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dc.contributor.authorMeuser, Tobias
dc.contributor.authorStavrakakis, Ioannis 
dc.contributor.authorFernández Anta, Antonio 
dc.contributor.authorSteinmetz, Ralf 
dc.date.accessioned2021-07-13T09:39:16Z
dc.date.available2021-07-13T09:39:16Z
dc.date.issued2019-10-14
dc.identifier.urihttp://hdl.handle.net/20.500.12761/735
dc.description.abstractAdvanced Driver Assistance Systems require atremendous amount of sensor information to support the driver’scomfort and safety. In particular, systems that provide (good)route options to a vehicle rely on information, such as traffic jamsand road blockages, which is sensed by other (possibly distant)vehicles and distributed by a central server. This information isclearly dynamic and may be invalid by the time the vehicle arrivesat the affected location. In this work, we develop an innovativeapproach to determine optimal routes (minimizing the costs liketravel-time to their destination) for vehicles whose original routeis adversely impacted by a (severe) road event. The route is inprinciple reassessed just before each upcoming road intersection(decision-point), considering updated information about the roadevent and an estimate of the remaining lifetime of the road event.A set of recursive equations is developed that yields the optimaldecision for each vehicle at each decision-point, accounting foraspects such as the vehicle’s destination, driver characteristics,etc. In practice, the decision may be taken by the vehicle itself (ifall the needed information is transferred to it), or by the remoteserver and be communicated to the vehicle (if all needed privatevehicle information is transferred to the server). A discussion ispresented, along with some ideas, their assessment, and associatedtradeoffs, aiming at reducing communications costs. Simulationsshow that our approach adapts to the considered event andfinds routes of similar quality as a full-knowledge approach withlimited communication overhead.
dc.language.isoeng
dc.titleDynamic Vehicle Path-Planning in the Presence of Traffic Eventsen
dc.typeconference object
dc.conference.date14-17 October 2019
dc.conference.placeOsnabrück, Germany
dc.conference.titleThe 44th IEEE Conference on Local Computer Networks (LCN 2019)*
dc.event.typeconference
dc.pres.typepaper
dc.type.hasVersionVoR
dc.rights.accessRightsopen access
dc.subject.keywordDemand-driven
dc.subject.keywordvehicular networks
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttp://eprints.networks.imdea.org/id/eprint/2031


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