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See detailMeteorological variation in daily travel behaviour: evidence from revealed preference data from the Netherlands
Creemers, Lieve; Wets, Geert; Cools, Mario ULg

in Theoretical & Applied Climatology (in press)

This study investigates the meteorological variation in revealed preference travel data. The main objective of this study is to investigate the impact of weather conditions on daily activity participation ... [more ▼]

This study investigates the meteorological variation in revealed preference travel data. The main objective of this study is to investigate the impact of weather conditions on daily activity participation (trip motives) and daily modal choices in the Netherlands. To this end, data from the Dutch National Travel Household Survey of 2008 were matched to hourly weather data provided by the Royal Dutch Meteorological Institute and were complemented with thermal indices to indicate the level of thermal comfort and additional variables to indicate the seasonality of the weather conditions. Two multinomial logit–generalised estimation equations (MNL-GEE) models were constructed, one to assess the impact of weather conditions on trip motives and one to assess the effect of weather conditions on modal choice. The modelling results indicate that, depending on the travel attribute of concern, other factors might play a role. Nonetheless, the thermal component, as well as the aesthetical component and the physical component of weather play a significant role. Moreover, the parameter estimates indicate significant differences in the impact of weather conditions when different time scales are considered (e.g. daily versus hourly based). The fact that snow does not play any role at all was unexpected. This finding can be explained by the relatively low occurrence of this weather type in the study area. It is important to consider the effects of weather in travel demand modelling frameworks because this will help to achieve higher accuracy and more realistic traffic forecasts. These will in turn allow policy makers to make better long-term and short-term decisions to achieve various political goals, such as progress towards a sustainable transportation system. Further research in this respect should emphasise the role of weather conditions and activityscheduling attributes. [less ▲]

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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 detailMeteorological variation in travel behaviour
Creemers, Lieve; Wets, Geert; Cools, Mario ULg

Conference (2014)

Weather causes a variety of impacts on the transportation system. This paper contributes to the weather-related transport literature by investigating the meteorological variation in revealed preference ... [more ▼]

Weather causes a variety of impacts on the transportation system. This paper contributes to the weather-related transport literature by investigating the meteorological variation in revealed preference travel data. The main objective of this paper is to investigate the impact of weather conditions on revealed activity participation (trip motives) and revealed modal choices in the Netherlands. To this end, data from the Dutch national travel household survey 2008 was matched to hourly weather data provided by the Royal Dutch Meteorological Institute. Two GEE-MNL models are constructed, namely one for modelling the impact of weather conditions on trip motive and one to assess the effect on modal choice. The parameter estimates of the weather variables indicate that, depending on which travel attribute one focuses, other factors might play a role. Nonetheless, fog, sunshine duration and temperature have a significant impact in both models. Unexpected is the fact that snow and ice cover do not play a role at all. Nonetheless, this finding can be accounted for by the relative low occurrence of these weather types in the study area. It is important to integrate these identified impacts of weather in travel demand modelling frameworks, since this will help to achieve a higher accuracy and more realistic traffic forecasts. This allows policy makers to make better long-term and short-term decisions to achieve various political goals, such as the development towards a sustainable transportation system. Further research in this regard, should emphasize on the role of weather conditions and activity-scheduling attributes. [less ▲]

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See detailClimatological influences on inland waterway transport capacity
Cools, Mario ULg; Limbourg, Sabine ULg

Conference (2014)

Climate change may affect inland waterway transport through disturbances in waterway hydrology: longer periods with strong water swells and drops. To allow fully loaded barges, the water level must be ... [more ▼]

Climate change may affect inland waterway transport through disturbances in waterway hydrology: longer periods with strong water swells and drops. To allow fully loaded barges, the water level must be neither too high (limited air draught) nor too low (limited draught). Therefore, the water level impacts the load factor of barges and thus the transportation costs. Moreover, in winter, ice jams can paralyze inland waterway traffic on the river. In this paper, the effect of various climatological changes on the capacity of inland waterway in terms of barge transport is examined. The paper focusses on the development of a methodology for assessing the sensitivity of inland waterway systems to climatological changes and takes into account an experts' opinion survey that provides insight into the perceived likelihood of the different scenarios that are investigated. The analysis focusses on the inland waterway systems in Belgium, which has the second highest density of European inland waterways. It enables the integration of inland waterway transport in the intermodal supply chain. The results are related to investment planning and management in inland waterways transport. They are intended to be interesting to researchers and to inland waterways actors developing intermodal transport as well. [less ▲]

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See detailA bi-objective optimization model for a bimodal network of oil transportation
Belaid, Emna ULg; Saadi, Ismaïl ULg; Rigo, Philippe ULg et al

Conference (2014)

Transportation of oil requires attention for a variety of reasons, the most important being the external costs caused by adverse events. These adverse events affect not only the environment costs but also ... [more ▼]

Transportation of oil requires attention for a variety of reasons, the most important being the external costs caused by adverse events. These adverse events affect not only the environment costs but also the societal costs. In this paper, a bi-objective optimization model for a bimodal network of oil transportation is presented. The paper discusses a mathematical model that takes into account two main decision criteria, namely cost and safety. A linear programming model is presented, in which the focus is laid on the different elements that affect the performance of the bi-modal transportation chain of oil. The disturbing elements that are considered include technical failures, road conditions and vandalism acts. Thus, in this study, it is investigated how the bimodal network must be designed to avoid adverse effects caused by these disturbing elements. The goal of the approach is to maximize safety and minimize costs. Data from a real life example (i.e. the Tunisian national oil company) will be used to calibrate the model. [less ▲]

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See detailModeling travel behavior: Whether weather matters
Cools, Mario ULg

Speech (2013)

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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 detailUnravelling the determinants of carpool behaviour in Flanders, Belgium: Integration of qualitative and quantitative research
Cools, Mario ULg; Tormans, Hans; Briers, Steffen et al

in Hesse, Markus; Caruso, Geoffrey; Gerber, Philippe (Eds.) et al Proceedings of the BIVEC-GIBET Transport Research Days 2013 (2013)

The goal of this study is to identify those factors that trigger carpoolers to share their rides and the barriers that restrain non-carpoolers from doing so. To this end, four focus group sessions were ... [more ▼]

The goal of this study is to identify those factors that trigger carpoolers to share their rides and the barriers that restrain non-carpoolers from doing so. To this end, four focus group sessions were organized. In addition, information from the 2009-2010 Flemish household travel survey was analysed. From the focus group discussions, it can be concluded that the concept of carpooling is generally well known, but that the media attention and stimuli for the topic seem to have faded away over time. The main motivations to carpool are the social aspect, the financial benefit or a combination of both. The quantitative analysis underlined for the difference between the distinct types of employees. Furthermore, the finding that the home-work distance increases the likelihood to carpool emphasizes the importance of the financial benefits of carpooling. Financial stimuli are thought to have the most potential to increase the share of carpooling in the modal split. [less ▲]

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See detailA journey across scales, borders and data sources: minimum commute distance (MCD) analysis of home-to-work trips in Belgium
Teller, Jacques ULg; Cools, Mario ULg

in Hesse, Markus; Caruso, Geoffrey; Gerber, Philippe (Eds.) et al Proceedings of the BIVEC-GIBET Transport Research Days 2013 (2013)

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See detailIntegration of Inland Waterway Transport in the Intermodal Supply Chain: a Joint Research Agenda
Caris, An; Limbourg, Sabine ULg; Macharis, Cathy et al

in Rigo, Philippe; Wolters, Milou (Eds.) Proceedings of the PIANC SMART Rivers Conference 2013 (2013)

This paper identifies research opportunities which will enable the further integration of inland waterway transport in the intermodal supply chain. Intermodal transport may be interpreted as a chain of ... [more ▼]

This paper identifies research opportunities which will enable the further integration of inland waterway transport in the intermodal supply chain. Intermodal transport may be interpreted as a chain of actors who supply a transport service. Inland navigation can play a crucial role in increasing supply chain service performance. A first group of research challenges has the objective to encourage efficient operations in IWT: development of a system wide model for IWT, integration of operational planning systems and analysis of bundling networks. A second group of research efforts is directed towards shippers and consignees who use the intermodal transport chain to send or receive their goods: further development of models that integrate intermodal transport decisions with supply chain decisions and creation of green supply chains. A third group of research challenges concerns the problem domain of external cost calculations. Finally detailed time series data on freight transport should be collected to support these future research tracks. [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 detailImpact of urban form on daily travel: a comparative analysis
Cools, Mario ULg; Laterrasse, Jean; Le Néchet, Florent

Conference (2013)

Along with the emergence of Mega City Regions (MCRs) in Europe, mobility patterns have become increasingly polycentric. Since urban planning issues are especially difficult at this scale, it is important ... [more ▼]

Along with the emergence of Mega City Regions (MCRs) in Europe, mobility patterns have become increasingly polycentric. Since urban planning issues are especially difficult at this scale, it is important to assess the impact of the different evolutions in Mega City Region on important indicators such as daily travel times and daily travel distances. Therefore, in this study the differences between monocentric and polycentric MCRs in terms of travel distances and travel times for constraint and unconstraint mobility are investigated. To this end, four different MCRs were selected for the study: the Paris and Rhine-Ruhr metropolitan areas and the Randstad and Belgian Mega-City Region. For these MCRs regions, the travel times and distances were derived from the national travel surveys. Special attention was paid to the harmonization exercise based, calculating the daily travel distances for 7 different purposes and 9 different transport modes. With respect to the socio-demographics, the least common denominator was used to define comparable socio-demographics. Results indicate clear differences between the monocentric and polycentric regions, especially with respect to shopping and leisure trips. In addition, some policy interventions could be defined based upon the results of the disaggregation based on the socio-demographics. [less ▲]

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See detailModelling Route Choice Decisions of Car Travellers Using Combined GPS and Diary Data
Ramaekers, Katrien; Reumers, Sofie; Wets, Geert et al

in Networks & Spatial Economics (2013), 13(3), 351-372

The aim of this research is to identify the relationship between activity patterns and route choice decisions. The focus is twofold: on the one hand, the relationship between the purpose of a trip and the ... [more ▼]

The aim of this research is to identify the relationship between activity patterns and route choice decisions. The focus is twofold: on the one hand, the relationship between the purpose of a trip and the road categories used for the relocation is investigated; on the other hand, the relationship between the purpose of a trip and the deviation from the shortest path is studied. The data for this study were collected in 2006 and 2007 in Flanders, the Dutch speaking and northern part of Belgium. To estimate the relationship between the primary road category travelled on and the corresponding activity-travel behaviour a multinomial logit model is developed. To estimate the relationship between the deviation from the shortest path and the corresponding activity-travel behaviour a Tobit model is developed. The results of the first model point out that route choice is a function of multiple factors, not just travel time or distance. Crucial for modelling route choices or in general for traffic assignment procedures is the conclusion that activity patterns have a clear influence on the road category primarily driven on. Particularly, it was shown that the likelihood of taking primarily through roads is highest for work trips and lowest for leisure trips. The second model shows a significant relationship between the deviation from the shortest path and the purpose of the trip. Furthermore, next to trip-related attributes (trip distance), also socio-demographic variables and geographical differences play an important role. These results certainly suggest that traffic assignment procedures should be developed that explicitly take into account an activity-based segmentation. In addition, it was shown that route choices were similar during peak and off-peak periods. This is an indication that car drivers are not necessarily utility maximizers, or that classical utility functions in the context of route choices are omitting important explanatory variables. [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 detailThe dual role of weather forecasts on changes in activity-travel behavior
Cools, Mario ULg; Creemers, Lieve

in Journal of Transport Geography (2013), 28

A deeper understanding of how human activity-travel behavior is affected by various weather conditions is essential for both policy makers and traffic managers. To unravel the ambiguity in findings ... [more ▼]

A deeper understanding of how human activity-travel behavior is affected by various weather conditions is essential for both policy makers and traffic managers. To unravel the ambiguity in findings reported in the literature, the main objective of this paper is to obtain an accurate assessment of how weather forecasts trigger changes in Flemish activity-travel behavior. To this end, data were collected by means of a stated adaptation experiment, which was administered both on the Internet and via traditional paper-and-pencil questionnaires. To address the main research question of this paper, two statistical techniques were adopted. The first technique is the computation of Pearson chi-square independence tests. The second approach is the estimation of a GEE-MNL-model. The results from both techniques underscore the dual role of weather forecasts on changes in activity-travel behavior. On the one hand, the results clearly illustrate the significant effect of forecasted weather; the likelihood of changes in activity-travel behavior significantly depends on the weather forecasted. On the other hand, different methods of acquiring weather information (exposure, media source, or perceived reliability) do not impact the probability of behavioral adaptations. This duality may be partially attributable to the discrepancy that exists between weather forecasts and true traffic and roadway conditions. Therefore, the implementation of a road weather information system that is directly linked to the weather forecasts is recommended. [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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