Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/27188
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dc.contributor.authorCoelho, Margarida C.pt_PT
dc.contributor.authorBahmankhah, Behnampt_PT
dc.contributor.authorFerreira, Elisabetept_PT
dc.contributor.authorGuarnaccia, Claudiopt_PT
dc.date.accessioned2019-12-16T16:13:20Z-
dc.date.available2019-12-16T16:13:20Z-
dc.date.issued2019-09-
dc.identifier.urihttp://hdl.handle.net/10773/27188-
dc.description.abstractThe main objective of this vision paper is to present the project “DICA-VE: Driving Information in a Connected and Autonomous Vehicle Environment: Impacts on Safety and Emissions”, which aims to develop an integrated methodology to assess driving behavior volatility and develop warnings to reduce road conflicts and pollutants/noise emissions in a vehicle environment. A particular attention will be given to the interaction of motor vehicles with vulnerable road users (pedestrians and cyclists). The essence of assessing driving volatility aims the capture of the existence of strong accelerations and aggressive maneuvers. A fundamental understanding of instantaneous driving decisions (through a deep characterization of individual driver decision mechanisms, distinguishing normal from anomalous) is needed to develop a framework for optimizing these impacts. Thus, the research questions are: 1) Which strategies are adopted by each driver when he/she performs short-term driving decisions and how can these intentions be mapped, in a certain road network?; 2) How is driver’s volatility affected by the proximity of other road users, namely pedestrians or cyclists?; 3) How can driving volatility information be integrated into a platform to alert road users about potential dangers in the road infrastructure and prevent the occurrence of crash situations?; 4) How can anomalous driving variability be reduced in autonomous cars, in order to prevent road crashes and have a performance with a minimum degree of emissions? This paper brings a literature review on this topic and an evaluation of methods that can be used to assess driving behavior patterns and their influence on road safety, pollutant and noise emissions.pt_PT
dc.language.isoengpt_PT
dc.relationDICA-VE (POCI-01-0145-FEDER-029463)pt_PT
dc.relationMobiWise (P2020 SAICTPAC/0011/2015)pt_PT
dc.relationCENTRO-01-0145-FEDER-022083pt_PT
dc.relationUID-EMS-00481-2019pt_PT
dc.rightsopenAccesspt_PT
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectDriving volatilitypt_PT
dc.subjectPollutant emissionspt_PT
dc.subjectSafetypt_PT
dc.subjectNoisept_PT
dc.titleDriving Information in a Transition to a Connected and Autonomous Vehicle Environment: Impacts on Pollutants, Noise and Safetypt_PT
dc.typeconferenceObjectpt_PT
dc.description.versionpublishedpt_PT
dc.peerreviewedyespt_PT
ua.event.date23 - 24 setembro 2019-
degois.publication.titleTIS ROMA 2019 - AIIT 2nd International Congress on Transport Infrastructure and Systems in a Changing World-
Appears in Collections:DEM - Comunicações
TEMA - Comunicações

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