Download Adaptive Cooperation between Driver and Assistant System: by Frédéric Holzmann PDF

By Frédéric Holzmann

One of the following demanding situations in vehicular expertise box is to enhance enormously the line safeguard. present advancements are concentrating on either automobile platform and numerous suggestions structures. This publication offers a brand new engineering strategy in accordance with lean automobile structure prepared for the drive-by-wire technology.

Based on a cognitive performance cut up, execution and command degrees are precise. The execution point centralized over the steadiness keep an eye on plays the movement vector coming from the command point. At this point the motive force generates a movement vector that is always monitored via a digital co-pilot. the mixing of assistance structures in a security suitable multi-agent method is gifted right here to supply first an sufficient suggestions to the driving force to allow him recuperate a perilous state of affairs. strong suggestions also are provided for the intervention section as soon as the command motor vehicle needs to be optimized to stick in the safeguard envelope.

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Additional info for Adaptive Cooperation between Driver and Assistant System: Improving Road Safety

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4 Local control of the predictive measures 47 Fig. 20. 20 shows the right recognition of cobblestones with a punctual patch. Even if the patch is an abrupt change of the road surface, it will be detected only with a small latency time that corresponds to the time needed for the Fourier analysis to measure the new stabilized frequencies. 4 Local control of the predictive measures In normal situation the checking algorithm is looking at the consistency of the results coming from both predictive estimation with a camera and reactive measurement with a microphone.

7), as estimation and as class. On the last sub-figure the difference between reactive and predictive measures can be detected after the time 25 s. Actually the predictive measure has not detected the surface change and will not provide a correct class. 21 shows also the limits of the estimation of the μ-coefficient. Actually, one can see the quick and continuous changes of the μ class by adding some noise to the estimations. Thus, the virtual driver is supposed to upgrade the minimal distances to other vehicles, the safe speed in a curve etc.

Fig. 2. Functions integrated into the vehicle platform 26 1 Requirements for the executive level (a) Realization time of each vehicle command (b) Extrapolation of the limits by use of the Kamm circle Fig. 3. Fusion of the envelope transfer functions by using the Kamm circle At the end, the model provides the maximal acceleration, minimal acceleration considering engine brake, minimal acceleration with brakes intervention and for maximal steering capacity. The transfer function describing the minimal acceleration with engine brake will not be sent to the command level, but instead will be used to select the best braking parameters.

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