Shirdhish Chakravarthi

Customer:- Stellantis

ECU:- ADAS System(L0,L1,L2,L2plus)

Advanced Driver Assistance Systems (ADAS) features testing over HIL benches

Feature Function testing :- HighwayAssist(HAS),Assisted Lane Change(ALC),Adaptive Cruise Control(ACC),Automatic Emergence Braking(AEB),Lane Keep Assist(LKA),Evasive Maneuver(ESA),Lane Split Module(LSM)),Lane Biasing(LB),Inane Safestop(ILSS)

Roles and Responsibilities:-

• Performed Restbus simulation using Simulink for the dSPACE HIL system.
• Integrated IPG Carmaker with dSPACE test bench setups.
• Modeled ADAS features for looping ECU outputs with Scalexio hardware.
• Developed AuD libraries and automated test sequences for feature testing.
• Estimated efforts for new projects and requirements, providing insights to management.
• Conducted test reviews and ensured adherence to quality standards.
• Delivered detailed presentations and live demonstrations to customers.
• Led daily stand-ups, defined sprint scopes, and coordinated tasks with engineers.
• Communicated effectively with clients, stakeholders, and management to align on objectives and project milestones.
• Mentored internal and external engineers through knowledge-sharing sessions and technical training programs.
• Coordinating Offshore and Onsite team for Product development (PDT) meetings, Software,Change Control Board (SCCB) meetings.

Protocols:- CAN,CAN-FD

Tools Used:- Carmaker,dSPACE tool chain,Simulink,DV tool.

Process tools:- Polarion,JIRA,Git Hub,Confluence

Customer: - FORD

ECU:- ADAS ECU(L0,L1,L2 Systems)

Description:-Advanced Driver Assistance Systems (ADAS) in the automotive industry use sensors like cameras and radar to enhance vehicle safety and driving comfort. Key features include Adaptive Cruise Control (ACC), Lane Departure Warning (LDW), Automatic Emergency Braking (AEB), and Blind-Spot Detection (BLIS). These systems improve situational awareness, reduce human errors, and support autonomous driving capabilities.

Roles and Responsibilities:-

• Responsible for verification and validation of ADAS vision and fusion features.
• Created scenarios and road environments for testing ADAS functionalities.
• Implemented automated testing frameworks in dSPACE (AuD) to validate software functionality and performance, reducing manual efforts and accelerating deployment cycles.
• Executed test scenarios in dSPACE to verify feature functionality.
• Developed test specifications, test cases, and AuD scripts.
• Created accident scenarios, SOTIF scenarios, and corner cases to validate the ADAS system.
• Developed tools such as Cyber Security Corrupter and Test Shell Creator.
  

Protocols:- CAN,CAN-FD

Tools Used:- dSPACE,Simulink,Canoe

Process tools:- Polarion,JIRA,Plastic-SCM

Customer:- SGM

ECU:- Camera

Project :- SGM K226 and K228

Description: The SGM 358 Sensor System provided by Aptiv is a single sensor system called a Forward-Looking Camera (IFV 300). This sensor detects traffic information in front of the car and provides data to vehicle control feature functions like LDW, FCA, and FDI to warn or inform the driver accordingly.

Roles and responsibilities:-

• Performed requirement analysis, developed test case designs, and automated test scripts.
• Managed defect tracking and resolution processes efficiently.
• Conducted CAR feature testing using video playback methods, including Lane Departure Warning, Lane Keeping Assist, Forward Collision Alert, and Low-Speed Automatic Emergency Braking.
• Worked on multiple modules such as Host SW, Vehicle CAN, LROS, XCP, DTCs, UDS services, CAN signal decoding, NVM testing, and feature inhibits.
• Performed cybersecurity testing, including bootloader and functional safety testing.
• Executed power waveform tests (PWTT), monkey testing, stress testing, robustness testing, and lesson-learned testing.
• Automated testing using test nodes and conducted peer reviews.
• Led team management activities, facilitated discussions with customers, and analyzed issues effectively.
• Developed tools including Report Analyzer, Variable Generator, Summary Generator, and an Automatic Reprogramming Tool using Python.

Protocols:- CAN

Tools used:- Canoe,DPS,PWTT.

Process tools:- Polarion,JIRA,Plastic-SCM

Customer :- FCA

ECU:- EPS

Project: TRW EPS Diagnostic testing/ Regression / 7z -Testing

Electric Power Steering (EPS) Gen3 column Drive in the automotive industry uses sensors like the torque sensor to detect the driver's steering input and adjust assistance accordingly. The steering angle sensor monitors the wheel position, ensuring stability and responsiveness, while the vehicle speed sensor adjusts steering effort based on speed. These sensors work together with the EPS control module to provide precise and efficient steering assistance.

Role and Responsibilities:

• Analyzed functional requirements and developed comprehensive test specifications and test cases using CAPL.
• Simulated test environments using CANoe for validation purposes.
• Validated application software to ensure adherence to specifications and performance standards.
• Created detailed Test Trouble Reports (TTRs) to document observed failures and support defect resolution.
  

Protocols: CAN,UDS

Tools used: CANalyzer, CANape, Diagnostic Engineering Tool, vflash

Languages: CAPL