Semantic Annotation of GPS Traces: Activity Type Inference

in Transportation Research Record: Journal of the Transportation Research Board (in press)

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 ▲]

Changes in Travel Behavior in Response to Weather Conditions: Do Type of Weather and Trip Purpose Matter

in Transportation Research Record: Journal of the Transportation Research Board (2010), 2157

Weather can influence travel demand, traffic flow, and traffic safety. A hypothesis—the type of weather determined the likelihood of a change in travel behavior, and changes in travel behavior because of ... [more ▼]

Weather can influence travel demand, traffic flow, and traffic safety. A hypothesis—the type of weather determined the likelihood of a change in travel behavior, and changes in travel behavior because of weather conditions depended on trip purpose—was assayed. A stated adaptation study was conducted in Flanders (the Dutch-speaking region of Belgium). A survey, completed by 586 respondents, was administered both on the Internet and as a traditional paper-and-pencil questionnaire. To ensure optimal correspondence between the survey sample composition and the Flemish population, observations in the sample were weighted. To test the main hypotheses, Pearson chi-square independence tests were performed. Results from both the descriptive analysis and the independence tests confirm that the type of weather matters and that changes in travel behavior in response to these weather conditions are highly dependent on trip purpose. This dependence of behavioral adjustments on trip purpose provides policy makers with a deeper understanding of how weather conditions affect traffic. Further generalizations of the findings are possible by shifting the scope toward revealed travel behavior. Triangulation of both stated and revealed travel behavior on the one hand and traffic intensities on the other hand is a key challenge for further research. [less ▲]

Calibrating Activity-Based Models with External Origin-Destination Information: Overview Of Different Possibilities

in Transportation Research Record: Journal of the Transportation Research Board (2010), 2175

Many practitioners question the advantages of activity-based models over conventional four-step models in regard to replication of traffic counts. This paper highlights a framework that actively links ... [more ▼]

Many practitioners question the advantages of activity-based models over conventional four-step models in regard to replication of traffic counts. This paper highlights a framework that actively links travel demand models in general and activity-based models in particular with traffic counts. Two approaches are presented that calibrate activity-based models with traffic count—an indirect and a direct approach. The indirect approach tries to incorporate findings based on the analysis of traffic counts into the components of the activity-based models. The direct approach calibrates the parameters of the travel demand model in such a way that the model replicates the observed traffic counts (quasi-) perfectly. A practical example is provided to illustrate the direct approach. The study area for this practical example is Hasselt, Belgium, a city of about 70,000 residents, and its surrounding municipalities. The practical examples revealed not a single roadway to success in calibrating activity-based models, but different options exist in fine-tuning the activity-based model. It is important to recognize some open issues and avenues for further research. First, it is not always appropriate to assume that traffic counts are completely correct. Setting up some belief structure might increase the responsiveness of the activity-based model. In addition, the origin-destination matrix calibration that optimizes the correspondence between estimated and observed screen-line counts could negatively affect the correspondence to other measures, such as vehicle miles traveled. To conclude, the formulation of a multiobjective calibration method is a key challenge for further research. [less ▲]

Road Pricing as an Impetus for Environment-Friendly Travel Behavior: Results from a Stated Adaptation Experiment

in Transportation Research Record: Journal of the Transportation Research Board (2009), 2115

An important policy instrument for governments to modify travel behavior and manage the increasing travel demand is the introduction of a congestion pricing system. In this study, the influence of a ... [more ▼]

An important policy instrument for governments to modify travel behavior and manage the increasing travel demand is the introduction of a congestion pricing system. In this study, the influence of a detailed classification of activities is examined to assess likely traveler response to congestion pricing scenarios. Despite the fact that most studies do not differentiate between activity categories, the value of time and in general the space–time properties and constraints of different types of activities vary widely. For this reason, it is of importance to provide sufficient detail and sensitivity in assessing the impact of congestion pricing scenarios. In addition, a first assessment of travelers’ possible multifaceted adaptation patterns is presented. For these purposes, a stated adaptation study was conducted in Flanders, the Dutch-speaking region of Belgium. The experiment was conducted through an interactive stated adaptation survey. In the stated adaptation experiment, respondents could indicate their responses to the congestion pricing scenario. The most prevalent conclusion is that the activity type significantly predetermines the willingness to express a more environment-friendly behavior (i.e., reducing the number of trips, reducing the total distance traveled, switching to more environment-friendly modes). Also, the willingness to show ecological activity-travel behavior (e.g., carpooling and using public transport) in a nonpricing situation is a major differentiator of future behavior in a congestion pricing scenario. [less ▲]

Investigating Effect of Holidays on Daily Traffic Counts: Time Series Approach

in Transportation Research Record: Journal of the Transportation Research Board (2007), 2019

In this paper, different modeling philosophies are explored in order to explain and forecast daily traffic counts. The main objectives of this study are the analysis of the impact of holidays on daily ... [more ▼]

In this paper, different modeling philosophies are explored in order to explain and forecast daily traffic counts. The main objectives of this study are the analysis of the impact of holidays on daily traffic, and the forecasting of future traffic counts. Data coming from single inductive loop detectors, collected in 2003, 2004 and 2005, were used for the analysis. The different models that were investigated showed that the variation in daily traffic counts could be explained by weekly cycles. The Box-Tiao modeling approach was applied to quantify the effect of holidays on daily traffic. The results showed that traffic counts were significantly lower for holiday periods. When the different modeling techniques were compared with respect to forecasting with a large forecast horizon, Box-Tiao modeling clearly outperformed the other modeling strategies. Simultaneous modeling of both the underlying reasons of travel, and revealed traffic patterns, certainly is a challenge for further research. [less ▲]