References of "Bellemans, Tom"
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See detailUncertainty in forecasts of complex rule-based systems of travel demand: Comparative analysis of the Albatross/Feathers model system
Rasouli, Soora; Cools, Mario ULg; Kochan, Bruno et al

in Proceedings of the 13th International Conference on Travel Behaviour Research (2012)

This paper documents the results of a comparative analysis of model uncertainty of the Albatross/Feathers model system for respectively the Rotterdam region, The Netherlands and Antwerp region, Belgium ... [more ▼]

This paper documents the results of a comparative analysis of model uncertainty of the Albatross/Feathers model system for respectively the Rotterdam region, The Netherlands and Antwerp region, Belgium. The assessment concerned the calculation of the coefficient of variation for the daily distance travelled per person. The calculations are performed both at the aggregated level and the disaggregated level (e.g. disaggregation by certain socio-demographics). Results indicate that model uncertainty differs by socio-demographic groups. Results of a regression analysis also indicate that in both regions uncertainty in daily distance travelled per person is strongly correlated with the inverse square root of the relevant socio-demographic population and the complexity of the classification, measured in terms of the number of possible classes. [less ▲]

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See detailQuantifying Input Uncertainty in Traffic Assignment Models
Perrakis, Konstantinos; Cools, Mario ULg; Karlis, Dimitris et al

in Proceedings of the 91st Annual Meeting of the Transportation Research Board (DVD-ROM) (2012)

Traffic assignment methods distribute Origin-Destination (OD) flows throughout the links of a given network according to procedures related to specific deterministic or stochastic modeling assumptions. In ... [more ▼]

Traffic assignment methods distribute Origin-Destination (OD) flows throughout the links of a given network according to procedures related to specific deterministic or stochastic modeling assumptions. In this paper, we propose a methodology that enhances the information provided from traffic assignment models, in terms of delivering stochastic estimates for traffic flows on links. Stochastic variability is associated to the initial uncertainty related to the OD matrix used as input into a given assignment method, and therefore the proposed methodology is not constrained by the choice of the assignment model. The methodology is based on Bayesian estimation methods which provide a suitable working framework for generating multiple OD matrices from the corresponding predictive distribution of a given statistical model. Predictive inference for link flows is then straightforward to implement, either by assigning summarized OD information or by performing multiple assignments. Interesting applications arise in a natural way from the proposed methodology, as is the identification and evaluation of critical links by means of probability estimates. A real-world application is presented for the road network of the northern, Dutch-speaking region of Flanders in Belgium, under the assumption of a deterministic user equilibrium model. [less ▲]

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See detailA Data Imputation Method with Support Vector Machines for Activity-Based Transportation Models
Yang, Banghua; Janssens, Davy; Ruan, Da et al

in Wang, Y.; Li, T. (Eds.) Foundations of Intelligent Systems: Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China, Dec 2011 (ISKE 2011) (2011)

In this paper, a data imputation method with a Support Vector Machine (SVM) is proposed to solve the issue of missing data in activity-based diaries. Here two SVM models are established to predict the ... [more ▼]

In this paper, a data imputation method with a Support Vector Machine (SVM) is proposed to solve the issue of missing data in activity-based diaries. Here two SVM models are established to predict the missing elements of ‘number of cars’ and ‘driver license’. The inputs of the former SVM model include five variables (Household composition, household income, Age oldest household member, Children age class and Number of household members). The inputs of the latter SVM model include three variables (personal age, work status and gender). The SVM models to predict the ‘number of cars’ and ‘driver license’ can achieve accuracies of 69% and 83% respectively. The initial experimental results show that missing elements of observed activity diaries can be accurately inferred by relating different pieces of information. Therefore, the proposed SVM data imputation method serves as an effective data imputation method in the case of missing information. [less ▲]

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See detailAn estimation of total vehicle travel reduction in the case of telecommuting. Detailed analyses using an activity-based modeling approach.
Kochan, Bruno; Bellemans, Tom; Cools, Mario ULg et al

in Proceedings of the 39th European Transport Conference (2011)

Transportation Demand Management (TDM) is often referred to as a strategy adopted by transport planners with the goal to increase transport system efficiency. One of the potential measures that can be ... [more ▼]

Transportation Demand Management (TDM) is often referred to as a strategy adopted by transport planners with the goal to increase transport system efficiency. One of the potential measures that can be adopted in TDM is the implementation of telecommuting. A significant number of studies have been conducted in the past to evaluate the effect of telecommuting on the amount of peak-period trips. However it is less studied whether telecommuting also effectively and significantly reduces total vehicle travel in terms of kilometers traveled throughout the day. For this reason, a conventional modeling approach was adopted in this paper to calculate total kilometers of travel saved in the case telecommuting would materialize in the Flanders area. In a second part, this paper introduces the use of an activity-based modeling approach to evaluate the effect of telecommuting on a more detailed time scale. As the second approach provides a more disaggregate result, both models can be compared on the more aggregate level to validate whether they correspond. [less ▲]

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See detailAn estimation of total vehicle travel reduction in the case of telecommuting. Detailed analysis using an activity-based modeling approach
Kochan, Bruno; Bellemans, Tom; Cools, Mario ULg et al

in Cornelis, Eric (Ed.) Proceedings of the BIVEC-GIBET Transport Research Day 2011 (2011)

ransportation Demand Management (TDM) is often referred to as a strategy adopted by transport planners with the goal to increase transport system efficiency. One of the possible measures that can be ... [more ▼]

ransportation Demand Management (TDM) is often referred to as a strategy adopted by transport planners with the goal to increase transport system efficiency. One of the possible measures that can be adopted in TDM is the implementation of telecommuting. A significant number of studies have been conducted in the past to evaluate the effect of telecommuting on peak-period trips. However it is less studied whether telecommuting also effectively and significantly reduces total vehicle travel. For this reason, a conventional modeling approach was adopted in this paper to calculate total kilometers of travel saved in the case telecommuting would materialize in the Flanders area. In a second part, the paper also introduces the use of an activity-based modeling approach to evaluate the effect of telecommuting. By doing so, an operational activity-based framework is externally validated by means of another completely different model, both calibrated for the same application and study area. [less ▲]

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See detailAssessment of the Effect of Micro-Simulation Error on Key Travel Indices: Evidence from the Activity-Based Model FEATHERS
Cools, Mario ULg; Kochan, Bruno; Bellemans, Tom et al

in Proceedings of the 90th Annual Meeting of the Transportation Research Board (DVD-ROM) (2011)

Current transportation models often do not explicitly address the degree of uncertainty in travel forecasts. Of particular interest in activity-based travel demand models is the model uncertainty that is ... [more ▼]

Current transportation models often do not explicitly address the degree of uncertainty in travel forecasts. Of particular interest in activity-based travel demand models is the model uncertainty that is caused by the statistical distributions of random components, i.e. micro-simulation error. Therefore, the main objective of this paper is to assess the impact of micro-simulation error on two key travel indices, namely the average daily number of trips per person and the average daily distance traveled per person. The effect of micro-simulation error will be investigated by running the activity-based modeling framework FEATHERS 200 times using the same 10% fraction of the population. Results show that micro-simulation errors are limited especially when disaggregation is limited to two levels. Notwithstanding, results indicate that for more elaborate analyses a 10% fraction might not be sufficient. The size of micro-simulation error increases along with complexity. Moreover, more commonly used transport modes such as using the car as driver have a lower error rate. Further research should investigate the impact of the population fraction on the micro-simulation error rates. Besides, one could also investigate other aspects (e.g. the number of activities) involved in the activity-scheduling process. [less ▲]

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See detailAn integrated micro-simulation modeling framework to measure and predict emissions and dynamic exposure
Janssens, Davy; Cools, Mario ULg; Vanhoof, Koen et al

Conference (2010)

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See detailThe presentation of an integrated microsimulation modeling framework to measure and predict emissions and dynamic exposure
Janssens, Davy; Beckx, C.; Cools, Mario ULg et al

in Proceedings of the Next Generation Data Summit 2009 (2009)

In this paper, an integrated modelling methodology for the assessment of population exposure to air pollution, involving all compartments of the DPSIR-concept, is illustrated by an application in The ... [more ▼]

In this paper, an integrated modelling methodology for the assessment of population exposure to air pollution, involving all compartments of the DPSIR-concept, is illustrated by an application in The Netherlands. The application demonstrates the advantages of an activity-based approach by presenting three kinds of applications: the calculation of vehicle emissions, the simulation of pollutant concentration patterns and the assessment of the population exposure to air population. Understanding exposure variations among activities and subpopulations can be very useful for scientific and policy purposes: it can provide information on locations or population groups most at risk, or can indicate where and when the largest exposure values occur. [less ▲]

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See detailSurveying activity-travel behavior in Flanders: Assessing the impact of the survey design
Cools, Mario ULg; Moons, Elke; Bellemans, Tom et al

in Macharis, C.; Turcksin, L. (Eds.) Proceedings of the BIVEC-GIBET Transport Research Day 2009, Part II (2009)

Ever since car ownership and car use started to increase in Western Europe and the USA, transportation planners attempted to model people’s travel behavior. In the context of the Feathers project a ... [more ▼]

Ever since car ownership and car use started to increase in Western Europe and the USA, transportation planners attempted to model people’s travel behavior. In the context of the Feathers project a dynamic activity-based travel demand framework is developed for Flanders. In this paper, the complete survey design of the data collection effort required for such dynamic activity-based model is discussed. A mixed survey design of using a PDA application on the one hand, and using traditional paper and pencil diaries on the other hand, turns out to be a very suitable way of collecting detailed information about planned and executed activity-travel behavior of households. The results show that no attrition effects are present, not on the number of out-of-home activities reported, nor on the number of trips reported. Moreover the survey mode (PDA versus paper and pencil) has no direct impact on the quantities investigated. Notwithstanding, it is essential for further analysis on the Feathers data to explicitly take into account mode effects because of two reasons. First, the effect of explanatory variables can be influenced by the survey mode. Second, the variance in the estimation of the quantity investigated can differ significantly. Heteroscedatisc linear regression models provide the required framework to explicitly take into account these mode effects. [less ▲]

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