Asian Transport Studies最新文献

The efficient operation of container terminals facilitates the seamless flow of goods across borders. New technologies such as big data, data mining, and simulation models, have emerged in the maritime industry, enabling optimization and performance evaluation. This study investigated how data science using operational data can improve container terminal operations, drive efficiency, enhance throughput, and bolster competitiveness in the shipping sector. Decision-making within container terminals, particularly in determining optimal container stacking locations, poses a significant challenge owing to the multitude of factors at play. By analyzing the datasets, new strategies and policies can be simulated to minimize container rehandling operations. This study focuses on the Hakata International Container Terminal in Japan, where daily operational data from rubber-tired gantry equipment are used to investigate container movements. A significant reduction in the total number of movements required to perform container-handling operations was demonstrated by implementing data-driven strategies and simulation modeling.

The East Japan Railway Company is planning a new access railway line to the Tokyo International (Haneda) Airport. This paper proposes an evaluation method for the development of the new airport access line considering the socioeconomic characteristics of the Greater Tokyo Area and indicates what is needed to increase its social value. As the evaluation method, we develop an econometric model that considers commuters’ trip behaviors across prefectures and the relationship between the increased number of Meeting, Incentive Travel, Convention, Exhibition and Event (MICE) visitors and the regional economy. We also conduct a simulation analysis using an empirical econometric model and a cost-effectiveness analysis based on multiple scenarios. The results indicate that a 50% increase in MICE visitors is needed to make the present discounted value of the total increase in the gross regional product larger than the construction cost of the line.

In high-density pedestrian crossflow locations, pedestrians considerably affect the vehicle flow. On arterial roads where speed is the main concern, unanticipated pedestrian crossings generate conflicts between vehicles and pedestrians, thereby creating congestion and increasing the travel time cost. In this study, the viability of various pedestrian crossing facilities is evaluated in terms of the flow characteristics and benefit-cost ratio (BCR). Grade-separated pedestrian crossing facilities offer high mobility and save travel time costs for vehicles; however, these are sometimes discouraged because of high construction costs. The optimal crossing facility is determined by comparing the travel time costs for both the vehicles and pedestrians. This study argues that grade-separated crossings yield a superior BCR in areas with limited pedestrian traffic, whereas in densely pedestrianized areas, pedestrian signals boast the highest BCR among all pedestrian crossing facilities. These findings will improve the planning of cost-effective pedestrian crossing facilities.

This study analyzed the relationship between gaze behavior and physical functions of elderly drivers at unsignalized intersections, which have spatial characteristics that make elderly drivers more likely to be on the at-fault side of a collision. Twenty-nine elderly and 14 non-elderly drivers were asked to view 360-degree videos from five different routes of two unsignalized intersections under conditions similar to actual driving. The results were as follows. (1) The eye movement distance (EMD) was shorter for elderly drivers in most of the driving sections, with the section "At slowdown" on non-priority roads being the section where a significant difference was likely to occur. (2) For both elderly and non-elderly drivers, the amount of EMD was significantly related to visual and general physical functions such as flexibility, equilibrium, and agility.

Ride-hailing has been introduced and has become popular in many major cities worldwide. The service often relies on the use of dynamic pricing, in which fares are adjusted in real time. Therefore, understanding the impact of fare on demand is necessary for the operation of ride-hailing. The aim of this study is to empirically investigate the impact of fares on demand through price elasticities using the session data of Uber taxis from Uber Japan's experiments in two cities: Nagoya and Kyoto. A mixed logit model with a flexible mixing distribution was estimated to capture the taste heterogeneity among riders, which increased the reliability of the result. The estimation results indicated that most riders were price inelastic, with an average price elasticity of approximately −0.2 to −0.1. These findings are useful for ride-hailing companies and policymakers because they provide valuable information to enable the maximization of profit or benefit to customers.

The public transportation system in densely populated areas is often managed as a self-financing system due to fare passenger revenues. In a self-financing system, the network structure and the monetary fare mutually interact; therefore, it is efficient to design both simultaneously. We developed an optimization model that endogenously determines the bus network and fares to maximize the total social surplus of the region. In this study, we conducted numerical applications of the model to a public transportation system around a railroad station in a metropolitan suburb area. The results showed that the optimal network topology changes with the scale of demand, and network shape significantly alters the optimal fare structure. Three types of virtual regions were examined to illustrate optimal fares.

Transit-oriented development (TOD) is a major planning tool to promote green transport mode share. There are many previous studies in this field but with very diverse research focuses and outcomes. This study has classified the research purposes of previous studies into four categories: exploratory; potential and challenges; performance evaluation; and in-depth investigation. To identify critical factors that might influence green transport systems, a systematic literature review is delivered via a meta-analysis. Specifically, green transport mode share was set as the dependent variable and a proxy for TOD outcomes. From the model results, several key factors are identified. For example, built environment planning (e.g., pedestrian sidewalks) plays a critical role in green transport systems. The main findings of this paper can provide clear direction to current TOD, such as how to improve TOD outcomes and providing planning guidance for potential TOD.

This study proposes two tourist excursion behavior models. One is the trip chain-based model, in which the tourist behavior is represented by a trip chain and the duration of stay at each tourist spot in the trip chain. The model is based on the tourist's utility maximization, where a tourist allocates the time budget along the trip chain generated from our proposed algorithm formulated as dynamic programming. The proposed model assumes that travel data obtained from Wi-Fi sensors are available. We also proposed the Trip-based model, which estimates the transition ratio of a tourist trip between tourist spots based on the tourist's utility maximization. The trip-based model only partially captures the excursion behavior but is available when only tip data between two nodes in the network is available. To demonstrate the models presented in the paper, we calibrated parameters and predicted the tourist demand in a test and real networks.

With the increasing importance of sustainability, warehouse sharing arises as a possible way to improve the logistics system efficiency. This paper studied the warehouse sharing platform systems (WSPS) and proposed an enhanced modelling approach for the WSPS design problem (WSPSDP) using the multi-allocation hub location routing problem framework. New elements, such as inter-warehouse transportation and multi-allocation scheme, were considered compared to the existing WSPS model. Then, an adaptive large neighbourhood decomposition search heuristic was applied to solve our problem. Computational experiments were conducted on different-sized instances to compare the WSPS model without inter-warehouse transportation (WSPSDP-WI) and the WSPS model with single-allocation scheme (WSPSDP-SA). The results suggested that our proposed WSPSDP model is more cost-efficient than the existing WSPS models, reducing 15.38% and 1.43% operation costs compared to the WSPSDP-WI and WSPSDP-SA models. Finally, our proposed WSPSDP model also has the potential to promote the utilisation of existing cheap idle warehouses.

This study evaluated drivers' collision avoidance behavior by focusing on the timing of their visual detection of pedestrians when turning right at signalized intersections. A headset-based virtual reality driving simulator was used to monitor drivers' behavior. The experiment showed that early detection of pedestrians can reduce the potential for severe conflicts. Drivers found it difficult to detect pedestrians early when using a gap between oncoming vehicles to turn right. Based on gaze tracking, we propose and validate a safety level that could potentially evaluate the potential for conflict between pedestrians and a right-turning vehicle. To increase safety level reliability, the speed of the right-turning vehicle should be included in addition to the eye measurements.