IMPROVING ADAS VALIDATION WITH MBT
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1 Sophia Antipolis, French Riviera October 2015 IMPROVING ADAS VALIDATION WITH MBT Presented by Laurent RAFFAELLI ALL4TEC
2 AGENDA What is an ADAS? ADAS Validation Implementation Using the Results Applicability against Standards To Conclude 2
3 WHAT IS AN ADAS? Advanced Driver Assistance Systems
4 What is an ADAS? ADAS missions : Warn the driver Message on screen Vibrations on steering wheel Sound signal Take control of the vehicle Torque on steering wheel Autonomous Braking 4
5 What is an ADAS? More and more functions are available : Lateral guidance : LDW (Lane Departure Warning), LKA (Lane Keeping Assist) Longitudinal guidance : AEB (Autonomous Emergency Braking) Park the car : PA (Park Assist) Adapt the front light source : AFS (Advanced Front lighting System), AHA (Adaptive High beam assist) Regulate the speed of the car : ACC (Adaptive Cruise Control) And so on 5
6 ADAS VALIDATION How validate an ADAS?
7 The ADAS Validation The System under Test : Sensor(s) Situation Analysis ADAS Decision 7
8 The ADAS Validation Signal sent by the camera : Y pixels X pixels Need to reduce the number of possible stimuli 8
9 The ADAS Validation ADAS Validation by driving test Use of video sequence libraries But this has many drawbacks : Driving situations are limited have a bad representativeness are costly 9
10 IMPLEMENTATION The COVADEC Methodology
11 Implementation Purpose : Prove that the ADAS behavior is compliant with safety goals Validate the reliability of the ADAS function How : By using a sufficiently representative test campaign to measure if the safety goals are achieved 11
12 Implementation Terminology : Influent Parameter : Parameter of ADAS environment which has an influence on ADAS behavior and response Test Case : Short video sequence for which for each Influent Parameter a value is selected from one of the possible Equivalence Classes Equivalence Class : A set of values associated with an Influent Parameter for which the ADAS behavior and response are assumed to be the same 12
13 Implementation Pre requisites : System Under Test : ADAS with camera sensors Identification of influent parameters and associated probabilities (usage profiles) It must be possible to simulate influent parameters Probabilities distributed in such a way that there are a lot of duplicate test cases ADAS algorithms must be available at a level (HIL, MIL, SIL) for which simulation is available 13
14 Implementation Phases : 1. Identification of influent parameters 2. Identification of dependencies between parameters 3. Identification of statistical profiles and equivalence classes 4. Identification of reliability goal 5. Construction of a test model 6. Generation of test cases 7. Execution of test cases on simulation tools 8. Identification of problem cases 9. Conclusion on reliability objectives 14
15 Implementation Methodology goals : Build quickly on request and with reduce cost a test campaign equivalent to hundreds of thousand kilometers With Good representativeness of : Road environments Weather conditions 15
16 Implementation Test effort reduction : Time to test in hours 72 h 24 h 36 h 360 h Equivalent time of driving in hours 16
17 USING THE RESULTS How the test campaigns database can be used
18 Using the Results Results are test campaigns with a set of test cases representative of thousands of kilometers of driving Generate database of computer generated images Provide input for the selection of the test drives 18
19 Using the Results Use for test automation : MBT Tool Test Cases Configuration Test Results Test Server Initiate video sequence Video Simulator Simulated Video + CAN data Initiate ADAS Algorithms ADAS Module Simulation (MIL, SIL, HIL) ADAS Decision Simulation Data Test Oracle Test Oracle Decision 19
20 APPLICABILITY AGAINST STANDARDS Conformance with automotive safety standards
21 Applicability against Standards ADAS are not covered by the ISO standard (Road Vehicles Safety) : ISO does not address the nominal performance of E/E systems ADAS errors are not security related events as defined by ISO
22 Applicability against Standards A new automotive standard (ISO evolution) is currently being prepared : For ADAS For autonomous vehicle The COVADEC project is, with other R&D projects, used to integrate new concepts and prepare for this future standard. 22
23 TO CONCLUDE Conclusion
24 To Conclude The proposed methodology shall be one of the one of the methods provided by the future standards It will not replace real driving test, but would be used to maximize efficiency of test validation What we are seeing today is the beginning of an era where cars will become more and more autonomous 24
25 Thank you Questions? 25
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