References of "Janssens, Davy"
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See detailBayesian inference for transportation origin–destination matrices: the Poisson–inverse Gaussian and other Poisson mixtures
Perrakis, Konstantinos; Karlis, Dimitris; Cools, Mario ULg et al

in Journal of the Royal Statistical Society. Series A Statistics in Society (in press)

Transportation origin–destination analysis is investigated through the use of Poisson mixtures by introducing covariate-based models which incorporate different transport modelling phases and also allow ... [more ▼]

Transportation origin–destination analysis is investigated through the use of Poisson mixtures by introducing covariate-based models which incorporate different transport modelling phases and also allow for direct probabilistic inference on link traffic based on Bayesian predictions. Emphasis is placed on the Poisson–inverse Gaussian model as an alternative to the commonly used Poisson–gamma and Poisson–log-normal models. We present a first full Bayesian formulation and demonstrate that the Poisson–inverse Gaussian model is particularly suited for origin–destination analysis because of its desirable marginal and hierarchical properties. In addition, the integrated nested Laplace approximation is considered as an alternative to Markov chain Monte Carlo sampling and the two methodologies are compared under specific modelling assumptions. The case-study is based on 2001 Belgian census data and focuses on a large, sparsely distributed origin–destination matrix containing trip information for 308 Flemish municipalities. [less ▲]

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See detailBuilding a validation measure for activity-based transportation models based on mobile phone data
Liu, Feng; Janssens, Davy; Cui, JianXun et al

in Expert Systems with Applications (2014), 41(14), 6174-6189

Activity-based micro-simulation transportation models typically predict 24-h activity-travel sequences for each individual in a study area. These sequences serve as a key input for travel demand analysis ... [more ▼]

Activity-based micro-simulation transportation models typically predict 24-h activity-travel sequences for each individual in a study area. These sequences serve as a key input for travel demand analysis and forecasting in the region. However, despite their importance, the lack of a reliable benchmark to evaluate the generated sequences has hampered further development and application of the models. With the wide deployment of mobile phone devices today, we explore the possibility of using the travel behavioral information derived from mobile phone data to build such a validation measure. Our investigation consists of three steps. First, the daily trajectory of locations, where a user performed activities, is constructed from the mobile phone records. To account for the discrepancy between the stops revealed by the call data and the real location traces that the user has made, the daily trajectories are then transformed into actual travel sequences. Finally, all the derived sequences are classified into typical activity-travel patterns which, in combination with their relative frequencies, define an activity-travel profile. The established profile characterizes the current activity-travel behavior in the study area, and can thus be used as a benchmark for the assessment of the activity-based transportation models. By comparing the activity-travel profiles derived from the call data with statistics that stem from traditional activity-travel surveys, the validation potential is demonstrated. In addition, a sensitivity analysis is carried out to assess how the results are affected by the different parameter settings defined in the profiling process. [less ▲]

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See detailInvestigation of the determinants of the mental knowledge of public parking facilities
Cools, Mario ULg; van der Waerden, Peter; Janssens, Davy

in Proceedings of the 13th World Conference on Transport Research (2013)

This paper presents a study regarding the determinants of travellers’ mental knowledge of public parking facilities. The data regarding the mental knowledge were collected in the city of Hasselt, Belgium ... [more ▼]

This paper presents a study regarding the determinants of travellers’ mental knowledge of public parking facilities. The data regarding the mental knowledge were collected in the city of Hasselt, Belgium, by means of an internet-based questionnaire. In total 1007 respondents completed the questionnaire. Two different dependent variables were specified: the mental representation of parking facilities (known or not) and the identification of parking facilities (identified first or not). In addition, three different groups of determinants were included in the models: parking attributes, personal characteristics, and mental knowledge of the city. The data are analyzed using generalized estimating equations (GEE) models for binary data. The analyses show a considerable influence of the following parking attributes: type of parking facility, Park & Ride status, charged parking, number of places, and location of parking facility. Furthermore our study revealed that personal characteristics and mental knowledge of the city play a marginal role. [less ▲]

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See detailSemantic Annotation of Global Positioning System Traces: Activity Type Inference
Reumers, Sofie; Liu, Feng; Janssens, Davy et al

in Transportation Research Record: Journal of the Transportation Research Board (2013), 2383

Because of the rapid development of technology, larger data sets on activity travel behavior have become available. These data sets often lack semantic interpretation. This lack of interpretation implies ... [more ▼]

Because of the rapid development of technology, larger data sets on activity travel behavior have become available. These data sets often lack semantic interpretation. This lack of interpretation implies that annotation of activity type and transportation mode is necessary. This paper aims to infer activity types from Global Positioning System (GPS) traces by developing a decision tree-based model. The model considers only activity start times and activity durations. On the basis of the decision tree classification, a probability distribution and a point prediction model were constructed. The probability matrix described the probability of each activity type for each class (i.e., combination of activity start time and activity duration). In each class, the point prediction model selected the activity type that had the highest probability. Two types of data were collected in 2006 and 2007 in Flanders, Belgium (i.e., activity travel data and GPS data). The optimal classification tree constructed contained 18 leaves. Consequently, 18 if-then rules were derived. An accuracy of 74% was achieved when the tree was trained. The accuracy of the model for the validation set (72.5%) showed that overfitting was minimal. When the model was applied to the test set, the accuracy was almost 76%. The models indicated the importance of time information in the semantic enrichment process. This study contributes to future data collection in that it enables researchers to infer activity types directly from activity start time and duration information obtained from GPS data. Because no location information is needed, this research can be easily and readily applied to millions of individual agents. [less ▲]

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See detailProfiling workers’ activity-travel behavior based on mobile phone data
Liu, Feng; Janssens, Davy; Wets, Geert et al

in Proceedings of the Third International Conference on the Analysis of Mobile Phone Datasets (NetMob) (2013)

Activity-based micro-simulation models typically predict 24-hour activity-travel patterns for each individual in a study area. These patterns reflect the characteristics of the available transportation ... [more ▼]

Activity-based micro-simulation models typically predict 24-hour activity-travel patterns for each individual in a study area. These patterns reflect the characteristics of the available transportation infrastructure and land-use system as well as individuals’ lifestyles and needs. However, the lack of a reliable benchmark to evaluate the generated patterns has been a major concern. To address this issue, we explore the possibility of using mobile phone data to build such a validation measure. Our investigation consists of three steps. First, the daily trajectory of locations, where a user performed activities, is constructed from the mobile phone records. To account for the discrepancy between the movements revealed by the call data and the real traces that the user has made, the daily trajectories are then transformed into travel sequences. Finally, all the inferred travel sequences are classified into typical activity-travel patterns which, in combination with their relative frequencies, define a profile. The established profile represents the activity-travel behavior in the study area, and thus can be used as a benchmark for the validation of the activity-based models. By comparing the benchmark profiles derived from the call data with statistics that stem from activity-travel surveys, the validation potential is demonstrated. In addition, a sensitivity analysis is carried out to assess how the results are affected by the different parameter settings defined in the profiling process. [less ▲]

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See detailAnnotating mobile phone location data with activity purposes using machine learning algorithms
Liu, Feng; Janssens, Davy; Wets, Geert et al

in Expert Systems with Applications (2013), 40(8), 32993311

Individual human travel patterns captured by mobile phone data have been quantitatively characterized by mathematical models, but the underlying activities which initiate the movement are still in a less ... [more ▼]

Individual human travel patterns captured by mobile phone data have been quantitatively characterized by mathematical models, but the underlying activities which initiate the movement are still in a less-explored stage. As a result of the nature of how activity and related travel decisions are made in daily life, human activity-travel behavior exhibits a high degree of spatial and temporal regularities as well as sequential ordering. In this study, we investigate to what extent the behavioral routines could reveal the activities being performed at mobile phone call locations that are captured when users initiate or receive a voice call or message. Our exploration consists of four steps. First, we define a set of comprehensive temporal variables characterizing each call location. Feature selection techniques are then applied to choose the most effective variables in the second step. Next, a set of state-of-the-art machine learning algorithms including Support Vector Machines, Logistic Regression, Decision Trees and Random Forests are employed to build classification models. Alongside, an ensemble of the results of the above models is also tested. Finally, the inference performance is further enhanced by a post-processing algorithm. Using data collected from natural mobile phone communication patterns of 80 users over a period of more than one year, we evaluated our approach via a set of extensive experiments. Based on the ensemble of the models, we achieved prediction accuracy of 69.7%. Furthermore, using the post processing algorithm, the performance obtained a 7.6% improvement. The experiment results demonstrate the potential to annotate mobile phone locations based on the integration of data mining techniques with the characteristics of underlying activity-travel behavior, contributing towards the semantic comprehension and further application of the massive data. [less ▲]

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See detailSemantic Annotation of GPS Traces: Activity Type Inference
Reumers, Sofie; Liu, Feng; Janssens, Davy et al

in Proceedings of the 92nd Annual Meeting of the Transportation Research Board (DVD-ROM) (2013)

Due to the rapid development of technology, larger data sets concerning activity travel behavior become available. These data sets often lack semantic interpretation. This implies that annotation in terms ... [more ▼]

Due to the rapid development of technology, larger data sets concerning activity travel behavior become available. These data sets often lack semantic interpretation. This implies that annotation in terms of activity type and transportation mode is necessary. This paper aims to infer activity types from GPS traces by developing a decision tree-based model. The model only considers activity start times and activity durations. Based on the decision tree classification, a probability distribution and a point prediction model were constructed. The probability matrix describes the probability of each activity type for each class (i.e. combination of activity start time and activity duration). In each class, the point prediction model selects the activity type that has the highest probability. Two types of data were collected in 2006 and 2007 in Flanders, Belgium, i.e. activity travel data and GPS data. The optimal classification tree constructed comprises 18 leaves. Consequently, 18 if-then rules were derived. An accuracy of 74% was achieved when training the tree. The accuracy of the model for the validation set, i.e. 72.5%, shows that overfitting is minimal. When applying the model to the test set, the accuracy was almost 76%. The models indicate the importance of time information in the semantic enrichment process. This study contributes to future data collection in that it enables researchers to directly infer activity types from activity start time and duration information obtained from GPS data. Because no location information is needed, this research can be easily and readily implemented to millions of individual agents. [less ▲]

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See detailInvestigation of the Determinants of Travelers’ Mental Knowledge of Public Parking Facilities
Cools, Mario ULg; van der Waerden, Peter; Janssens, Davy

in Proceedings of the 92nd Annual Meeting of the Transportation Research Board (DVD-ROM) (2013)

This paper describes a study of car drivers’ familiarity with the parking situation in the vicinity of a regional shopping center. The data used for this study are collected in Hasselt, a medium sized ... [more ▼]

This paper describes a study of car drivers’ familiarity with the parking situation in the vicinity of a regional shopping center. The data used for this study are collected in Hasselt, a medium sized city in Belgium. The central shopping area of Hasselt is surrounded by 23 public parking facilities. 1007 residents have been asked to indicate if they are familiar with each parking facility. The concept of familiarity was related to the socio-demographic and cognitive attributes of the respondents, their trips to the city center and the type of parking facility using multinomial logistic regression and bivariate probit regression. The results show that familiarity with parking facilities is especially related to age and education, and to the frequency of car use towards the city centre, and to a lesser extent to place of residence, income and perceived mental knowledge. In addition to these results, this paper demonstrates the value of collecting virtual buffer data by means of an online survey tool. The authors recommend that simulation models that predict parking choice behavior take into account the different levels of familiarity with parking facilities, and the contributing factors. An important avenue for further research is the combination of personal and facility specific information to assess the familiarity with different types of parking facilities. [less ▲]

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See detailPerformance Assessment of Local Mobility Policy-Making Administrations Using the Principles of Total Quality Management in Flanders, Belgium: Expounding the Decision-Making Processes
Tormans, Hans; Miermans, Willy; Cools, Mario ULg et al

in International Journal of Sustainable Transportation (2013), 7(4), 318-346

This article describes a quality assessment of the processes underlying municipal mobility policy-making in Flanders, Belgium. 25 criteria and 176 aspects were queried during 25 interview sessions ... [more ▼]

This article describes a quality assessment of the processes underlying municipal mobility policy-making in Flanders, Belgium. 25 criteria and 176 aspects were queried during 25 interview sessions. Results were aggregated at the level of 7 quality domains of action and suggest that Flemish municipal mobility policy-making is generally fairly frail and of an ad-hoc nature. Four factors are found to be determining for this finding: default of political continuity, internal conflicts between stakeholders, lacking internal expertise, and deficient financial resources. Inter-stakeholder collaboration, residents’ participation, and policy-integration with higher-level programs are the strengths of current mobility policy practices in Flanders. [less ▲]

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See detailKnowledge of the Concept Light Rail Transit: Determinants of the Cognitive Mismatch between Actual and Perceived Knowledge
Creemers, Lieve; Cools, Mario ULg; Tormans, Hans et al

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

The Flemish public transport company “De Lijn” is planning the development of a new Light Rail network for medium range distance trips (10 to 40km). A challenge exists in the fact that the concept of ... [more ▼]

The Flemish public transport company “De Lijn” is planning the development of a new Light Rail network for medium range distance trips (10 to 40km). A challenge exists in the fact that the concept of Light Rail Transit (LRT) is relatively unknown in Flanders. Therefore this paper explores the knowledge of the concept ‘Light Rail Transit’ among the Flemish population. To investigate the knowledge, two separate binary logit models are estimated to explore the determinants of the overall actual knowledge and the determinants of a cognitive mismatch. The results show that age, sex, public transit use, household size, bicycle ownership and weekly number of shopping activities contribute significantly to the overall actual knowledge of the LRT-concept. Besides, cognitive mismatch is only significantly affected by age and gender. Moreover, the results reveal a serious lack of knowledge of the concept of LRT. Consequently, a successful implementation of the LRT-system in Flanders may be jeopardized and thus it is of crucial importance to raise the level of knowledge. A first option is knowledge acquisition based on experience of the transit network. In this view, it can be a good idea to develop “travel-one-day-for-free” marketing actions. Second, it is important to provide information to the travelers by contriving information campaigns based on the determinants identified by the models. How the campaigns should be constructed from an intrinsic and psychological point of view and deliberating between the methods of communication to reach the various target groups are some important considerations for further research. [less ▲]

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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 detailIdentifying the Determinants of Light Rail Mode Choice for Medium/Long Distance Trips: Results from a Stated Preference Study
Creemers, Lieve; Cools, Mario ULg; Tormans, Hans et al

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

The introduction of new public transport systems can influence society in a multitude of ways, ranging from modal choices and the environment to economic growth. This paper examines the determinants of ... [more ▼]

The introduction of new public transport systems can influence society in a multitude of ways, ranging from modal choices and the environment to economic growth. This paper examines the determinants of light rail mode choice for medium/long distance trips (10-40km) for a new light rail system in Flanders, Belgium. To investigate these choices, the effects of various transport system specific factors (i.e. travel cost, in-vehicle travel time, transit punctuality, waiting time, access/egress time, transfers, and the availability of empty seats) as well as the travelers’ personal traits, are analyzed using an alternating logistic regression model, which explicitly takes into account the correlated responses for binary data. The data used for the analysis stem from a stated preference survey which was conducted in Flanders, Belgium. The modeling results yield findings that are in line with literature: most transport system specific factors as well as socio-economic variables, attitudinal factors, perceptions and the frequency of using public transport contribute significantly to the preference of light rail transit. In particular, it is shown that the use of light rail is strongly influenced by travel cost and in-vehicle travel time and to a lesser extent by waiting and access/egress time. It also appeared that seat availability plays a more important role than transfers in the decision process to choose light rail transit. The findings of this paper can be used by policy makers as a frame of reference to make light rail transit more successful. [less ▲]

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See detailIdentifying the Determinants of Light Rail Mode Choice for Medium- and Long-Distance Trips: Results from a Stated Preference Study
Creemers, Lieve; Cools, Mario ULg; Tormans, Hans et al

in Transportation Research Record: Journal of the Transportation Research Board (2012), 2275

he introduction of new public transport systems can influence society in a multitude of ways ranging from modal choices and the environment to economic growth. This paper examines the determinants of ... [more ▼]

he introduction of new public transport systems can influence society in a multitude of ways ranging from modal choices and the environment to economic growth. This paper examines the determinants of light rail mode choice for medium- and long-distance trips (10 to 40 km) for a new light rail system in Flanders, Belgium. To investigate these choices, the effects of various transport system-specific factors (i.e., travel cost, in-vehicle travel time, transit punctuality, waiting time, access and egress time, transfers, and availability of seats) as well as the travelers' personal traits were analyzed by using an alternating logistic regression model, which explicitly takes into account the correlated responses for binary data. The data used for the analysis stem from a stated preference survey conducted in Flanders. The modeling results are in line with literature: most transport system-specific factors as well as socioeconomic variables, attitudinal factors, perceptions, and the frequency of using public transport contribute significantly to the preference for light rail transit. In particular, the results indicate that the use of light rail is strongly influenced by travel cost and in-vehicle travel time and to a lesser extent by waiting and access-egress time. Seat availability appeared to play a more important role than did transfers in deciding to choose light rail transit. The findings of this paper can be used by policy makers as a frame of reference to make light rail transit more successful. [less ▲]

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See detailA Bayesian approach for modeling origin–destination matrices
Perrakis, Konstantinos; Karlis, Dimitris; Cools, Mario ULg et al

in Transportation Research. Part A : Policy & Practice (2012), 46(1), 200212

The majority of origin destination (OD) matrix estimation methods focus on situations where weak or partial information, derived from sample travel surveys, is available. Information derived from travel ... [more ▼]

The majority of origin destination (OD) matrix estimation methods focus on situations where weak or partial information, derived from sample travel surveys, is available. Information derived from travel census studies, in contrast, covers the entire population of a specific study area of interest. In such cases where reliable historical data exist, statistical methodology may serve as a flexible alternative to traditional travel demand models by incorporating estimation of trip-generation, trip-attraction and trip-distribution in one model. In this research, a statistical Bayesian approach on OD matrix estimation is presented, where modeling of OD flows derived from census data, is related only to a set of general explanatory variables. A Poisson and a negative binomial model are formulated in detail, while emphasis is placed on the hierarchical Poisson-gamma structure of the latter. Problems related to the absence of closed-form expressions are bypassed with the use of a Markov Chain Monte Carlo method known as the Metropolis–Hastings algorithm. The methodology is tested on a realistic application area concerning the Belgian region of Flanders on the level of municipalities. Model comparison indicates that negative binomial likelihood is a more suitable distributional assumption than Poisson likelihood, due to the great degree of overdispersion present in OD flows. Finally, several predictive goodness-of-fit tests on the negative binomial model suggest a good overall fit to the data. In general, Bayesian methodology reduces the overall uncertainty of the estimates by delivering posterior distributions for the parameters of scientific interest as well as predictive distributions for future OD flows. [less ▲]

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See detailOnderzoek Verplaatsingsgedrag Vlaanderen 4.2 (2009-2010): Analyserapport
Janssens, Davy; Cools, Mario ULg; Miermans, Willy et al

Report (2011)

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See detailOnderzoek Verplaatsingsgedrag Vlaanderen 4.2 (2009-2010): Tabellenrapport
Cools, Mario ULg; Declercq, Katrien; Janssens, Davy et al

Report (2011)

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See detailThe dual role of weather forecasts on changes in activity-travel behavior
Cools, Mario ULg; Creemers, Lieve; Janssens, Davy et al

Conference (2011)

In previous studies, conflicting results could be found regarding the impact of weather forecasts on travel decisions, e.g. Khattak and De Palma (1997) found no significant effect of acquiring forecasted ... [more ▼]

In previous studies, conflicting results could be found regarding the impact of weather forecasts on travel decisions, e.g. Khattak and De Palma (1997) found no significant effect of acquiring forecasted weather information on the probability of adapting mode and departure time, whereas the results reported by Hagens (2005), Niina (2009) and Kilpelainen and Summala (2007) indicated that weather forecast do play an important role. Therefore this paper investigates the changes in activity-travel behavior in response to weather forecasts. The data for this study is collected by means of a stated adaptation survey, which is both administered on the internet and via a traditional paper and pencil questionnaire. In total, 595 respondents completed the survey. To obtain an optimal correspondence between the true population and the sample weights are assigned to the observation. Results indicate that weather information plays a dual role. On the one hand people do alter their activity-travel behavior in response to weather information, albeit these changes are not as pronounced when compared to actual weather. On the other hand the extent (frequency and media type) to which people are exposed to these weather forecasts appears to play only a marginal role. This dual role weather information plays in this study appears to be supported by the conflicting international literature and therefore revealing the underlying psychological motivations to change one's activity-travel behavior is a key challenge for further research. [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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