Reverse FMEA Training Course

This instructor-led, live training (available online or onsite) is designed for advanced-level robotics engineers and AI researchers who intend to implement sophisticated path planning algorithms to enhance autonomous vehicle performance.

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

• Grasp the theoretical underpinnings of advanced path planning algorithms.
• Deploy algorithms like RRT*, A*, and D* to facilitate real-time navigation.
• Refine path planning strategies to effectively manage obstacle avoidance and dynamic settings.
• Seamlessly integrate path planning algorithms with sensor data to boost precision.
• Assess the efficacy of different algorithms within practical contexts.

This course explores the application of AI, with a particular emphasis on Machine Learning and Deep Learning, within the automotive industry. It aids in identifying technologies that can be (potentially) applied across various automotive scenarios, ranging from basic automation and image recognition to autonomous decision-making.

This instructor-led, live session Romania (available online or onsite) targets advanced data scientists, AI specialists, and automotive AI developers who aim to build, train, and optimize AI models for autonomous driving.

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

• Comprehend the basics of AI and deep learning within autonomous vehicle contexts.
• Apply computer vision methods for real-time object detection and lane following.
• Use reinforcement learning for decision-making in self-driving systems.
• Implement sensor fusion techniques to improve perception and navigation.
• Create deep learning models to predict and analyze driving scenarios.

AUTOSAR (AUTomotive Open System ARchitecture) represents a global partnership among automotive manufacturers, suppliers, and tool developers, dedicated to standardizing software architectures for automotive electronic control units (ECUs).

This instructor-led live training, available both online and onsite, is designed for intermediate to advanced automotive software developers who aim to design, develop, and integrate software utilizing AUTOSAR Classic and Adaptive platforms, with a specific emphasis on Advanced Driver Assistance Systems (ADAS).

Upon completing this training, participants will be able to:

• Grasp the architectures of AUTOSAR Classic and Adaptive, including their primary distinctions.
• Develop and configure automotive software components using AUTOSAR-compliant tools.
• Integrate and test ADAS software components within AUTOSAR Adaptive environments.
• Implement best practices for safety, security, and performance optimization in automotive systems.

Course Format

• Interactive lectures and discussions.
• Practical exercises using industry-standard AUTOSAR tools.
• Project-based learning and simulation of real-world automotive scenarios.

Customization Options

• To arrange customized training for this course, please contact us.

This instructor-led, live training in Romania (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 on-site) is designed for intermediate-level embedded software developers and automotive engineers who want to utilize 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 basic software modules (BSW).

Design and implement the AUTOSAR Operating System (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 (online or onsite) is aimed at intermediate-level embedded software developers or 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:

• Grasp 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 Romania (online or onsite) is aimed at advanced-level safety engineers and automotive safety professionals who wish to develop comprehensive safety strategies for autonomous vehicles, including hazard analysis, functional safety assessments, and compliance with international standards.

By the end 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 Romania (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:

• Understand 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 Romania (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 Romania (online or onsite) is designed for intermediate-level professionals who aim 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.
• Analyze 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 Romania (online or onsite) targets beginner-level professionals and enthusiasts eager to grasp the fundamental concepts, technologies, and practical applications of autonomous vehicles.

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

• Comprehend the essential components and operational principles of autonomous vehicles.
• Investigate the role of AI, sensors, and real-time data processing in self-driving systems.
• Assess various levels of vehicle autonomy and their practical implementations.
• Explore the ethical, legal, and regulatory dimensions of autonomous mobility.
• Acquire practical experience through autonomous vehicle simulations.

This instructor-led, live training in Romania (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 Romania (online or onsite) is aimed at intermediate-level engineers, automotive professionals, and IoT specialists who wish to understand the role of sensors in self-driving cars, covering LiDAR, radar, cameras, and sensor fusion techniques.

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

• Understand the different types of sensors used in autonomous vehicles.
• Analyze sensor data for real-time vehicle perception and decision-making.
• Implement sensor fusion techniques to improve vehicle accuracy and safety.
• Optimize sensor placement and calibration for enhanced autonomous driving performance.

This instructor-led, live training in Romania (online or onsite) is tailored for intermediate-level network engineers and automotive IoT developers seeking to understand and implement V2X communication technologies for autonomous vehicles.

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

• Grasp the core principles of V2X communication.
• Evaluate V2V, V2I, V2P, and V2N communication models.
• Deploy V2X protocols, including DSRC and C-V2X.
• Create simulations for connected vehicle ecosystems.
• Tackle cybersecurity and privacy issues within V2X networks.