Proposal of geographic information systems methodology for quality control procedures of data obtained in naturalistic driving studies

2015 ◽  
Vol 9 (7) ◽  
pp. 673-682 ◽  
Author(s):  
José Balsa-Barreiro ◽  
Pedro M. Valero-Mora ◽  
Ignacio Pareja-Montoro ◽  
Mar Sánchez-García
Keyword(s):  
Quality Control ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Geographic Information ◽  
Systems Methodology ◽  
Control Procedures ◽  
Naturalistic Driving

scholarly journals Extraction of Naturalistic Driving Patterns with Geographic Information Systems

2020 ◽  
Author(s):  
José Balsa-Barreiro ◽  
Pedro M. Valero-Mora ◽  
Mónica Menéndez ◽  
Rashid Mehmood
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Smart Cities ◽  
Spatial Scales ◽  
Geographic Information ◽  
Small Population ◽  
Driving Patterns ◽  
Valid Data ◽  
Naturalistic Driving ◽  
Definition Of

Abstract A better understanding of Driving Patterns and their relationship with geographical driving areas could bring great benefits for smart cities, including the identification of good driving practices for saving fuel and reducing carbon emissions and accidents. The process of extracting driving patterns can be challenging due to issues such as the collection of valid data, clustering of population groups, and definition of similar behaviors. Naturalistic Driving methods provide a solution by allowing the collection of exhaustive datasets in quantitative and qualitative terms. However, exploiting and analyzing these datasets is complex and resource-intensive. Moreover, most of the previous studies, have constrained the great potential of naturalistic driving datasets to very specific situations, events, and/or road sections. In this paper, we propose a novel methodology for extracting driving patterns from naturalistic driving data, even from small population samples. We use Geographic Information Systems (GIS), so we can evaluate drivers’ behavior and reactions to certain events or road sections, and compare across situations using different spatial scales. To that end, we analyze some kinematic parameters such as speeds, acceleration, braking, and other forces that define a driving attitude. Our method favors an adequate mapping of complete datasets enabling us to achieve a comprehensive perspective of driving performance.

scholarly journals GIS Mapping of Driving Behavior Based on Naturalistic Driving Data

2019 ◽  
Vol 8 (5) ◽  
pp. 226 ◽  
Author(s):  
José Balsa-Barreiro ◽  
Pedro M. Valero-Mora ◽  
José L. Berné-Valero ◽  
Fco-Alberto Varela-García
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Driving Behavior ◽  
Geographic Information ◽  
Limited Resources ◽  
Gis Mapping ◽  
Research Groups ◽  
Naturalistic Driving ◽  
Gis Software ◽  
Operational Capacity

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.

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