Electronic Control Unit (ECU) - Practical Vector Training Course

This instructor-led, live training in India (online or onsite) is aimed at advanced-level robotics engineers and AI researchers who wish to implement sophisticated path planning algorithms to enhance autonomous vehicle performance.

By the end of this training, participants will be able to:

• Understand the theoretical foundations of advanced path planning algorithms.
• Implement algorithms such as RRT*, A*, and D* for real-time navigation.
• Optimize path planning for obstacle avoidance and dynamic environments.
• Integrate path planning algorithms with sensor data for enhanced accuracy.
• Evaluate the performance of various algorithms in practical scenarios.

This instructor-led live training in India (available online or onsite) is designed for advanced data scientists, AI specialists, and automotive AI developers who aim to build, train, and optimize AI models for autonomous driving applications.

By the conclusion of this training, participants will be able to:

• Comprehend the basics of AI and deep learning within the context of autonomous vehicles.
• Execute computer vision techniques for real-time object detection and lane following.
• Leverage reinforcement learning for decision-making in self-driving systems.
• Incorporate sensor fusion techniques to improve perception and navigation.
• Create deep learning models to predict and analyze driving scenarios.

AUTOSAR (AUTomotive Open System ARchitecture) is a global collaborative effort among automotive OEMs, suppliers, and tooling vendors to standardize the software architecture for electronic control units (ECUs) in vehicles.

This instructor-led live training (available online or at your facility) targets intermediate to advanced automotive software engineers looking to design, develop, and integrate software leveraging both AUTOSAR Classic and Adaptive platforms, with a special emphasis on ADAS (Advanced Driver Assistance Systems).

Upon completing this training, participants will be equipped to:

• Grasp the architectures of AUTOSAR Classic and Adaptive, along with their primary distinctions.
• Create and configure automotive software components using tools compliant with AUTOSAR standards.
• Integrate and validate ADAS software components within AUTOSAR Adaptive environments.
• Implement best practices for safety, security, and performance optimization in automotive systems.

Course Format

• Engaging lectures and interactive discussions.
• Practical exercises using industry-standard AUTOSAR tools.
• Project-based learning with simulations of real-world automotive scenarios.

Customization Options

• To arrange a customized training session for this course, please reach out to us.

This instructor-led live training in India (online or onsite) is primarily aimed at engineers who wish to use AUTOSAR to design automotive components.

By the end of this training, participants will be able to:

• Install and configure AUTOSAR.
• Set up a workflow.
• Navigate smoothly in the AUTOSAR environment.
• Work efficiently.

This instructor-led, live training (available online or onsite) is designed for intermediate-level embedded software developers and automotive engineers who want to leverage the AUTOSAR Classic Platform to develop, integrate, and test standardized software components for electronic control units (ECUs).

Upon completion of this training, participants will be able to:

Install and configure AUTOSAR development tools (such as DaVinci Developer, EB Tresos, or ETAS ISOLAR-A/B).

Comprehend the AUTOSAR layered architecture and its basic software modules (BSW).

Design and implement the AUTOSAR OS and communication stack (COM stack).

Utilize CANoe or similar tools for simulation, testing, and diagnostics within an AUTOSAR environment.

This instructor-led, live training in India (online or onsite) is aimed at automotive engineers who wish to use AUTOSAR to design automotive motor controllers.

By the end of this training, participants will be able to:

• Understand AUTOSAR architecture and methodology.
• Learn how to design motor controllers using AUTOSAR.

This instructor-led, live training (available online or onsite) is designed for intermediate-level embedded software developers and automotive engineers who wish to understand and configure AUTOSAR OS (based on OSEK/VDX) and the COM Stack to enable reliable task scheduling and communication in automotive ECUs.

By the end of this training, participants will be able to:

• Understand the AUTOSAR OS architecture and scheduling policies
• Implement and manage tasks, events, alarms, and counters
• Describe and configure the COM Stack layers, including PDUR and communication services
• Explain protocol stacks (CAN, LIN, FlexRay, Ethernet) and how AUTOSAR interfaces with them
• Configure OS and COM modules using industry tools (Vector DaVinci or ETAS ISOLAR)
• Simulate and validate task and communication flow in an AUTOSAR-based ECU

This instructor-led, live training in India (online or onsite) is designed for advanced-level safety engineers and automotive safety professionals who aim to develop robust safety strategies for autonomous vehicles. The programme covers hazard analysis, functional safety assessments, and compliance with international standards.

Upon completion of this training, participants will be able to:

• Identify and assess safety risks associated with autonomous driving systems.
• Conduct hazard analysis and risk assessment using industry standards.
• Implement safety validation and verification methods for AV systems.
• Apply functional safety standards, such as ISO 26262 and SOTIF.
• Develop risk mitigation strategies for AV safety challenges.

This instructor-led, live training in India (online or onsite) is aimed at intermediate-level AI developers and computer vision engineers who wish to build robust vision systems for autonomous driving applications.

By the end of this training, participants will be able to:

• Grasp the fundamental concepts of computer vision in autonomous vehicles.
• Implement algorithms for object detection, lane detection, and semantic segmentation.
• Integrate vision systems with other autonomous vehicle subsystems.
• Apply deep learning techniques for advanced perception tasks.
• Evaluate the performance of computer vision models in real-world scenarios.

This instructor-led, live training in India (online or onsite) is aimed at beginner-level professionals who wish to explore the ethical dilemmas and legal frameworks surrounding autonomous vehicles.

By the end of this training, participants will be able to:

• Understand the ethical implications of AI-driven decision-making in autonomous vehicles.
• Analyze global legal frameworks and policies regulating self-driving cars.
• Examine liability and accountability in the event of autonomous vehicle accidents.
• Evaluate the balance between innovation and public safety in autonomous driving laws.
• Discuss real-world case studies involving ethical dilemmas and legal disputes.

This instructor-led, live training in India (online or onsite) is aimed at intermediate-level professionals who wish to gain a comprehensive understanding of EV powertrain architectures, battery chemistry, battery management systems (BMS), and the factors affecting energy efficiency in electric vehicles.

By the end of this training, participants will be able to:

• Understand the structure and function of EV powertrains.
• Analyse different battery chemistries and their applications in EVs.
• Implement battery management techniques to enhance performance and safety.
• Evaluate energy efficiency in various EV configurations.

This instructor-led, live training in India (online or onsite) is aimed at beginner-level professionals and enthusiasts who wish to understand the fundamental concepts, technologies, and applications of autonomous vehicles.

By the end of this training, participants will be able to:

• Understand the key components and working principles of autonomous vehicles.
• Explore the role of AI, sensors, and real-time data processing in self-driving systems.
• Analyze different levels of vehicle autonomy and their real-world applications.
• Examine the ethical, legal, and regulatory aspects of autonomous mobility.
• Gain hands-on exposure to autonomous vehicle simulations.

This instructor-led, live training in India (online or onsite) is aimed at advanced-level sensor fusion specialists and AI engineers who wish to develop multi-sensor fusion algorithms and optimize real-time navigation in autonomous systems.

By the end of this training, participants will be able to:

• Understand the fundamentals and challenges of multi-sensor data fusion.
• Implement sensor fusion algorithms for real-time autonomous navigation.
• Integrate data from LiDAR, cameras, and RADAR for perception enhancement.
• Analyze and evaluate fusion system performance under various conditions.
• Develop practical solutions for sensor noise reduction and data alignment.

This instructor-led, live training in India (online or onsite) is designed for intermediate-level engineers, automotive professionals, and IoT specialists who want to comprehend the role of sensors in self-driving cars. The curriculum covers LiDAR, radar, cameras, and sensor fusion techniques.

Upon completing this training, participants will be able to:

• Grasp the various types of sensors utilized in autonomous vehicles.
• Analyze sensor data to support real-time vehicle perception and decision-making.
• Apply sensor fusion techniques to enhance vehicle accuracy and safety.
• Optimize sensor placement and calibration to improve autonomous driving performance.

This instructor-led, live training in India (online or on-site) is intended for intermediate-level network engineers and automotive IoT developers who wish to understand and implement V2X communication technologies for autonomous vehicles.

By the end of this training, participants will be able to:

• Understand the fundamental concepts of V2X communication.
• Analyze V2V, V2I, V2P, and V2N communication models.
• Implement V2X protocols such as DSRC and C-V2X.
• Develop simulations for connected vehicle environments.
• Address cybersecurity and privacy challenges in V2X networks.