Comparison of updating techniques in transferability analysis of work trip mode choice models in developing countries

This study analyzes the performances of updating techniques in transferability of mode choice models in developing countries. A model specification, estimated in Ho Chi Minh City, was transferred to Phnom Penh. Naïve transfer and four updating methods associated with small sized samples were used in the transfer process and were evaluated based on statistical perspective and predictive ability. The study also illustrates the problems faced in model transferability development, due to the lack of available and suitable data in Phnom Penh. This lack is strongly related to different methods and structures applied in collecting the data. Simplified approaches to the difficulties are proposed in the study. The results show that updating ASCs, updating both ASCs and scale parameter, and use of combined transfer estimators all produce significant improvement, both statistically and in predictability, in updating the model. The last two methods have proven to be superior to the first method, owing to the inclusion of transfer bias considerations in the estimations. However, small data samples should not have large transfer bias when using combined transfer estimators. It is also concluded that naïvely transferring a model is not recommended, and Bayesian updating should be avoided when transfer bias exists. Copyright © 2010 John Wiley & Sons, Ltd.     

Using the Bayesian updating approach to improve the spatial and temporal transferability of real-time crash risk prediction models

This study aimed to improve the spatial and temporal transferability of the real-time crash risk prediction models by using the Bayesian updating approach. Data from California’s I-880N freeway in 2002 and 2009 and the I-5N freeway in 2009 were used. The crash risk models for these three datasets are quite different from each other. The model parameters do not remain stable over time or space. The transferability evaluation results show that the crash risk models cannot be directly transferred across time and space. The updating results indicate that the Bayesian updating approach is effective in improving both spatial and temporal transferability even when new data are limited. The predictive performance of the updated model increases with an increase in the sample size of the new data. In addition, when limited new data are available, updating an existing model is better than developing a model using the limited new data.     

Evaluation of transfer methods for spatial travel demand models

The main goal of the research was to compare alternative methods of spatial transfer as a function of sample size. The study was based on the mobility surveys conducted in the Helsinki Metropolitan Area in 1995 and in the Turku region in 1997. The Helsinki Metropolitan Area data base was used to estimate the models that were to be transferred. The data base in the Turku region represents the application context to which the estimated Helsinki Metropolitan Area models are transferred. The transfer procedures examined were Bayesian updating, combined transfer estimation, transfer scaling, and joint context estimation procedures. To explore the impact of sample size on transferring performance, model transferability was tested using six different sample sizes. The model transferability was examined by comparing the transferred models to the models estimated using the entire set of the data which can be regarded as the best estimate representing “the real situation”. The results indicated that joint context estimation gives the best prediction performance in almost all cases. In particular, the method is useful if the difference in the true parameters between the two contexts is large or only some of the model coefficients are precise. The applicability of joint context estimation can be improved by viewing the coefficients as variable-oriented and emphasizing precise and imprecise coefficients differently.     

Temporal transferability of updated alternative-specific constants in disaggregate mode choice models

Methods of updating disaggregate discrete choice models have been proposed as a means of obtaining better transferability. However, the temporal transferability of models updated for better spatial transferability has rarely been analysed, and the factors affecting temporal transferability have not been determined. This paper deals with one updating method—the use of disaggregate data to update alternative-specific constants—and investigates the factors affecting the temporal transferability of the updated constants. In the analysis, repeated cross-section data collected in the Chukyo metropolitan area are divided, efficiently generating many application areas. The analysis showed that the factors can depend on regional characteristics and past travel behaviours (inertia), and are anti-symmetric and path-dependent of changes in the level of service.     

A study of motorcyclist's idling stop behavior at red lights

Abstract

Motorcycle activity in Asian economies is a significant contributor to carbon dioxide (CO₂) emissions, both when moving and when idling at traffic lights. This paper investigates Taiwanese motorcyclists’ behavior of turning off the idling engine while stopping at traffic lights based on the theory of planned behavior (TPB), which recognizes that the achievement of voluntary change behavior can be identified by knowing an individual's attitudes (or behavioral intentions [BIs]) in the context of social norms (SN). A structural equation model system is used to identify candidate causal links between attitudes, SN, BI and behavior related to the idling stop behavior of motorcyclists. A partial least squares (PLS) model is built to correct the covariance matrix, given the relatively small sample size. Results suggest that attitudes, SN and perceived behavioral control, are significant determinants of idling stop BI at red lights.     

Measuring and enhancing the transferability of hidden Markov models for dynamic travel behavioral analysis

As an emerging dynamic modeling method that incorporates time-dependent heterogeneity, hidden Markov models (HMM) are receiving increased research attention with regards to travel behavior modeling and travel demand forecasting. This paper focuses on the model transferability of HMM. Based on a series of transferability and goodness-of-fit measures, it finds that HMMs have a superior performance in predicting future transportation mode choice, compared to conventional choice models. Aimed at further enhancing its transferability, this paper proposes a Bayesian conditional recalibration approach that maps the model prediction directly to the context data. Compared to traditional model transferring methods, the proposed approach does not assume fixed parameterization and recalibrates the utilities and the prediction directly. A comparison between the proposed approach and the traditional transfer-scaling favors our approach, with higher goodness-of-fit. This paper fills the gap in understanding the transferability of HMM and proposes a practical method that enables potential applications of HMM.

     

Assessment of spatial transferability of an activity-based model,TASHA

Spatial transferability has been recognized as a useful validation test for travel demand models. To date, however, transferability of activity-based models has not been frequently assessed. This paper assesses the spatial transferability of an activity-based model, TASHA (Travel Activity Scheduler for Household Agents), which has been developed for the Greater Toronto Area (GTA), Canada. TASHA has been transferred to the context of the Island of Montreal, Canada using the 2003 Origin–Destination (O–D) travel survey and the 2001 Canadian Census. It generates daily schedules of activities (individual and joint) for each individual in this region. The modelled activity attributes (frequency, start time, duration and distance) from TASHA and observed attributes from the 2003 O–D travel survey are compared for five different activities (i.e. work, school, shopping, other, and return to home). At the aggregate level, TASHA provides quite reasonable outcomes (in some cases – better results than for the Toronto Area) for all four attributes for work, school and return to home activities with few exceptions (for instance, school start time). The model outcomes are also promising for shopping frequency and start times; however, TASHA provides larger differences for average shopping durations and distances. Only the forecasts for all four attributes for the ‘other’ activity type differ greatly with the observed attributes for the Montreal Island. These large differences most likely indicate the differences in behaviour between the Montreal Island and the Toronto Area. In general, we conclude that re-estimation of model parameters and the use of local activity attribute distributions (frequency, start time and duration) is a desirable step in the transfer of the TASHA model from one context to another.     

Relationships Between US Consumer Expenditures on Communications and Transportation Using Almost Ideal Demand System Modeling: 1984–2002

Abstract

This study analyzes aggregate consumer expenditure data from the US between 1984 and 2002, to determine relationships between expenditures on transportation and communications. We first identified 15 categories of goods – nine for transportation, five for communications, and one for all others – and obtained prices for each category across time. Then, we applied the linear approximate almost ideal demand system (AIDS) method for estimating consumer demand functions, aggregating the categories to six (non-personal vehicle (PV), PV capital, PV operation, electronic communications media, print communications media, and all others) due to the small sample size. The results indicate that transportation and communications categories have both substitution and complementarity relationships. The existence of effects in both directions (substitution and complementarity) is testimony to the complexity of the relationships involved, with both generation and replacement possible and happening simultaneously. In addition, expenditures in the transportation categories are generally more income-elastic and price-elastic than those in communications, indicating that communications expenditures are more essential than those for travel. The transportation categories have both substitution and complementarity relationships with each other, while the two communications categories have a substitution relationship.     

Cross-sector Analysis of Four Renegotiated Transport PPPs in Portugal

Abstract

This paper uses the Fertagus renegotiation results as a reference and explores the features that made it such a widely commended case, aiming to identify the best practice to be followed in other cases. The two main questions that this paper aimed to respond were: Was the success of the renegotiation process in the Fertagus contract due to mode-specific factors? Are those factors (mode specific or not) transferable to other modes under public private partnership (PPP) contracts and if so, to what extent? Regarding the mode specificity and transferability analysis, it can be noticed that much of the features were not mode specific in theory, however for the successful transferability to other transport modes, some changes should be made to the PPP model taking into account modal specificities and national contexts.     

Cycle Network Planning: Towards a Holistic Approach Using Temporal Topology

ABSTRACT

Current cycle-network planning (CNP) at the local level tends to be dominated by a subjective-pragmatic approach in which it is only possible to consider a limited number of route alignment possibilities and development-sequencing scenarios. Although this method may produce acceptable results, it may also be true that the final design could be improved – and the construction efficiency could be enhanced – by a more comprehensive review of the available options in relation to the objectives of the intervention. Such objectives may include accident reduction, modal shift in favour of cycling, health benefits or strategic expansion of a network. This article presents work undertaken to demonstrate a holistic approach to CNP, based on a logically defined spatio-temporal model and allowing some semi-automated multiobjective optimization of network designs in a GIS-based decision-support system. The model is introduced briefly before a case study applying this model to development of a cycle network in a small town in northeast England is described. The results obtained from this case study and the implications of this research for cycle network planners are discussed.     

In Search of the Link between Ship Size and Operations

Abstract

Since 1990s the liner shipping industry has faced a period of restructuring and consolidation, and been confronted with a continuing increase in container vessel scale. The impact of these changes is noticeable in trade patterns, cargo handling methods and shipping routes, in short ‘operations’. After listing factors influencing size, growth in container ship size is explained by economies of scale in deploying larger vessels. In order to quantify economies of scale, this paper uses the liner service cash flow model. A novelty in the model is the inclusion of +6000-20-foot Equivalent Unit (TEU) vessels and the distinction in costs between single and twin propeller units on ships. The results illustrate that scale economies have been – and will continue to be – the driving force behind the deployment of larger container vessels. The paper then assesses the link between ship size and operations, given current discussions about the increase in container vessel scale. It is found that (a) ship size and operations are linked; (b) optimal ship size depends on transport segment (deep-sea vs. short-sea shipping, SSS), terminal type (transhipment terminals vs. other terminals), trade lane (East-West vs. North-South trades) and technology; and (c) a ship optimal for one trade can be suboptimal for another.     

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.     

Transport Demand Management in Turkey: A Genetic Algorithm Approach

Abstract

This article proposes new models for estimating transport demand using a genetic algorithm (GA) approach. Based on population, gross national product and number of vehicles, four forms of the genetic algorithm transport planning (GATP) model are developed – one exponential and the others taking quadratic forms – and applied to Turkey. The best fit models in terms of minimum total average relative errors in the test period are selected for future estimation. Demand management strategies are proposed based on three scenarios: restricting private car use, restricting truck use and the simultaneous management of private car use and goods movement. Results show that the GATP model may be used to estimate transport demand in terms of passenger-kilometers traveled (pass-km), vehicle-kilometers traveled (veh-km) and ton-kilometers completed (ton-km). Results also show that the third scenario – simultaneous restrictions on private car use and goods movement – could reduce total veh-km by about 35% by 2025 in this study of Turkish rural roads.     

Evaluation of the Transferability of Incident Detection Algorithms Developed for Singapore Expressways

ABSTRACT

Two new detection algorithms, single-station DV (dual-variable) and dual-station CODE (COmbined Detector Evaluation) were developed earlier using 160 incidents collected along Singapore's Central Expressway (CTE). The transferability of these CTE-developed algorithms is assessed, as a case study, using 100 incidents collected from the Tullamarine Freeway and South Eastern Freeway in Melbourne, Australia. The investigation covers the differences in traffic detector systems (loop detectors versus video-based), road geometry and behaviour between drivers in Singapore and Australia. The re-calibrated application of these algorithms to freeways in Melbourne yielded a reasonably good detection performance as well as satisfying the average expected performances of seven traffic management centres surveyed in the USA. The results suggested that the detection logic of the algorithms developed for CTE possessed reasonably good transferability and are also suitable for receiving traffic inputs from video-based detectors as well as from loop detectors.     

Multidimensional choice model transferability

Transferability studies have focused on the component models of the conventional four-step urban travel forecasting model system. This study extends previous analyses by examining the transferability of models describing multidimensional travel and related choices. In particular, we examine the hypothesis that joint and sequential choice models are equally transferable against the alternative hypotheses that either of the model types is more transferable. Measures of goodness of fit and transfer effectiveness are formulated for sequential choice models to provide a consistent comparison between the joint and sequential models. An empirical analysis is undertaken in the context of joint (multinomial logit) and sequential (nested logit) models of automobile ownership and mode choice to work. This study finds little difference between the transferability of these joint and sequential models. However, this conclusion appears to be dependent on the similarity of the estimation results for the joint and sequential models in this case. These results suggest a need for additional testing in other empirical contexts to identify the relative transferability of joint versus sequential models when the estimation results are distinct.     

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.     

Towards a general microeconomic model for the operation of public transport

After Vickrey's view, Mohring constructed a microeconomic model to determine the optimal frequency of buses serving a corridor with fixed demand. The main result was that frequency should be proportional to the square root of demand. The role of users' costs was shown to be crucial. This approach has evolved over the past decades, improving our understanding of public transport operations. This paper describes and analyses the evolution of microeconomic models for the analysis of public transport services with parametric demand, leading towards a more comprehensive one. An in-depth review of all the contributions in the academic literature is presented, emphasizing both the treatment of variables and the form of the results mostly in terms of frequency and fleet size. A series of partial new elements is also identified. An extension of Jansson's model for a single period is developed analytically, including the effect of vehicle size on operating costs and the influence of crowding on the value of time. Numerical simulations are used for comparison and analysis. A general model is then proposed where bus operations are optimized accounting for a number of simultaneous relations. Finally, the different models are discussed and compared.     

Synchronized Production and Transportation Planning Using Subcontracted Vehicles in a Production-Distribution Network

Abstract

Effective management of interfaces between procurement, supply, production and distribution for higher efficiency in the supply chain is an important issue in global manufacturing, where the synchronization of production and transportation planning represents important savings in operational costs. This paper focuses on the synchronization of production planning and transportation planning in a production distribution network, where transportation is subcontracted to a professional transportation enterprise (PTE) for vehicle-hiring. Dynamic and flexible numbers of vehicles are used to cater for fast changing market demands. Thus, the number of vehicles to be hired is viewed from the planning point of view as an operational decision considered simultaneously with production and transportation planning. A mathematical model – SPTP/MTDS – for synchronized production and transportation planning under multiple times and direct shipping strategy (MTDS) is discussed, and a Lagrange relaxation decomposition-based two layer decision procedure (LRD-TLDP) is developed. By introducing artificial decision variables and Lagrange multipliers, SPTP/MTDS is decomposed into a production decision sub-problem (SPTP-PD), and a distribution decision sub-problem (SPTP-DD). A priority-based assignment heuristic and a partial chain-based genetic algorithm are developed to solve SPTP-PD and SPTP-DD, respectively. An illustration of the application of the model in an electronic appliance manufacturing enterprise in China is presented.     

Travel demand forecasts improved by using cross-sectional data from multiple time points

Forecasts of travel demand are often based on data from the most recent time point, even when cross-sectional data is available from multiple time points. This is because forecasting models with similar contexts have higher transferability, and the context of the most recent time point is believed to be the most similar to the context of a future time point. In this paper, the author proposes a method for improving the forecasting performance of disaggregate travel demand models by utilising not only the most recent dataset but also an older dataset. The author assumes that the parameters are functions of time, which means that future parameter values can be forecast. These forecast parameters are then used for travel demand forecasting. This paper describes a case study of journeys to work mode choice analysis in Nagoya, Japan, using data collected in 1971, 1981, 1991, and 2001. Behaviours in 2001 are forecast using a model with only the most recent 1991 dataset and models that combine the 1971, 1981, and 1991 datasets. The models proposed by the author using data from three time points can provide better forecasts. This paper also discusses the functional forms for expressing parameter changes and questions the temporal transferability of not only alternative-specific constants but also level-of-service and socio-economic parameters.