Search results for "car-following"

showing 2 items of 2 documents

Car following: Comparing distance-oriented vs. inertia-oriented driving techniques

2018

The rationale behind most car-following (CF) models is the possibility to appraise and formalize how drivers naturally follow each other. Characterizing and parametrizing Normative Driving Behavior (NDB) became major goals, especially during the last 25 years. Most CF models assumed driver propensity for constant, safe distance is axiomatic. This paper challenges the idea of safety distance as the main parameter defining a unique (or natural) NDB. Instead, it states drivers can adapt to reactive and proactive car following. Drawing on recent CF models close to the Nagoya paradigm and on other phenomena (e.g., wave movement in Nature), we conceived car following by Driving to keep Inertia (D…

EngineeringInjury controlmedia_common.quotation_subjectDriving techniquesGeography Planning and DevelopmentPoison controlTransportationInertia01 natural sciencesCar following0502 economics and business0103 physical sciences010306 general physicsSimulationAxiommedia_common050210 logistics & transportationCar-following modelsbusiness.industry05 social sciencesDriver behaviorDriving simulatorPsychological paradigmsTRIPS architecturebusinessConstant (mathematics)
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Real-time smoothing of car-following data through sensor-fusion techniques

2011

Abstract Observation of vehicles kinematics is an important task for many applications in ITS (Intelligent Transportation Systems). It is at the base of both theoretical analyses and application developments, especially in case of positioning and tracing/tracking of vehicles, car-following analyses and models, navigation and other ATIS (Advanced Traveller Information Systems), ACC (Adaptive Cruise Control) systems, CAS and CWS (Collision Avoidance Systems and Collision Warning Systems) and other ADAS (Advanced Driving Assistance Systems). Modern technologies supply low-cost devices able to collect time series of kinematic and positioning data with medium to very high frequency. Even more da…

sensor fusionEngineeringbusiness.industryVehicle controlControl engineeringKalman filterData fusionTracingSensor funsionSensor fusionADASNavigationcar-followingV2VInformation systemGeneral Materials ScienceKalman filterITSbusinessACCIntelligent transportation systemCruise controlCollision avoidanceSmoothingProcedia - Social and Behavioral Sciences
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