This paper is aimed to propose a new framework and methodology to incorporate service quality and inertia effect into stated preference model. We use structure equation model and stated preference method to conduct with psychological and quantitative attributes. The logistics regression is used to generalize inertia effect and to explore casual influences of important factors on inertia effect. The empirical data is focus on the choice behavior of intercity bus transport. The computer questionnaire is based on the each traveler’s experiences in RP choice to design the corresponding SP scenario in avoiding to the response bias. The results of logistics regression show that there are significant casual influences between inertia index and number of alternative, traveling frequency, and personal income. The estimating results of MNL model prove that the specification of generalizing inertia index has the better model fitness than the traditional 0-1 inertia index.

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In this research, we first categorized transport surveys of passenger flow in Japan and found out their situations. Large-scale transport statistic surveys have been conducted and they provide information for planning or just for statistics purposes. Next, we analyze current situations of urban transport using the results from Nationwide PT Survey, and found the following. a) The number of trips has declined in Japanese cities as the society ages. The vehicle ownership and driver’s license holders increased further. Thus, automobile use has increased overall. This could exacerbate environmental burdens in the future. b) Compared to younger age groups, the elderly use car less often and makes fewer trips. As aging progresses, the number of elderly without mobility is anticipated to increase. c) In Japanese cities, modal split varies by the size of urban area and population density. Lately, with the declining trend of population density, it may contribute significant increase in car use.

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This study proposes a methodology for estimating places where people may perform additional activities with utilizing the concept of space-time prism. Decision about travel behaviour can be affected by time constraints of their life and spatial structure where they live. Considering such constraints is important to estimate which place is likely to be chosen for the additional activities. This study develops a method to estimating the place which people may choose as an additional destination. This method proposes the concept of path constrained potential path area (P-PPA) by incorporating the concept of space-time prism with information of revealed trip trajectories which can be taken by position detection tools such as GPS and so on. An efficient calculation algorithm with considering actual network structure is proposed. An empirical test has been carried out in the real network to check the proposed methodology.

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A travel cost function is critical in traffic assignment in that the route choice behaviors of users could be described by the function. Parameter calibration of the function is to adjust parameters in a model so as to represent local traffic conditions. In order to describe correctly the real travel patterns in the model, we should calibrate the parameters by observed information. This paper presents a calibration method for travel cost function, which widely used in traffic assignment. It is based on bi-level programming such that the upper level is to minimize the difference between observed link flows and estimated ones computed from traffic assignment, while the lower is to describe the route choice behaviors of users on the transportation network. A solution algorithm will be given and through a numerical example it is also shown that multiple solutions is existed in such problem.

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Confronted with rapid urban growth in developing cities, it is expected that configurations of transportation network, as well as their operation conditions, could have significant impacts on various aspects of trip-making behavior. Meanwhile, trip-making behavior is one of the most important determinants during the design and management process of transportation network. To properly reflect such interdependency mechanism, this paper first attempts to establish a travel demand prediction model with feedback for the Jabodetabek metropolitan area, Indonesia. Compared to the traditional four-step model without feedback, it is empirically confirmed that introduction of feedback mechanisms could improve the model accuracy a lot. Based on the estimation results of the feedback model, some urban and transport development policies are evaluated from the perspective of realizing environmentally sustainable cities.

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Passengers choose the mode and path of public transport for their daily trip according to the different individual demands. The typical factors are like fare condition and trip time etc. But, the condition of comfort for passenger becomes an important factor now. At present, the applied modeling softwares begins to take account into aspect of comfort; however it still stays the beginning now. Effectively, passengers can choose the mode of public transport according to their different comfortable level. The goal of studying aims to create a new algorithm of comfort of passengers in order to reinforce the missing aspects in the actual software. The first part of the report consists in presentation a longitude aspect of comfort. In the second part has to establish a mathematical algorithm model according to the aspect of comfort defined, and then codified a calculating program by Scilab for algorithm inducted. Finally, we will give a simple numerical case to display these relations between the trip cost and the comfort of passenger.

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It is expected that vehicle holding durations differ substantially across households. Some households may keep their vehicles as long as possible, while others may replace some of their vehicles after holding several years. Even though existing studies have incorporated such heterogeneity using duration models, one-peak distribution is usually assumed. In reality, this assumption can be easily violated. In this sense, the heterogeneity of duration distributions has not been satisfactorily represented in existing literature. To represent the heterogeneity in the household vehicle holding duration, the paper proposes to apply a latent class modeling approach to simultaneously integrate different duration distributions. Such modeling approach could deal with multi-peak distribution of vehicle holding duration. Using a data collected in several Japanese cities in 2006, this paper confirms the model effectiveness from both model performance and applicability. It is found that household characteristics are important factors to explain the latent classes.

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This paper investigates freight forwarders’ perceived satisfaction on service attributes of ocean carriers and their choice behaviors. The mail surveys were conducted to freight forwarders, providing services between Taiwan and the United States. This research employs factor analysis to combine a large number of service attributes into few latent factors and the multinomial logit model to examine ocean carrier choice by freight forwarders. The result of factor analysis obtained three factors, namely speed/reliability, safety/empathy and convenience. The estimation results of the multinomial logit model reveal that transit time, frequency of sailing, record of cargo delay, freight rate and latent service quality factors are the significant variables influencing the choice of ocean carriers. Freight forwarders are sensitive to the changes in service frequency and transit time, indicated by the values of direct elasticities. The findings provide useful insights into ocean carrier choice behaviors by forwarders.

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Recently, various retail shops are installed in the railway stations in the Tokyo Metropolitan Area (TMA). Many passengers enjoy shopping and window-shopping while transferring trains, and waiting in the station. Such passenger behavior causes issues such as crossing of the passengers’ flow and the decline in walking speed. Therefore, it is important to consider such behavioral patterns in the planning and management of facilities in the railway station. Pedestrian simulation model is a powerful analytical tool for determining optimal layout of facilities. So far, many pedestrian simulation models have been developed. These models can reproduce the average walking speed, and sectional pedestrian volume. However, these models do not consider behavioral patterns in visiting the facilities into consideration. For developing the pedestrian simulation model applicable also to the facilities arrangement planning, the study conducts a basis analysis aimed to grasp passengers’ visitation patterns of facilities in the railway station.

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This paper presents a discrete choice modeling framework for analysis of repeated choices associated with expensive automobile insurance policy (AIP) — the bundled physical damage coverage and the number of consecutive years the insured has purchased the same type of AIP. A four-year panel data with 9,949 voluntary automobile insurance records, randomly drawn from a non-life insurance company in Taiwan, is used to test the empirical case. The estimation results of the preferred multinomial logit model show that engine capacity and vehicle make significantly affect selection of AIP bundles. Older adults and owners of newer vehicles, of larger engine capacities, and of imported vehicles tend to repeat purchase expensive AIP bundles for three or four consecutive years. The preferred nested logit model further confirms that the inertia of the same individuals leads to repeat buying of the same physical damage coverage policies for several consecutive years.

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Public transportation (PT) plays a major role in order to meet the ever-increasing travel demand in developing cities. With urbanization trend at the fringes of the region, away from the city core, travelers must take different modes or to chain trips to reach their final destination. This study investigates the travelers’ decisions on choice of mode and modal combination patterns through modeling tools. Specifically, it looks into the travelers’ preferences for different modes in performing PT chains. Empirical analysis using logit-based extreme value models such as multinomial logit (MNL), and nested logit (NL) was performed. It introduces the applicability of cross-nested logit (CNL) model structure in analyzing PT mode choice behavior. Utilizing variables such as total travel time and cost, with some socioeconomic variables, for all model formulations, estimation results point to the flexibility of more advanced models in dealing with the choice situations involving PT chains.

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This study focuses on the trip generation characteristics of business process outsourcing (BPO) companies in the Philippines. Business process outsourcing is a rapidly growing industry and as such, has spawned land use that has significant differences in trip generation characteristics from traditional offices. Travel demand characteristics for BPOs, for example, are quite different because of the unusual nature of operation of such companies due to the varying times in countries served by employees. Many BPOs were initially located in central business districts in Philippine cities. However, as the demand for BPOs continue to increase, offices have been established away from the urban areas at business and industrial parks. The paper examines the characteristics of BPO trip generation. It presents the formulation of strategies to address problems pertaining to transport demand as well as the provision of facilities to accommodate the continued growth of the industry.

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This paper aims to develop alternative forms of emergency trip destination (emergency shelter) and investigate the evacuee behaviors affecting the shelter choices for future tsunamis and other disasters. The shelter allocation forms are developed using the logistic regression model and neural network model in estimating the probability of evacuee choice of selecting evacuation destinations between public and private shelters. Not only the socio-economic factors that affect the selection decisions are presented, but this paper also intends to analyze the shelter attributes based on evacuee’s perceptions. These perceptions are expected to influence evacuee’s preferences among different alternatives. Data are collected in one of the most recent tsunami affected areas, Phuket, Thailand. Results of this study revealed that the emergency trip destination demand estimation does not provide only information for shelter requirement and shelter space but it can also be used to plan for emergency materials needed.

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In Asia, many developing countries are facing the issue whether to develop the motorcycle market as a transitional phase or to jump to the automobile market directly. In order to examine the issue, this study attempts to develop a mixed discrete/continuous demand model to analyze the characteristics of household’s decision behavior associated with the mode to work, ownership and usage of cars, and ownership and usage of motorcycles. Empirical analyses indicate that it is not easy to suppress the ownership levels of motorized vehicles by adopting price mechanism or by improving the quality of public transportation. Thus, in order to prevent a great deal of problems resulting from mixing car and motorcycle flows, we suggest that it is better for developing countries not to approve the development of motorcycles as a transitional phase.

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Based on the travel psychology of citizens, this article considered about the six indices of being safe, comfortable, swift, convenient, in-time and economic comprehensively, analyzed the relationship between these indices and then built up an evaluation index system. Then using fuzzy evaluation model and multi-objective decision making method, it researched on citizens’ traveling behavior, built a mathematic model and thus located comparatively scientifically the traveling modes citizens adopt. With live examples of citizens of a district, this article proved that the model is simple and practical, could be applied to practice basically.

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Many past researches have invoked time, cost and specific mode attributes to explain transportation mode choice. Alternatively, this paper attempts to study an additional dimension by incorporating latent factors. The general structure comprises two models, namely a latent variable model and a discrete choice model. The estimation is performed by first determining the significance of specific latent variables— safety, comfort, convenience and flexibility. In the second stage, the discrete choice model is estimated by integrating the choice and the latent variable in the choice process. The discrete choice model is estimated via logit and probit regressions. The main findings are that the latent factors are statistically significant and thus enrich the discrete choice model. Hence, latent factors must not be ignored in describing individual preferences towards travel mode. By providing better explanation to mode choice behaviour, the enriched discrete choice model could prove useful to policy makers in managing transportation infrastructure and services to maximize welfare.

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This study investigates the vehicle routes for a firm with its own delivery fleets and a single depot. A mathematical programming approach is employed to construct a vehicle routing model for handling mixed pickup and delivery operations by referring to the Vehicle Routing Problem with Pickup and Delivery (VRPPD). Furthermore, this study utilizes a heuristic algorithm to develop a problem-solving procedure. A revised Nearest Neighbor (NN) method is developed to obtain an initial solution. The 2-Opt exchange and Simulated Annealing (SA) method are adopted to develop the solution-improving procedure. Analytical results of this study are the optimal sequence of vehicle routes and the customer sets served by each vehicle. A sensitivity analysis among vehicle capacity, travel distance and number of routes is also proposed.

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Convenience stores in Taiwan have made remarkable successes with retail delivery services by integrating E-commerce and logistics systems to form a new retail delivery model: “On-line shopping with pick-ups at convenience stores.” The main purpose of this study is to explore what kind of factors can influence the pick-up point choice behavior by using a catastrophe model. In this paper, the catastrophe characteristic of the choice behavior has been discussed and used by cusp catastrophe model that is based on the empirical data. The outcome has shown that these characteristics include bimodality, hysteresis, and catastrophe are present in the research data. When increasing the value of the retail delivery services through some marketing strategies, the loyalty relationship between customer and convenient stores will be enhanced.

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This paper presents multi-agent models for evaluating the behaviour and interaction among stakeholders who are involved in urban freight transport systems as well as effects of city logistics measures. Multi-agent simulation on a small test road network demonstrated that the VRPTW-D model which dynamically adjusted vehicle routing planning to the current travel times generated good performance in terms of increasing profits for freight carriers and decreasing costs for shippers. After applying multi-agent models on a large test road network, it was observed that introducing the VRPTW-D model generated a win-win situation by increasing profits for freight carriers and decreasing the costs for shippers. The results also show that the implementation of road pricing can reduce NOx emissions but may increase the costs for shippers. To avoid such effects, introducing cooperative freight transport systems helps shippers to reduce their costs.

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This study establishes a discrete process-interaction simulation model to solve cold chain home delivery peak-demand problem at operation center. We simulate its ceiling capacity and use it to evaluate alternatives to over-capacity. A Penghu case study shows that current capacity is around 360 packages under five members/vehicle assignments. However, capacity can be increased to 435 once staff’s operation efficiency was increased by 20% (i.e., decreased by 20% operation time for each job-item). In case of over-capacity or trucking delay, dropping out unnecessary job-items such as cargo number and weight recording is a workable option to save operation time. In addition, depending on package amount, truck’s arrival delay at operation center is acceptable for fleet control. For example, a late arrival truck with 30% (of 361 units) packages carried, a delay of thirty minutes is allowable. At 79%, only five minutes is allowable.

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The design of a logistics system can be defined as a Location Routing Problem (LRP), which is to find the optimal number and locations of the distribution centers, simultaneously with the vehicle routing to minimize the total system cost. In this research, a three-phase hybrid heuristic approach (LH-SA), combining the Lagrangian heuristic (LH) and simulated annealing (SA), is developed to solve the multi-depot location routing problem (MDLRP). Firstly, the LH is applied to determine the facility location set and the allocation of customers. Then an independent vehicle routing problem (VRP) for each selected facility location is solved by SA. Finally, the SA is used to perform a global search for all routing moves. The performance of the proposed algorithm is tested on two different groups of benchmark instances and compared with other algorithms in the literature. The results show that the LH-SA is competitive and updates 20 best-known solutions.

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Recently, a set of probe equipment comprising the GPS and an information terminal is increasingly mounted on goods vehicles to gather data on their operations. This study aims to better understand cargo deliveries over a middle/long-distance and within a city, using the probe data of trucks linked with the drivers’ operation status. It is learned that truck drivers are constantly under psychological pressure to make the designated delivery time, which is getting more demanding in recent years. In this study, we estimate safety margin against the designated arrival time based on the probability of being late calculated from the truck’s travel data. This is because the probability gives us an objective way to evaluate the risk of getting late. As this safety margin lessens the driver’s psychological pressure for sticking to the delivery schedule, it is expected to greatly contribute to safety drive while improving the efficiency of deliveries.

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City cooperative freight transportation system is considered as an effective way to solve traffic problems. However, cooperation problems remain on the stage. With this in mind, this paper applies some important concepts in a cooperative game theory with focuses on core and ε-core to analyze cooperation among members of an alliance of truck-focused logistics companies, which will involve 1) Providing a detailed and systematic standards of essence to judge the rationality of alliance formation by core; 2) Seeking rational payoff for partner companies and optimal subsidies given by public sector as to formation of an urban cooperative alliance by ε-core; 3) Illustrating the crucial factors for promoting alliance formation and 4) Suggesting practical measures on how to make practical measures in order to boost cooperative alliance easily. This paper aims to enhance the understanding of interagency cooperation and decision-making behaviors facing truck logistics companies and local public sectors.

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Insufficient numbers of parking space and lack of (off) loading areas are some of common problems that driver of delivery trucks have to deal with. One way to address this problem is by increasing the utilization rate of the limited parking spaces by ensuring short parking time of trucks. Attaining this brief parking time, however, requires a shift from a traditional way of delivering goods to a policy-driven method. Traditional way presents a situation where the driver has to leave his truck and make his way to the floor of the building to make delivery. Although this method remains to be popular due to its simplicity, there exist methods that when carefully enforce would present sizeable benefits. One of these policies is by assigning workers inside the building to facilitate the (un)loading activities to free the driver immediately. This paper discusses implementation of cooperative delivery system and tries to produce a guideline regarding what CDS design is suitable depending on the characteristics of the CBD.

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This paper focuses on strategic planning in developing countries, particularly in freight transport network design and terminal development. An optimal set of transport projects is determined using a transport network design model with some objective function, which can be a single objective function or a multi-objective function. The model involves bi-level modelling approach, where multimodal multi-user assignment is incorporated in the lower level problem and the combination of transport interventions or projects is optimized in the upper level problem. Application of the model is undertaken using data from the two archipelagic countries of Indonesia and the Philippines - both countries that would definitely benefit from a multimodal transport design.

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Marshalling yards serve as switching and transshipment points in rail networks. The selection of optimal marshalling yard location influences not only total costs and delays but also economies of scale due to the consolidation of flows. The purpose of this paper is to develop an optimal marshalling yard location model considering economies of scale due to the consolidation of flows. This model also includes several cost components and capacity constraints related to rail networks. Test results are presented for rail freight transportation problems with 25 origins/destinations. Also they are compared with recently published studies. The proposed model can be used in the several decisions on the improvement of the efficiency in rail networks.

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This paper discusses how to integrate forward and reverse logistics to decrease the total cost of third party logistics service providers. A mathematic model is provided without the assumption of straight-line distance. Demand for product and return amount of product can vary randomly in this model. We also allow that the demand of customers can exceed the capacity of their suppliers. Then we develop a Genetic Algorithm to solve this NP-hard problem and discuss its convergence. At last a numerical example is available.

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Given the high level of complexity and wide application of the vehicle routing problem (VRP), numerous solution algorithms have been developed for the past several decades, including many recent meta-heuristic algorithms with great success and popularity. In order to balance computational load and solution quality and to address the issue of flexibility and simplicity, this study developed a heuristic algorithm based on several classical mathematical programming techniques. The VRP is first formulated in the form of the set covering problem (SCP), 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 maintain a partial set of potential routes to reduce computational load. Based on the numerical experiment, the solution quality of the heuristic algorithm is stable. The result suggests that the solution algorithm should be able to deal with the operational problems arising from a highly dynamic environment.

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Logistics management has been one of the most important parts in the supply chain management. More and more distribution centers (DC) have been established to provide the flexibility of sales and supply. Major daily operation issues in distribution centers are routes and schedules of trucks. The dynamic vehicle routing problems (DVRP) is an extension of VRP in order to consider possible variations of travel times in the network. In this research, a two-stage framework for solving DVRP is proposed. In the first stage, a well known approach, the sweep method, is conducted in vehicle assignment. In the second stage, a tabu search algorithm is implemented to improve routes under real-time information. The heuristic approach is then applied in an evaluation framework in which assigning and routing operations could be simulated in a realistic traffic environment. The simulation-assignment model, DynaTAIWAN is applied to evaluate assigning and routing strategies in a traffic network.

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Until now, the authors have been developing a model for international container cargo simulation (MICCS) which can produce the movement of the cargo with the volume of OD container cargo as a given input, focused in East Asian region, in order to simulate and evaluate international freight transport policy. This paper aims to evaluate the effects of the policies on port investment in China, using the model with two cross-sectional data in different years. The outputs of the model, incorporating with initial condition of transport environment in 1998 and OD container volume in 2003, are compared between cases with and without port investments during these five years in China. By this, it will become clear how degree these policies contribute to the change of container cargo flow on maritime and land transport network.

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This study estimates light and heavy truck origin-destination (OD) matrices based on the commodity flows in the Tokyo metropolitan area. There are three major concepts in this study. First, the truck OD is estimated using the commodity approach because it can reveal the important characteristics of the shipments. Second, the ability to estimate both loaded and empty trips is the main contribution of the model. Finally, loaded trips are mainly concentrated and modeled with trip chains behavior and shipment characteristics such as average payload, adjacent zones, and others that provide the most attractive zones traveled by trucks. The performance of the model is demonstrated using the relative mean absolute error between the estimated and observed truck OD matrices. The numerical analysis based on the light product of the food industry demonstrates that the proposed concept with trip chain behavior always outperforms the model without trip chain behavior.

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This paper proposes two ant colony system (ACS) based approaches, called stepwise-ACS (SACS) and cheapest-insertion-stepwise-ACS (CISACS), to solve the air-express courier’s routing problem. The courier visits N predetermined delivery points and M pickup requests during the en route delivery. The SACS performs an ACS to obtain the initial tour for the N delivery points and then to find the shortest Hamiltonian path, in a stepwise manner, when the M requests arrive. The CISACS, following the SACS, incorporates the cheapest insertion into the SACS as new requests become known. Experiments with various pickup emergence patterns that characterize the real-world circumstances are tested for the proposed algorithms. The computational results, in terms of total traveled distance, are compared with the baseline results by a cheapest insertion (CI) heuristic. The results show that both SACS and CISACS perform better than the CI heuristic and that CISACS yields the lowest traveled distance.

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This paper presents an integrated microscopic simulation model that would be applicable for examining potential emissions impacts of truck-involved transportation policies in urban freeway system. Basic idea of the model is to integrate an emission model into existing microscopic traffic simulation framework. Considering truck-only lane policies, the effectiveness and applicability of the integrated model was evaluated with an application to the Long Beach freeway (I-710), a main corridor for freight transportation that provides regional access to the Ports of Long Beach and Los Angeles in the United States. The case study shows that the proposed model is useful in that when considering alternative policies of truck-only lane, it enables transportation planners to evaluate potential emissions impacts and traffic conditions simultaneously without real implementation of each alternative.

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This paper presented the VRPTW-D (Vehicle Routing and scheduling Problems with Time Windows-Dynamic) model with real time information on travel times. After applying the model to a test road network, results indicated that the VRPTW-D model presented more efficient routing and scheduling in reducing the delivery costs than those of the VRPTW-F (Vehicle Routing and scheduling Problems with Time Windows-Forecasted) model. This reduction of delivery costs was mainly attributed to the reduction of delay penalty. If the depot costs of construction and maintenance were taken into account, the case with two depots was chosen as the optimal solution with traffic impediments even in urban areas where the land price was very high. It can be noted that efficient vehicle routing and scheduling using the VRPTW-D model can also provide environmentally friendly systems in terms of reducing CO2, NOx and SPM emissions

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A long-term strategic planning tool called RECATS^©: is introduced. It explores the link between urban form and susceptibility to fuel shortages in order to quantify a risk factor at a queried year in the future for a given urban form and travel demand configuration. RECATS includes interactive models for global peak in oil production, development scenarios for alternative or bio-fuels, and fuel rationing or supply management. On the transport side, RECATS allows the user to specify the distance, mode, and frequency matrix which has been determined for a given urban form using standard transport modelling. RECATS was applied to a case study in which four different urban development forms for Christchurch, New Zealand were simulated. Results show that all urban forms would lose and/or change trips according to the land use-transport system configuration options, but the risk to activities would be very different for different future cities.

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Advanced Traffic Control Systems (ATCS) have been used in large cities in developing countries to ease traffic congestion problems. Congestion causing poor traffic performance has negative impacts on economic productivity, environmental quality and safety. The aim of this paper is to evaluate the impact of ATCS on fuel consumptions and pollution emissions in a large city in a developing country with specific geometric and traffic behaviour. A large road network area in Bandung, Indonesia was used as a case study. Fuel consumptions and pollution emissions (CO, NO_x, HC) data was obtained from combustion and emissions laboratory. The results found that the impact of ATCS on reducing fuel consumption and pollution emission is not good especially during peak periods that usually have more traffic congestion. In conclusion, the application of ATCS in the large city in a developing country is not effective to reduce traffic congestion and enhancing environmental quality.

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In order to manage the transportation demand through land use planning, we developed a model to optimize the distribution of shopping centers in a China’s city. In the model the location behavior of shopping centers and the destination selection behavior of the shoppers are considered. It is a p-median style model, in which we considered the modal split model. Models respectively based on road network and super transportation network are structured. The objective of both of them is to decrease the distance of shopping trip. With survey data of Dalian city we calibrated the two models and verified their validity. After that in order to solve this nonlinear programming problem, genetic algorithm with dynamic parameters is designed and numerical test is done with the data of Dalian city in China.

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Earlier research had identified association between telecommuting and commute travel. Telecommuting is considered as a travel demand management measure in mitigating travel especially work trip to the central business district. However, whether it acts as an effective travel demand management measure is still remain to be seen. This paper investigates potential of telecommuting as a travel substitute especially for work related trips. The analysis of travel substitution as a result of practicing telecommuting was made based on stated preference of the employees in the selected business organizations by questionnaire survey. The survey was administered in two major cities namely Kuala Lumpur and Johor Bahru in Malaysia. Work trip components include commute trip and vehicle-km. Telecommuting frequency between 1 and 3 days per week was considered for this study. The analysis revealed that the commute trip reduction from stated preferred telecommuters was not more than 10% of the total commute trips.

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Tourism is one of the most dynamic and fastest growing global industries. Brand image of a tourist destination is important to attract tourists. Sudden calamities highly affect the brand image of tourist destinations; recently several destinations were found with declined brand images following massive calamities. Maintaining a positive brand image is challenging due to external fluctuations and because decision making depends on individual motives. Travelers’ destination decisions are attained after trading-off personal and destination attributes. It is complex and could be unreliable depending on available information sources. A Tourist Destination Branding Index (TDBI) which incorporates a weighted combination of destination attributes is therefore worthwhile. This paper explains TDBI, based on the Total Utility Value (TUV) of a destination. A visual representation of brand image fluctuation with disasters is meaningful for tourists as well as tourism planners for decision making and destination management.

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Disorderly urban sprawl in developed countries was aggravated by the progress of motorization. City planners in developing countries can avoid similar mistakes to be repeated. Since personal income level and car ownership seems to have a positive relationship, the objective of this study is to clarify the influence of rising income level on traffic behavior in developing countries. It was found that the car usage rate will rise with increasing income levels for cities with income levels above a certain value. One of the reasons is the relocation of high income people to the peripheral area of a city and this has been proven. Solutions to this imminent problem include development of a pleasant living environment in the city center so as to attract more people from high income level groups to reside in the city center area, and the compound use of city land in order to reduce trip length.

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The different transport stakeholders with diverse demands have different needs for transport infrastructures and services in an urban transportation system. To meet the objectives of sustainable transportation implies the trade-off consideration of benefits among different stakeholders and creates the issues of transport diversity. However, few researches have focused on these issues. The aim of this study was to provide a framework to evaluate the transport diversity in the Taipei Metropolitan Area. The transport diversity is defined as the satisfied level among the needs of stakeholders in this study and measured as the gap between the goal and present values of stakeholders’ needs in the form of Shannon-Weaver Index. The result revealed that the higher diversity means the more equitably stakeholders’ needs satisfied. It is hoped that the findings of spatiotemporal analysis would help transport planners to understand what infrastructures or services at where have to be improved.

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This paper presents a study of land use transportation interaction in the developing countries context. Several issues regarding the development of land use model in developing metropolis are discussed. A case study of Bangkok is presented. The present situation of urban and transport development is described, showing that land use interaction is not explicitly considered in the transportation analysis. Empirical evidence from the railway projects shows that interaction of land use and transportation interaction is quite strong and must not be ignored. To analyze land use and transportation interaction, an effective tool is required. Among the existing urban models, TRANUS is selected as a pilot system for Bangkok for several reasons. The design and calibration of Bangkok model are described. Scenario analyses provide insight how land use is incorporated in the comprehensive urban transportation analysis scheme. Policies such as road pricing or TOD are effective countermeasures to compact the city and relieve traffic congestion. Lessons learned from the present system gave an idea of to develop an integrated land-use transport and the environment for Bangkok.

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Interaction between regions is commonly focused on regional policies from the viewpoint of local revitalization. An interaction whose main purpose is sightseeing is analyzed in this study. An interaction index is proposed which can evaluate influence on the region of destination quantitatively in consideration of economic consumption. Economic consumption varies along with the sojourn time at the region of destination. An interaction model is formulated by constructing a consumer behavior model which is based on the Utility Maximization Theory. In order to develop a method to measure the degree of influence due to interaction, parameters of this model are estimated. As a result, it is clarified that interaction is influenced by travel cost, attraction of destination region and relationship between regions. In addition, degree of influence on prefectures in Japan by interaction is calculated and revitalization is discussed.

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This paper presents a mixed logit framework to identify residential location choice behavior in households. The model integrates a “direct parametric representation” approach to capture the correlation between spatial units, as well as a comprehensive structure of zonal accessibility to reflect the effects of employment, school, shopping and recreational opportunities. Households are clustered based on demographic and daily trip data to extract their different residential choice characteristics. The model is applied to the central city of Dalian, China. The empirical results reveal that 11675 households are clustered into 5 groups, with distinct characteristics in each group. Results also show the significant differences in sensitivity to female, male and children commuting behavior while households make residential choices, as well as their preferences to zonal accessibility to different activity opportunities.

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This study aims to identify the significant attributes that influence the utilization of the park-and-ride scheme in three fringe areas of the Kuala Lumpur conurbation namely Shah Alam, Rawang and Seremban. In understanding the characteristics of the park-and-ride users, three main areas of concern are the socioeconomic, trip and the parking-related characteristics of the users at the stations. Geographical Information Systems (GIS) is applied in order to delineate the catchment area and calculate the access distance of the respective stations. Information was retrieved by means of personally-administered questionnaire at the park-andride site via random sampling and car park utilization survey to determine the hours of parking. By applying standard multiple linear regression, the attributes that were found to significantly influence the duration of the utilization of the facility are total travel time by rail (via the park-and-ride), income, trip purpose, egress mode and types of rail ticket used.

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A case study of metropolitan Sydney is given on the dynamics of polycentric employment location and land-use and transport policies that encourage such a spatial formation of jobs. Spatial plans from 1948 to 2005 are reviewed. Employment decentralisation into major centres has been a consistent objective. Changes in the location of metropolitan employment and journey to work using Census data from 1961 to 2001 and the current metropolitan strategy to 2031 are analysed to help assess whether policy objectives have been met. An historical study of Parramatta, one of the major sub-centres, illustrates the problems of implementation. Current initiatives to create the “two harbour and three river cities” are described.

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This paper aims to clarify urban development potentiality in term of the total number of vehicle trips under an anti global warming policy on which CO₂ emission should not exceed urban transportation environmental capacity. Regarding to the CO₂ emission environmental capacity implementation, authorities and users have different attitudes that is, authorities want steady urban economic growth while considering to reduce CO₂ emission, on the other hand, users always eager to minimize their costs on various activities. Therefore, in order to examine maximum possible increase in the vehicle trips generated in association with urban economic activities subjecting to urban transportation CO₂ emission environmental capacity constrain, a bilevel model that combined authorities and users intention, is proposed. And the model is verified on a real urban network of Chengdu, China.

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This research aims at studying impacts of real-time information on mixed traffic flows through an integrated dynamic simulation-assignment model, DynaTAIWAN. The DynaTAIWAN model is composed of two layers, namely simulation-layer and real-time control layer. The simulation layer is designed to simulate traffic flow patterns according to assumed tripmaker characteristics and/or under a set of given conditions; the real-time control layer receives real-time vehicle information and forecast short-term traffic flow patterns. In the simulation process, each vehicle is moved and tracked individually. Four different vehicle types are explicitly considered in DynaTAIWAN, including car, bus, motorcycle, and truck. Vehicles are moving along the link through macroscopic flow relationships, speeds of each type of vehicle are adjusted. Numerical experiments based on real-time information are conducted in a 50-node test network and a Taichung City Network.

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Empirical experiences showed that improving the urban transport problems should rely on integrated multi-dimensional transport policies which can also soften the demand of infrastructure investment. However, to fully consider the multi-dimensional transport polices in transportation planning framework would be very difficult due to the factor that there would be too many possible policy combinations to be evaluated. Therefore, this study attempts to develop an analytic framework for evaluating urban integrated transport policies comprehensively, including strategies of investment, pricing, management and regulation. In particular, to deal with the difficulty of too many policy combinations, genetic algorithms will be employed to search for the optimal strategy combination for integrated transport policy. Finally, the relationships between quantified objectives, policy combinations, and assessment performances would be analyzed using the proposed model in this study. The results can also provide a reference to decision makers when drafting urban integrated transport policies.

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This study first re-examined the relationship between urban density and per capita car use which most of previous studies supported. We showed that the relationship was also interpreted as one between total urban area and total car kilometers. Next, with person trip surveys conducted in Asian and American mega-cities, the factors affecting both total urban area and total car kilometers were analyzed. We studied total urban area and total car kilometers, and their relationship with average travel speed and modal split, which were found to significantly affect these elements. Finally, we revealed that increase in average travel speed and car share contributed to the expansion of both total urban area and total car kilometers. Also, to supply efficient public transportation, in terms of travel speed, could have the effect of constraining urban area and car use.

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