Model-based Development for Vehicular Embedded Systems
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The document discusses model-based development for vehicular embedded systems. It outlines the Model-based Engineering of Embedded Systems research group, which has 16 research projects and focuses on model-based engineering and real-time systems design. The document then discusses the background of vehicular embedded systems, noting their increasing complexity, size of code, and challenges of multi-core platforms. It proposes a solution of a model-based software development methodology supporting early timing analysis. Key aspects are reducing accidental complexity, early timing verification, and support for uncertainty and multi-core platforms. An example of an intelligent parking assist system is used to illustrate the methodology.
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Model-based Development for Vehicular Embedded Systems
- 1. Model-based Development for Vehicular Embedded Systems Alessio Bucaioni 13-10-2016 STEW 2016 Arcticus Systems
- 2. 2 OUTLINE • MESS RESEARCH GROUP • BACKGROUND • PROBLEM FORMULATION • PROPOSED SOLUTION • UNIQUENESS • RUNNIN EXAMPLE • ACCADEMIA-INDUSTRY TRANSFER
- 3. 3 MODEL-BASED ENGINEERING OF EMBEDDED SYSTEMS RESEARCH GROUP 16 research projects 15 members Born in 2011 as a spin-off from the ”Real-Time System Design” group 2 main research areas
- 4. 4 0 5 10 15 20 25 30 35 2011 2012 2013 2014 2015 2016 Numberofpublications Years Conference Paper Doctoral Thesis Licentiate Thesis Book Chapter Journal Article MODEL-BASED ENGINEERING OF EMBEDDED SYSTEMS RESEARCH GROUP
- 5. 5 Arcticus Systems MODEL-BASED ENGINEERING OF EMBEDDED SYSTEMS RESEARCH GROUP
- 6. 6 BACKGROUND – VEHICULAR EMBEDDED SYSTEMS PARENTAL CONTROL WINDSHIELD WIPER CONTROL ENGINE CONTROL AIRBAG DEPLOYMENT ADAPTIVEFRONT LIGHTING ADAPTIVECRUISE CONTROL AUTOMATIC BRAKING ELECTRICPOWERSTEERING ELECTRONIC THROTTLE CONTROL ELECTRONICVALVE TIMING IDLE STOP/START CYLINDER DE-ACTIVATION ACTIVE VIBRATION CONTROL OBDII REMOTE KEYLESS ENTRY BLINDSPOT DETECTION LANE DEPARTURE WARNING TRANSMISSIONCONTROL SEATPOSITION CONTROL ACTIVEYAW CONTROL PARKING SYSTEM ELECTRONIC STABILITY CONTROL ANTILOCK BREAKING TIREPRESSURE MONITORING NIGHT VISION HEAD-UP DISPLAY DRIVERALERTNESS MONITORING INSTRUMENT CLUSTER ACCIDENT RECORDER EVENTDATA RECORDER AUTO-DIMMING MIRROR INTERIOR LIGHTING ACTIVECABINNOISE SUPPRESSION VOICE/DATA COMMUNICATION CABINENVIRONMENT CONTROLS DSRC ENTERTAINMENTSYSTEMS BATTERYMANAGEMENT LANECORRECTION ELECTRONIC TOLLCORRECTION DIGITALTURN SIGNALS NAVIGATIONSYSTEM SECURITYSYSTEM ACTIVEEXHAUST NOISESUPPRESION RIGENERATIVE BREAKING ACTIVESUSPENSION HILLHOLD CONTROL Courtesy of www.volvo.com
- 7. 7 BACKGROUND - VEHICULAR EMBEDDED SYSTEMS “More than 80 percent of vehicle innovation comes from embedded systems” - MANFRED BROY Professor of informatics at Technical University, Munich
- 8. 8 0 50000000 100000000 150000000 200000000 250000000 300000000 350000000 Late 1970s Nowadays Linesofcodes Years Size of vehicular embedded software BACKGROUND - VEHICULAR EMBEDDED SYSTEMS
- 9. 9 BACKGROUND - VEHICULAR EMBEDDED SYSTEMS Courtesy of www.bmw.com
- 10. 4,5 times more expensive Multi-core platforms 25% longer schedules 3 times as many software engineers 6 * S. Balacco, C.Rommel. Next Generation Embedded Hardware Architectures:Driving Onset of Project Delays, Costs Overruns and Software Development Challenges. Klockwork Inc. 2010. BACKGROUND - VEHICULAR EMBEDDED SYSTEMS ON MULTICORE
- 11. BACKGROUND - MODEL-DRIVEN ENGINEERING 11 - BRAN SELIC Father of Real-Time UML “As our systems grow in complexity traditional code- centric development methods are becoming intractable”
- 14. 14 Vehicle Level Analysis Level Design Level Implementation Level Activities Abstraction levels Format Capture requirements on E2E vehicle functionality Consistency analysis of requirements. Functional verification Prototyping, system properties, timing and resource analysis. Complete SW architecture Modelling of features. SW architecture, HW architecture, SW to HW allocation, Often informal. Textual. Solution-independent Formal, model-based. Allocation independent Formal, model-based. Implementation-independent. Formal, model-based. Implementation details. BACKGROUND – EAST-ADL
- 15. 15 PROBLEM FPRMULATION - PONTUS DE LAVAL CTO at Saab AB “It is so much cheaper to find defects at design time”
- 16. 16 PROPOSED SOLUTION - MY RESEARCH IN A NUTSHELL Model-based software development methodology which supports early timing analysis for vehicular embedded systems. Design Level Implementation Level Timing analysis
- 17. 17 PROPOSED SOLUTION - METHODOLOGY Analysis results M2M transformation Timing analysis & filter Analysis results M2M in-place transformation DesignlevelImplementationlevel EAST-ADL design model u-Rubus model u-Rubus model with analysis results Negative feedback
- 18. 18 UNIQUENESSES – WHAT DO YOU GAIN ? • Reduce accidental complexity • Early timing verification • Support uncertainty • Support for multi-core
- 19. RUNNING EXAMPLE: INTELLIGENT PARKING ASSIST 19 Proximity_Sensor_DFP Input_Process_DFP Path_Calculator_DFP CAN_Send_DFP CAN_Receive_DFP Control_DFP Brake_Actuator_DFP IPAssistant_DFP Actuator_DFP 15 ms 20 ms
- 20. 20 (1) (2) (3) (4) Software Circuit Clock Connector data Connector trigger Data ports Trigger ports Timing constraints Timing constraints RUNNING EXAMPLE: INTELLIGENT PARKING ASSIST Reduce complexity Support uncertainty
- 21. 21 Timing analysis has filtered the solution space. However there are still 14 RCM models to inspect. (1) (2) (3) Software Circuit Clock Connector trigger Trigger ports RUNNING EXAMPLE: INTELLIGENT PARKING ASSIST Early timing verification
- 22. 22 Support uncertainty RUNNING EXAMPLE: INTELLIGENT PARKING ASSIST
- 23. 23 METHODOLOGY FOR MULTICORE START Functional Model RubusMM_SW Platform Model RubusMM_HW M2M Transformation JTL Execution Models μ-RubusMM_SW + Timing Model-based Timing Analysis Modify the Allocation Models Modify the Functional Model Code Generation END Are the Timing Requirements Met? Is It a Single-core Platform? Are all the Allocations Model checked? YES NO NO YES YES NO
- 24. 24 MEES CONTRIBUTIONS Vehicle Level Analysis Level Design Level Implementation Level Abstraction levels Contribution of the MEES research group finished contribution ongoing contribution Rubus Component Model (RCM) RCM metamodel definition (RubusMM) Exact RTA RTA for CAN and high level protocol, e.g., HCAN, CANopen E2E response time E2E delays, e.g., age and delay Shared stack analysis Switched ethernet SWEET benchmark Extensions for multi-core platforms RubusMM extensions for multi-core platforms Model-based methodology for early predictability Predictability enabled on design assumptions Predictability enabled for legacy nodes RubusEASTandtranslationofTADL2constraints
- 25. 25 ACADEMIA-INDUSTRY TRANSFER MDH BASEMENT SaveComp ProSave EMDEF FEMMVA SynthSoft RCM 1&2 RCM 3 RCM 4 Extension of timing analysis, modelling support Multicore Arcticus 1994 1996 2002 2005 2005 2012 2009 2012 2014 2014 2018 RCM 4 +
- 26. 26 ACADEMIA-INDUSTRY TRANSFER Arcticus Systems Requirements, Existing tools, Certified RTOS Methods, Technbiques, Prototypes
- 27. Thank you for the attention! Questions?