A Practical Guide to an Open-Source Map-Matching Approach for Big GPS Data

Saki, Siavash; Hagen, Tobias

doi:10.1007/s42979-022-01340-5

Cited by 12 publications

(7 citation statements)

References 37 publications

(44 reference statements)

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“…If, on the other hand, no such route exists (i.e., mapMatchedTrajectory is nil at Line 7, Algorithm 2), the trajectory is discarded as unfeasible. An approach to map matching similar to the one adopted in the present study was recently presented by Saki and Hagen in [48]. In that study, the authors reported that the solution was able to correctly map match approximately 95% of the input trajectories.…”

Section: Empirical Procedurementioning

confidence: 80%

Vehicular Crowdsensing with High-Mileage Vehicles: Investigating Spatiotemporal Coverage Dynamics in Historical Cities with Complex Urban Road Networks

Starace

Torrepadula

Martino

et al. 2023

Journal of Advanced Transportation

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Background. Vehicular crowdsensing (VCS) can be a cost-effective solution to gather data in urban environments, leveraging the onboard sensors of modern vehicles moving around the city. Many experimental studies have proven that high-mileage vehicles, such as taxis, can be effectively used for VCS. However, these studies have been mostly carried out in cities with regular, grid-based, road networks. Conversely, little work has been conducted to assess the suitability of VCS in cities with more complex urban road networks, such as historical ones. Goal. As a step towards filling this gap, the present study investigates the feasibility of using different-sized fleets of taxis to crowdsense information in the urban areas of the historical cities of Porto (Portugal) and Rome (Italy), whose road networks evolved over the centuries and feature a complex topology. Data and Methodology. This work leverages massive real-world datasets of taxi trajectories collected over three contiguous weeks in the cities of Porto and Rome to estimate the spatiotemporal coverage achievable by different-sized fleets of taxis if they were used for VCS. Indeed, using these trajectories, several simulations were conducted, considering four sizes of taxi fleets, ranging from 50 to 400 vehicles, for both cities. The achievable spatiotemporal road network coverage metrics were computed at a fine-grained scale of single road segments. Results. Results show that the achievable coverage in both historical cities exhibits very similar trends, with as few as 50 vehicles being capable of visiting a relevant part of the road network at least once in the considered time frame. As expected, increasing the number of involved vehicles improves spatial and temporal coverage. Still, time gaps between subsequent visits can be possibly inadequate for some VCS use cases. As a consequence, recruiting more vehicles and/or devising specialized routing/incentivization mechanisms might be necessary to achieve more comprehensive coverage of the urban road network.

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Section: Empirical Procedurementioning

confidence: 80%

Vehicular Crowdsensing with High-Mileage Vehicles: Investigating Spatiotemporal Coverage Dynamics in Historical Cities with Complex Urban Road Networks

Starace

Torrepadula

Martino

et al. 2023

Journal of Advanced Transportation

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“…They defined the map-matching problem as finding the sequence of street segments most likely to match the sequence of GPS points. We used the routing engine Valhalla in our research project ( 31 ). Alternatively, we could have completely removed the points with poor accuracy from the data.…”

Section: Methodsmentioning

confidence: 99%

Modeling of Parking Violations Using Zero-Inflated Negative Binomial Regression: A Case Study for Berlin

Hagen

Reinfeld

Saki

2023

Transportation Research Record: Journal of the Transportation R

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Parking violations cause numerous problems, thus affecting daily mobility. Nevertheless, there are no extensive statistics on illegal parking in Germany, implying that the causes of this misconduct are still unexplored. The objective of this paper is to present a count data modeling approach for parking violations based on video footage taken from the windshields of driving vehicles, incorporating spatial data from OpenStreetMap (OSM). The main benefit of this data source is the transferability of the data collection procedure just by installing a recording device in vehicles of municipal services like waste collection. Moreover, the data from OSM are freely available for all cities. To account for excess zero counts in the street segments, a zero-inflated negative binomial distribution model was used to explain the number of violations per 100 m. “Excess” zeros were modeled using the logit part of the model, whereas the remaining counts of parking violations were fitted by the negative binomial model. Much effort was made to present the results of the count data models in an interpretable way. The most intuitive way seemed to be predictions of parking violations per 100 m (incidence rate) for different settings. Incidence rates were predicted for variations in explanatory variables, holding all other variables constant. We found parking violations per 100 m to be highest in main shopping streets. In addition, free parking spaces negatively- and the number of points of interest (such as buildings, craft stores, and shops) positively affected illegal parking.

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“…SageMaker is a machine-learning platform that makes it easy for scientists and developers to build, train, and deploy machine-learning models [49]. These models can predict learning outcomes based on historical data and provide insights to personalize the educational experience in the metaverse.…”

Section: ) Big Data Analyticsmentioning

confidence: 99%

Educational Advances in the Metaverse: Boosting Learning Through Virtual and Augmented Reality and Artificial Intelligence

Villegas-Ch,

García-Ortiz,

Sánchez-Viteri

2024

IEEE Access

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This work delves into the emerging field of the metaverse and its application in education, exploring how virtual and augmented reality technologies can transform teaching and learning methods. Focusing on aspects of educational effectiveness, security, privacy, accessibility, and inclusive design, the study provides a comprehensive analysis of the potential of the metaverse in the educational field. Through a methodology that combines quantitative and qualitative analyses, including ANOVA and Pearson's correlation coefficient, we evaluate the impact of the metaverse on academic performance and student engagement. The results indicate significant improvements in knowledge retention, student engagement, and user satisfaction, evidencing the value of the metaverse as an immersive and engaging educational tool. The study also highlights the importance of security and privacy in virtual learning environments, with tests and audits confirming the robustness of the metaverse against various cyber threats. Additionally, particular emphasis is placed on accessibility and inclusive design, demonstrating how the metaverse can provide equal learning opportunities for all students, regardless of their abilities or background. The results show that the metaverse represents a promising opportunity to revolutionize education, offering a more interactive, personalized, and accessible environment INDEX TERMS Student participation, academic retention, online courses.

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A Practical Guide to an Open-Source Map-Matching Approach for Big GPS Data

Cited by 12 publications

References 37 publications

Vehicular Crowdsensing with High-Mileage Vehicles: Investigating Spatiotemporal Coverage Dynamics in Historical Cities with Complex Urban Road Networks

Vehicular Crowdsensing with High-Mileage Vehicles: Investigating Spatiotemporal Coverage Dynamics in Historical Cities with Complex Urban Road Networks

Modeling of Parking Violations Using Zero-Inflated Negative Binomial Regression: A Case Study for Berlin

Educational Advances in the Metaverse: Boosting Learning Through Virtual and Augmented Reality and Artificial Intelligence

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