Automotive SPICE (A-SPICE) - Introduction Training Course

This instructor-led, live training in Vietnam (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 program explores the application of AI, with a specific focus on Machine Learning and Deep Learning, within the automotive industry. It guides participants in identifying technologies suitable for various scenarios inside a vehicle, ranging from basic automation and image recognition to complex autonomous decision-making processes.

This instructor-led, live training in Vietnam (online or onsite) is aimed at advanced-level data scientists, AI specialists, and automotive AI developers who wish to build, train, and optimize AI models for autonomous driving applications.

Upon completing this training, participants will be able to:

• Comprehend the fundamentals of AI and deep learning within the context of autonomous vehicles.
• Apply computer vision techniques for real-time object detection and lane following.
• Leverage reinforcement learning to enhance decision-making in self-driving systems.
• Integrate sensor fusion methods to improve perception and navigation capabilities.
• Construct deep learning models to predict and analyze driving scenarios.

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

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

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

• Grasp the architectures of AUTOSAR Classic and Adaptive systems and identify their key distinctions.
• Create 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 with simulations of real-world automotive scenarios.

Customization Options

• To request tailored training for this course, please contact us to make arrangements.

This instructor-led, live training in Vietnam (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 use the AUTOSAR Classic Platform to develop, integrate, and test standardized software components for electronic control units (ECUs).

Upon completing 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 (BSW) modules.

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 (available online or onsite) is designed for intermediate-level embedded software developers and automotive engineers who aim to comprehend and configure AUTOSAR OS (derived from OSEK/VDX) along with the COM Stack to facilitate robust 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
• Developing and overseeing tasks, events, alarms, and counters
• Describing and setting up COM Stack layers, encompassing PDUR and communication services
• Elaborating on protocol stacks (CAN, LIN, FlexRay, Ethernet) and AUTOSAR's interaction with them
• Configuring OS and COM modules utilizing industry-standard tools (such as Vector DaVinci or ETAS ISOLAR)
• Simulating and verifying task and communication sequences in an AUTOSAR-based ECU

This instructor-led live training in Vietnam (online or onsite) targets 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 Vietnam (online or onsite) targets 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 within autonomous vehicles.
• Implement algorithms for object detection, lane detection, and semantic segmentation.
• Integrate vision systems with other subsystems of autonomous vehicles.
• Utilize deep learning techniques for advanced perception tasks.
• Evaluate the performance of computer vision models in real-world scenarios.

This instructor-led, live training in Vietnam (online or onsite) is designed for beginner-level professionals seeking to explore the ethical dilemmas and legal structures surrounding autonomous vehicles.

By completing this training, participants will be able to:

• Grasp the ethical implications of AI-driven decision-making in autonomous vehicles.
• Analyze global legal frameworks and policies that regulate self-driving cars.
• Investigate liability and accountability issues arising from autonomous vehicle accidents.
• Assess the balance between fostering innovation and ensuring public safety within autonomous driving regulations.
• Discuss real-world case studies involving ethical dilemmas and legal disputes.

This instructor-led, live training in Vietnam (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:

• Grasp the structure and function of EV powertrains.
• Evaluate various battery chemistries and their applications in EVs.
• Apply battery management techniques to enhance performance and safety.
• Assess energy efficiency across different EV configurations.

This instructor-led, live training in Vietnam (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 Vietnam (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 Vietnam (online or onsite) targets intermediate-level engineers, automotive professionals, and IoT specialists seeking 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 Vietnam (online or onsite) is designed for intermediate-level network engineers and automotive IoT developers seeking to understand and deploy V2X communication technologies for autonomous vehicles.

By the conclusion of this training, participants will be capable of:

• Gaining a solid grasp of core V2X communication concepts.
• Evaluating V2V, V2I, V2P, and V2N communication models.
• Implementing V2X protocols including DSRC and C-V2X.
• Creating simulations for connected vehicle ecosystems.
• Tackling cybersecurity and privacy challenges within V2X networks.