1,720,977 research outputs found
Application of Non-Linear Model Predictive Control to the Driving Task
No full textThe previous research on the application of Model Predictive Control (MPC) to aspects of driving a vehicle is considered and extended. The control algorithm differs significantly from previous work and complements previous studies by the application of MPC in the nonlinear domain. A virtual rider for the guidance of a nonlinear vehicle model has been created. The control algorithm is built considering two main loops: one
for the real world and one for the mental world in which the driver predicts the future states of the vehicle. Due to its formulation this method can be called Time-Variant MPC (TV-MPC), and it is loosely comparable with a multi-model MPC approach, but the solution is not dependent on the displacement about a trim state but only on the time step defined in the integration settings. The TV-MPC driver capability is assessed by U-turn manoeuvres and considerations on the effective preview distance and on the information used by the driver in order to accomplish the task are included
Vehicle and driver modeling and threat assessment for driving support functions
No full textThe article reports a novel method to assess the driving risk level and design a human friendly
warning strategy. The method is built on a Receding Horizon (RH) approach that is instanced for a
set of predefined driving scenarios such as driving in the lane, change lane, etc. In control field, the
RH is a technique that solves a sequence of optimization problemin real-time and, at each time step,
applies only the first value of the control plan to steer the system towards a desired behavior. In this
work, differentlythan in the control application, the initial value of the each control plan is used as a
measure of the correction that the rider should apply to conform to the computed optimal maneuver.
This choice has the advantage to provide an homogenous measure of the threat independently from
the scenario and it is directly linked with the control variable that the rider should use to accordingly
changethevehicledynamics. Additionally,theRH approachnaturallyaccommodatesroadgeometry
and attribute constraints, vehicle dynamics, driving input and styles. A proper development of the
vehicle model and a quantitative characterization of the human driving skills play an important role
in the method effectiveness. Additionally the method make use of a dedicated solver to compute the
probleminrealtime. Themethodwas appliedwithsuccess todevelopdrivingsupportfunctionsboth
for cars in the the FP6th European project PReVENT and the FP7th interactIVe and for motorcycles
in the FP7th European Project SAFERIDER.
The article introduces the RH approach as defined for the driving threat assessment. Then it
discusses in details the vehicle modelling requirements and how human driving skills are included
in the proposed method. Examplary use of how the system works in different driving scenario will
be given. Finally, the experimental results of pilot tests are shown for all the developed applications
Advanced Rider Assistance Systems for motorcycles
No full textThis paper illustrates the Advanced Rider Assistance Systems (ARAS) developed at the University
of Padova within the European Research project SAFERIDER (www.saferider-eu.org), which aims
at studying the potential of ARAS to enhance rider safety, comfort and, hopefully, reduce fatalities.
Three different ARAS functions have been designed, implemented and validated with a common
architecture: the Curve Warning (CW), Frontal Collision Warning (FCW) and Intersection Support
(IS). These systems are able to detect in advance potential dangerous situations and warn the rider
by means of suitable Humane Machine Interface (HMI) elements.
This paper explains in detail SAFERIDER ARAS concepts, illustrates their integration first into
the riding simulator of the University of Padova and then into a real vehicle for final validation, and
finally summarize pilot tests results. ARAS systems are organized into a three layers architecture:
perception, decision and action. As shown in Figure 1, the perception layer includes sensors like
GPS, Inertial Measurement Unit and Laser scanner. Sensors are connected to a dedicated CAN bus
that gathers scenario information to the decision layer. The latter consists of the ARAS Control
Module, which actually is a PC/104+, and manages ARAS software, i.e. a Scenario Reconstruction
module. This module produces a consistent estimate of the vehicles state of motion and position,
which are the input of FCW, CW and IS modules. These modules evaluate the risk of the riding
according to the scenario and drive the action layer, which includes the HMI manager and a set of
HMI elements (visual display, haptic handle, vibratinggloveand helmet) employedto warn the rider
on acoustic, visual and tactile channels
Application to cycling of a bioenergetic model: Towards a multi-level biomechanical model for global cyclist performance analysis
No full textModels of bioenergetic systems are developed to explain how a biological system behaves while interacting with the environment. Recent attempts in sport science research advocate the evidence-based training prescription and performance assessment and help in translating laboratory-based research into real world practice by the means of bioenergetic models. Such models have been developed for cycling activity for constant work rate or intermittent exercise for a single training session (e.g. critical power CP model and reconstitution of the anaerobic work capacity, (Chidnok et al., 2012, Medicine & Science in Sports and Exercise, 44(5), 966-976)), as well as for describing how the performance capacity changes over time (Clarke & Skiba, 2013: Advances in Physiological Education, 37, 134-152). The model here adopted (Moxnes et. al, 2012, Theoretical Biology and Medical Modelling, 9:29) claims to predict both oxygen consumption (V’O2) and lactate production [La]’ dynamically at a given power output requirement. In this work we model the bioenergetics processes involved in human exercise and recovery for the case of a cyclist in outdoor training
Experimental and Theoretical Study of Motorcycle Transfer Functions for Handling Evaluation
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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