TUSHAR P. PEDKAR

• Total Experience: 5+ years as a Software Developer in the automotive domain.
• Methodologies: Expertise in Agile, SCRUM, and V-Model software development methodologies.
• Technical Proficiency: Advanced skills in Model-Based Design (MBD) with MATLAB, SIMULINK, Stateflow; proficient in Model-in-the-Loop (MIL), Test Performance Tool (TPT), and Build & Integration; skilled in auto-code generation with Real-Time Workshop (RTWEC); extensive experience with ARXML files for system configuration and software components, MIL & SIL testing, unit testing, and developing Model Advisor Checks for Simulink Verification & Validation (MAAB).
• Requirements Management: Proficient in DOORS for requirements management, gathering system-level requirements, and drafting robustness use cases for EURO NCAP documents.
• Ensured compliance with ISO-26262 safety standards, focusing on traceability from system-level to software functional requirements. Managed updates to NCAP regulations, created use cases in MagicDraw (MD), and wrote scenarios in DOORS to maintain safety and compliance throughout the development process.
• Basic understanding of TRACE32 and configuring CANoe tools for validation.
• Basic with AUTOSAR architecture, including the application layer, RTE, and BSW, with basic experience in configuring AUTOSAR components.
• Team Leadership: Leads retrospective and weekly meetings, promoting team collaboration and continuous improvement.

• Developed Lane Keeping Assist (LKA) systems by designing, simulating, and validating lane boundary detection and corrective steering algorithms, ensuring high accuracy in real-world scenarios.
• Conducted comprehensive model testing and coverage reporting to verify system performance and ensure reliability across various conditions and scenarios.
• Performed Model-in-the-Loop (MIL) and Unit Testing, generating application component code, ensuring thorough verification of system functionality.
• Managed requirements and test plans, ensuring full traceability from system-level to software requirements, while maintaining alignment with client expectations and industry standards.
• Ensured compliance with ISO-26262 and other regulatory safety standards by creating use cases, writing detailed scenarios, and adhering to relevant guidelines throughout the development process.
• Developed advanced lane detection algorithms, integrated sensor fusion from multiple sources, and validated results using MATLAB scripts to improve system performance.
• Created and applied custom Model Advisor checks to ensure code quality and adherence to best practices, while analyzing and addressing software defects to enhance reliability.
• Coordinated with the Client team, generating clear and organized delivery folders and facilitating thorough review processes to meet project milestones.
• Developed scalable and maintainable code, ensuring long-term stability of the software.

Objective: Create a labeled dataset for machine learning to recognize trailer coupling by vehicle hitch balls.

Focus: Annotate data to improve ADAS and autonomous systems in handling real-world challenges with trailer coupling, especially under various environmental conditions (dull, sunny, snowy, rainy).

• Lead Trailer Annotation Project , managing an 8-member team, assigning tasks, and conducting daily status meetings and weekly client connect sessions.
• Coordinated the project using Jira for task management, ensuring timely delivery of milestones on AWS, and collecting requirements from AWS tools.
• Utilized MATLAB for image processing, run Python scripts for image enhancement, and oversaw the annotation of images, reviewing JSON files, and uploading data to HATCI's AWS system.
• Ensured data quality, maintained efficient workflows, balanced technical and support tasks to aid ADAS development, and communicated progress and updates with stakeholders, addressing any issues promptly.
• The project focused on annotating scenarios where environmental factors affect trailer coupling, with the goal of training machine learning models to recognize these conditions and improve ADAS and autonomous systems.

• Worked with ladder chassis , a robust vehicle frame designed for heavy loads and off-road driving due to its durability and high ground clearance.
• Provided technical support during the development and testing phases of chassis-related projects.
• Researched new technologies and materials to improve chassis performance and efficiency.
• Developed logic for new functionalities, added attributes to the data dictionary in the client database, and generated delivery folders for review.
• Conducted unit-level testing using Signal Builder based on low-level requirements.
• Validated models through MIL to ensure compliance with new requirements.
• Analyzed proposals, provided feedback to the technical team, and updated Requirement and Test Plans in IBM DOORS.
• Analyzed defects and identified root causes using the TPT tool.
• Actively learned new technologies and adapted to evolving tasks and requirements.

• AEB System Development : AEB is a safety feature that automatically applies the vehicle's brakes if a collision is imminent, helping to prevent or reduce the severity of accidents.
• Assisted in the development and testing of Advanced Emergency Braking (AEB) systems.
• Supported the integration of AEB features with vehicle safety systems.
• Helped gather and analyze requirements for the AEB system to ensure they were accurately captured.
• Worked with IBM DOORS to track and link AEB requirements to system components.
• Conducted basic testing and supported model validation to meet functional requirements.
• Assisted in ensuring AEB systems met safety standards, including Euro NCAP compliance.
• Supported the identification and resolution of defects using testing tools like TPT.