Driver - Vehicle Environment simulation. Mauro Marchitto Kite Solutions



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Transcription:

Driver - Vehicle Environment simulation Mauro Marchitto Kite Solutions

Summary From the DVE to the SSDrive tool Overview of SSDrive model Matlab Simulink SSDrive model SSDrive model validation: VTI driving simulator test Preliminary results. VTI data vs SSDrive prediction 1/2 & 2/2 SSDrive final release Driver model Environment model Images of SSDrive simulator final release 1/3, 2/3 & 3/3

From the DVE to the SSDrive tool The theoretical formulation of the Embedded Driver Vehicle Environment system was reproduced on a numerical simulation called SSDrive (Simple Simulation of Driver).

Overview of SSDrive model Driver s decision making: Attain higher speed, change lane, overtake, maintain speed Error generation Permanent tasks: keep lateral safety margins, keep longitudinal safety margins Normative and descriptive driver behaviour. Main parameters describing the Driver model: Experience Attitude Task Demand (TD) Situation Awareness (SA) Driver State (DS)

Matlab Simulink SSDrive model The first release of the SSdrive was developed in Simulink, Firstly with model of steering based on Control Theory. Then by means of an approach based on Proprioceptive and visual anticipation & Empirical Correlations

SSDrive model validation: VTI driving simulator test The test involved 36 persons divided into Novice, Average and Professional drivers (according to their age and driving experience). Drivers were asked to drive in a 60 km dry road maintaining a 90km/h speed An on board display simulated the activation of an IVIS (HASTE arrow task) Three driving events (e.g. pedestrian crossing) caused the driver to slow down. Data on driver behaviour (steering wheel angle, speed, lateral position, etc.) were recorded to validate the SSDrive system. The VTI driving simulator Driving scenario and tasks Collection of data (e.g. steering angle variation) for SSDrive validation

Preliminary results: VTI data vs SSDrive prediction 1/2 Observed measures of driver behaviour on VTI driving simulator vs SSDrive model prediction Predicted steering angle (deg) vs driven distance (m) Observed steering angle (deg) vs driven distance (m)

Preliminary results: VTI data vs SSDrive prediction 2/2 Comparing observed mean values from the SSDRIVE simulation with those supplied from the experiments in the VTI simulator, small differences are found (19%). Predicted lat. dist. from lane centre-line (m) vs driven dist. (m) Observed lat. dist. from lane centre-line (m) vs driven dist. (m) in VTI Simulator

SSDrive final release C++ code which relies on Delta3D library Input: STAGE Lua Lua script Output: Log files SSDrive Main Engine VR Simulation STAGE Delta3D suite Log files VR simullation

Driver model V Position Speed ADAS, IVIS and OBS states E Road data Weather Sun position Obstacles Control warning Decision model Task selection process DEP and error generation Desired Path Desired Speed Control model Proprioceptive and visual anticipation Empirical Correlations Steering angle Accelerator position Brake position Tasks DEP ADAS, IVIS and OBS commands

Environment model VR representation Road model Road shape, signs, restrictions Traffic model V( t) = fvi (, t) i P( t) = P( t 1) + V( t) Δt i i i Obstacles Weather model Weather condition Sky dome model Sun position

SSDrive final release 1/3 Driver parameters, vehicle configuration and traffic conditions are set with the STAGE Editor Interface

SSDrive final release 2/3 Follow Overtake: Change Lane

SSDrive final release 3/3 Different initial conditions lead to different dynamics