International Standard requires emergency medical service (EMS) response time to be less than 8 minutes. To reduce the response time for improving the survival rate needs to know the phenomena of EMS call for better management. This article focuses on analyzing the factors of such a problem. A total of 13,871 records from in 2004 were employed to identify the probability distribution of EMS calls and to establish several occurrence probability models. The population data were found to be day dependent; the weekday pattern is different from the weekend pattern. In addition, the data are also time-dependent. Results of Chi-square tests show that the occurrence intervals follow the exponential distribution which means the pattern of EMS calls follows a nonhomogeneous Poisson process.
The downpour which had occurred in Nagoya city area from September 11 to 12, 2000 had caused severe damage to the city’s traffic network, and highlighted the problem about the method of giving information, traffic management, and driver’s behavior under the downpour. Therefore, in this paper, we focus on automobile traffic, and aim to consider the traffic information and traffic management for promoting driver’s appropriate behavior under a heavy rainfall disaster. Especially, we analyze driver’s consciousness and activity under downpour by using driver’s experience data, and develop departure behavioral models of drivers under downpour in order to analyze the relationship between the driver’s departure behavior and the traffic network and rainfall situation.
Concepts and methods for analysing accessibility are essential for understanding many significant social, economic, and political issues. All accessibility measures seek to define the level of opportunity and choice taking account of both the existence of opportunities, and the transport options available to reach them. To study these issues this research has focused on the Australian road network as the primary database with the interest in accessibility directed at those who live in rural and remote areas, rather than urban dwellers. At first stage, this research focuses on spatial approaches to the conceptualisation, measurement, and analysis of accessibility at the regional level. At next level, this research attempts to analyse socio-economic indicator (Income) in regional Australia and relate it to road network accessibility. In the final stage attempt has been made to identify the weak spots in the regional road network based on the extent of accessibility changes.
Methodologies for assessing the seismic risk of a high speed railway system were limited to analysis of fragilities of structures and vibration dynamics of vehicles in the past. A deterministic or scenario based approach assuming a particular devastating earthquake was also used in some methodologies. A seismic risk assessment methodology that can estimate the risk of derailment caused by earthquake is proposed in this study. Among constituent factors, the effectiveness of the seismic early warning system that detects the occurrence of earthquakes before the strong ground motion reaches the line is concerned. This study addresses a formulated method to quantify cost-benefit tradeoffs between gain in safety and false alarms. In addition, an assessment model of consequences in terms of injuries and fatalities in derailment disaster, an approach method for network of Shinkansen, and a graphical user interface are considered as perspective studies.
The purpose of this research is to estimate risk models, which can assess the safety at a railway level crossing. The accident risk, in terms of equivalent fatalities in a period of time, is decomposed into two parts: the accident likelihood, in terms of number of accidents per period, and the accident impact, in terms of equivalent fatalities per accident. Each of the risk dimensions is investigated, using nonlinear regression, Poisson regression, and negative binomial regression, and considering the effect of exposure variables, highway characteristics, railway characteristics, and the control devices, at railway level crossings. Empirical results indicate that Poisson regression is good for the estimation of accident likelihood; and negative binomial regression is good for the estimation of accident risk and accident impact.
In the recent years, passenger van is a new form of the small-medium transit service in Bangkok. In comparison to bus, passenger van offers shorter journey time, increased headway, improved reliability, higher levels of comfort, less frequent stopping, guaranteed seating and air conditioning. The objectives of this paper are to investigate the preferences of public transit users in general, and passenger van users in particular, towards several service quality attributes, and to exploit such insights in the planning of future services. The main Stated Preference (SP) surveying techniques were based on 1200 passenger van users which were drawn from three strata pertaining to different spatial locations, specifically inner-city, urban-fringe and suburban. The analysis was exploited the merger of the various SP experiments and the phenomenon of repeated observations.
The present study is a follow-up study of Wang and Hu (2005). We extend the study of the previous study by decomposing the emergency network reconstruction problem into an emergency evacuation network reconstruction and an emergency rescue network reconstruction problem. In this study, the emergency evacuation network reconstruction problems are the main focus. We formulate the emergency evacuation network reconstruction for natural disasters as a bi-level programming model. In the model, the victims’ evacuation route choice behaviors and evacuation destinations choice behaviors are both considered at the same time. This concern is the most different point from Wang and Hu (2005). Moreover, the multi-class users’ evacuation route choice behaviors are also considered in the model. Finally, the optimal network reconstruction planning, multi-class users’ emergency evacuation routes and destinations planning can be obtained.
This study aims to investigate task complexity problems in attribute-based stated choice valuation of non-monetary costs of automobile use. Two factors leading to task complexity problems were considered: (1) non-linearity in the utility function indicating uncertainty in preferences, and (2) parameterization of the scale of the stochastic error of the utility indicating decision complexity. Empirical investigations on the complexity of non-market attributes valuation were made based on a web-based stated route choice survey of work trips in Metro Manila. The results show strong suggestions that degree of complexity of the choice problem is affected by not only the number of alternatives but also by the range and the description of attributes.
This paper investigates the characteristics of motorcycle ownership and car ownership in three typical cities in Taiwan. In the paper, Poisson regression models are estimated for the cities using the household survey data. The motorcycle ownership characteristics are found significantly different among the cities. In general, there are substitution effects between car ownership and motorcycle ownership. High usage of public transportation in the city will cause motorcycle ownership reduce, when the city has better public transportation service. The income level has significant negative influence on motorcycle ownership. The motorcycle ownership will also be influenced by transportation supply level of the city. The research results illustrate a valuable experience in perspective to future development tendency of motorcycle ownership.
The development of traffic data collection is promoted by IT technology. Probe vehicles are playing an increasingly important role in the field of ITS, and showing high ability for various ITS applications in the last decade. The overwhelming superiority of probe technology relies on a good coverage and a high penetration rate of probe vehicles. Although conceivable, the expectation of ubiquitous coverage of the entire road network is still far away from actual implementation nowadays. Through the review of current studies on the probe systems in ITS projects around the world, recent advances in probe technology are explored, following by an analysis of the impending obstacles or trade-offs that were faced by the extension of probe implementation. It is recognized that a cost-efficiency probe deployment scheme is of certainty to be the impetus of probe system evolution.
This paper analyzes how the value of travel time savings (VTTSs) varies over individual’s income. First, we formulate a time allocation model and examine the variation of VTTS over income with the comparative static analysis. The results show that the variation of VTTS over income depends on whether the marginal utility is increasing or decreasing with respect to the work time. As a shape of utility function cannot be fixed a priori, we cannot know clearly the variation of VTTS over income. Then, we analyze the VTTS over income empirically with the travel data of urban rail in Tokyo. We estimate the multinomial logit model and the mixed logit model for six different income groups. The empirical analysis shows that the VTTS increases as the income increases.
This paper first theoretically analyzes the current problem of air ticket pricing in China, and investigates the consciousness of travelers on price level with Price Sensitivity Measurement. Secondly, from the perspective of air transports suppliers, optimal air ticket model is built for suppliers benefit increment; and from the perspective of travelers, rational air ticket price model is built for market scale enlargement. With the consideration of different price sensitivity of business and private consumers, this paper distinguishes them. Finally, by taking the flight from Dalian to Beijing as an example, data are collected from questionnaire analysis and optimal air ticket price point and rational price point are estimated with the models, respectively. The results of the example show that current ticket price is higher both for business consumers and for private one, which matches the theoretical analysis. And the numerical test verifies the feasibility and availability of the method.
Advanced Driver Information Systems can benefit drivers by switching routes while encountering traffic congestion to alleviate congestion. Therefore, it is important to realize the latent variables of real-time traffic information that affect drivers’ enroute switching behavior. This paper identified the latent variables that will positively or negatively affect drivers’ enroute switching behavior and explored the causal effect by applying structural equation modeling. Then binary logit model was used to confirm whether latent variables and information scenarios will affect drivers’ enroute switching behavior. Empirical findings indicate that the latent variables of perceived value, usage attitude and compliance rate toward traffic information would positively enhance freeway drivers’ enroute switching rates, but switching barrier and congestion tolerability would largely impede them in the case of Taiwan. However, providing more detailed information on alternative routes can motivate drivers’ enroute switching behavior during traffic congestion.
This paper presents a Real-time Traveler Information System (RTIS) for Hong Kong, in which a novel solution algorithm is proposed for estimating current travel times using automatic vehicle identification (AVI) and global positioning system (GPS) data. The proposed algorithm can deduce the travel times on road links either with or without real-time traffic data by integration of real-time and off-line traffic database together. The on-line travel times, in RTIS, are estimated and updated at five-minute intervals based on the real-time traffic data, the off-line travel time estimates, and the simulated and real-time updated variance-covariance relationships between road links. Observation surveys are carried out during different time periods at a selected path in Hong Kong urban area to validate the RTIS travel time estimates. The estimations of travel times on the road segments of the selected path have been conducted with and without using available real-time data. The validation results show that the performance of RTIS is satisfactory and acceptable for both cases.
Recently, while building or expanding of a large hub airport becomes controversial in economic, social and environmental facets, the idea of inter-modal substitution of short-haul air spokes by high-speed trains (HST) becomes a realistic option. This paper aims to analyze what shape of inter-modal network is efficient, and how beneficial it would be on passengers. Genetic Algorithm is applied to find the best mixture of Haneda Airport’s operation capacity allocation to domestic destinations and the spatial configuration of HST network, maximizing the consumer surplus of Japanese domestic inter-city passengers. The result of our analysis shows that HST service of 2400 km as provided in 2000 is essential for keep mobility, and that operation capacity shortage problem at Haneda is solved by additional HST service. The shape of optimal HST network becomes different according to the change of the operation capacity of Haneda.
It is widely agreed that sustainable public transport is important for developing cities. However, there is a wide variation in definition of sustainable public transport. Thus, this article has an aim to explore the sustainability of urban public transport in the city of Medan, as one of the main cities in Indonesia. Based on rigorous literature, it can be deduced the red line of the definition of sustainable urban transport. Based on the data of urban transport and its social demographic of the city of Medan, it can be concluded that the urban transport in Medan is not sustainable in many facets. In addition, the comprehensive urban transport planning to reach and to shape the public transport in Medan has been proposed.
This study proposes an extension of the theory of planned behavior (TPB) to investigate whether psychological factors can potentially be predictors for the behavioral intention of private car use in future work trips. The study sample comprised 156 undergraduate students who were in their senior year and were expected to graduate in the next few months. A questionnaire survey was conducted to measure several psychological variables related to private car use for future work trips after graduation. Core constructs included subjective norm, attitude, and perceived behavioral control, with an addition of moral obligation. Based on structural equation modeling, we found subjective norm, attitude and moral obligation to be significant determinants for the behavioral intention. Contrary to the TPB, the perceived behavioral control was not found to be a statistically significant factor influencing the intention of private car use in future work trips. Practical implementations of the results are discussed.
In Asian and African developing cities, decisions on transportation projects are made with capital cost constraints and administrative influences, thus, providing a well-designed public transport is not a simple task. Therefore, multi-criteria decision-making methods that can incorporate the conflicting considerations are essential. This case study introduced the application of ANP for public transportation development programs. Even though ANP is the generalization of AHP, the results of the two models were compared to see the effects of the feedback, outer and inner dependences of the elements. According to the result, ANP model give a relative importance for environmental and socio-economic benefits as a criteria of public transport development, however, the AHP model turned out to give importance for the capital cost and capacity. Providing Bus Rapid Transit and Light Rail are the chosen alternatives in the case of ANP, where as AHP model choose expanding the existing bus services.
Consider a city of an arbitrary shape where difference classes of users are distributed continuously over the city region. Within this region, the road network is dense and can be represented as a continuum and users patronize a two-dimensional continuum transportation system to the central business district. In this paper, two different congestion-pricing models for this continuum transportation system with multiple user classes are studied. The first model is concerned about the social welfare maximization, which determines the optimal toll rates that maximize the total benefit of the whole system, and the second model is cordon-based congestion-pricing, which offers a sub-optimal but more practical tolling strategy. Both of these models are solved by the finite element method and a promising Newtonian-based solution algorithm. Finally, a numerical example is adopted for giving an idea on the impact of cordon toll charges on the resultant social welfare.
Congestion pricing is one of the most popular strategies to tackle the congestion problem in recent TDM practices. Because of its special inherent performance to combat the congestion problem at specific time and period, transport professionals are become interested to introduce to their cities. For the fact that, study on the characteristics of congestion pricing is ever more demanding and playing an important role in entire process. Taking this into consideration, this paper analyzes and explores the characteristics of time based, distance based and area wide congestion pricing schemes by tiss-NET microscopic simulator. The hypothesis based algorithms were developed to conduct the simulation, and the function value of time from the developed algorithms has been estimated from route choice behavior model. State preference data has achieved to estimate the value of time for motorists. The simulation results show the effectiveness, impacts, and their characteristics on the congested imaginary road network.
In developing countries, poor geographical accessibility due to poor quality of roads and ineffective public facility locations has made a negative impact on rural residents’ welfare. The lack of proper planning of these public infrastructures is also a major problem. The objective of this study is to investigate an integrated model to design an optimal rural road network considering financial and spatial constraints. The rural road network and new multi public facility locations are to be optimally designed simultaneously to achieve least total cost spent by government and residents. Having defined a specific objective and a set of constraints, an optimal rural road network configuration is determined endogenously by searching for an optimal combination value of the decision variables. The model is going to provide the decision makers with useful information of the rural infrastructure investment to explore the validity and effectiveness of capital allocation through the sensitivity analyses.
Public involvement (PI) has recently been introduced into the road planning process at the concept stage in Japan. However, there is a lack of agreed-upon evaluation methods for individual processes. It is very difficult for citizens to distinguish between planning process evaluation and planning decision evaluation. This study developed a method for citizens’ evaluation withdrawing items assessing procedure from other outcome items for road planning. A body of questions for citizens’ evaluation was constructed and a residential questionnaire survey was conducted in Yokohama North-West Corridor (YNWC), of which the public was involved in the development of the “rough plan”. The feasibility of citizens’ evaluation for planning process was discussed while examining the question items; the effects of respondent’s attributes on perception were analyzed; the determinants of citizens’ impression on government and citizens’ attitude to participatory planning process were studied by performing regression analysis.
This article provides a description of the influences of motorization trends on the urban residents’ travel patterns in the Jakarta Metropolitan Area (JMA) in the last decade. The performance of the first year of the Bus Rapid Transit (BRT) system implementation, as a way to suppress the motorization in JMA, is also described. A comprehensive discussion of the existing problems, lessons learned and the possible future implications that can be applied in Indonesia and also in other developing countries are presented.
This paper investigates the vertical relationship between infrastructure provision and railway operations and evaluates the effects of privatization and deregulation on the firm-specific efficiency and total factor productivity (TFP) growth in the Korean and Japanese railways. Using a stochastic frontier approach and a generalized translog functional form, the paper specifies the equation system consisting of a multiproduct variable cost function and input share equations which is estimated with the Zellner’s iterative seemingly unrelated regression and the corrected least squares method. The empirical results indicate that there are cost complementarities between infrastructure provision and overall railway operations and cost anticomplementarities between incumbent passenger and freight outputs in the Korean railways, and between Shinkansen and incumbent passenger outputs in the Japanese railways. They also indicate that the firm-specific efficiencies and TFP growth rates of the privately-owned JRs are higher than those of the government-owned KNR and JNR.
This paper proposes a multi-class probit-based stochastic user equilibrium model for assessing the effects of multi-modal traveler information systems (MTIS) on a multi-modal transport network. It can be formulated as a fixed-point problem and solved by a simulation-based heuristic solution algorithm. It is assumed in this paper that the travelers equipped and unequipped with MTIS would make their travel choices following a probit-based stochastic manner when considering alternative paths or modes according to their perceived utilities. The proposed model and solution algorithm can be used to evaluate explicitly the impacts of MTIS services. Numerical results show that the introduction of MTIS would improve the network performance and promote the utilization of public transit under certain market penetration and congestion levels.
Sapporo, a major city in northern Japan, has an annual snowfall of over 5 metres and snow removal is a major civic concern. In this study, we analysed and compared various examples of road pricing projects around the world to ascertain their various characteristics. From these findings, we then imposed a hypothetical road pricing system in Sapporo, on the basis of providing revenue to help cover the city’s winter road maintenance costs. We designed two different winter-time road pricing systems; a bounded cordon toll and a mileage charge. To get an indication of the acceptability of road pricing for the citizens, a survey was conducted. Findings indicate that residents would be willing to pay a minimal amount in support of road pricing and the bounded cordon toll as the preferable design. Residents residing within and around the cordon were also found to be more sensitive to road pricing changes
This paper develops a single-level optimization model to determine time-dependent optimal tolls while considering the dynamic relationships between land use, transport, and environment. To illustrate the importance of incorporating land use, transport, and environment considerations in determining time-dependent tolls, and the effect of tightening vehicular emission standards on link tolls, numerical studies are set up. The results show that the tighter the vehicular emission standards, the higher the toll charges are required, and that the vehicular emission standards have direct impacts on the overall vehicular emissions, the operational strategies and profit of public transit, the mode and route choices of travelers, the residential and employment distributions, the profits of land owners, and rents. The government should consider these impacts when determining the vehicular emission standard of each road.
The paper identifies the most appropriate transport infrastructure investment among three alternative transport modes — land, air, water — across five delineated regions in the Philippines. The analytical tool used is a spatial computable general equilibrium (SCGE) model with a five-region social accounting matrix (SAM) as database. An exogenous shock in the form of technological improvement in transport infrastructure is introduced for each transport mode in each region. This results to higher output elasticity with respect to transport input. The transport infrastructure with greatest impact on gross output is then isolated using a SAM-based SCGE model. The impact on relative welfare of households via equivalent variation concept and on interregional flows among production sectors via changes in spatial impedance ratio is then presented. The completion of Skyway project connecting Northern Luzon to Southern Luzon via National Capital Region is a concrete example of infrastructure project which meets aforementioned criteria.
This paper discusses the issue of Chinese transportation system’s resource allocation in the background of integrative transportation system. Firstly, the definition of “resource allocation” in this paper is given, then a brief introduction about data envelopment analysis is presented. After that, the data envelopment analysis is used to evaluate resource allocation of Chinese transportation system, different periods’ resource allocation efficiency, scale income, ideal input/output are calculated as well. In the end, some suggestions about Chinese transportation system’s resource allocation are put forward.
Existing computable general equilibrium (CGE) model in a static framework has weakness that it cannot simulate impacts on employment. As for neoclassical type dynamic CGE model, reproducibility of macro economic variables such as gross product and private capital investment is very bad. This paper proposes a dynamic CGE model considering disequilibrium accumulation process of labor and capital which can evaluate impacts of transport developments on employment and whose reproducibility is better than existing models. The model consists of a static CGE model for describing the economy in each year and macro economic functions that express changes in number of employees, private capital investment and private capital stock. As results of empirical analysis for an expressway development project in the Tokyo metropolitan area with the model and a neoclassical type model, it is found that project evaluation by existing CGE model or dynamic CGE model has possibility of underestimation.
For a government, one important subject as regards public infrastructure program is how to effectively allocate budget, especially when it is in financial difficulty, in order to put the budget to the best use and maximize the function of the budget. Otherwise, it may generate the problem that some units are faced with excessive budget and hurry to absorb the budget while other units are left in the dilemma of insufficient budget. Therefore, the question of how to allocate budget according to the priority, constitutes an important subject for government. In the budget allocation of transportation construction projects, the first issue is to determine the priority. In this paper, the authors used the Fuzzy Multi-Criteria Grade Classification Model to deal with the grade of prioritized execution of transportation construction projects. In this way, the budget will first go to prioritized projects which enjoy the right to the prioritized performance.
This paper proposes integrated data envelopment analysis (DEA) models to jointly evaluate the transport efficiency and effectiveness by measuring the efficiency scores under three aspects of technical efficiency, service effectiveness, and technical effectiveness simultaneously. The underlying reason for requiring joint evaluation is that when the transport services are produced and a portion of which are not consumed, the technical effectiveness would be less than the technical efficiency. A case study on 15 bus companies in Taipei is conducted. Results show that the number of efficient companies determined by the proposed models is fewer than that determined by conventional two-stage DEA models. It indicates a superior benchmarking power of the proposed models.
This paper studies location externality with a simple model. Firstly, the paper shows that Nash (competitive) equilibrium locations can differ from that of social optimum, and that under what conditions Nash equilibrium location is not equal to that of social optimum. Secondly, we demonstrate that, by examining the impacts of transportation cost on locations, how the Nash equilibrium location can be brought to the social optimum location by imposing the toll tax or subsidies
Multinomial and nested logit models were developed for urban transport mode choice of urban travelers during the morning home-to-work trips in Metro Manila. In the multinomial logit model, seven mode choices were available including the private car, regular taxi, light rail transit, air-conditioned bus, non-air-conditioned bus, jeepney, and fx megataxi. Two-level nested logit models were further developed which divided the available modes into private and public, and the public modes were further divided into air-conditioned and non-air-conditioned modes in the three-level nested logit models. Important deterministic variables included in the utility equations include in-vehicle time, out-of-vehicle time, individual monthly income divided by out-of-pocket cost, among others. The developed models were then used to determine the utility ranking of transport modes in Metro Manila and to test the effect of proposed urban transport-related developments in Metro Manila on mode choice probabilities of urban travelers.
Developing precise travel behavior models and testing its forecasting capability are essential when planning transportation systems. However, emphasis is observed in estimating while forecasting still needs to be better understood. This study examines the temporal transferability of a Multinomial Logit Model and a hybrid Neuro-Fuzzy Multinomial Logit model, which differ primarily by including linear and non-linear utilities. Geographic Information System is successfully used during the forecasting process. Overall, the hybrid model presents better performance, even though both models do not show satisfactory behavior when directly transferred to the application context. Small sample model results show good behavior of the hybrid model. Accordingly, a sensitivity analysis suggests this model is able to capture travelers’ sensitivity to parking cost variations, which is not well described by the classical model. Travelers’ behavior could be better explained by the hybrid model rather than by the classical Multinomial Logit structure.
LISREL and neural networks have recently become popular methodology for causal models. However, few researches have applied either of these two methods in behavioral research of passengers. To investigate the differences between LISREL and neural networks in research of passengers’ behavioral intentions, this study applied these two methods to a case of inter city bus transport in Taiwan. First, we applied LISREL to test the goodness of fit of the research model. Second, two competitive models of the NN model were tested, in which one was the full connected network and the other was the non-full connection network. The results indicated that LISREL can be a convenient and effective analysis tool if the causal relationships are known. At the same time, no matter if the causality has been derived in advance or not, NN provided a suitable prediction after the proper training procedure.
Most existing activity time allocation models assume that individuals allocate their time to different activities over a period in such a way that the marginal utilities of time across activities are equal. Their argument is that, if not equal, an individual is free to allocate more time to those activities whose marginal utilities of time are higher and, finally allocates the optimal time to each activity with equal marginal utility. However, such an ideal situation may not always prevail in reality, especially when an individual is under income constraint and/or under intense time pressure. In order to incorporate such differences in marginal utilities of time across activities, we enrich the traditional activity time allocation model by explicitly including income constraint and by adding marginal extension activity choice model. As an application, the developed integrated model is used to estimate the value of activity time during weekends in Tokyo. The results are encouraging in that they forecast the individual time allocation more accurately and estimate realistically the value of activity time for each activity in a set of different activities than do by existing traditional models.
Supply chain networks represent economic entities in tiers such as manufacturers, distributors and demand markets. To study how the market share among the commodities is determined under the assumption of profit maximization, we formulate the supply chain network equilibrium problem with logit demand functions using the variational inequality approach. A nested diagonalization method, along with the specially designed supernetwork representation, is then proposed for the solution. The test example shows that the obtained results comply with the generalized Wardrop second principle in that: the market share of the two commodities is determined according to the binary logit formula and for each origin-destination pair, the same commodity at the destination is charged with the same price no matter which transport route is used. In addition, a sensitivity analysis shows that the larger of price difference of the two commodities, the more deviation of their market share, which is consistent with our intuition.
The fast growing rate of motorcycle ownership in Malaysia has become a serious problem in safety issues and management of traffic system in urban areas throughout Malaysia. To date, approximately 5.8 million motorcycles are on the roads in Malaysia and accidents rate involving motorcycles is high, almost half of the total road fatalities recorded. However, regardless of the high accident rate involving motorcycles, motorcycle ownership in Malaysia has increased rapidly from 0.13 motorcycles per person in year 1990 to 0.26 in year 2004. In this research, issues concerning motorcycle ownership were investigated. A stated preference survey was conducted in Penang state, Malaysia to determine the trend of motorcycle ownership. An attempt to develop a disaggregate choice model based on the data collected was also conducted. Development of this model will give an indication on the future trend of motorcycle ownership in Malaysia which is important in forecasting future travel demand.
The objective is to obtain the most appropriate transport demand models which can likely represent the behavior of port-to-port sea freight movements in terms of OD matrices. The model is developed for the purpose of forecasting the Indonesian sea freight movements using the current OD pattern and the forecasted loading and unloading volumes. The paper will report on a family of aggregate models containing a flexible Gravity-Opportunity model for modeling the trip making behavior in which standard forms of the Gravity and Intervening-Opportunity model can be obtained as special cases. Non-Linear-Least-Squares and Maximum-Likelihood estimation methods were then used to calibrate the parameter of the model. The models have been tested using the total domestic sea freight movements in 2003 (Stramindo 2003 Data) for 25 major ports in Indonesia. The models were found to provide a reasonably good fit and the calibrated parameters can then be used for forecasting purposes.
The travel behavior is a result of complex decision making process affected by individual’s socioeconomic, mode and trip characteristic as well as unobserved variables. The focus of this research was to identify the unobserved factors influencing travel behavior. Six latent variables named as travel factors were identified through factor analysis. Structural equation modeling (SEM) was used to identify casual relationship between observed variables and travel factors. It was noted that SEM cannot predict the travel demand but it has ability to express relationships between unobserved and observed variables. Then, travel factors were employed in discrete choice model to consider individual preferences on unobserved variables. It was found that the model with travel factors perform superior than model without travel factors. Conclusively, the further application of these factors in its different forms can effectively measure their effect in the travel demand model.
This paper addresses a maximal transit reserve trip generation which quantitatively reflects interaction between land-use and public transit system. It firstly proposes a variational inequality and a diagonalization method for the combined transit trip distribution/logit-based stochastic user equilibrium transit assignment with elastic frequencies of transit lines. Secondly, this paper develops a generalized bilevel programming model for the maximal transit trip generation, which consists of two level problems — upper and lower level problems. The upper level problem aims to maximize the reserve transit trip for each origin subject to the transit equity constraints, which is formulated as a multi-objective maximization problem. The lower level problem is the proposed variational inequality for the combined trip distribution/logit-based stochastic user equilibrium transit assignment. A genetic algorithm embedded with the diagonalization method is designed for solving the generalized bilevel programming model. Finally, a numerical example is carried out.
Abstract: Under Intelligent Transportation Systems (ITS), real-time or daily operations of traffic management measures depend on long-term planning results, such as origin-destination (OD) trip distribution; however, results from current planning procedure are unable to provide fundamental data for dynamic analysis. In order to capture dynamic traffic characteristics, transportation planning models should play an important role to integrate basic data with real-time traffic management and control. In this research, an estimation framework for dynamic traffic assignment is proposed and field data is applied in estimation and calibration processes. In this framework, results from transportation planning projects in terms of Origin-Destination (OD) trips, are considered and extended to the dynamic models. DYNASMART, a simulation-assignment model, is applied to generate time-dependent flows. The results show high agreement between actual flows from vehicle detectors and simulated flows from DYNAMSART.
This paper proposes a bi-level programming model to determine the optimal lane configuration for contraflow operations. For the bi-level programming model, the upper level problem aims to minimize the total travel time of a study area by choosing the appropriate number of lanes of candidate links to reserve their travel directions, which is formulated as an integer programming; the lower level is a logit-based stochastic user equilibrium (SUE) traffic assignment model that is able to predict the network flow pattern with respect to the change of network topological structure made by the upper level problem. Furthermore, this paper also proposes a hybrid genetic algorithm embedded with a SUE traffic assignment method for solving the proposed bi-level programming model. The proposed model and solution algorithm are tested using the Sioux Falls network. Results show that the methodology proposed can produce promising results.
This paper examines an applicability of the traffic assignment model overcoming some drawbacks of conventional models. The developed model has the following characteristics: 1) integration of trip generation (i.e. activity choice), destination choice, mode choice and route choice; 2) expression of traveler’s choice behavior as a nested logit structure; 3) consideration of hourly traffic condition variations including queue evolution; and 4) approximate reproduction of trip chain along the time axis. The reproducibility of developed model is shown under application to the Nagoya Metropolitan Area, Japan. Furthermore, as case study, we evaluate road pricing and railway’s fare discount. These results suggest that the model allows us to compare various TDM policies effectively and evaluate in detail.
This paper studies how equilibrium is achieved in day-to-day traffic dynamics. Trip-makers update their perceived cost on a daily basis and adjust their route choice accordingly. The limiting behavior of day-to-day dynamics is characterized by the notion of equilibrium, which forms a stationary state. The attractiveness of an equilibrium state is examined by stability and can be quantified by its attraction basin. This paper illustrates how instability, as well as the problem of non-convergence from states outside the attraction basin, can be removed by modifying network configuration. This paper further investigates other attractors including cycles and chaos that are associated with the dynamic process in the pursuit of traffic equilibrium.
Route choice models are widely used for the prediction of passengers and cargo movements by planners. This paper presents the application of a methodology, introduced initially for the prediction of route choice of bicycles, now adapted to motorcycles and trucks. The adaptation of the methodology allowed the improvement of the original analysis algorithm increasing the number of considered network attributes and adding a user related attribute: Value of Time. The case study of truck routes in Tokyo Metropolitan Area produced satisfactory results relating the route choice behavior and the network attributes, especially indicating the relevant attributes to truck trips. As a result, the value of time for trucks in Tokyo and the parameters relating route choice and network attributes were obtained.
Choice models with individual decision-making mechanisms have been dominating in transportation, even though it has been long recognized that in many cases, an individual makes his/her choice together with other people. This paper establishes an additional household choice model with group decision-making mechanisms based on a multi-linear household utility function, which can theoretically and endogenously deal with intra-household interaction and members’ relative influences in joint decision-making process. The model is applied to represent households’ vehicle type choices, using a data collected in two Japanese cities in 2004. The effectiveness of the model is empirically confirmed from both model performance and applicability to analysis of household car ownership behavior.
This paper proposes a multi-class schedule-based dynamic transit assignment model to investigate the impacts of En-route Transit Information Systems (ETIS). The proposed model considers simultaneously the departure time and route choices of passengers in congested transit network with ETIS. There are two classes of passengers: those equipped and those unequipped with ETIS. These passengers would make their travel choices to follow the stochastic dynamic user optimal principles, with the equipped passengers having a lower perception variation of the travel cost due to the availability of better information. The numerical example indicates some important insights on passenger travel behaviors and the performance of the transit network with ETIS. The effects of the service cost and service quality of ETIS on the market penetration of ETIS and the total passenger travel cost are assessed under different conditions with various levels of transit passenger demand.
Travelers inevitably make multi-modal route choices — a combination of modes making a trip. It is particularly important in the analysis of inter-regional travels, including access modes, trunk modes, egress modes etc. The paper focuses on the mode choice behavior in the entire trip covering each part of the trip. This paper also aims to give contributions to the evaluation of the policies aiming to more efficient and smooth transfer between travel modes. An advanced discrete choice model called “Multi-Nested GEV (MN-GEV) Model” is formulated to capture the correlations among the elements of the inter-modal travel behaviors. The stability of MN-GEV model parameters is also examined to show the capability of the model. It is applied for the inter-regional travel survey data of Japan and the estimation results are compared with other types of discrete choice models.