A tour-based model of travel mode choice

This paper presents a new tour-based mode choice model. The model is agent-based: both households and individuals are modelled within an object-oriented, microsimulation framework. The model is household-based in that inter-personal household constraints on vehicle usage are modelled, and the auto passenger mode is modelled as a joint decision between the driver and the passenger(s) to ride-share. Decisions are modelled using a random utility framework. Utility signals are used to communicate preferences among the agents and to make trade-offs among competing demands. Each person is assumed to choose the best combination of modes available to execute each tour, subject to auto availability constraints that are determined at the household level. The households allocations of resources (i.e., cars to drivers and drivers to ride-sharing passengers) are based on maximizing overall household utility, subject to current household resource levels. The model is activity-based: it is designed for integration within a household-based activity scheduling microsimulator. The model is both chain-based and trip-based. It is trip-based in that the ultimate output of the model is a chosen, feasible travel mode for each trip in the simulation. These trip modes are, however, determined through a chain-based analysis. A key organizing principle in the model is that if a car is to be used on a tour, it must be used for the entire chain, since the car must be returned home at the end of the tour. No such constraint, however, exists with respect to other modes such as walk and transit. The paper presents the full conceptual model and estimation results for an initial empirical prototype. Because of the complex nature of the model decision structure, choice probabilities are simulated from direct generation of random utilities rather than through an analytical probability expression.     

Modeling Car Ownership in Turkey Using Fuzzy Regression

Abstract

This article develops a model which can be used to determine car ownership in Turkey. Because of the lack of disaggregated data, the model is based on aggregated data. As owning a car is mainly affected by economic, social and demographic factors, the car ownership model has a multi-variable form. In order to explain the effects of these factors on car ownership in Turkey, a fuzzy multiple-regression model is used. The major reason for applying fuzzy regression is to overcome the intercorrelation problem associated with the independent variables. In this study, the urbanization rate, average family size, gross national product per capita, average car cost, gasoline price and total length of roads are selected as independent variables. The results show that, by applying a multi-variable approach to possibilistic regression, the model provides not only a crisp output but also an output range for car ownership in Turkey between 1970 and 2000.     

Gantry crane operations to transfer containers between trains: A simulation study of a Spanish terminal

Freight transfer operations are critical in combined transport networks. In this paper a simulation model and modelling approach to the transfer of cargo between trains at rail terminals is presented. The model is used to study the Port-Bou terminal, the main intermodal terminal at the Spanish-French frontier. Four different gantry crane operation modes to interchange containers between trains are evaluated. These operation rules are tested in several scenarios to examine the critical factors of the system and the best operation rule for each situation. Latest generation software is used to develop the model that incorporates modular programming and enhanced graphic systems for output representation. It allows a dynamic display of the simulated system and, likewise, the possibility of developing modules that can be reused in other studies. The research shows how simulation can be a useful planning tool in the rail transportation context.     

Planning guidelines for metro–bus interchanges by means of a pedestrian microsimulation model

The big paradigm for cities nowadays is to study the movement of pedestrians at the interface between metro and bus systems – metro–bus interchanges. When these interchanges are not well designed, walking is inefficient and can be unsafe for pedestrians. This paper analyses, by means of a pedestrian microsimulation model, metro–bus interchange spaces in order to propose planning guidelines for the city of Santiago de Chile. Specific objectives are (1) to identify the variables that provide efficiency and safety in those spaces; (2) to simulate different scenarios using the pedestrian simulation model LEGION; (3) to propose planning and design guidelines for pedestrian spaces at metro–bus interchanges; and (4) to contrast the recommendations in the recently opened terminal station on Line 1 of Metro de Santiago: Los Dominicos Station.     

Analyzing the impact of a planned transit-oriented development on mode share and traffic conditions

ABSTRACT

Transit-oriented development (TOD) is a popular planning strategy used to maximize accessibility to transit for various trip purposes. The quantitative effects of TOD on travel mode shift and traffic congestion have not been extensively tested in the current literature. This paper utilizes a seemingly unrelated regressions (SUR) mode share model and a mesoscopic dynamic traffic assignment (DTA) model to analyze the impact of a planned TOD in Maryland. The proposed model aims at improving the understanding of the quantitative impacts of such a TOD on mode share and traffic congestion. The main result of the mode share model indicates that the increase in transit ridership for a transit accessible shopping center is not that significant. Local traffic conditions will deteriorate due to a lack of investment in road infrastructure planned for the TOD area. The proposed method could be a valuable tool for other indicative land development or transportation policy analyses.     

Development of a delay model for unsignalized intersections applicable to traffic assignment

Abstract

This paper develops a model for estimating unsignalized intersection delays which can be applied to traffic assignment (TA) models. Current unsignalized intersection delay models have been developed mostly for operational purposes, and demand detailed geometric data and complicated procedures to estimate delay. These difficulties result in unsignalized intersection delays being ignored or assumed as a constant in TA models.

Video and vehicle license plate number recognition methods are used to collect traffic volume data and to measure delays during peak and off-peak traffic periods at four unsignalized intersections in the city of Tehran, Iran. Data on geometric design elements are measured through field surveys. An empirical approach is used to develop a delay model as a function of influencing factors based on 5- and 15-min time intervals. The proposed model estimates delays on each approach based on total traffic volumes, rights-of-way of the subject approach and the intersection friction factor. The effect of conflicting traffic flows is considered implicitly by using the intersection friction factor. As a result, the developed delay model guarantees the convergence of TA solution methods.

A comparison between delay models performed using different time intervals shows that the coefficients of determination, R ², increases from 43.2% to 63.1% as the time interval increases from 5- to 15-min. The US Highway Capacity Manual (HCM) delay model (which is widely used in Iran) is validated using the field data and it is found that it overestimates delay, especially in the high delay ranges.     

Analysis of Work Zone Traffic Behavior for Planning Applications

Abstract

Understanding work zone traffic behavior is important for the planning and operation of work zones. The objective of this paper is to develop a mathematical model of work zone traffic flow elements by analyzing the relationships between speed, flow, and density that can be used to estimate the capacity of work zones. Traffic flow data were collected from 22 work zone sites on South Carolina interstate highways. The scatter plots of the collected data demonstrate that the relationship between speed and density does not follow Greenshields’ linear model. A non-linear hyperbolic model was developed to describe the relationship between speed and density. Using this model the capacity of a work zone was estimated to be 1550 passenger cars per hour for 2-lane to 1-lane closures. Adjustments to this capacity value to consider other types of vehicle as well as the work zone intensity are provided. Highway agencies can use this estimated capacity along with anticipated traffic demand to schedule work zone operations to avoid long periods of over-saturation.

The tapered approach to work zone lane closures used by South Carolina is similar to methods used in work zones throughout the world. The authors believe that the methodology described in this paper for modeling work zone traffic as well as estimating work zone capacity is transferable to other countries. The conversion of actual volumes to passenger car equivalents may have to be modified due to the significant differences in traffic makeup between the United States and other countries.     

Airline scheduling: a heurisitic approach

In this paper a practical technique for finding improved airline routings and schedules is developed. A dynamic programming algorithm is combined with a heuristic method for assigning routes to the aircraft such that the expected total contribution to profit is maximum. Expected passenger demands and priorities are taken to be an input to the model. The model may be used to check the effect on the total system of adding or removing aircraft or of varying aircraft capacity. Although the test runs were made on data for a six city‐ten aircraft array a smaller, more simple numerical example is given to demonstrate the model logic.     

A comparative study of aggregate and disaggregate gravity models using Seoul metropolitan subway trip data

Abstract

Existing origin constrained and doubly constrained gravity models have not been compared, theoretically or empirically, in terms of their forecasting power. Due to the newly advanced technology of intelligent transport systems, the expanded data presently available have made various models more comparable in terms of forecasting power. This paper uses archived automatic passenger counting (APC) data for urban rail in the Seoul metropolitan area. The APC data contains information about each trip's origin, destination, ticket type, fare, and distance on a daily basis. The objective of this paper is to compare the goodness-of-fit of aggregate and disaggregate gravity modeling using these data. A Hyman aggregate gravity model is used as the aggregate model without the spatial effect. The disaggregate model adopts a multinomial logit as the destination choice model with the spatial effect. In general, while the formulation of aggregate and disaggregate gravity model models are similar, the calibration and parameter estimation methods of the two models are different. As a result, this empirical study demonstrates that the variation in goodness-of-fit and forecasting power largely depends on the estimation method and selected variables. The forecasting power of the disaggregate modeling approach outperforms that of the aggregate model. This paper further confirms that spatial arrangement plays important roles in gravity modeling.     

A stochastic optimization approach for the selection of reflective cracking mitigation techniques

PurposeIn Hot Mix Asphalt (HMA) overlays, the existing cracks in the underlying pavements can propagate upward to the new added overlay and may cause Reflective Cracks (RC). These cracks allow water infiltration to the underlying layers and causes further moisture damage as well as weakening the unbound layers. Over the years, several methods have been developed for mitigating the RCs. This study aims to investigate the current reflective cracking mitigation methods and develop a methodology for the selection of appropriate mitigation technique. The developed model is then applied to a case study in the state of Florida.MethodTo accomplish this goal, a nationwide literature review was conducted to better understand the current in practice methods in the United States. Moreover, a life cycle cost analysis (LCCA) in five different road types was performed to find the annuity of roadway rehabilitation for each of the mitigation methods. The uncertainty in the LCCA results is represented using Exploratory Modeling and Analysis (EMA) method. Then through a Multi Criteria Decision Making (MCDM) model, a stochastic optimization model was developed to find the appropriate reflective cracking mitigation solution under Florida’s climate and road conditions, based on different cost and performance weights.ResultsBased on the available data for the state of Florida, the LCCA results indicate that the annuity of maintaining the roadway with Fabrics and ISAC are lower compared to other methods. However, the results of stochastic optimization model reveal that while looking at the performance and cost at the same time, different methods would be more feasible. For instance, while the cost of the used method does not matter at all and only performance matters, STRATA® is more probable to be the appropriate mitigation technique. The findings of this research are critical for decision makers to better understand the most cost-effective mitigation technique in different conditions.     

Optimum Capacity for Intermodal Container Terminals

Abstract

Achievement of a desirable level of customer service at intermodal terminals mainly depends on the efficient loading and unloading of trains without delays. The efficiency of the transfer between the modes in the terminal area can have a significant effect on these delays. In this article, an analytically based simulation model is developed to investigate delays of trains for different service configurations. Simulation outputs are used to find an optimum balance of the cost of train delays and variation from the desired level of service. Data from the Acacia Ridge Terminal in Brisbane, Australia are used to validate and test the model.     

Some features of non-linear travel time models for dynamic traffic assignment

Abstract

This paper investigates some features of non-linear travel time models for dynamic traffic assignment (DTA) that adopt traffic on the link as the sole determinant for the calculation of travel time and have explicit relationships between travel time and traffic on the link. Analytical proofs and numerical examples are provided to show first-in-first-out (FIFO) violation and the behaviour of decreasing outflow with increasing traffic in non-linear travel time models. It is analytically shown that any non-linear travel time model could violate FIFO in some circumstances, especially when inflow drops sharply, and some convex non-linear travel time models could show behaviour with outflow decreasing as traffic increases. It is also shown that the linear travel time model does not show these behaviours. A non-linear travel time model in general form was used for analytical proofs and several existing non-linear travel time models were adopted for numerical examples. Considering the features addressed in this study, non-linear travel time models seem to have limitations for use in DTA in practical terms and care should be taken when they are used for modelling time-varying transportation networks.     

The Measurement of Efficiency of UK Airports,Using a Stochastic Latent Class Frontier Model

Abstract

In this paper, the latent stochastic frontier model is used to estimate the technical efficiency of UK airports. These airports are ranked according to their technical efficiency for the period 2000–06 and the airports are disentangled and segmented by the cost frontier model, which leads us to advise the implementation of policies by segments. Economic implications arising from the study are also considered.     

Modelling car trip generations for UK residential developments using data from TRICS

Abstract

This paper models trip generation for a cross-section of residential developments around the UK. Consistent with recent literature, the empirical model tests whether trip making patterns for residential developments are independent of car ownership and finds that trip generation is dependent upon car ownership socio-economic factors and site-specific characteristics, in particular land-zone type (e.g. town centre, out of town, etc.). However, public transport services are not found to have a significant relationship with trip generation; consequently, a policy implication of the results is that increasing bus services to residential developments is not associated with a reduction in generated trips.     

Shifting from car to active transport: A systematic review of the effectiveness of interventions

IntroductionA promising way to stimulate physical activity is to promote the choice for active modes of transport (walking and cycling). Over the past years, several interventions and policies have been implemented to stimulate this mode shift. However, information concerning the effectiveness of these interventions and policies is still limited. The aim of the present study was to systematically review the effectiveness of interventions designed to stimulate a shift from car use to cycling or walking and to obtain insight into the intervention tools that have been used to promote and/or implement these interventions.MethodsFive databases were searched and articles published in English, Dutch, German, Danish, Norwegian and Swedish were included. Only studies that focussed on a mode shift from car use towards active transport in a general adult population, which were published in peer reviewed journals and which investigated effectiveness were included. Intervention tools used were categorized by using the model of Hoogerwerf & Herweijer, as either legal, economic (subsidy, reward system, penalty), communicative (written materials, behavioural tools) and physical tools (providing bicycles, providing better bicycle facilities at work, adjustment of the environment).ResultsNineteen studies met our inclusion criteria. Studies included described work-place-based interventions, architectural and urbanistic adjustments, population-wide interventions, and bicycle-renting systems. Nearly all studies (except three) showed positive effects concerning a mode shift. Most of the included studies used more than one intervention tool and the tools used differed between types of interventions. However, information about the statistical significance of these results was often lacking and the study methodologies used were not of high quality.ConclusionNearly all studies showed results in a positive direction. However, the quality of the included studies was mostly low and intervention characteristics were poorly described.     

A data envelopment analysis model for evaluating the performance of taxi operators: a case study in Harbin,China

ABSTRACT

This paper measures the performance of taxi operators using data envelopment analysis (DEA) and the improvement of performance based on benchmarks. This includes basic DEA models and a cross efficiency model. In the present work, a sample set of 20 taxi operators are considered, and an evaluation indicator framework is constructed, which mainly involves the identification of decision-making units (DMUs) and the determination of input-output variables. The combined results of multiple DEA models are used to evaluate the performance of taxi operators in a case study of Harbin. The results highlight the significance of the combined application of multiple DEA models, especially a cross-efficiency model that can obtain more objective efficiency values. Finally, the benchmarking method is used to capture the achievements of best-performing operators and provide valuable improvement recommendations for inefficient operators. Conclusions provide a suitable basis for the operation and management of the taxi market.     

The Vehicle Routing Problem: The Case of the Hong Kong Postal Service

Abstract

With the growth in population and development of business activities in Hong Kong, the range and level of services provided by Hongkong Post have multiplied. However, the schedule of its postal vehicles, including mail collection and delivery, is still constructed manually on a daily basis, based on the experience of staff and transportation reviews. In this paper, the problem of scheduling a set of n collection points (District Post Offices) from a depot (General Post Office) in Hong Kong Island is addressed. The objectives pursued are the maximization of resource utilization and minimization of operation costs. In other words, the variable cost is expected to be reduced. To achieve these goals, an integer linear programming (IP) model of the vehicle routing problem (VRP) is developed in an effort to obtain optimal solutions. As the model involves computational complexity, a commercial software package CPLEX is used to solve the problems efficiently. The results show that the proposed model can produce optimal vehicle routes and schedules.     

Estimating the long-term effects of different passenger car technologies on energy/fuel consumption and emissions of greenhouse gases in Europe

Abstract

A stated preference (SP) experiment of car ownership was conducted in Mumbai Metropolitan Region (MMR) of Maharashtra in India. A full factorial experiment was designed to considering various attributes such as travel time, travel cost, projected household income, car loan payment and servicing cost. Data on 357 individuals were collected which resulted in 3213 observations for the calibration of the work trip and recreational trip car ownership models. The car ownership alternatives considered 0, 1 and 2 cars. A multinomial logit framework was used to develop the car ownership model taking the household as a decision unit. The specification and results of the SP car ownership model are discussed. The observed and predicted values matched reasonably when the validity of the SP car ownership model was tested against revealed preference (RP) data. The car ownership models developed in this study exhibit a satisfactory goodness of fit. It is concluded that the SP modelling approach can be successfully used for modelling car ownership decisions of households in developing countries.     

Integrating a traffic router and microsimulator into a land use and travel demand model

Abstract

This paper describes one of the first known attempts at integrating a dynamic and disaggregated land-use model with a traffic microsimulator and compares its predictions of land use to those from an integration of the same land-use model with a more traditional four-step travel demand model. For our study area of Chittenden County, Vermont, we used a 40-year simulation beginning in 1990. Predicted differences in residential units between models for 2030 broken down by town correlated significantly with predicted differences in accessibility. The two towns with the greatest predicted differences in land use and accessibility are also the towns that currently have the most severe traffic bottlenecks and poorest route redundancy. Our results suggest that this particular integration of a microsimulator with a disaggregated land-use model is technically feasible, but that in the context of an isolated, small metropolitan area, the differences in predicted land use are small.     

Evacuation Modelling in the United States: Does the Demand Model Choice Matter?

Abstract

This paper reviews the literature on the evacuation demand problem, with an emphasis on the impact of various modelling approaches on network‐wide evacuation performance measures. First, a number of important factors that affect evacuee behaviour are summarized. Evacuation software packages and tools are also investigated in terms of the demand generation model they use. The most widely used models are then selected for performing sensitivity analysis. Next, a cell‐transmission‐based system optimal dynamic traffic assignment (SO‐DTA) model is employed to assess the effects of the demand model choice on the clearance time and average travel time. It is concluded that evacuation demand models should be selected with care, and policy makers should make sure the selected demand curve can replicate real‐life conditions with relatively high fidelity for the study region to be able to develop reliable and realistic evacuation plans.