Modal Split Model Research Articles

Combined Modal Split and Stochastic Assignment Model for Congested Networks with Motorized and Nonmotorized Transport Modes

A network equilibrium model is proposed for the simultaneous prediction of mode choice and route choice in congested networks with motorized and nonmotorized transport modes. In Hong Kong, motorized and nonmotorized modes are competing travel alternatives, as the average trip length is relatively short because of high-density development in urban areas. In addition, nonmotorized modes such as walking usually serve as complements to motorized trips. For example, transit passengers have to walk to gain access to and egress from transit stops. Here, the transit and walking modes are representatives of motorized and nonmotorized transport modes, respectively. The fundamental congestion effects of each mode and intermodal interactions are taken into account in the simultaneous mode and route choice problem. An equivalent variational inequality (VI) problem is formulated to capture all the components of the proposed model in an integrated framework. A solution algorithm is presented for solving the VI problem. A numerical example is used to illustrate the application of the proposed model and solution algorithm. More refined estimates of travel times and network flows can be obtained with the proposed model.

Congestion pricing and roadspace rationing: an application to the San Francisco Bay Bridge corridor

This paper presents an empirical application of a congestion–alleviation strategy that C. Daganzo [Transportation Research B 29 (1995) 139–154] proposed as a “hybrid between rationing and pricing”. This strategy is applied to the San Francisco Bay Bridge corridor, in search of a practical and Pareto-improving solution to the Bridge's congestion. The work relies on a mode-split model for work trips across four different income groups residing in 459 origin zones, and it applies an equilibrium analysis based on Bridge performance. Results indicate that modal utilities (and thus choices) are sensitive to the specific combination of toll and rationing rate, as well as to the Bridge's travel-time (or performance) function, and the length of the congested section. Though no combination of tolls plus rationing rates was found to benefit all groups of travelers studied, further investigations may improve upon these results by refining some of the assumptions made here.

Application of a Combined Network Equilibrium Model to Mega Metropolitan Area

The combined equilibrium models can overcome some problems of the conventional Four Step Models, but these models have rarely applied to a real metropolitan area. In this study, we build a Nested Logit type combined trip generation, trip disribution, modal split, and assignment model with stochastic user equilibrium in both automobile and railway networks, and apply this model to Tokyo Metropolitan Area. We formulate models for each traveler's trip purposes in trip generation, trip disribution, and modal split phase and the final results show good reproduction accuracy.

Comparison of Two Approaches for Modeling Freight Movement at Seaports

Seaports host international cargo operations and are primary generators of freight traffic in the United States. Truck/rail trip generation and modal split models provide public agencies with valuable information necessary to prioritize funds for roadway upgrade projects and port infrastructure modifications. This paper presents two approaches for developing freight trip generation models: regression analysis and backpropagation neural networks (BPN). These models are used for predicting the levels of cargo truck traffic moving inbound and outbound at seaports. Based on the Port of Miami case, it was found that the BPN model is more accurate than the regression model. However, the BPN model requires a sizable database. Using the BPN approach, the paper presents a new combined truck trip generation and truck-rail modal split model for the Port of Jacksonville. It was found that the primary factors affecting truck-rail volume are the amount and direction of cargo vessel freight, commodity type, and the particular weekday of operation. In summary, the neural network model results were found significantly accurate for both Florida ports.

An Examination about the Modal Shift to the Marine Transportation by the Modal Split Model

The examinations of the modal shift to the marine transportation were carried out by many researchers. But, the multi-mode choice in the transportation was not sufficiently analyzed.So, we build the model of the multi-mode choice based on the freight rates and the time required. In this paper, the examination results of the modal shift to the marine transportation which used the modal-split model (minimum sacrifice model) are shown. The effect of the modal shift by the decrease of the freight rates and the shortening of the time required becomes clear. The difference of the effect by the classification of the cargo is also found out.

Which Method Is Better for Developing Freight Planning Models at Seaports—Neural Networks or Multiple Regression?

Ports are the primary generators of freight traffic in the United States. Seaport operations will require operational and infrastructure changes to maintain the growth of international cargo operations. Truck and rail trip generation and modal split models will provide transportation planners and public agencies with valuable information for prioritizing funds for roadway upgrade projects and port infrastructure modifications. Two methods are presented for developing freight trip generation models—regression analysis and back-propagation neural networks. These models are applied in predicting the levels of cargo truck traffic moving inbound and outbound at seaports. For the Port of Miami, the back-propagation neural network model was more accurate than the regression analysis model. However, the neural network model requires a sizable database. A second application of the back-propagation neural networks approach developed a truck trip generation model and a truck-rail modal split model for the Port of Jacksonville. The primary factors affecting truck and rail volume were found to be the amount and direction of cargo vessel freight, commodity type (bulk, break bulk, or liquid bulk), and weekday of operation. In summary, the neural network model results were found significantly accurate for both Florida ports.

An Integrated Object-Oriented Network – and Modal Split-Model

The text deals with the developement of an integrated object-oriented network - and modal split-model. The subtasks are a multimode network model, alternative paths within traffic networks, a multi-paths-algorithm, the combination of the defined subtasks within an integrated modal-split-model and the implementation of the developed model and algorithms. The subtasks, problems and solutions are shortly described.

A Study on Service Plan for Inter-city Express Train based on the Holiday Passenger Behavior

Passenger demand on holidays is influenced by some factors, such as an economic growth and weather condition during in vacation week. In order to grasp a trend of inter-city passenger trips on holidays, the originally designed questionnaire survey is conducted to residents in Tokyo metropolitan area. Modal split models between inter-city train and automobile are calibrated using the preference data derived from the survey. This paper disasses some findings, which imply the increase of inter-city railway passenger demand on holidays.

Investigating the role of relative level‐of‐service characteristics in explaining mode split for the work trip

This paper presents an investigation into the role that relative Level‐of‐Service (LOS) characteristics of travel modes play in explaining heterogeneity of work‐trip mode split. The LOS characteristics examined in this study include cost and travel time of modes. The investigation is carried out primarily through a comparative analysis between mode split models with and without LOS measures. A total of four models are developed, three of which are binary trees constructed using a non‐parametric procedure known as Classification and Regression Trees (CART). The results show that relative LOS characteristics explain a modest portion of the mode split heterogeneity. The analysis detects correlation between LOS measures and other explanatory variables. The results also show that mode split appears to vary with relative LOS at a higher rate for trips in corridors where the transit service is superior to or comparable with the auto service than for trips in corridors better served by auto. In contrast, auto ownership appears to vary with relative LOS at a higher rate for trips in corridors better served by auto. The implications of these findings to the practice of transportation planning are presented in the paper.

A MODAL SPLIT MODEL FOR MEDIUM AND LONG DISTANCE FREIGHT TRANSPORTATION TAKING INTO ACCOUNT COMMODITY PRICE AND DISTRIBUTION LOTS

A MODAL SPLIT MODEL FOR MEDIUM AND LONG DISTANCE FREIGHT TRANSPORTATION TAKING INTO ACCOUNT COMMODITY PRICE AND DISTRIBUTION LOTS

Increasing job opportunities in a subregion for region-wide fuel conservation and air-quality improvement

Presently, there is much interest in defining urban development patterns for reducing energy consumption in transportation and in improving air quality. This research examined the effects of improving job opportunities in a subregion on region-wide transportation fuel consumption and emissions. A research framework, consisting of travel simulation models, and energy and emissions factors, was developed for testing land use – transportation scenarios. The travel simulation modelling framework consisted of the four-step approach, including the calibration of trip distribution and modal split models. Fuel consumption and emissions were estimated by using vehicle kilometres of travel. The city of Kanata within the Regional Municipality of Ottawa – Carleton, Canada, was used as a case study. Five scenarios illustrating possible future employment schemes were developed. Vehicle kilometres, fuel, and emissions for both automobile and public transit were estimated for year 2011 scenarios. The results are presented as totals for both the overall National Capital Area and for the subregion, Kanata. From these results, it is concluded that providing more job opportunities and enhancing the job to housing ratio in a satellite city could reduce fuel consumption and emissions from a regional perspective. Key words: air pollution, emissions, fuel consumption, land use, transportation modelling, simulation.

Nonresponse and Urban Travel Models

Considerable attention has been paid to the presence of nonresponse in large-scale travel surveys on the basis of which urban travel demand models are developed. It has been shown that the effect of nonresponse can be reduced by careful model building, with categorical trip generation models as an example. The same philosophy is extended to logit mode split models and exponential gravity models to show that the usual levels of nonresponse that one encounters in urban travel surveys have virtually no adverse effects on the parameter estimates of these models if the model has been specified correctly. Some simulation results are also presented to show the behavior of logit and exponential gravity model parameter estimates under conditions on nonresponse.

Nonresponse and Urban Travel Models

Considerable attention has been paid to the presence of nonresponse in large-scale travel surveys on the basis of which urban travel demand models are developed. It has been shown that the effect of nonresponse can be reduced by careful model building, with categorical trip generation models as an example. The same philosophy is extended to logit mode split models and exponential gravity models to show that the usual levels of nonresponse that one encounters in urban travel surveys have virtually no adverse effects on the parameter estimates of these models if the model has been specified correctly. Some simulation results are also presented to show the behavior of logit and exponential gravity model parameter estimates under conditions on nonresponse.

Integrating geographic information systems into transit ridership forecast models

AbstractResearchers have produced sophisticated modal split and transit demand models, including forecasts that are sensitive to the level of service. However, little effort has been made to integrate these models into corridor studies and route alignment analyses since (a) re‐routing is itself an extremely complex modeling task, and (b) the results of the demand models are presented in tabular form with no facility to visualize spatial patterns and relationships that, if recognized, would aid in the routing tasks.GIS tools can be used, together with the demand models, to identify both clusters of city blocks that house families with certain socioeconomic characteristics and potential trip destinations conducive to transit use. In other words, GIS tools can be used to better measure some of the factors that are needed by transit demand models. The results of these models can be displayed graphically, enabling analysts to target places needing improved service, evaluate route re‐alignment alternatives, and operate more efficient and effective bus lines.This paper examines how a particular class of model used by transit agencies for estimating ridership can be integrated with GIS tools in order to facilitate such analyses. It also explores the effects of visualization of routes, demographics, and employment data on the process of designing route alignments with better targeting of high transit ridership areas. This paper is part of a research project sponsored by the Region One University Transportation Center, at MIT.

Linearly-Constrained Entropy Maximization Problem with Quadratic Cost and Its Applications to Transportation Planning Problems

Many transportation problems can be formulated as a linearly-constrained convex programming problem whose objective function consists of entropy functions and other cost-related terms. In this paper, we propose an unconstrained convex programming dual approach to solving these problems. In particular, we focus on a class of linearly-constrained entropy maximization problem with quadratic cost, study its Lagrangian dual, and provide a globally convergent algorithm with a quadratic rate of convergence. The theory and algorithm can be readily applied to the trip distribution problem with quadratic cost and many other entropy-based formulations, including the conventional trip distribution problem with linear cost, the entropy-based modal split model, and the decomposed problems of the combined problem of trip distribution and assignment. The efficiency and the robustness of this approach are confirmed by our computational experience.

A Study on Formulation of a Combined Modal Split and Assignment Equilibrium Model: — with Analysis on Practical Application

Based on the analysis of asymmetry effect of bus and car, a combined modal split and assignment users equilibrium model with varied demand is proposed. The concept of generalized cost is introduced into the model. The time values are divided into four kinds in order to get the tradeoff between time and cost exactly. In the process of analyzing mass transit network, a minimum generalized cost route searching technique with considering of passenger fare is also proposed. The model is verified by applying to Nagoya City and is proved to be practicable.

Interprovincial rail/truck competition in the 1990s

As Vehicle Weight and Dimension (VWD) regulations governing the Canadian trucking industry are relaxed, the need to understand the competitive relationship between trucking and the nation's railways becomes acute. The 1990s will see the highway freight industry adapt to larger allowable vehicle weights and dimensions, strengthening its competitive position in the freight service marketplace. This paper examines rail/truck competition and the effects of VWD reform for freight of the commodity classification “Fabricated materials, inedible.” A modal split model is developed and presented, and competition between trucks and trains in the deregulated environment is analysed. This research concludes that the competitive relationship between the two principal modes is the greatest over distances less than 1500 km, and that while 95% of the types of “Fabricated materials” freight carried by truck is also carried by rail, only 75% of the railway market in the same classification is subject to truck competition. T...

Extension of Newell's dispatching policy to the case of sensitive demand

This paper has extended Newell's dispatching policy to the case of sensitive demand which is characterized by a linear mode split model with two major factors, wait time and transit fare. Three objective functions both with and without vehicle capacity constraint are analyzed, including profit maximization, maximization of a combination of net user benefit and operator profit, and maximization of net user benefit subject to a deficit constraint. Closed-form solutions associated with various system parameters are obtained. It is shown that under sensitive demand conditions the optimal dispatching rate is approximately proportional to the square root of the total demand rate, if vehicle size is not binding and it is strictly proportional to the total demand rate, if vehicle size is binding.

Determinants of modal choice in freight transport

In the next few years, exciting developments in the field of freight transport are likely to occur. The Channel Tunnel will be perceived as giving railways much greater distance of operation, compared to the current train ferry to/from Great Britain. The further development of swap-body technology will allow easier modal transfer and the creation, in 1992, of a single market in Europe will transform the pattern of trade. All of these are likely to have significant impacts on modal choice, and hence modal split, in freight transport. Reappraisal by many firms of the modes of transport used is likely but will it result in a net transfer of freight from road to rail and, if so, to what extent? To answer such questions, an accurate and reliable method of predicting modal split is required. Research in the past has concentrated on the development of modal split models based on generalised costs. These fail to explain adequately the prevalence of road freight in the UK. From surveys of freight managers within industry, it is clear that models to date rely too heavily on the economic cost factor and too little on behavioural factors (Jeffs 1985). This paper derives from a recent study of freight transport modal choice from the standpoint of the transport decision-maker within the firm. It attempts to shed light on the actual parameters which should be incorporated into a modal split model.

An entropy-based modal split model

A mathematical programming model for modal split predictions based on entropy maximization is presented. The relationship between this type of entropy-based model and the more traditional logit-type models is clarified. The entropy model presented has been used to predict travel patterns in the Stockholm region and has been based on census and survey data. A balancing procedure has been used in the solution process. It is shown how additional information, in this case traffic count information, can be included in the model. Computational results and experiences are discussed.