GIS mapping of driving behavior based on naturalistic driving data

View/ Open
Use this link to cite
http://hdl.handle.net/2183/23331Collections
- Investigación (ETSECCP) [817]
Metadata
Show full item recordTitle
GIS mapping of driving behavior based on naturalistic driving dataAuthor(s)
Date
2019Citation
Balsa-Barreiro, J.; Valero-Mora, P.M.; Berné-Valero, J.L.; Varela-García, F.-A. GIS mapping of driving behavior based on naturalistic driving data. ISPRS Int. J. Geo-Inf. 2019, 8, 226.
Abstract
[Abstract:] Naturalistic driving can generate huge datasets with great potential for research. However, to analyze the collected data in naturalistic driving trials is quite complex and difficult, especially if we consider that these studies are commonly conducted by research groups with somewhat limited resources. It is quite common that these studies implement strategies for thinning and/or reducing the data volumes that have been initially collected. Thus, and unfortunately, the great potential of these datasets is significantly constrained to specific situations, events, and contexts. For this, to implement appropriate strategies for the visualization of these data is becoming increasingly necessary, at any scale. Mapping naturalistic driving data with Geographic Information Systems (GIS) allows for a deeper understanding of our driving behavior, achieving a smarter and broader perspective of the whole datasets. GIS mapping allows for many of the existing drawbacks of the traditional methodologies for the analysis of naturalistic driving data to be overcome. In this article, we analyze which are the main assets related to GIS mapping of such data. These assets are dominated by the powerful interface graphics and the great operational capacity of GIS software.
Keywords
Big Data
Data visualization
Driving behavior
Geographic information systems
Kinematic (driving) data
Mapping
Microscopic traffic model
Naturalistic driving
Data visualization
Driving behavior
Geographic information systems
Kinematic (driving) data
Mapping
Microscopic traffic model
Naturalistic driving
Description
Este artigo pertence ao número especial Smart Cartography for Big Data Solutions.
Editor version
Rights
Atribución 3.0 España
Related items
Showing items related by title, author, creator and subject.
-
Developing a Simulation Model for Autonomous Driving Education in the Robobo SmartCity Framework
Juanatey, Daniel; Naya, M.; Baamonde, Tamara; Bellas, Francisco (MDPI, 2021-10)Abstract: This paper focuses on long-term education in Artificial Intelligence (AI) applied to robotics. Specifically, it presents the Robobo SmartCity educational framework. It is based on two main elements: the ... -
Enhancement handling performance of 4-wheels drive electrical vehicle using advanced control technique
Hassan, Ahmed; D. Frejo, José Ramón; Maestre, Jose María (Universidade da Coruña. Servizo de Publicacións, 2022)[Abstract] Electric vehicles (EVs) are gaining attention because they are environmentally friendly. Also, EVs can use in-hub motors, which can be independently controlled, improving maneuverability and allowing to set more ... -
Highway travel time information systems: from traditional to cooperative driving environments
Martínez-Díaz, Margarita (2018)[Abstract] Travel time information is and will continue to be one of the key indicators of highway quality of service and a highly valued knowledge for drivers. Therefore, most administrations have already implemented ...