Sensor Testing for Smart Mobility Scenarios: From Parking Assistance to Automated Parking

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dc.contributor.authorLarrauri, J. Murgoitio
dc.contributor.authorMuñoz, E. D. Martí
dc.contributor.authorRecalde, M. E. Vaca
dc.contributor.authorHillbrand, B.
dc.contributor.authorTengg, A.
dc.contributor.authorPilz, Ch.
dc.contributor.authorDruml, N.
dc.contributor.institutionCCAM
dc.contributor.institutionTecnalia Research & Innovation
dc.date.issued2019
dc.description.abstractVehicle automation is one of the major challenges of nowadays’ transport system and its goals are to achieve the ideal energy efficiency, the minimum environment impact and the highest safety rate. In this context, IoSense is the project which will deploy new capabilities (Sensors, Components and Systems) through several demonstrators, one of them called “SmaBility” (Smart Mobility scenarios). So, the intelligent perception and decision making for safer and autonomous driving are the main objectives of the SmaBility demonstrator focus on the “Automated parking”. Then this chapter firstly lists the capabilities in the design, modelling and simulation area of each partner (TECNALIA, IFAT and VIF) involved on the title “From Parking Assistance to Automated Parking” within the Smability. In a second stage, several simulations considering a Time-of-Flight (ToF) camera, as the main perception technology, are explained at both levels: Sensor (ToF) and System (Automated parking). In parking assistance scenario (system level), a ToF camera, similar to the previous one analysed at sensor level, is considered as substitute for ultrasonic range sensors. The expected advantages of using such camera include faster answer, better resolution and object recognition capabilities. Combining depth information with a vehicle geometry model and ego-information (position, speed, steering angle), it is possible to estimate distance to collision point and time to collision (TTC) with great accuracy. Finally, summary and conclusions are reported.en
dc.description.statusPeer reviewed
dc.format.extent35
dc.identifier.citationLarrauri , J M , Muñoz , E D M , Recalde , M E V , Hillbrand , B , Tengg , A , Pilz , C & Druml , N 2019 , Sensor Testing for Smart Mobility Scenarios: From Parking Assistance to Automated Parking . in unknown . Springer, Cham , pp. 331-365 . https://doi.org/10.1007/978-3-030-16577-2_12
dc.identifier.doi10.1007/978-3-030-16577-2_12
dc.identifier.isbn978-3-030-16576-5
dc.identifier.isbn978-3-030-16577-2
dc.identifier.otherresearchoutputwizard: 11556/829
dc.language.isoeng
dc.publisherSpringer, Cham
dc.relation.ispartofunknown
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsTime-of-Flight 3D sensor
dc.subject.keywordsRoad automation
dc.subject.keywordsSmart mobility
dc.subject.keywordsAutomated Parking
dc.subject.keywordsSimulation
dc.subject.keywordsSensors
dc.subject.keywordsTime-of-Flight 3D sensor
dc.subject.keywordsRoad automation
dc.subject.keywordsSmart mobility
dc.subject.keywordsAutomated Parking
dc.subject.keywordsSimulation
dc.subject.keywordsSensors
dc.subject.keywordsProject ID
dc.subject.keywordsinfo:eu-repo/grantAgreement/EC/H2020/692480/EU/Flexible FE/BE Sensor Pilot Line for the Internet of Everything/IoSense
dc.subject.keywordsinfo:eu-repo/grantAgreement/EC/H2020/692480/EU/Flexible FE/BE Sensor Pilot Line for the Internet of Everything/IoSense
dc.subject.keywordsFunding Info
dc.subject.keywordsH2020 | ECSEL-IA, 692480, IoSense
dc.subject.keywordsH2020 | ECSEL-IA, 692480, IoSense
dc.titleSensor Testing for Smart Mobility Scenarios: From Parking Assistance to Automated Parkingen
dc.typeconference output
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