Scipediacontent: Scipediacontent moved page Draft Content 498573053 to 238,295rt

2021-03-23T05:48:13Z

Scipediacontent moved page Draft Content 498573053 to 238,295rt

Scipediacontent: Created page with " == Abstract == Shared spaces are gaining presence in cities, where a variety of players and mobility types (pedestrians, bicycles, motorcycles, and cars) move without specif..."

2021-03-23T05:46:10Z

Created page with " == Abstract == Shared spaces are gaining presence in cities, where a variety of players and mobility types (pedestrians, bicycles, motorcycles, and cars) move without specif..."

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== Abstract ==

Shared spaces are gaining presence in cities, where a variety of players and mobility types (pedestrians, bicycles, motorcycles, and cars) move without specifically delimited areas. This makes the traffic they comprise challenging for automated systems. The information traditionally considered (e.g., streets, and obstacle positions and speeds) is not enough to build suitable models of the environment. The required explanatory and anticipation capabilities need additional information to improve them. Social aspects (e.g., goal of the displacement, companion, or available time) should be considered, as they have a strong influence on how people move and interact with the environment. This paper presents the Social-Aware Driver Assistance System (SADAS) approach to integrate this information into traffic systems. It relies on a domain-specific modelling language for social contexts and their changes. Specifications compliant with it describe social and system information, their links, and how to process them. Traffic social properties are the formalization within the language of relevant knowledge extracted from literature to interpret information. A multi-agent system architecture manages these specifications and additional processing resources. A SADAS can be connected to other parts of traffic systems by means of subscription-notification mechanisms. The case study to illustrate the approach applies social knowledge to predict people&rsquo

s movements. It considers a distributed system for obstacle detection and tracking, and the intelligent management of traffic signals.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_498573053-beopen1488-3951-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.3390/s19020221 http://dx.doi.org/10.3390/s19020221] under the license https://creativecommons.org/licenses/by

* [http://dx.doi.org/10.3390/s19020221 http://dx.doi.org/10.3390/s19020221] under the license http://creativecommons.org/licenses/by/3.0/

* [http://europepmc.org/articles/PMC6359130 http://europepmc.org/articles/PMC6359130] under the license https://creativecommons.org/licenses/by/4.0

* [https://www.mdpi.com/1424-8220/19/2/221/pdf https://www.mdpi.com/1424-8220/19/2/221/pdf]

* [https://dblp.uni-trier.de/db/journals/sensors/sensors19.html#Fernandez-Isabel19 https://dblp.uni-trier.de/db/journals/sensors/sensors19.html#Fernandez-Isabel19],
: [https://www.mdpi.com/1424-8220/19/2/221/pdf https://www.mdpi.com/1424-8220/19/2/221/pdf],
: [https://www.mdpi.com/1424-8220/19/2/221 https://www.mdpi.com/1424-8220/19/2/221],
: [https://www.ncbi.nlm.nih.gov/pubmed/30634439 https://www.ncbi.nlm.nih.gov/pubmed/30634439],
: [https://academic.microsoft.com/#/detail/2909929459 https://academic.microsoft.com/#/detail/2909929459] under the license cc-by

* [https://www.mdpi.com/1424-8220/19/2/221/pdf https://www.mdpi.com/1424-8220/19/2/221/pdf],
: [http://dx.doi.org/10.3390/s19020221 http://dx.doi.org/10.3390/s19020221]

under the license https://creativecommons.org/licenses/by/4.0/

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Scipediacontent: Scipediacontent moved page Draft Content 498573053 to 238,295rt

Scipediacontent: Created page with " == Abstract == Shared spaces are gaining presence in cities, where a variety of players and mobility types (pedestrians, bicycles, motorcycles, and cars) move without specif..."