Journal ArticleDOI
Vehicle classification using GPS data
Zhanbo Sun,Xuegang Ban +1 more
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TLDR
Methods to classify vehicles using GPS data extracted from mobile traffic sensors, which is considered to be low-cost especially for large areas of urban arterials, are proposed.Abstract:
Vehicle classification information is crucial to transportation planning, facility design, and operations. Traditional vehicle classification methods are either too expensive to be deployed for large areas or subject to errors under specific situations. In this paper, we propose methods to classify vehicles using GPS data extracted from mobile traffic sensors, which is considered to be low-cost especially for large areas of urban arterials. It is found that features related to the variations of accelerations and decelerations (e.g., the proportions of accelerations and decelerations larger than 1 meter per square second, and the standard deviations of accelerations and decelerations) are the most effective in terms of vehicle classification using GPS data. By classifying general trucks from passenger cars, the average misclassification rate is about 1.6% for the training data, and 4.2% for the testing data.read more
Citations
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Inferring transportation modes from GPS trajectories using a convolutional neural network
Sina Dabiri,Kevin Heaslip +1 more
TL;DR: This research contrasts the methodology with traditional machine learning algorithms as well as the seminal and most related studies to demonstrate the superiority of the CNN framework.
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Mobile Big Data: The Fuel for Data-Driven Wireless
TL;DR: In this survey, in-depth and comprehensive coverage on the features, sources and applications of mobile big data, as well as the current state-of-the-art, challenges and opportunities for research and development in this field are provided, with an emphasis on the user modeling, infrastructure supporting, data management, and knowledge discovery aspects.
Journal ArticleDOI
A cell-based logit-opportunity taxi customer-search model
TL;DR: In this paper, a cell-based model is proposed to predict local customer-search movements of vacant taxi drivers, which incorporates the modeling principles of the logit-based search model and the intervening opportunity model.
Journal ArticleDOI
Trajectory-based vehicle energy/emissions estimation for signalized arterials using mobile sensing data
TL;DR: In this paper, a trajectory-based energy/emissions estimation method is proposed for signalized arterials, which offers a cost-effective way to estimate fuel consumption and emissions for large areas.
Journal ArticleDOI
Real-time trip purpose prediction using online location-based search and discovery services
TL;DR: Developing trip purpose prediction models based upon online location-based search and discovery services and a limited set of trip data that are usually available upon the completion of the trip show that Google Places information is a useful predictor of trip purpose in situations where activity- and person-related information is uncollectable, missing, or unreliable.
References
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A survey of cross-validation procedures for model selection
Sylvain Arlot,Alain Celisse +1 more
TL;DR: This survey intends to relate the model selection performances of cross-validation procedures to the most recent advances of model selection theory, with a particular emphasis on distinguishing empirical statements from rigorous theoretical results.
Journal ArticleDOI
A survey of cross-validation procedures for model selection
Sylvain Arlot,Alain Celisse +1 more
TL;DR: In this paper, a survey on the model selection performances of cross-validation procedures is presented, with a particular emphasis on distinguishing empirical statements from rigorous theoretical results, and guidelines are provided for choosing the best crossvalidation procedure according to the particular features of the problem in hand.