrating diverse types of data into the analysis, and creating a model for simulating the effects of urban planning revisions and traffic management strategies.

This study addresses the lack of knowledge regarding the diversity in commuter travel behavior, particularly the effects of different types of ride-hailing services (RHS). It focuses on the distinct impacts of motorcycle-based RHS (MRHS) and car-based RHS (CRHS) on user behaviors. By applying multinomial logit and bivariate probit regression analyses to data from 500 RHS users gathered in March 2023, the study reveals that increases in income and personal vehicle ownership have contrasting effects on MRHS and CRHS usage. Notably, MRHS usage is positively associated with employing RHS as a feeder mode to metro stations, while CRHS usage demonstrates a negative correlation. Furthermore, the study establishes a user preference for MRHS over CRHS during peak traffic times. These insights highlight the importance of creating specific policies for different types of RHS, which is vital for the development of successful urban transportation strategies.

In rapidly urbanizing regions of low- and middle-income countries as found in Asia, transportation management faces significant challenges, particularly with the popularity of two-wheeled vehicles. While these vehicles offer convenience in Asian megacities, their increasing prevalence has led to many urban traffic issues, including air pollution and traffic management problems. Consequently, several countries have contemplated or implemented bans on motorized two-wheeled vehicles in urban areas. With a forthcoming ban on motorcycles in 2030, this study investigates potential switches in transportation travel modes among motorcyclists. Analyzing factors influencing choices between electric bicycles (e-bikes) and buses, the results indicate a probable widespread adoption of e-bikes over buses post-ban. Income, place of residence, and access to bus stops emerge as key determinants.

The aviation industry has a key role in international trade activities. Most studies measure aviation performance based on airlines or airports. However, the frontline operation is delivered via air routes and more operating characteristics can be revealed with route-based performance evaluation. Further, the traditional data envelopment analysis (DEA) approach cannot rank performance in a particular context which represents an efficiency frontier built by decision making units (DMUs). Therefore, this study uses a context-dependent DEA approach to measure and rank the performance of air routes with a case study of 112 international routes from two airlines in Taiwan. Model results identify eight performance levels with most air routes at efficiency performance level 2 and level 3 and most route destinations in East Asia (e.g., Japan). The results of this study can inform operators about a clear relationship between performance and potential markets as well as improvement strategies.

Renewing feeder transit services is crucial for maximizing the potential of the public transport system and advancing toward a decarbonized Bangkok. Herein, we propose a smart feeder transit service using small electric vehicles for limited areas (sois) and target facilities in central Bangkok. A 1-year proof of concept was conducted to verify the feasibility and effectiveness of this service and assess its potential for deployment as a new mobility service. We found that 1) the introduction of a small mobility service in sois can considerably reduce both road congestion levels and CO₂ emissions owing to the improved capacity utilization rate, downsizing, and the use of electric vehicles, 2) advantages of scaling could be garnered by expanding the number of facilities to be serviced, and 3) providing a mobility service that is cooperatively operated by neighboring facilities is more convenient and profitable than providing a shuttle service for each facility.