Automotive Training in Maia

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

Upon completion of this training, participants will be capable of:

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

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

Upon completion of this training, participants will be equipped 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.
• Navigate cybersecurity and privacy challenges within V2X networks.

This instructor-led live training in Maia (online or onsite) is tailored for 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.

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

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

This instructor-led, live training in Maia (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 Maia (online or onsite) targets advanced 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.

AUTOSAR (AUTomotive Open System ARchitecture) is a global partnership of automotive manufacturers, suppliers, and tool developers that standardises the software architecture for automotive electronic control units (ECUs).

This instructor-led live training (available online or onsite) targets intermediate to advanced automotive software developers wishing to design, develop, and integrate software using AUTOSAR Classic and Adaptive platforms, with a particular focus on ADAS (Advanced Driver Assistance Systems).

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

• Understand the AUTOSAR Classic and Adaptive architectures and their key differences.
• Develop and configure automotive software components using AUTOSAR-compliant tools.
• Integrate and test ADAS software components within AUTOSAR Adaptive environments.
• Apply best practices for safety, security, and performance optimisation in automotive systems.

Format of the Course

• Interactive lecture and discussion.
• Hands-on practice with industry-standard AUTOSAR tools.
• Project-based learning and simulation of automotive use cases.

Course Customisation Options

• To request a customised training course, please contact us to arrange.

This instructor-led, live training in Maia (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 Maia (online or onsite) is designed for intermediate-level automotive engineers and technicians who wish to acquire hands-on experience in testing, simulating, and diagnosing ECUs using Vector tools such as CANoe and CANape.

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

• Comprehend the role and function of ECUs in automotive systems.
• Set up and configure Vector tools such as CANoe and CANape.
• Simulate and test ECU communication on CAN and LIN networks.
• Analyze data and perform diagnostics on ECUs.
• Create test cases and automate testing workflows.
• Calibrate and optimize ECUs using practical approaches.

This instructor-led, live training in Maia (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 Maia (online or onsite) targets intermediate-level automotive engineers and embedded systems developers who wish to understand the theoretical aspects of ECUs, focusing on Vector-based tools and methodologies used in automotive design and development.

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

• Understand the architecture and functions of ECUs in modern vehicles.
• Analyze communication protocols used in ECU development.
• Explore Vector-based tools and their theoretical applications.
• Apply model-based development principles to ECU design.

This instructor-led live training, held in Maia (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 realm of autonomous vehicles.
• Deploy computer vision techniques for real-time object detection and lane following.
• Employ reinforcement learning for decision-making in self-driving systems.
• Integrate sensor fusion techniques for enhanced perception and navigation.
• Develop deep learning models to predict and analyze driving scenarios.

This instructor-led, live training in Maia (online or on-site) is designed for quality engineers at a beginner level who want to learn how to apply Core Quality Tools to ensure product quality within the manufacturing industry.

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

• Grasp the significance and integration of the Core Quality Tools.
• Master the concepts and application of APQP processes to facilitate effective product quality planning.
• Identify potential failures in products and processes, understand their impact on product quality, and implement actions to mitigate risks.
• Use statistical methods to monitor and control manufacturing processes, ensuring product quality and process efficiency.

This instructor-led, live training in Maia (online or onsite) is aimed at beginner-level quality control professionals who wish to learn the fundamentals of Statistical Process Control (SPC) and apply it in real-world scenarios.

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

• Grasp the fundamentals of Statistical Process Control (SPC).
• Utilise essential SPC tools such as control charts, histograms, Pareto charts, and scatter diagrams to monitor process performance.
• Construct and interpret various types of control charts for variable and attribute data to detect and analyse process variations.
• Calculate and interpret process capability indices.

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

The 'Automotive SPICE (A-SPICE) - Introduction' workshop focuses on reviewing the Automotive SPICE process assessment model, discussing its structure, classification, and interpretative guidelines. Participants acquire competencies to understand the assessment process from the perspective of project managers and stakeholders. The course covers the significance of ASPICE in the market, compliance, different process groups, and ASPICE levels through examples of real implementations.

This instructor-led, live training in Maia (online or onsite) is aimed at engineers who wish to safeguard connected vehicles from cyber attacks.

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

• Implement cybersecurity in automotive systems.
• Choose the most suitable technologies, tools, and approaches.

This instructor-led, live training in Maia (online or on-site) is primarily designed for engineers who wish to utilize AUTOSAR to design automotive components.

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

• Install and configure AUTOSAR.
• Establish a development workflow.
• Navigate the AUTOSAR environment with confidence.
• Work efficiently within the framework.

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

Upon completing this training, participants will be able to:

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

Gain a solid understanding of the AUTOSAR layered architecture and Basic Software modules (BSW).

Design and implement the AUTOSAR Operating System (OS) and Communication stack (COM stack).

Utilise CANoe or comparable tools for simulation, testing, and diagnostics within an AUTOSAR environment.

This instructor-led live training, available online or on-site, targets intermediate embedded software developers and automotive engineers seeking to master the configuration and understanding of AUTOSAR OS (based on OSEK/VDX) and the COM Stack. The course focuses on enabling reliable task scheduling and communication within automotive ECUs.

Upon completion of this training, participants will be capable of:

• Grasping the AUTOSAR OS architecture and its scheduling policies
• Implementing and managing tasks, events, alarms, and counters
• Describing and configuring COM Stack layers, including PDUR and communication services
• Explaining protocol stacks (CAN, LIN, FlexRay, Ethernet) and their interaction with AUTOSAR interfaces
• Configuring OS and COM modules using industry-standard tools (Vector DaVinci or ETAS ISOLAR)
• Simulating and validating task and communication flows in an AUTOSAR-based ECU