References of "Cools, Mario"
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See detailInvestigating the impact of river floods on travel demand based on an agent-based modeling approach: The case of Liège, Belgium
Saadi, Ismaïl ULiege; El Saeid Mustafa, Ahmed Mohamed ULiege; Teller, Jacques ULiege et al

in Transport Policy (in press)

In Belgium, river floods are among the most frequent natural disasters and they may have important consequences on travel demand. In order to better understand how the travel patterns vary, we propose to ... [more ▼]

In Belgium, river floods are among the most frequent natural disasters and they may have important consequences on travel demand. In order to better understand how the travel patterns vary, we propose to set up a large scale scenario based on MATSim for guarantying an accurate assessment of the impact of river floods on the transportation system. As inputs, the current agent-based model requires a base year population. A synthetic population with respective set of attributes is generated as a key input. Afterwards, agents are assigned activity chains through an activity-based generation process. Finally, the synthetic population and the transportation network are integrated into MATSim. Regarding data, households travel surveys, OD matrix of Belgium have been used to set up the demand. For simulating river floods effects, a steady-state inundation map has been integrated within MATSim. In the current study, five scenarios have been tested where critical links are associated various levels of service, i.e. 10%, 25%, 50%, 75% and 100% (base case scenario). They are systematically compared to the standard scenario to estimate the deviations in terms of traffic patterns and travel times. The results suggest that compared to the standard scenario, the average trip travel time increased by 16.36%, 44.44%, 126.77% and 144.44% with respect to scenarios 75%, 50%, 25% and 10% respectively. Also, the traffic flows have been re-distributed more uniformly across the transportation network. Roads with important traffic volumes are subjected to a decrease of activity on the contrary of roads with low traffic volumes. A very few studies have focused on how river floods affect transportation systems, this paper provided new insights in term of methodology and traffic patterns analysis under disruptions. [less ▲]

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See detailThe use of time series forecasting in zone order picking systems to predict order pickers’ workload
van Gils, Teun; Ramaekers, Katrien; Caris et al

in International Journal of Production Research (in press)

In order to differentiate from competitors in terms of customer service, warehouses accept late orders while providing delivery in a quick and timely way. This trend leads to a reduced time to pick an ... [more ▼]

In order to differentiate from competitors in terms of customer service, warehouses accept late orders while providing delivery in a quick and timely way. This trend leads to a reduced time to pick an order. This paper introduces workload forecasting in a warehouse context, in particular a zone picking warehouse. Improved workforce planning can contribute to an effective and efficient order picking process. Most order picking publications treat demand as known in advance. As warehouses accept late orders, the assumption of a constant given demand is questioned in this paper. The objective of this study is to present time series forecasting models that perform well in a zone picking warehouse. A real-life case study demonstrates the value of applying time series forecasting models to forecast the daily number of order lines. The forecast of order lines, along with order pickers’ productivity, can be used by warehouse supervisors to determine the daily required number of order pickers, as well as the allocation of order pickers across warehouse zones. Time series are applied on an aggregated level, as well as on a disaggregated zone level. Both bottom-up and top-down approaches are evaluated in order to find the best-performing forecasting method. [less ▲]

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See detailModelling built-up expansion and densification with multinomial logistic regression, cellular automata and genetic algorithm
El Saeid Mustafa, Ahmed Mohamed ULiege; Heppenstall, Alison; Omrani, Hichem et al

in Computers, Environment and Urban Systems (2018), 67

This paper presents a model to simulate built-up expansion and densification based on a combination of a non-ordered multinomial logistic regression (MLR) and cellular automata (CA). The probability for ... [more ▼]

This paper presents a model to simulate built-up expansion and densification based on a combination of a non-ordered multinomial logistic regression (MLR) and cellular automata (CA). The probability for built-up development is assessed based on (i) a set of built-up development causative factors and (ii) the land-use of neighboring cells. The model considers four built-up classes: non built-up, low-density, medium-density and high-density built-up. Unlike the most commonly used built-up/urban models which simulate built-up expansion, our approach considers expansion and the potential for densification within already built-up areas when their present density allows it. The model is built, calibrated, and validated for Wallonia region (Belgium) using cadastral data. Three 100 × 100 m raster-based built-up maps for 1990, 2000, and 2010 are developed to define one calibration interval (1990–2000) and one validation interval (2000 − 2010). The causative factors are calibrated using MLR whereas the CA neighboring effects are calibrated based on a multi-objective genetic algorithm. The calibrated model is applied to simulate the built-up pattern in 2010. The simulated map in 2010 is used to evaluate the model's performance against the actual 2010 map by means of fuzzy set theory. According to the findings, land-use policy, slope, and distance to roads are the most important determinants of the expansion process. The densification process is mainly driven by zoning, slope, distance to different roads and richness index. The results also show that the densification generally occurs where there are dense neighbors whereas areas with lower densities retain their densities over time. [less ▲]

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See detailUnderstanding urban development types and drivers in Wallonia. A multi-density approach
El Saeid Mustafa, Ahmed Mohamed ULiege; Saadi, Ismaïl ULiege; Cools, Mario ULiege et al

in International Journal of Business Intelligence and Data Mining (2018), 13(Nos. 1/2/3), 309330

In this study, urban development process in the Walloon region (Belgium) has been analysed. Two main aspects of development are quantitatively measured: the development type and the definition of the main ... [more ▼]

In this study, urban development process in the Walloon region (Belgium) has been analysed. Two main aspects of development are quantitatively measured: the development type and the definition of the main drivers of the urbanisation process. Unlike most existing studies that consider the urban development as a binary process, this research considers the urban development as a continuous process, characterised by different levels of urban density. Eight urban classes are defined based on the Belgian cadastral data for years 2000 and 2010. A multinomial logistic regression model is employed to examine the main driving forces of the different densities. Sixteen drivers were selected, including accessibility, geo-physical features, policies and socio-economic factors. Finally, the changes from the non-urban to one of the urban density classes are detected and classified into different development types. The results indicate that zoning status (political factor), slope, distance to roads, population densities and mean land price, respectively, have impact on the urbanisation process whatever maybe the density. The results also show that the impact of these factors highly varies from one density to another. [less ▲]

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See detailA Markov Chain Monte Carlo Cellular Automata Model to Simulate Urban Growth
El Saeid Mustafa, Ahmed Mohamed ULiege; Nishida, Gen; Saadi, Ismaïl ULiege et al

in GEOProcessing 2017 proceedings, The Ninth International Conference on Advanced Geographic Information Systems, Applications, and Services (2017, March 25)

This paper investigates the potential of a cellular automata (CA) model based on logistic regression (logit) and Markov Chain Monte Carlo (MCMC) to simulate the dynamics of urban growth. The model ... [more ▼]

This paper investigates the potential of a cellular automata (CA) model based on logistic regression (logit) and Markov Chain Monte Carlo (MCMC) to simulate the dynamics of urban growth. The model assesses urbanization likelihood based on (i) a set of urban development driving forces (calibrated based on logit) and (ii) the land-use of neighboring cells (calibrated based on MCMC). An innovative feature of this CA model is the incorporation of MCMC to automatically calibrate the CA neighborhood transition rules. The MCMC based CA model is applied to Wallonia region (Belgium) to simulate urban growth from 1990 to 2000 using Corine Land Cover data (CLC). The outcome of logit model is evaluated by the relative operating characteristic (ROC). The simulated map of 2000 is then validated against 2000 actual map based on cell-to-cell location agreement. The model outcomes are realistic and relatively accurate confirming the effectiveness of the proposed MCMC-CA approach. [less ▲]

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See detailLanduse change and future flood risk: the influence of micro-scale spatial patterns (FloodLand) - 5th progress report
Dewals, Benjamin ULiege; Bruwier, Martin ULiege; El Saeid Mustafa, Ahmed Mohamed ULiege et al

Report (2017)

The goal of the project FloodLand is to investigate the complex interactions between landuse change and future flood risk. Landuse change is assumed to be mainly driven by population growth and socio ... [more ▼]

The goal of the project FloodLand is to investigate the complex interactions between landuse change and future flood risk. Landuse change is assumed to be mainly driven by population growth and socio-economic factors. It affects future flood risk by altering catchment hydrology as well as vulnerability in the floodplains; but the feedback effect of (the perception of) changes in flood hazard on landuse evolution is also considered. The research is based on a chain of modelling tools, which represent parts of the natural and human systems, including: landuse change modelling, transportation modelling as an onset for the estimation of indirect flood damage, continuous hydrological modelling (forced by precipitation and temperature data disturbed according to climate change scenarios), as well as efficient hydraulic modelling of inundation flow in the floodplains. Besides reproducing a broad spectrum of processes, the modelling approach spans over multiple scales, from the regional or catchment level down to the floodplain and building levels. This distinctive feature is reflected both within the individual models and through their combination involving fine-scale detailed analyses (or data) embedded within coarser models at a broader level. [less ▲]

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See detailCoupling agent-based, cellular automata and logistic regression into a hybrid urban expansion model (HUEM)
El Saeid Mustafa, Ahmed Mohamed ULiege; Cools, Mario ULiege; Saadi, Ismaïl ULiege et al

in Land Use Policy (2017), 69C

Several methods for modeling urban expansion are available. Most of them are based on a statistical, a cellular automaton (CA) and/or an agent-based (AB) approach. Statistical and CA approaches are based ... [more ▼]

Several methods for modeling urban expansion are available. Most of them are based on a statistical, a cellular automaton (CA) and/or an agent-based (AB) approach. Statistical and CA approaches are based on the implicit assumption that people's behavior is not likely to change over the considered time horizon. Such assumption limits the ability to simulate long-term predictions as people's behavior changes over time. An approach to consider people's behavior is the use of an AB system, in which the decision-making process of agents needs to be parameterized. Most existing studies, which make use of empirical data to define the agents’ decision-making criteria, rely on intensive data collection efforts. The considerable data requirements limit the AB-system's ability to model a large study area, as the number of agents for which data on decision-making criteria is required, increases with the size of the study area. This paper presents a hybrid urban expansion model (HUEM) that integrates logistic regression (Logit), CA and AB approaches to simulate future urban development. A key feature of HUEM lies in its ability to address various people behaviors that are variable over time through AB relying on a sample approach that combines Logit and CA. Three agent sets are defined; developer agents, farmer agents and planning permission authority agent. The agents’ decision-making process is parameterized using CA and Logit models. The interactions of the agents are simulated through a series of rules. To assess HUEM performance, it is calibrated for Wallonia (Belgium) to simulate urban expansion between 1990 and 2000. Calibration results are then assessed by comparing the 2000 simulated map and the actual 2000 land-use map. Furthermore, the performance of HUEM is compared to a number of typical spatial urban expansion models, i.e. Logit model, CA model and CA-Logit to assess the added-value of HUEM. The comparison shows the performance of HUEM is better than other models in terms of allocation ability. [less ▲]

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See detailCan Autonomous Vehicles Reduce Car Mobility? Evidence from a Stated Adaptation Experiment in Belgium
Cools, Mario ULiege; Rongy, Caroline; Limbourg, Sabine ULiege

in Transportation Research Board Annual Meeting. Compendium of Papers (2017)

From literature, it is clear that the discussion about the potential benefits and drawbacks of autonomous vehicles is not finished. In order to provide insight into this discussion, this paper ... [more ▼]

From literature, it is clear that the discussion about the potential benefits and drawbacks of autonomous vehicles is not finished. In order to provide insight into this discussion, this paper investigates different attitudes with respect to different key factors for the deployment of system of autonomous taxis. To this end, a stated adaptation experiment was carried out in Belgium in March 2016. To investigate which factors influence the variables of interest, i.e. (i) the number of minutes one is prepared to wait before an autonomous taxi picks up the person, (ii) the ownership of a private car when autonomous taxis are available, (iii) the willigness to share an autonomous taxi, (iv) the permittance for the autonomous vehicle to take a detour when it is beneficial for the society, and (v) the willigness to share your private agenda to ensure a timely autonomous taxi, different regression models are constructed. The results show that the considered explanatory factors only capture a small part of the variability five variables of interest. This is as signal that market segmentation might be very challenging. Besides, this is an indication that a broader range of factors should be included such as life-style factors and psychological constructs. Finally, this acknowledges the need for some skepticism with regard to the potential benefits of autonomous vehicles. The results are interesting for providing realistic boundaries and cross-classification in further simulation studies that look at the benefits of autonomous vehicles. [less ▲]

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See detailA Comparison of Micro-objective Non-parametric Statistical Matching Techniques for the Integration of Different Survey Data
Eftekhar, Hamed ULiege; Cools, Mario ULiege

in Proceedings of the 96th Annual Meeting of the Transportation Research Board (2017)

Lack of information is often reported as one of the main study limitations in transport research. Other data sources provide an important opportunity, as the information from these data sources might be ... [more ▼]

Lack of information is often reported as one of the main study limitations in transport research. Other data sources provide an important opportunity, as the information from these data sources might be fully exploited when they are integrated using an appropriate mathematical framework. This paper determines which data integration techniques can be adopted in the context of road safety, and which criteria should be used to assess the quality of the integrated dataset. The paper contributes to the literature by providing a comparison of different techniques that allow the tabulation of the joint micro-data. To compare the suitability of different Statistical Matching techniques, data from the 2012 Belgium Road Safety Institute (BRSI) Attitude Survey and data from the 2010 Belgian National Household Travel Survey (BELDAM) are integrated. In particular, the socio-economic factor "Income" is being matched to the BRSI Attitude Survey data. The paper discusses and compares different non-parametric micro-objective Statistical Matching techniques, in which the “Income” variable from the BELDAM survey was added to the BRSI Attitude Survey. Based on similarity/dissimilarity measures, the Rank hot-deck Statistical Matching yielded the best result, which is in line with the existing literature. Moreover, from the results, it can be concluded that statistical data matching is a practically applicable technique, which can help overcome the lack of additional information. Further research should focus on using the integrated datasets with an attempt of expanding the scope of variables, and explicitly testing for omitted variable bias. [less ▲]

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See detailLanduse change and future flood risk: the influence of micro-scale spatial patterns (FloodLand) - 4th progress report
Dewals, Benjamin ULiege; Bruwier, Martin ULiege; El Saeid Mustafa, Ahmed Mohamed ULiege et al

Report (2016)

The goal of the project FloodLand is to investigate the complex interactions between landuse change and future flood risk. Landuse change is assumed to be mainly driven by population growth and socio ... [more ▼]

The goal of the project FloodLand is to investigate the complex interactions between landuse change and future flood risk. Landuse change is assumed to be mainly driven by population growth and socio-economic factors. It affects future flood risk by altering catchment hydrology as well as vulnerability in the floodplains; but the feedback effect of (the perception of) changes in flood hazard on landuse evolution is also considered. The research is based on a chain of modelling tools, which represent parts of the natural and human systems, including: landuse change modelling, transportation modelling as an onset for the estimation of indirect flood damage, continuous hydrological modelling (forced by precipitation and temperature data disturbed according to climate change scenarios), as well as efficient hydraulic modelling of inundation flow in the floodplains. Besides reproducing a broad spectrum of processes, the modelling approach spans over multiple scales, from the regional or catchment level down to the floodplain and building levels. This distinctive feature is reflected both within the individual models and through their combination involving fine-scale detailed analyses (or data) embedded within coarser models at a broader level. [less ▲]

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See detailCellular automata urban expansion model based on support vector machines
El Saeid Mustafa, Ahmed Mohamed ULiege; Rienow, Andreas; Saadi, Ismaïl ULiege et al

in Mostafavi, Mir‐Abolfazl; Pinto, Nuno (Eds.) PROCEEDINGS of Second International Symposium on Cellular Automata Modeling for Urban and Spatial Systems (2016, October 30)

Land-use change models are used to explore the dynamics and drivers of land-use/landcover change and to inform policies affecting such change. A broad array of applications and modeling methods are ... [more ▼]

Land-use change models are used to explore the dynamics and drivers of land-use/landcover change and to inform policies affecting such change. A broad array of applications and modeling methods are available and each type has certain advantages and disadvantages depending on the objective of the research. This work presents an approach combining cellular automata (CA) model and supported vector machine (SVM) and binary logistic regression model (Logit) for simulating urban expansion in Wallonia (Belgium). This article emphasizes the interest in comparing combining CA with conventional Logit versus combining CA with SVM method as a base of CA model transition rule. Relative operating characteristic (ROC) and spatial matrices are used to validate the model. Model validation shows that the allocation performance of CA-SVM outperformed CALogit approach. [less ▲]

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See detailThe reinforcement opportunitie of a cross-border train connection: the example of the railway between Liège (Belgium) and Maastricht (Netherlands)
Wilmotte, Pierre-François ULiege; Lambotte, Jean-Marc ULiege; Cools, Mario ULiege et al

Conference (2016, October 07)

The research topic was to understand why it is so difficult to increase the train frequency on Liège - Maastricht line. The outline of our presentation was structured in 4 parts : the (current, potential ... [more ▼]

The research topic was to understand why it is so difficult to increase the train frequency on Liège - Maastricht line. The outline of our presentation was structured in 4 parts : the (current, potential and future) supply, the (current, potential and future) demand, some options to solve the deadlock between the Belgian's and the Dutch's outlooks and the conclusions. [less ▲]

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See detailForecasting travel behavior using Markov Chains-based approaches
Saadi, Ismaïl ULiege; El Saeid Mustafa, Ahmed Mohamed ULiege; Teller, Jacques ULiege et al

in Transportation Research. Part C : Emerging Technologies (2016), 69

Recent advances in agent-based micro-simulation modeling have further highlighted the importance of a thorough full synthetic population procedure for guaranteeing the correct characterization of real ... [more ▼]

Recent advances in agent-based micro-simulation modeling have further highlighted the importance of a thorough full synthetic population procedure for guaranteeing the correct characterization of real-world populations and underlying travel demands. In this regard, we propose an integrated approach including Markov Chain Monte Carlo (MCMC) simulation and profiling-based methods to capture the behavioral complexity and the great heterogeneity of agents of the true population through representative micro-samples. The population synthesis method is capable of building the joint distribution of a given population with its corresponding marginal distributions using either full or partial conditional probabilities or both of them simultaneously. In particular, the estimation of socio-demographic or transport-related variables and the characterization of daily activity-travel patterns are included within the framework. The fully probabilistic structure based on Markov Chains characterizing this framework makes it innovative compared to standard activity-based models. Moreover, data stemming from the 2010 Belgian Household Daily Travel Survey (BELDAM) are used to calibrate the modeling framework. We illustrate that this framework effectively captures the behavioral heterogeneity of travelers. Furthermore, we demonstrate that the proposed framework is adequately adapted to meeting the demand for large-scale micro-simulation scenarios of transportation and urban systems. [less ▲]

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See detailModelling Urban Expansion: A Multiple Urban-Densities Approach
El Saeid Mustafa, Ahmed Mohamed ULiege; Saadi, Ismaïl ULiege; Cools, Mario ULiege et al

in Proceedings of GEOProcessing 2016 (2016, April 24)

Most existing spatio-temporal urban expansion models consider urban land-use as a binary process, through the identification of urban versus non-urban areas. The main aim of this study is to analyze and ... [more ▼]

Most existing spatio-temporal urban expansion models consider urban land-use as a binary process, through the identification of urban versus non-urban areas. The main aim of this study is to analyze and model the expansion of multiple urban densities in Wallonia, Belgium. To this end, this study employs a multinomial logistic regression model that enables to visualize the consequence of different urban densities expansion. Cadastral datasets of years 2000 and 2010 are used to set four urban classes (non-urban, low-density, medium-density and high-density urban). Besides, several socio-economic, geographic and political driving forces dealing with urban development were operationalized to create maps of urban expansion probability for each urban density class. These probability maps are then utilized to predict future urban expansions for years 2020 and 2030. The model is validated using relative operating characteristic method for different urban classes. Our results suggest that different urban densities expansions are mainly linked to zoning status, neighboring areas that are urban and accessibility. Most importantly, this study highlights that the contribution of different driving forces to urban expansion process varies along with urban density. [less ▲]

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See detailUncertainty quantification in profile Hidden Markov Models (pHMM)-based activity sequences characterization
Saadi, Ismaïl ULiege; Liu, Feng; El Saeid Mustafa, Ahmed Mohamed ULiege et al

Poster (2016, April)

Recently, Liu et al. (2015) proposed a method to characterize activity sequences stemming from activity-travel diaries. The framework is structured as follows: from an extracted set of activity sequences ... [more ▼]

Recently, Liu et al. (2015) proposed a method to characterize activity sequences stemming from activity-travel diaries. The framework is structured as follows: from an extracted set of activity sequences, (a) the occurrence probabilities of the different activities are determined as well as their sequential order for aligning the activity sequences. Then, (b) profile Hidden Markov Models (pHMM) are defined based on the previous output. This technique is interesting given the fact that it is also able to include the irregular activities and, as a result, their derived trips. In this context, thinking about integration with an agent-based micro-simulation model requires, as a preliminary step, an uncertainty quantification analysis in order to measure the variability of the outcome. This approach is all the more necessary when agent-based micro-simulation is used to predict mid- and long-term system states. [less ▲]

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See detailDevelopment trajectory of an integrated framework for the mitigation of future flood risk: results from the FloodLand project
Saadi, Ismaïl ULiege; Bruwier, Martin ULiege; El Saeid Mustafa, Ahmed Mohamed ULiege et al

in Transportation Letters: The International Journal of Transportation Research (2016)

In this paper, the development trajectory of an integrated framework for the mitigation of future flood risk of the Ourthe river basin in Belgium is discussed. The paper contributes to the state-of-the ... [more ▼]

In this paper, the development trajectory of an integrated framework for the mitigation of future flood risk of the Ourthe river basin in Belgium is discussed. The paper contributes to the state-of-the-art by presenting an integrated multidisciplinary framework capable of making long-term projections (time horizon 2050 and 2100) with the objective of mitigating future flood risk by proposing alternative land-use scenarios. It bridges numerous different fields, including urban planning, transport engineering, hydrology, geology, environmental engineering, and economics. The overall design and validation results of the different sub-modules of the framework are presented, and ongoing and future enhancements are highlighted. [less ▲]

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See detailTrends in regional jobs-housing proximity based on the minimum commute: The case of Belgium
Saadi, Ismaïl ULiege; Boussauw, Kobe; Teller, Jacques ULiege et al

in Journal of Transport Geography (2016), 57

This paper investigates recent trends in the efficiency of the Belgian territorial structure in terms of commuting, at both the urban and regional scales. The minimum commute distance (MCD) and excess ... [more ▼]

This paper investigates recent trends in the efficiency of the Belgian territorial structure in terms of commuting, at both the urban and regional scales. The minimum commute distance (MCD) and excess rate (ER) are used to compare observed home-to-work trip lengths with an “optimal” alternative commuter pattern in which the sum of the distance traveled by the working population is minimized. The MCD is a proximity indicator that measures the spatial match between the labor market and the housing stock, which can also be regarded as an interesting indicator of potential border effects on travel behavior, especially in the inter-regional context of Belgium. An MCD calculation requires an origin–destination (OD) matrix and a distance matrix. In our Belgian case study, we employ a recent OD matrix (2010) originating from Social Security (ONSS) data. We compare this matrix with data from the 2001 and 1991 census surveys. In addition to identifying trends in jobs-housing proximity, the article assesses methodological implications regarding geographical scale arising from the use of the two data sources mentioned. Based on the available data, it was found that average actual commuting distance increased over both periods studied, while in general, growth rates of MCD are considerably lower than growth rates of the actual commuting distance. This indicates that the spatial proximity between the labor market and the housing stock in Belgium has declined over all periods studied, although this loss of spatial proximity only explains a small part of the increase of the actual commuting distance. Furthermore, we found that the comparison of excess commuting metrics between regions and time periods sets high standards on data requirements, in which uniformity in data collection and spatial level of aggregation is of great importance. Finally, as the main contribution of this study, the results demonstrate, through a statistical approach, that municipalities that are experiencing a higher-than-average increase in MCD and ER in one of the considered time frames are more likely to continue to exhibit a higher-than-average increase in the subsequent period. Therefore, the observed trends appear to be consistent over time. [less ▲]

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See detailHandling Intrahousehold Correlations in Modeling Travel: Comparison of Hierarchical Models and Marginal Models
Cools, Mario ULiege; Moons, Elke

in Transportation Research Record: Journal of the Transportation Research Board (2016), 2565

In this study, the necessity for treating intrahousehold correlation was investigated by analyzing two travel behavior indexes, travel time and travel distance, for three important travel motivations ... [more ▼]

In this study, the necessity for treating intrahousehold correlation was investigated by analyzing two travel behavior indexes, travel time and travel distance, for three important travel motivations (commuting, shopping, and leisure). Data stemming from the 2010 Belgian National Household Travel Survey were used in the analysis. Two model approaches that accommodated intrahousehold correlation were compared, namely, the generalized linear mixed model (GLMM) and the generalized estimating equation (GEE) model. Both model approaches showed that high levels of intrahousehold correlation were present, and therefore the use of models that took into account intrahousehold correlation was strongly recommended. Results indicated that this requirement was the most urgent for noncommuting trips. Moreover, the results showed that the GLMM and the GEE model yielded comparable estimates in the case of normally distributed data. Furthermore, evidence was provided that the more the estimates of the intrahousehold correlation provided by the two approaches differed, the less the homogeneity of the parameters was ensured. In this regard, if one has to choose between the GLMM and the GEE model, the negative consequences of choosing an inappropriate covariance model in the case of GLMM especially favor the selection of the GEE model. Further research is needed to compare the two approaches in the context of nonnormally distributed travel behavior data. [less ▲]

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See detailEffect of Traveler’s Nationality on Daily Travel Time Expenditure Using Zero-Inflated Negative Binomial Regression Models: Results from Belgian National Household Travel Survey
Eftekhar, Hamed ULiege; Creemers, Lieve; Cools, Mario ULiege

in Transportation Research Record: Journal of the Transportation Research Board (2016), 2565

In this study, data stemming from the 2010 Belgian National Household Travel Survey were used to assess the effect of a traveler’s nationality on daily travel time expenditure. Negative binomial (zero ... [more ▼]

In this study, data stemming from the 2010 Belgian National Household Travel Survey were used to assess the effect of a traveler’s nationality on daily travel time expenditure. Negative binomial (zero-inflated) models were estimated to isolate the effect of nationality after other contributing factors such as sociodemographics, residential characteristics, transport options, and temporal characteristics were controlled for. The results indicate that even if one controls for a series of other influencing factors, nationality plays a significant role in differences in travel time expenditure. This finding is especially relevant in the development of policy packages that are targeted at social inequalities. From a methodological perspective, methodological options—two weighting schemes and two bootstrap solutions—were presented to provide sufficient support for the conclusions. To generalize the results in further studies, an oversampling of travelers of different nationalities is strongly recommended. Future research should focus more on the underlying psychological constructs of why ethnic and cultural differences persist even if one accounts for other determinants. [less ▲]

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