Assessing asymmetric response effect of behavioral intention to service quality in an integrated psychological decision-making process model of intercity bus passengers: a case of Taiwan

This study introduces the concept of loss aversion to consumer behavioral intention at the personal psychological level to develop an integrative structural equation model for analyzing traveler psychological decision making. In this model, the relationship between behavioral intention and service quality is a non-smooth function based on the theory of loss aversion. The expectation service quality in the SERVQUAL model proposed by Parasuraman, Zeithaml, and Berry (PZB) serves as a reference point. This model can be applied to analyze the effect of non-smooth response of behavioral intention to service quality in a traveler psychological decision-making process model. Intercity travel among cities in Taiwan is used as an empirical example. Data were gathered in cities in Taiwan via a questionnaire survey, and the model was tested using path analysis performed by LISREL. The empirical result shows that all causal relationships are statistically significant. Service quality loss influences repurchase intention more than does Service quality gain. Finally, this study concludes by discussing managerial implications and suggesting directions for future research.

Urban form,travel time,and cost relationships with tour complexity and mode choice

The primary purpose of this study was to investigate how relative associations between travel time, costs, and land use patterns where people live and work impact modal choice and trip chaining patterns in the Central Puget Sound (Seattle) region. By using a tour-based modeling framework and highly detailed land use and travel data, this study attempts to add detail on the specific land use changes necessary to address different types of travel, and to develop a comparative framework by which the relative impact of travel time and urban form changes can be assessed. A discrete choice modeling framework adjusted for demographic factors and assessed the relative effect of travel time, costs, and urban form on mode choice and trip chaining characteristics for the three tour types. The tour based modeling approach increased the ability to understand the relative contribution of urban form, time, and costs in explaining mode choice and tour complexity for home and work related travel. Urban form at residential and employment locations, and travel time and cost were significant predictors of travel choice. Travel time was the strongest predictor of mode choice while urban form the strongest predictor of the number of stops within a tour. Results show that reductions in highway travel time are associated with less transit use and walking. Land use patterns where respondents work predicted mode choice for mid day and journey to work travel.

Factors influencing support for local transportation sales tax measures

Sales tax measures passed at the local level and dedicated to transportation projects have become increasingly popular in the United States. While revenues from fuel taxes stagnate, growth of local transportation sales taxes (LTSTs), most approved in local elections, has led to a gradual shift of the financial base for transportation projects away from user fees and toward broader-based taxes. In this study, the relationship between voter support and the social, political, and geographic characteristics of the voters is explored. Using precinct-level voting data and census demographic data for three local transportation sales tax elections in Sonoma County, in the San Francisco Metropolitan area of California, regression models were constructed to analyze this relationship. In addition, the relationship between the outcomes of the three measures was explored to better understand which transportation projects might have garnered more support for the successful measure. It was found that the closer voters lived to the transportation projects to be funded, the greater their support. Higher incomes were also positively related to support, controlling for other variables. Political leanings were found to affect support, with the direction of the effect dependent upon the project list in each measure’s expenditure plan. Finally, it appears that the latest measure, which passed successfully, benefited greatly from its multi-modal expenditure plan.     

Simulating the impacts of household travel on greenhouse gas emissions,urban air quality,and population exposure

This paper establishes a link between an activity-based model for the Greater Toronto Area (GTA), dynamic traffic assignment, emission modelling, and air quality simulation. This provides agent-based output that allows vehicle emissions to be tracked back to individuals and households who are producing them. In addition, roadway emissions are dispersed and the resulting ambient air concentrations are linked with individual time-activity patterns in order to assess population exposure to air pollution. This framework is applied to evaluate the effects of a range of policy interventions and 2031 scenarios on the generation of vehicle emissions and greenhouse gases in the GTA. Results show that the predicted increase of approximately 2.6 million people and 1.3 million jobs in the region by 2031 compared to 2001 levels poses a major challenge in achieving meaningful reductions in GHGs and air pollution.     

Isolating high-priority metro and feeder bus transfers using smart card data

Fixed-rail metro (or ‘subway’) infrastructure is generally unable to provide access to all parts of the city grid. Consequently, feeder bus lines are an integral component of urban mass transit systems. While passengers prefer a seamless transfer between these two distinct transportation services, each service’s operations are subject to a different set of factors that contribute to metro-bus transfer delay. Previous attempts to understand transfer delay were limited by the availability of tools to measure the time and cost associated with passengers’ transfer experience. This paper uses data from smart card systems, an emerging technology that automatically collects passenger trip data, to understand transfer delay. The primary objective of this study is to use smart card data to derive a reproducible methodology that isolates high priority transfer points between the metro system and its feeder-bus systems. The paper outlines a methodology to identify transfer transactions in the smart card dataset, estimate bus headways without the aid of geographic location information, estimate three components of the total transfer time (walking time, waiting time, and delay time), and isolate high-priority transfer pairs. The paper uses smart card data from Nanjing, China as a case study. The results isolate eight high priority metro-bus transfer pairs in the Nanjing metro system and finally, offers several targeted measures to improve transfer efficiency.     

Aerodynamic design optimization of rear body shapes of a sedan for drag reduction

This study proposes an aerodynamically optimized outer shape of a sedan by using an Artificial Neural Network (ANN), which focused on modifying the rear body shapes of the sedan. To determine the optimization variables, the unsteady flow field around the sedan driving at very fast speeds was analyzed by CFD simulation, and fluctuations of the drag coefficient (C _D ) and pressure around the car were calculated. After consideration of the baseline result of CFD, 6 local parts from the end of the sedan were chosen as the design variables for optimization. Moreover, an ANN approximation model was established with 64 experimental points generated by the D-optimal methodology. As a result, an aerodynamically optimized shape for the rear end of the sedan in which the aerodynamic performance is improved by about 5.64% when compared to the baseline vehicle is proposed. Finally, it is expected that within the accepted range of shape modifications for a rear body, the aerodynamic performance of a sedan can be enhanced so that the fuel efficiency of the sedan can be improved. The YF SONATA, a sedan manufactured by Hyundai Motors Corporate, played a major role in this research as the baseline vehicle.     

Fuel consumption of fuel cell hybrid vehicles considering battery SOC differences

Fuel cell hybrid vehicles (FCHVs) have become one of the most promising candidates for future transportation due to current energy supply problem and environmental problem. Fuel economy is an important factor in FCHVs. In order to properly evaluate the fuel economy of an FCHV, the initial battery state of charge (SOC) and the final battery SOC have to be identical so that the effect of the battery energy usage on the fuel economy is neglected. In the simulation or in the real driving, however, the final battery SOC is usually different from the initial battery SOC, and the final battery SOC often depends on the power management strategy. To consider the difference between the two battery SOC values, the concept of equivalent fuel consumption is presented by two methods. One is based on the relationship between delta SOC and delta fuel consumption, and the other is based on the optimal control theory. Two rule-based power management strategies for an FCHV are presented, and for each strategy, the fuel economy is evaluated based on the two methods. The characteristics of the two methods are discussed and compared, and the superior one is selected based on the comparison.     

Simulation of mixed gas formation for a spray-wall complex guided LPG direct injection engine

To obtain an ultralean air-fuel ratio and to reduce engine-out NOX and HC emissions induced by the richer mixture near the spark plug, a spray and wall complex guided combustion system has been developed by utilizing the fuel characteristics of LPG. The new combustion system configuration is optimized by using a commercial CFD code, FIRE V2013, and the reliability of the system has been experimentally demonstrated by Plane Laser-Induced Fluorescence (PLIF). The mixture formation in the new combustion system under part load (2,000 rpm) is numerically simulated. With an injection timing of 40°CA BTDC, the LPG spray which is injected from two upper holes, reaches the ignition point, and the other part of the LPG spray which is injected from the bottom hole, is directed to the ignition point through the vertical vortices at the same time. At the ignition timing of about 20°CA BTDC, the two-part mixtures have been shown to form a stable and richer stratified mixture around the ignition point, and the maximum global air-fuel ratio reaches to 60: 1.     

Wave propagation in head on bonnet impact: Material and design issues

Head on bonnet impact is becoming more and more important in automotive design as regulations on pedestrian safety become more demanding. Despite the relatively low amount of energy involved, these impacts are truly dynamic phenomena as the event duration is comparable with the traveling time of the different wavefronts generated by the impact. In this paper, we show that we can build up a simplified model for the impact based on wave propagation analysis. Using this model, we can analyze head acceleration on existing bonnets or predict it on new ones. Head acceleration in a bonnet impact can thus be estimated over the whole area of the bonnet with a few minutes of CPU.