This research is to discuss the effects of display of travel information and radio traffic reports on the routes choice behaviors of drivers. Questionnaires are distributed in the Taian rest area, then, basic statistics are shown first, furthermore, binary logistic regressions are established on six topics respectively: (1) ever seeing a display of travel information or not, (2) changing route to third freeway or not when seeing a display of only travel time, (3) changing route to third freeway or not when seeing a display of both travel time and distance, (4) changing route to third freeway or not when seeing a display of travel time and distance as well as speed (5) changing route or not when seeing all alternative displays of travel information, (6) changing route or not due to traffic news from radio or travel information display from CMS, in order to help discuss separately whether relevant factors affect route choices of drivers.

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The bus interval is an important factor that represents the punctuality of a bus. Bus intervals are usually set in consideration of passengers? convenience. Previous studies have only considered the running cost of companies and the waiting time as determined by the interval time. In this study, using smartcard data, which is more accurate and reliable, an Evaluation Index is developed and evaluated to improve the efficient management of bus routes and the satisfaction of passengers. Using the smart card data, the accurate demand of each bus stop and route was calculated. Accordingly, an equation that adjusts the bus interval was developed, as was an index consisting of the running cost, the waiting time, the travel time to satisfy passengers. Finally, we evaluate the appropriate bus interval regarding the interval that will be more useful assuming that various selected bus lines can be analyzed with peak,nonpeak hourly data.

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Quantifying the effects of signal timing and crosswalk geometry on pedestrian speed is an important requirement for improving existing operational policies and for providing a rational safety assessment at signalized intersections. The objective of this paper is to macroscopically investigate the effects of signal timing, crosswalk length and pedestrian origin-destination on pedestrian speed at signalized crosswalks. Three signalized crosswalks in Nagoya City are videotaped. A pre-developed data processing program is utilized to extract speed data. Pedestrian signal timing is divided into six intervals. Depending on the entering time, each pedestrian is assigned to one of the intervals. Then the speed distributions in different time interval are estimated and compared. Generally, it is concluded the entering speeds of pedestrians increase as pedestrian green interval proceeds. Moreover, pedestrians show higher travel speeds at long crosswalks.

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This paper presents the proposed theory of facilitated behavior, which is the extension of the theory of planned behavior. The theory adds a new construct within the original theory, in order to take into account the influence of the conditions that facilitate or hinder a person to behave. Consistent with the previous theories of behavioral intention, this theory also hypothesized that the intention is a strong predictor of a behavior. In the transportation field, this theory is intended to account for the influence of TDM measures on transportation mode choice behavior. TDM measures are essentially an action taken to facilitate or otherwise hinder a person's behavior in using a mode of transportation, with the aim of influencing the behavior of person to switch from using private vehicles to using public transports. In general, this theory provides new insights that are useful for transportation planners and policy makers in transportation.

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Despite sufficient pedestrian road crossing facilities, pedestrians follow illegal road crossing patterns creating life threats and disturbing the smooth traffic flow. Primary objective of this research is to develop a methodology that evaluates the most influencing attributes predisposing to illegal road crossings. Current research exemplifies the effectiveness of Conjoint Analysis in evaluating the most influencing attributes. Literature suggests illegal road crossings are governed by two factors: psychological characteristics and physical environment. A sample of pedestrians completed the stated-preference survey by ranking nine hypothetical profiles. Results indicate familiarity is the most influencing attribute under psychological characteristics while reason for making an illegal road crossing is the least influencing attribute. Under physical environmental settings, traffic condition is the most influencing attribute while side walk condition is the least influencing attribute.

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This paper presents a new path-based algorithm for the static traffic assignment involving in solving the equilibrium conditions as the nonlinear complementarity problems. The algorithm would be a result of two existing path-based algorithms combined together. The nonlinear complementarity problem (NCP) is further developed as the unconstrained minimization problem which has global minima of zero value at all the complementarity problem solutions. In this paper, numerical tests were implemented based on the real network data. The obtained results, comparable with the Bar Gera origin-based algorithms results, show the applicability of the algorithm with the large-scale networks. The discussion, furthermore, on how to improve the computing time of the path-based algorithm is also provided.

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As the qualitative and quantitative improvement of transit stations has been achieved by introducing a variety of methodologies for activating public transportation, the transit demand of stations takes up considerable part of the whole demand at the present. The most important issue for such a transit-centered transportation system may be considered as the activation of transfer connections between SAA (station access/egress area) and transportations. This study would like to propose a methodology to establish the SAA considering the transfer characteristics for compensating a limit of the existing methodologies. Also, the concept of the transfer SAA based on transfer areas would be proposed for a classification criterion on 'complex transit center' in "Law on efficient national integrated transportation system," which is only conceptually represented so that the definite criterion is ambiguous.

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With a huge amount of information available from transit cards, efficient operation public of public transportation can be accomplished using various studies. This study used some of the traffic card data (SD) from a public transport system to promote competitive and efficient transportation and provide information on the smooth transfer of passengers and on how to improve comfort. In this study, the operator, the transit time, and delay time around a metro station were all taken into consideration to reform a system of public transportation routes and thereby improving the efficiency of the operations. The transit bus routes and delay times on the periphery of the regional transit subway could also be calculated to take advantage of transit delay metrics, services, and public transportation routes in coordination with the Metro and could be used as a criterion for efficient operations.

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This study uses the transportation card data to extract travel information and develop a trip generation model for subway stations based on this data. The model uses the number of ingress and egress of subway stations as a dependent variable, and the accessibility and land use characteristics as explanatory variables. Reasons of reflecting the accessibility as an explanatory variable for the trip generation model are, first, that the demand of ingress/egress for each station is affected by not only the socioeconomic index around stations but also the accessibility from a departure station to other arrival stations, second, that it make possible a feedback between the trip generation step and the trip assignment step in traditional 4-step demand model. Through this study, it was investigated the suitability of the trip generation model for subway ingress/egress demand considering the land use variable and accessibility.

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A part of the contribution to mixed traffic analysis, this paper proposes an algorithm for the network assignment. The algorithm is directly developed based on the nonlinear complementarity form of the user equilibrium equations. The nonlinear complementarity problem (NCP) is then converted to an equivalent system of nonlinear equations. An illustrative example of two-modal traffic assignment is provided for the application of model and algorithm.

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In this research,an enterprise comprise vendor and buyer is considered to find the optimal solution as well as best location for the warehouses.If there is no coordination exists between the members in a supply chain, vendor and buyer will act independently to maximize their own profit and reduce cost which does not guarantee the optimal state of the whole system.A single vendor-buyer with multiple products and consumers problem is formulated, and the coordination between vendor and buyer is emphasized to find not only the optimal network but also the best location for buyer's warehouse. Further,instead of constant demand function, a price-sensitive linear demand function is introduced to formulate the constraints.Finally, the formulated the Mixed Integer Problem (MIP)models are solved and hence the sensitivity on buyer's selling price is anylyzed to conclude this research.

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A heuristic approach is presented to solve allocation problem of distribution system, which is characterized as Minimum Concave cost Multicommodity Flow problem. Such problem is differentiated into uncapacitated and capacitated problem, as well as single and multisource network. Basically, this research propose solution of capacitated and multisource problem, while Gallo algorithm of solving single source and uncapacitated problem is treated to verify the proposed methods. The multisource and uncapacitated problem are solved by bilevel programming, while the capacitated one is solved by linear approximation. Linear approximation is also used to solve uncapacitated problem and confirm the result of bilevel programming. Both methods are represented in Network Representation form, in which some dummy nodes and links are added to the original network in order to represent all components of mathematical model. Some cases are discussed to show the application of both methods.

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This study concerns with the determination of locations of warehouses of Public Service Obligation State-owned Company distribution system. This paper will be focused on the heuristic solution of the proposed model. The mathematical model takes form of Minimum Concave-cost Multicommodity Flow (MCMF) problem. The solution is approached by Network Representation, in which all of the components of the original model are represented in the form of dummy links and nodes which are added to the original network. Then, the original problem is replaced by the problem of MCMF of the Network Representation. Due to the complexity of solution of such MCMF problem, our solution is approached by bilevel programming. Primaldual algorithm and heuristic algorithm associated to the searching of Destination Spanning Tree are employed to solve such bi-level programming. An illustrative example is presented to explain the mechanism of the bilevel programming.

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The dramatic decrease in global demand due to the financial tsunami of 2008 forced the ocean container carriers (OCCs) to re-examine their maritime marketing strategies. In an attempt to help the OCCs establish effective marketing strategies, this study conducted a survey regarding the ocean freight forwarders' (OFFs) needs on the OCCs' service. An evaluation framework with 21 attributes was developed based on the concept of marketing mix. The fuzzy Delphi method and DEMATEL were adopted to synthesize the OFFs' opinions and examine the perceived causal relationships between the attributes. The analysis results showed that sales representative's expertise and transportation reliability are the most important attributes valued by the OFFs instead of transportation fee. The OFFs with various characteristics have different perspectives on the importance of attributes and their causal relationships. The results reflect the distinct capabilities of handling cargoes and negotiation powers in dealing with business partners of various-sized companies.

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The B2C market in Taiwan is obviously becoming a noticeable market. As the market grows and matures, return becomes one of the challenges for E-retailers. In the past, most of the literature on return issues focused on the wholesaler-retailer relationship. Recently, due to the advent of Internet-based retailing within the past decade, attention is shifting to the issue of returns in the retailer-consumer relationship. In this study, we use empirical data and conduct a Decision Tree model to analyze the critical variables revealing the customer return propensity. There are 3 dimensions of variables in our data set- customer demographic variables, merchandise variables and service variables. We find that three variables- category, price and delivery days could be used to distinguishing customer return propensity more effectively. In accordance with these variables, we propose some strategies for website managers to control returns in E-retailing.

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With the development of food industry and food refrigerated transport, all kinds of refrigerated containers are becoming more and more popular. But the decay of perishable food takes place often due to improper loading and unreasonable design of air flow organization. Based on analysis, experiments and simulation with Fluent software, this paper studies the temperature field and air flow inside the refrigerated container in certain loading conditions. The results show that different inner temperatures need different air blowing-in velocities in order to obtain more uniform temperature field. And the blowing-in velocities have the different influences to different positions inside the container. The increase of blowing-in velocity is beneficial to the uniformity of the temperature field. The conclusions and suggestions are of reference value to the design and operation of refrigerated container.

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The vehicle routing problem (VRP) has received a lot of attention and has been applied extensively in the field of logistics. In practice, the heterogeneous fleet is usually used in the distribution center. The need for different types of vehicles is determined by the characteristics of the customers. Hence, the heterogeneous fleet vehicle routing problem (HVRP) is an important variant of VRP. The HVRP is a NP-hard combinatorial optimization problem which is very difficult to solve optimally within reasonable time. The ant colony optimization (ACO) algorithm has been applied to the VRP successfully, but much less for VRP variants. Therefore, this research aims to develop a two-stage ant colony optimization (TACO) algorithm to solve the HVRP. The TACO was tested on two sets of benchmark instances in the literature. The results show that the performance of the TACO is competitive with the state-of-the-art algorithms.

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This study examines the performance of genetic algorithms (GAs) on solving the pickup and delivery vehicle routing problem with soft time windows (PDVRPSTW), typically faced by home delivery service providers. We implement a number of combinations of GA's three main algorithmic operators, namely, selection, crossover, and mutation, and adopt the data envelopment analysis (DEA) to evaluate and rank these various combinations of GA operators. The numerical results show that DEA is appropriate in determining the efficient combinations of GA operators. Among the combinations under consideration, the combinations using tournament selection and simple crossover are generally more efficient. The findings also contribute to algorithm development and evaluation in vehicle routing problem from the operational research perspective.

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The delivery of goods from a warehouse to local customers is an important decision problem of a logistics operator. As the demand is fluctuating, the common carrier may be needed if the private fleet is insufficient. In this study, we focus on the vehicle routing problem with private fleet and common carrier (VRPPC). In order to balance computational load and solution quality, a heuristic algorithm is developed based on several classical mathematical programming techniques. The VRPPC is first formulated in the form of the set covering problem, and the Lagrangian relaxation is used as the backbone in designing the iterative algorithm. In addition, a concept similar to column generation is used to update the solution space, a partial set of routes. Based on the numerical experiment, the solution quality of the heuristic algorithm is stable, and the computation time is acceptable under the current highly dynamic environment.

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In these days, national logistics costs have been used as performance indicators. But it is not suitable as performance indicators because the better efficiency of logistics reduces its cost and the more logistics added value increases national logistics cost. This conflict makes national logistic costs cannot work well as performance indicators of logistics. This study was conducted to develop performance indicators which show achievement of national logistics policy quantitatively. To achieve this, strengths and weaknesses of existing performance indicators of logistics policy are analyzed, several alternatives are proposed and final alternative is obtained. Performance indicators of logistics policy that is finally proposed in this study is combined with 'Ratio of logistics added value to GDP' and 'Ratio of net National Logistics Costs to GDP' to achieve two goals, decrease in logistics costs and vitalizations of logistics and industries.

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The world is experiencing the issues of negatives impacts of delivering and collection of goods in urban areas as urban freight distribution is rapidly increasing over the recent years. Although urban goods distribution is essentially contributed to the economic and social development, the seemingly unsustainable impacts of urban freight transport result in an extensive research for a more sustainable urban freight distribution strategy. Numerous innovative solutions have been proposed and implemented both successes and failures. The objective of the paper is to review the current measures or initiatives implemented in urban freight distribution. The major measures or initiatives implemented will be presented. The case study of urban freight distribution in the City of Adelaide, South Australia will be introduced with some preliminary observations. In conclusion, the lesson learned from previous studies and some successful factors that need to be taken into consideration for future implementation will be discussed.

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The on-line vehicle routing problems (VRP) is an extension of VRP in order to consider real-time requests as well as possible variations travel times in the network. In this research, a solution algorithm for solving on-line VRP is proposed. The solution algorithm is divided into two phases, off-line route planning and on-line route updating. In the off-line phase, a time-dependent VRP formulation is constructed to assign initial routes. In the on-line routing phase, a hybrid heuristic approach with tabu search and genetic algorithm is proposed to handle real-time requests and to improve routes under real-time information. The simulation-assignment model, DynaTAIWAN is applied to evaluate assigning and routing strategies in a traffic network. Numerical experiments are conducted in a Kaohsiung city network.

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This paper considers a multi-plant and multi-distribution centers (DCs) supply chain distribution network (SCDN). The decisions are to locate the open DCs, allocate customers to DCs, and DCs to plants to minimize the total logistics cost including the fixed costs of DCs, warehousing cost of DCs and shipping cost from plants to DCs and from DCs to customers. Also, it takes workload balanced requirements into consideration to avoid DCs being congested or idle. A bi-level programming model is proposed to deal with this problem. The upper level considers DC location problem and production-allocation problem. The lower level focuses on allocating customers to DCs such that the workload of each open DC is balanced. We propose a double threshold accepting (TA) approach to solve this problem. Four different examples are tested and the results show that our double threshold accepting algorithm can obtain a good solution efficiently.

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The traffic conditions in urban areas change with time due to varying congestion levels and incidents resulting in unexpected varying travel time on the infrastructure links. These conditions lead to the formulation of the Dynamic Vehicle Routing and scheduling Problem with Soft Time Windows (D-VRPSTW) with dynamic travel time in the city logistics field. This paper presents a column generation-based exact solution approach for the D-VRPSTW. The performance evaluation on a test instance under different dynamic travel time events, shows that the D-VRPSTW solutions based on the updated travel times result in significant cost savings as compared to static version.

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In order to satisfy the transportation demand for elderly and disabled people, providing efficient dial-a -ride systems is an important issue. Appropriate vehicle routes for dial-a-ride systems can increase transportation efficiency and reduce the operation cost. Most literatures focus on improving the vehicle routing and scheduling and assume that the travel time is a constant value. However, the travel time can fluctuate dramatically due to traffic congestion or incident. Using the constant travel time to solve dial-a-ride problems (DARP) cannot obtain the efficient vehicle routes. To consider the variation of the travel time, this paper formulates a mixed integer programming formulation for the time-dependent DARP with time window. The simulation-assignment model, DynaTAIWAN is applied to generate time-dependent travel time matrices and simulate traffic flows in the real network. Numerical experiments are conducted in a Kaohsiung network.

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Compared with passenger demand forecasting method, freight demand forecasting method relatively has depressed to develop the reliable methodology and verify the outcome. At the present time, it is difficult to make a consistent analysis methodology model, because of a diversity of actual and estimate values by transport or item are just aggregated with the count. In this research, we propose a trip generation/attraction model for freight demand forecasting adequate for domestic circumstances in Korea by the change of socioeconomic indices. Proposed regression model also includes 248 zones and 33 items and the interpretation about the results. Test results are compared with current used models. This model can be improved to accurate and objective freight demand forecasting value in Korea.

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The traveling salesman problem with time windows (TSPTW) is a variety of the traveling salesman problem. In practice, temporal aspect is a necessary constraint with respect to the routing problems. TSPTW is a NP-hard problem, and computational time of exact algorithm increases as the number of customers increases. Hence, we present a beam search (BS) algorithm which is a heuristic based on breadth-first branch-and-bound without backtracking to solve the TSPTW. BS filters out worse nodes by a local evaluation and only keeps  (called beam width) nodes according to global evaluation at each level. In our BS, both one-step local evaluation and global evaluation are applied to estimate cost of nodes by inserting undetermined nodes of a given initial solution. The computational results on test instances from the literature show that our beam search can obtain good solutions with effective computational times for TSPTW.

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The focus of this study is to analyse the operations of solid waste transport from Christchurch (New Zealand) to a recently opened regional landfill 70km north of Christchurch by comparing two scenarios - road and rail transport. The thrust of the research is based on the logistics of transporting solid waste and identifying the CO2 emissions or in simple terms the energy used by the two modes. The study takes into consideration solid waste data from 2000-2005 and extrapolates future waste data to assess the situation in 2015. The modelling looks separately at road and a combination of rail-road operations by outlining the various planning and logistics requirements for transporting solid household waste from Christchurch to the new Kate Valley landfill.

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This paper tries to make some fundamental analyses on the situations of railway freight in two aspects such as the states of freight shippers and the transport conditions of actual railways. One part of this paper focuses on the comparative analysis of freights among different transport means, in order to estimate the potential freight of railways based on the inter-regional surface freight shipped by manufacturers. On the existing potential freight of railways, the other wants to investigate the actual situations of railway container transport through building a database of actual freight transport on railway corridors. Finally, promoting the modal shift of inter-regional surface freight from trucks to railways and improving the railway transport are discussed.

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Mindanao, despite its considerable potential for being the principal food basket of the country, has experienced very limited growth due to inefficient logistics operations. As such, an integrated logistics program aimed specifically at increasing agricultural production as well as diversification of economic activities is needed in the form of a Mindanao intermodal logistics network development plan. The development plan is envisioned to bring positive impacts on Mindanao's international competitiveness and inter-regional competitiveness. The realization of sustained growth will ultimately contribute to reinforce the government's efforts at consolidating the peace initiatives for the region.

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This paper presents an adaptive truck metering control algorithm to enhance the electronic screening (e-screening) operation at truck weigh stations. This algorithm uses a feedback control mechanism to control the level of truck vehicles entering the weigh station. Under overflowing truck conditions, the proposed algorithm attempts to prevent the queue spillback problem by allowing more trucks to bypass the weigh station. Alternatively, the algorithm leads the e-screening system to adopt a stricter bypass condition to preclude overweight trucks from being bypassed due to the Weigh-In-Motion measurement error. The proposed control concept is demonstrated and evaluated in a simulation environment representing a low capacity weigh station. The simulation results demonstrate considerable benefits of the proposed algorithm in improving the overweight enforcement with minimal negative impacts on legal truck vehicles.

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Traffic congestion is the major problem in Ulaanbaatar and requires an accurate solution from transportation and city planning professionals. The city logistics system is not advanced and there are insufficient warehouse, where goods are consolidated and shipped to recipient. About fifty percent of truck arriving to the major chain stores is partially loaded and the share of truck on the road movement is around 25 percent of total. Thus centralized logistics terminal that is to be built integrating the existing terminals and having additional warehousing facilities will enable the traders and producers to have sufficient warehouse, where freights from different sources can be consolidated. The terminal will reduce terminal- to-warehouse trips, whilst the consolidated freight shipment will reduce the trucks on the road. This better organization of the shipment will reduce the congestion and may result in decreasing the congestion costs by 3.14 billion tugrics per annum.

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The volume of international trade and freight transport has been growing very fast during the last decades in Asia. To facilitate this trade development of efficient intermodal transport is essential. Dry port, an extension of ports in hinterland inland locations, is an important component of intermodal transport. It can play important role in facilitating transshipment and distribution of goods in wider inland areas including Asia 12 landlocked countries. The paper presents selected case studies of dry port and intermodal transport development in Asia. Barriers, lessons and policy options to promote intermodal freight transport as well the role of dry ports in reducing CO2 emissions are presented. It is hoped that lessons from the case studies and cases and polices would help decision makers to initiate policies and plans to further develop intermodal freight transport.

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Similar to the Eastern Seaboard Project initiated with comprehensive approach to regional development, which included a world class port, petrochemical industries, a cluster of heavy industries facilitated by a dry port connected by super highway and cargo-oriented railway, Thailand now is proceeding with a similar project, which is called the Thailand landbridge project and would be located in the southern of Thailand. It is a logistics park concept to interface transport hubs intertwined with landbridge and heavy industries; light industries and services; and special and free economic zone. Several studies have already been done and analyzed its feasibility in terms flow, finance and environment. The project is a mega project and carries pros and cons in terms of the project, local community, and national development perspective. In these contexts, this paper has synthesized the critical components of the project, analyzed them, and brought forward their binding elements.

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When discussing a roadmap for realizing trade liberalization and efficient transport, a comprehension of the "quantitative effects" of the related policies could be highly supportive and suggestive. The authors had developed a successive prediction system of trade value and international cargo flow, which provides an effective tool for quantifying the impacts of trade and transport policy on international cargo shipping. In this paper, the forecasting system is arranged in order to support a discussion for realization of trade liberalization and efficient transport among APEC economies, called "Trade and Logistics Forecasting System for the APEC region".

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We will show a micro-economic based quantitative analysis scheme to evaluate the energy consumption efficiency of cities that takes into accounts 1) the utility theory based on transportation and composite goods consumption behavior, and 2) a consistency between the level of utility and energy consumption. By representing the individual quality of life by utility, which is decided by consumption of composite goods, car trips and Mass-transit trips, this study developed a CES-based model to estimate the actual and minimum individual energy consumption for maximum utility level. We applied this model to Kumamoto and Nagasaki region and found higher energy efficiency in Nagasaki with a more compact city structure and mass-transit trips. Most of the zones with higher energy efficiency are found located in higher population density area. Such findings suggest that a compact urban structure and higher mass-transit accessibility can induce greater urban energy efficiency.

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Sustainable development is an important goal for cities in the world. Green planning has attracted a lot of attention. Parking planning is a part of city traffic planning. The aim oftraditional parking planning is to well satisfy citizen's demand, which performs as a following type planning. While green parking planning is quite different. It controls and guides people's parking demand to realize high efficiency and low pollution. In this paper, we first make a study of advanced experiences both in home and abroad. At the same time, we absorb some excellent concepts and methods. Then a specific process of parking planning and management is proposed with a case study of Caofeidian ecological city. The characteristic of this planning is green, guiding and easy executable. We hope this paper is able to give some inspiration to researchers working on parking planning.

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In this paper we described the methodology to take control of air pollution due to toxic wastes from auto vehicles and experiment the state of the pollution from auto vehicles in Ulaanbaatar. In the paper we focused on the issues such as analyzing the pollution of toxic wastes from auto vehicles in Ulaanbaatar, processing the methodology to define the factors which affect ecological statistics adversely by auto vehicles, traffic organization during the use of the cars.

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Many cities recently have initiated efforts in the formation and development of sustainable cities through transport policies as a means to realize a low carbon city. But changes in the urban structure and transport as a result of the urban growth are not sufficiently analyzed and established including its evaluation methods as a result of such changes. The study aims to evaluate the changes in urban structure and transportation in a target city-wide two million people in Japan, in an era of depopulation in the country. Thus, an empirical analysis was performed to clarify the changes in the urban structure and journey-to-work travel characteristics. Also, in order to realize the formation of a low carbon sustainable city, an optimum commuting allocation solution was formulated by estimating reduction in the form of commuter trip length. As a result, by evaluating the changes of urban structures and transportation, estimation of the journey-to-work trip length reduction was analyzed.

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The purpose of this study is to build a system to rationally estimate the agent-based household micro-dataset of the base year for land-use microsimulation. Attributes of a household can be classified into a general set of categories. This system, wherein a Monte Carlo simulation is used, deals with those attributes, either continuous or discrete, in a generalized scheme. It uses sample data that contain full information on the micro-data to establish the correlation between the attributes and the available statistical data or census data. To reproduce the correlation between continuous attribute variables, independent variables that can be obtained based on the sample data are introduced and employed as intervening variables. Attributes of a whole household are probabilistically determined based on Logit and other models obtained from sample data. Finally, a case study of the system application to a person-trip-survey dataset of the Sapporo metropolitan area is presented.

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The impact of vehicle emissions on the global climate has drawn increasing concern in the past few decades. Patterns of housing development determine travel behaviors, thus affecting transport-related greenhouse gas emissions. Here, we establish a bi-level model to describe the relationships among housing allocation, traffic volume, and CO2 emissions using a continuum modeling approach. The user-equilibrium condition is achieved in the lower-level, and the minimum CO2 emissions are obtained by optimization the housing allocation in the upper-level. We consider a hypothetical city with one central business district (CBD) and a road network that is densely distributed outside of the CBD. Several commuter classes with different values of time are considered. The finite element method, the Newton-Raphson algorithm, and the convex combination approach are applied to solve the constrained optimization problem established in the bi-level model. A numerical example is given to demonstrate the effectiveness of the method.

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In order to understand the energy consumption patterns of different cities with varied economic development level in Asia, as well as examine the effects of car ownership and self-selection on household energy consumption behavior, four representative megacities, Tokyo, Beijing, Jakarta, and Dhaka were selected and a questionnaire survey about household energy consumption covering more than 1,000 households was conducted at each city in 2009. Based on the survey data, Heckman's latent index model is further built for each city by separating the effect of the car ownership itself and the effect of self-selection. The results showed that, on average, the effect of car ownership itself on the increase of household energy consumption accounts for 90.13% in Tokyo, 86.59% in Beijing, 78.31% in Jakarta, and 69.07% in Dhaka. While the effect of self-selection accounts for 9.87% in Tokyo, 13.41% in Beijing, 21.69% in Jakarta, and 30.93% in Dhaka.

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Transit-oriented development has been researched and implemented as one of the sustainable urban form, but not so much evaluated. Tokyo, as one of the famous transit-oriented cities, has several suburban areas to distribute the population concentration and provide affordable housing. The suburban centers of Tokyo were developed based on the railway network which was developed since late nineteenth centuries, and they have kept high railway ridership and dependency. However, with motorization starting since 1970s, development patterns have been differentiated: more railway-oriented or road-oriented. This paper compares two suburban centers centering Tachikawa Station and Machida Station, as two extreme examples in commercial activities regarding station development, in terms of commercial area distribution and consumer behaviors, and it analyzes what makes transit-oriented development success or difficult.

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Carbon footprint is a measure of the effect of human activities on the environment, and in particular on climate change. Here it has been used as an indicator to study the impact of the construction material used in the building, maintenance and repair of the highway. The objective of this paper is the calculation of the carbon footprint of a stretch of NH-228 in Gujarat state in India. The study contributes to a growing area of research and will help to analyze the design of the roads in a manner which will be more environmental friendly. This tool can even help to choose the construction materials which will be have lesser impact on the environment.

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This paper presents an instantaneous analysis for traffic emissions using GPS-based vehicle activity data. The different driving conditions, including real-time and average speed, short-time stops and long-time stops, acceleration and deceleration, etc., are extracted from GPS data. The hot emission, cold-start emission and idling emission, varied by nitrogen compounds and particulate matter are calculated, respectively, in terms of the driving condition and vehicle characteristics. Results simulated based on a one-day trip activity dataset show that trucks spend most kilometers on national roads, followed by municipal and provincial roads. The number of short-time stops is significantly higher than long-time stops, and the time spent for long-time stops is higher than short-time duration. The hot emission accounts for the largest proportion of emissions, and the idling emission also contribute substantially. Results of sensitivity analyses indicate that pollutions in urban area from freight transport can be significantly decreased by increasing the vehicle classes and guiding the heavy trucks out of the region.

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Climate change has become a global and environmental issue in the early 21st century. All natural, human, and transportation infrastructure systems are affected by the climate change. Several issues related to the climate change have been widely discussed, such as transportation planning, environmental protection, energy conservation and reduction of GHG (the emission of vehicular greenhouse gases) emission. Currently, the considerations of climate change are not fully incorporated within the transportation planning process in Taiwan. This paper proposes a conceptual framework of transportation planning process under climate change in Taiwan. The impact of precipitations on urban areas in an operational level is studied through a simulation-based model, DynaTAIWAN. The impact is measured in terms of average travel time, average travel distance, and average stopped time. Numerical experiments are conducted based on a sub-network of Kaohsiung City and different precipitation events are simulated.

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The congestion problems usually arise in cities with a population more than 1 million inhabitants, until 1996 had been attained by several cities in Indonesia, such as: DKI-Jakarta, Surabaya, Medan, Bandung, and, Yogyakarta. In 2025, an estimated urban population in Indonesia will reach 150 million inhabitants (about 60%) of the total population of Indonesia that estimated 250 million inhabitants. Centre for Sustainable Development (1997) defines sustainable transportation system as a system that provides access to basic needs of society as a safe and consistent with human health and ecosystems. Sustainable transportation is one aspect of the overall sustainability (global sustainability) which has three interrelated components, namely: environment, society, and economy. This paper aim to choose the strategies that can be implemented in Indonesia based on 16 studies before or best practice. There are two required criterions to determine the priority of strategies. The estimation is using Analytical Hierarchy Process or AHP. This technique utilizes mathematic approach to choose or categorized the strategies that spread from 16 important studies in Asia, Europe and America. Few studies were conducted by quantitative method and influence the most background the selection of strategies.

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This paper describes a model of logistic firm location choice decision which includes two levels such as the regional choice and zone choice process. In which, the main contributions of this study are an analyzing the influence of regional accessibility and zonal accessibility on the logistic firm location choice decision by using the discrete choice model. The results indicate that the distance to the nearest station keeps a key role in the location choice decision of miscellaneous light manufacturers. In addition, the distance to the nearest IC highway is also very important factor for these manufactures and product wholesalers. These accessibility variables, however, are less important for the retailers. Finally, the spatial effects strongly affect the zone choice decision-making process of all firms.

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This research attempts to evaluate emission measurement of on road vehicle. In this regard, the research develops failure probability model of vehicle emission test for passenger car which utilize binomial logit model. The model focuses on failure of CO and HC emission test for gasoline cars category and Opacity emission test for diesel-fuel cars category as dependent variables, while vehicle age, engine size, brand and type of the cars as independent variables. A survey to measure the vehicle emission and other information of the vehicle was done to the two categories of passenger cars on road. The survey was done at two main roads in Makassar City, one of the large cities in Indonesia. According to calculation result, vehicle age became significant variable to determine the failure probability of vehicle emission test of gasoline cars category. However, engine size gave significant contribution for diesel-fuel cars category.

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Electric vehicle (EV) use has been focused to reduce the amount of environmental emissions from private vehicles. However, the driving range of EV is much shorter than that of gasoline vehicles, because of the low capacity of battery. Our objective is to quantitatively estimate the risk of incurring an empting EV battery under the use of daily activities. A couple of surveys are conducted to investigate daily vehicle use, under the different usage environment. The questionnaire survey included the following items; a plan for vehicle use in tomorrow, and the actual vehicle use in today. A trajectory-monitoring survey using a Global Positioning System is conducted to collect a precise distance. We developed an energy consumption model based on a survival duration model, considering household, dominant vehicle user, and residential characteristics as covariate. The estimated model can give us a quantitative evaluation about the required driving range of EVs in daily vehicle use.

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