2020
DOI: 10.1007/s11036-020-01653-w
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Extraction of Naturalistic Driving Patterns with Geographic Information Systems

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 collecti… Show more

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Cited by 21 publications
(15 citation statements)
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References 35 publications
(39 reference statements)
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“…Establishing a P&R system in the urban environment of a city leads to a set of criteria that are part of the operation of the P&R system, such as the capacity that refers to the number of necessary parking places spaces that can be installed in the P&R system. Moreover, since the P&R system involves public transportation parameters such as demand, accessibility, frequency, and travel times of public transportation, these criteria are also taken into consideration [23][24][25][26][27]. Besides, when involving private vehicles, criteria such as traffic, travel time, and pollution are taken into account [28][29][30][31][32].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Establishing a P&R system in the urban environment of a city leads to a set of criteria that are part of the operation of the P&R system, such as the capacity that refers to the number of necessary parking places spaces that can be installed in the P&R system. Moreover, since the P&R system involves public transportation parameters such as demand, accessibility, frequency, and travel times of public transportation, these criteria are also taken into consideration [23][24][25][26][27]. Besides, when involving private vehicles, criteria such as traffic, travel time, and pollution are taken into account [28][29][30][31][32].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Moreover, the productive use of cars relies on the travelers' lifestyle, social and spatial engagements [28]. Certain car travelers cannot often drive without need but in addition to their preference [29][30][31]. Such strategies may involve advancement in the public transportation system and attract them to sustainable modes, for instance, cycling or walking.…”
Section: Literature Reviewmentioning
confidence: 99%
“…They also analyse the effective parameters of GIS mapping of naturalistic driving data. However, no study is found on automated intersection movement scenarios analysis with connected vehicle data using the deep transfer learning technique [17,18].…”
Section: Figure 1 Example Of An Erroneous Trajectorymentioning
confidence: 99%