The shared autonomous taxis system (SATS) has been regarded as a promising traffic mode for improving travel flexibility and reducing travel costs. This study aims to examine the potential benefits of replacing all taxis with ride-sharing autonomous vehicles (AVs). Specifically, two sharing strategies are discussed: nondetour sharing, in which a subsequent customer is picked up only if no detour is required, and detour sharing, where the detour may cause a delay for the first customer. An agent-based simulation is developed to demonstrate the advantage of the SATS. Results show that the nondetour and detour sharing strategies can respectively reduce fleet size by 19% and 27%, reduce waiting time by 62% and 82%, reduce operational costs by 16% and 24%, and reduce CO2 emissions by 17% and 19% in comparison with a nonsharing strategy.
In Japan, a national interregional travel demand survey has been conducted since 1990, but it has some limitations related to measuring seasonal demand variation as well as collecting trip frequency. A new survey was proposed and carried out in 2015 and early 2016 to capture travel demand and trip frequency in one year. To explore new survey data, in this study, a model, using eigenvector spatial filters specification, is developed to estimate interregional travel demand across the four seasons. As a result, the significance is seen in all likelihood ratio tests in all considered models, which proves that the spatial filter models are preferable to the unfiltered ones. The explanatory variables in each season have significantly different effects on travel demand, which would not appear in the model with cross-sectional data. For further studies, some remaining issues should be solved such as adding time effect or integration of more impedance variables into the model, developing specific models for each purpose or each travel mode, or an overall model considering a seasonal dummy variable.
The present study has been carried out for examining travel time reliability under heterogeneous traffic conditions on three different urban arterial road sections in the cities of Ahmedabad and Surat in India. Travel time reliability indices along with descriptive statistics over selected periods are calculated and a new reliability measure called Reliable Buffer Index (RBI) is proposed in this research work for evaluating the performance of selected urban arterial road sections. This new measure has the credibility of explaining inherent causes and factors that affect travel time variations in short time intervals for a given traffic volume. The study also focuses on the determination of best fit or potential statistical distributions for analyzing travel time variations using car travel time data. The study also highlights the development of the reliability-based Level of Service (LOS) thresholds on the basis of variation in identified effective reliability measures with respect to coefficient of variation using k-means clustering technique. The study results indicated that Buffer Time (BT) and Buffer Time Index (BTI) are the most effective measures that can capture the travel time variations. The study also presents a brief discussion on applications and limitations of existing travel time reliability measures that are commonly used. From the study results, it was observed that Burr or lognormal distributions are the potential distributions for modeling car travel times under heterogeneous traffic conditions. The methodology and study results can be helpful for transportation planners in comparing the performance or efficiency of different road facilities in a network in terms of travel time reliability in developing countries like India.
In recent years, the transformation in transportation mobility has seen an acceleration in numbers of studies establishing a sustainable, smooth and cost-efficient system by applying automated concepts to the conventional car-sharing system. The development from a personally owned vehicle-oriented scheme to shared automated transit provides us informative images to the optimal stage of the transportation mobility. This study aimed to find the gaps in impacts and features, demand and performance studies of SAVs by a systematic approach when looking at the corresponding aspects of car sharing in AVs and SAVs. This is the first attempt to review SAV studies and the author illustrates the importance of this research by demonstrating impacts and features of SAVs, future research aspects of demand analysis, as well as the research trend of performance studies on SAVs.
In this study, stochastic breakdown phenomena on a two-lane section of a Japanese urban expressway are analyzed and modeled. Because the bottleneck of the subject section is supposed to be a complex geometry with an on-ramp, a horizontal curve and an uphill, analysis is conducted not only by cross section but also by lane to understand the characteristics of breakdowns in detail. For such a detailed analysis, applicability and limitation of the detector data with different aggregation intervals are also considered. Through the analysis, it is found that about 40% of breakdowns in the section occur first on the shoulder lane; one of the causes would be higher merging traffic volume. The estimation of breakdown probability shows that the capacity of the median lane is about 300-veh/h greater than that of the shoulder lane. Furthermore, it is found that the discharge flow rate deteriorates as the elapsed time after breakdown increases, especially at the beginning of congestion.
This paper aims to identify management strategies for the improvement of urban bus services based on travelers' perceptions. A paper-and-pencil-based questionnaire was designed to collect responses from travelers. Priority areas for the improvement of bus services were identified by comparing factor structures and management schemes, which are derived using Revised Importance?Performance Analysis (Revised IPA). The study also aims to identify areas for improvement using conventional IPA and to compare the results obtained from IPA and Revised IPA. It was shown that there is a substantial difference between travelers' stated and derived importance for the travel attributes. The qualitative factors, which are often neglected in improvement planning of transportation services in emerging countries, were identified as major areas of intervention. Although the findings are case specific, the work is likely to encourage policy makers to apply a similar approach for formulating policy measures for improvement of services in other contexts.
To increase the utilization of existing resources, vehicle- and ride-sharing systems have been introduced as an efficient door-to-door service. To leverage the sharing concept, these systems have been combined as an integrated sharing transport system (ISTS) such that existing vehicles and services in the transport system are highly utilized. To operate ISTS efficiently, this study aims to introduce and formulate the optimal vehicle routing problem, which can simultaneously support vehicle- and ride-sharing features, and to provide the optimal solution that satisfies all users' activity patterns. As ISTS may degrade users' satisfaction because of discomfort, user preference is incorporated into the optimization model. With the developed model, the importance of considered factors, such as user preference, can be adjusted according to specified policies. The optimal solutions of several policies are compared and discussed using numerical experiments. Moreover, the equality operation policy, which equally considers user preference and system efficiency, is presented.
This study attempts to investigate motivations for individual modal shifts of motorcycle and car users for commuting trips in the context of new public transport projects in Ho Chi Minh City. We designed a survey to obtain information on five types of potential motivations, including service quality, social interaction, psychological determinants, situation of roadways, and socioeconomic characteristics. The analyses follow a two-stage approach consisting of a multiple-indicator-multiple-cause model for capturing psychological determinants and a bivariate ordered probit model for explaining the decisions of each user group on usage frequencies of the current buses and the new public transport system. The results show the significance of access/egress time, fare/cost, congestion/comfort, social interaction, agreement to the public transport projects, dissatisfaction with public transport, distance from home to workplace, motorcycle ownership, occupation, and age. Additionally, new public transport usage was correlated with bus usage. Car users were found to be harder to convince.
This paper develops a location model for the recharge services of heterogeneous electric scooter (ES) users. Despite the green and flexible characteristics of an ES, the major barrier for people to adopt electric vehicles (EVs) is range anxiety, a fear caused by uncertain battery life and/or electricity duration. To resolve this problem, this study proposes a location mode whose objective is to minimize the total cost of the supply and demand sides under different levels of ES users’ range anxiety and values of time. The empirical study results indicate that heterogeneous users need more recharge options compared with those of homogeneous users, and users with a higher value of time tend to choose faster recharge services. The ultimate goal of this study is to assist governments and/or commercial operators in making desirable location decisions for ES recharge services.
Utsunomiya City in Japan is planning a new light rail transit (LRT) system between the downtown area and Haga Town which is located just outside Utsunomiya. It will be open to the public in 2019. Development of the LRT may have a large impact on the population distribution in the city in the future. In this paper, a model that can evaluate the impact of developing an LRT and the feeder bus system (FBS) on population distribution in the city is developed. With the model, estimations of population distribution from 2015 to 2040 in the cases with and without LRT and FBS and the cost benefit analysis are conducted. As a result, it is indicated that developing an LRT and FBS will increase the population in the areas along the LRT and FBS lines, and developing feeder buses in addition to LRT increases the cost-benefit ratio compared to developing only LRT.
This paper presents the methods for measuring zero shear viscosity (ZSV) of binder-filler mastics. A viscometry test carried out on a dynamic shear rheometer was used to obtain the measurements. The Cross and Carreau models were then used to calculate the ZSV. The viscometry test used in this study is a less time-consuming and easier measurement technique for estimating ZSV. The Carreau model was found to produce a slightly lower ZSV compared to that obtained by the Cross model. Additionally, incorporating hydrated lime as a filler resulted in a higher ZSV compared to when using ordinary Portland cement (OPC), which is an indication of a stiffer binder-filler mastic. Higher filler contents result in higher viscosity. However, regardless of the filler content, subjecting the binder-filler mastics to aging conditions resulted in a more pronounced effect only in the case of the OPC binder-filler mastic when tested at 40°C.
Developing three orbital expressways is currently being implemented in the Tokyo metropolitan area. Recently, large-scale physical distribution facilities have been developed along the opened section of the Ken-O EXPWY, the outermost orbital expressway. This study develops a regional econometric model that analyzes the time series impact of developing the orbital expressway on reduction of logistics costs and the regional economy of the Tokyo metropolitan area. It also conducts an empirical analysis that estimates reduction of thelogistics costs using data of the Tokyo Metropolitan Freight Surveys in 2003 and 2013, and evaluates the development of the entire sections of the Ken-O EXPWY.
The prediction of road traffic accidents is of importance in locating the most hazardous sites in order to improve the safety management level. Through the comparative analysis of traditional road traffic accident prediction methods, an SCGM (1,1)c?Markov prediction model using the grey system theory and Markov chain theory is constructed. By taking the West, North, and South Terraces of Adelaide in South Australia as a case, training and verifying the prediction model is conducted, and the mean absolute percentage error of the combined prediction model is 2.55% which means a high prediction accuracy being achieved. Then, the predicted crash rates of West, North, and South Terraces, which are 99.50, 59.50, and 18.97 crashes/km, respectively, are resulted by the combined models respectively, with West Terrace shown to be the most hazardous road section. The results indicate that the prediction model can be well applied in road traffic accident prediction with strong engineering practicability.
Customers have various criteria for selecting which airline to use but these criteria changes when accidents occur frequently for a single airline. Accidents of Taiwan-based TransAsia Airways were selected for this case study. After the accident of TransAsia Airways flight GE222 on July 23, 2014, subjective data from Taiwanese citizens were collected throughan online survey. While sending out the questionnaires, another accident occurred with the same airline on February 4, 2015 (GE235). This unique data allowed us to analyze influences on the change in public attitude toward airlines for two different respondent groups. A structural equation model was built to express the two groups’ behavioral intention, and multi-group analysis showed that there were differences between the two groups: perception in safety contributes less to behavioral intention after repeated accidents because people lose faith in the safety management of the airline and tend to value reputation when selecting the airline. The results also indicated that people were unaware about aviation safety and this is a potentialproblem which induces airlines to not conduct safety measures.