Balancing Active and Passive Safety
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1 Balancing Active and Passive Safety Dnr: Cecilia Sunnevång Ulrich Sander, Ola Boström September 17 th, 2015 Driven for Life.
2 Background US legal & rating Automated Driving NHTSA Oblique (potential) Euro NCAP rating Rear Seat Improved passive Full Frontal Crash safety Human Machine Interface WorlSID Dummy Pedestrian Protection Autonomous Emergency Braking Far Side Protection (potential) Advanced sensors Driver monitoring System Highway assist incl. Overtaking function Traffic Jam Assist incl. Active steering Semi-auto Parking function Balance between passive and active safety necessary! Year Severe accidents with injured car occupants (Germany, Source: Destatis/GIDAS) Source: T. Unselt, Daimler, VDI conference 2013
3 Balancing Active and Passive Safety Objective Develop a methodology for prospective effectiveness estimations of present and future in-vehicle safety systems.
4 Severe Accidents, car - car GIDAS , MAIS3+F 2020 LSS AEB ESC SLA FCW AEB LDW BLIS Text inside column = System on the market
5 Virtual Tool for Integrated Safety Vehicle model Road environment Driver behavior and occupant model PRAEDICO = Prediction of Accident Evolution by Diversification of Influence factors in Computer simulation
6 Virtual Tool for Integrated Safety Input - Accident Reconstruction & Output - Baseline Simulation Baseline: Collision Speed: 93 km/h
7 Simulation Left turn across Baseline ADAS turning Today ADAS oncoming ADAS turning & oncoming Added benefit?
8 PRAEDICO Simulation Scenarios Baseline ADAS Turning ADAS Turning and Oncoming
9 Simulation Results ADAS turning ADAS turning 100,0% Vehicles are equipped with ADAS turning Remaining Accidents 90,0% 80,0% 70,0% 60,0% 50,0% 40,0% 30,0% 20,0% 10,0% 0,0% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Fleet Penetration Warning, turning vehicle AEB, turning vehicle
10 Simulation Results ADAS turning & oncoming ADAS turning & oncoming 100,0% Vehicles are equipped with ADAS turning and oncoming Remaining Accidents 90,0% 80,0% 70,0% 60,0% 50,0% 40,0% 30,0% 20,0% 10,0% 0,0% 0% 20% 40% 60% 80% 100% Fleet Penetration Warning, turning & oncoming vehicle AEB, turning & oncoming vehicle
11 Simulation Results ADAS turning AEB turning - Impact type of reamining accidents Front Impacts Right Side Impacts Left Side Impacts Impact Type 100,0% 90,0% 80,0% 70,0% 60,0% 50,0% 40,0% 30,0% 20,0% 10,0% 0,0% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Market Penetration AEB - turning - Closing velocity of remaining accidents Closing Velocity [km/h] Front Impact Mean-Cl.V Right Side Impact Mean-Cl.V Left Side Impact Mean-Cl.V 80,0 70,0 60,0 50,0 40,0 30,0 20,0 10,0 0,0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Market Penetration
![Penetration AEB - turning - Closing velocity of remaining accidents Closing Velocity [km/h] Front Impact Mean-Cl.](/docs-images/44/17086788/images/page_11.jpg "V Right Side Impact Mean-Cl.V Left Side Impact Mean-Cl.")
12 Conclusions Virtual tool for pre-crash evaluation developed Important to consider car fleet penetration to evaluate accident avoidance and mitigation Absolute number of left side impacts increases Output of from the virtual tool drives the input for the design of passive safety!
13 Balancing Active and Passive Safety - Future Accident data Real life data Test scenario Occupant injury risk
14 Balancing Active and Passive Safety - Future Occupant injury risk evaluation using crash test dummies: THOR (frontal/oblique) WorldSID (side) For complex scenarios and multiple iterations human body models are needed!
15 Balancing Active and Passive Safety - Future Expand virtual simulation tool P.E.A.R.S Driver behaviour Comfort bounderies Improve Human Body Models Injury prediction (FFI) Muscular response (FFI)
16 Every year, Autoliv s products save over 30,000 lives
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