ADAS motorcycle assistance systems course
About our
The Motorcycle ADAS Systems course explores the integration of advanced driver assistance technologies, including automatic braking systems, adaptive cruise control, and blind spot detection. It focuses on road safety and the development of systems that prevent accidents, using sensors, cameras, and radar. The course delves into the electronics and programming required for these systems to function, covering both theory and practice in the context of motorcycles.
The program includes aspects of diagnostics and maintenance of ADAS systems, along with considerations of current legislation and safety standards. V2X (Vehicle-to-Everything) communication is analyzed, exploring the potential of interconnectivity to improve transportation safety and efficiency. It prepares students for professional roles in the design, maintenance, and certification of ADAS systems in the motorcycle industry, improving road safety and the future of mobility.
ADAS motorcycle assistance systems course
- Format: Hybrid
- Duration: 3 months
- Hours: 300 H
- Language: English / Spanish
- Registration date: 23-10-2026
- Start date: 12-12-2026
- Available places: 3
399 $
Competencies and results
What you will learn
1. Expert Mastery of ADAS Systems for Motorcycles: Sensors, Functions and Calibration
Here is the requested content:
- Understand the architecture and operation of Advanced Driver Assistance Systems (ADAS) specific to motorcycles.
- Identify and analyze the different types of sensors used in motorcycle ADAS: radar, lidar, cameras, inertial sensors, and GPS.
- Study the key functions of ADAS in motorcycles: adaptive cruise control, blind spot detection, forward collision warning, lane keeping assist, and automatic emergency braking.
- Learn the calibration and adjustment procedures for ADAS sensors and systems, including the use of specialized tools and software.
- Evaluate the impact of ADAS systems on motorcycle safety, performance, and user experience.
- Diagnosticate and troubleshoot common problems in motorcycle ADAS systems.
- Become familiar with the relevant regulations and standards for ADAS in motorcycles.
Explore future trends and developments in ADAS technology for motorcycles, including connectivity and artificial intelligence.
Practice applying the acquired knowledge through practical exercises, simulations, and case studies.
2. In-depth Analysis of ADAS Systems in Motorcycles: Sensors, Advanced Functions and Professional Calibration.
2. **In-Depth Analysis of ADAS Systems in Motorcycles: Sensors, Advanced Functions, and Professional Calibration.**
3. Comprehensive user-oriented design and validation (from modeling to manufacturing)
You will learn to integrate the entire product development process, from initial model conception to final validation, applying user-centered methodologies. You will develop skills in parametric design, ergonomics, simulation, sustainable materials, 3D visualization, and manufacturing management, ensuring efficient, safe solutions that meet current industry standards.
4. Development of ADAS Skills in Motorcycles: Design, Operation and Optimization
4. ADAS Skills Development for Motorcycles: Design, Operation, and Optimization
- Fundamentals of ADAS Systems in Motorcycles: Introduction to driver assistance technologies, including radar, cameras, sensors, and processing units.
- Sensor Design and Integration: Selection, placement, and configuration of sensors (radar, ultrasound, cameras) for environmental sensing on motorcycles.
- Signal Processing and Data Fusion: Techniques for processing signals from sensors, including filtering, calibration, and data fusion for accurate environmental interpretation.
- ADAS Algorithm Implementation: Development and programming of algorithms for specific ADAS functions, such as adaptive cruise control (ACC), blind spot detection (BSD), and forward collision warning (FCW).
- Motorcycle Control and Actuation: Integration of ADAS systems with motorcycle control systems, including brakes, throttle, and steering, for the execution of Driver assistance functions.
- Testing and Validation of ADAS Systems: Testing and validation methodologies for ADAS systems in simulated and real-world environments, including performance, safety, and usability testing.
- Optimization and Continuous Improvement: Techniques for optimizing the performance and efficiency of ADAS systems, including parameter tuning, software updates, and data collection for continuous improvement.
- Safety and Regulatory Aspects: Safety considerations in the design and operation of ADAS systems, including compliance with industry regulations and standards.
- Case Studies and Applications: Analysis of case studies of ADAS systems in motorcycles, including examples of design, implementation, and evaluation.
- Future Trends in Motorcycle ADAS: Exploration of the latest trends in motorcycle ADAS technology, including artificial intelligence, connectivity, and autonomous vehicles.
5. Master's Degree in Motorcycle ADAS: Implementation, Configuration and Troubleshooting
5. **Master’s Degree in Motorcycle ADAS: Implementation, Configuration, and Troubleshooting**
- Fundamental principles of Advanced Driver Assistance Systems (ADAS) applied to motorcycles.
- Architecture and key components of ADAS systems: sensors (cameras, radar, LiDAR), electronic control units (ECUs), actuators, and communication systems.
- ADAS implementation: integration of systems into the motorcycle, design considerations, and safety requirements.
- Configuration and calibration of ADAS systems: parameter adjustments, functionality customization, and performance optimization.
- Diagnostics and troubleshooting of ADAS systems: problem identification, error code analysis, testing and repair procedures.
- Motorcycle-specific driver assistance systems: adaptive cruise control, emergency braking, blind spot detection, lane departure warning, among others Other.
- Regulations and standards related to ADAS systems in motorcycles: safety requirements, homologation tests, and industry standards.
- Simulation and modeling techniques for ADAS systems: use of specialized software to evaluate system performance and safety.
- Future trends in ADAS for motorcycles: development of new technologies, integration of artificial intelligence and connectivity.
- Workshop and laboratory practices: assembly, disassembly, and calibration of ADAS systems.
- Fundamentals of automotive electronics: circuit analysis, use of multimeters and oscilloscopes.
- Sensors and actuators used in ADAS systems: operation, types, and applications.
6. Expert in Motorcycle ADAS: Design, Calibration, Diagnosis and Troubleshooting
- Fundamentals of Motorcycle ADAS: Understand the evolution and current landscape of Advanced Driver Assistance Systems (ADAS) applied to motorcycles.
- ADAS System Design: Explore the architecture, key components (sensors, actuators, control units), and design of motorcycle-specific ADAS systems, considering aspects such as safety, integration, and performance optimization.
- Sensor and System Calibration: Learn to calibrate sensors (radar, lidar, cameras) and ADAS systems, ensuring accuracy and reliability in environmental detection and the execution of assistance functions.
- Fault Diagnosis and Troubleshooting: Develop skills to diagnose faults in ADAS systems, using advanced diagnostic tools, interpreting error codes, and applying effective solutions.
- Motorcycle-Specific ADAS Functions: Gain in-depth knowledge of the operation and application of ADAS functions. such as:
Adaptive Cruise Control (ACC)
Emergency Braking System (AEB)
Blind Spot Detection (BSD)
Lane Keeping Assist (LKA)
Integration and Communication: Understand the integration of ADAS systems with other motorcycle systems (brakes, engine, suspension) and the communication protocols used (CAN, Ethernet).
Standards and Regulations: Become familiar with the standards and regulations relevant to ADAS systems in motorcycles, including safety standards and performance testing.
Future Trends: Analyze emerging trends in motorcycle ADAS, such as artificial intelligence, connectivity, and autonomous driving, and their impact on the industry.
Laboratory Practices: Conduct laboratory exercises to apply the knowledge. acquired, including the configuration, calibration, and diagnostics of ADAS systems on real motorcycles.
Who this program is for:
ADAS motorcycle assistance systems course
- Engineers with degrees in Electronic Engineering, Telecommunications Engineering, Mechatronics Engineering, or related disciplines.
- Technicians and professionals with experience in the motorcycle sector, including manufacturers (OEM), repair and maintenance workshops (MRO), and component companies (Tier 1/2).
- Specialists in road safety, traffic engineering, and consulting who wish to delve deeper into ADAS technology applied to motorcycles.
- Software and hardware developers with knowledge of sensors, signal processing, control of Systems and vehicle communications.
Professionals interested in research and development (R&D) of ADAS systems for motorcycles, including researchers from technology centers and universities.
Recommended requirements: Basic knowledge of electronics, programming, and mechanics. Experience in the automotive or motorcycle sector is a plus. English level B2 (reading and understanding technical documentation).
- Standards-driven curriculum: you will work with CS-27/CS-29, DO-160, DO-178C/DO-254, ARP4754A/ARP4761, ADS-33E-PRF from the first module.
- Accreditable laboratories (EN ISO/IEC 17025) with rotor bench, EMC/Lightning pre-compliance, HIL/SIL, vibrations/acoustics.
- Evidence-oriented TFM: safety case, test plan, compliance dossierand operational limits.
- Mentored by industry: teachers with experience in rotorcraft, tiltrotor, eVTOL/UAM and flight test.
- Flexible modality (hybrid/online), international cohorts and support from SEIUM Career Services.
- Ethics and security: safety-by-design approach, cyber-OT, DIH and compliance as pillars.
Module 1 — Introduction to ADAS Systems in Motorcycles
1.1 Key components of ADAS systems in motorcycles: sensors and control units.
1.2 Basic functions of ADAS systems: ABS, traction control, blind spot detection.
1.3 Operating principles: how ADAS systems improve safety.
1.4 Advantages of ADAS systems for motorcycles: safety and performance.
1.5 Evolution of ADAS systems: history and future trends.
1.6 Impact of ADAS on motorcycle riding: user experience.
1.7 Legislation and regulations on ADAS in motorcycles: standards and compliance.
1.8 The future of ADAS in motorcycles: innovation and technological development.
1.9 Differences between ADAS for cars and motorcycles: specific challenges and solutions.
1.10 Essential terminology: glossary of key ADAS terms.
2.2 Types of ADAS Sensors for Motorcycles: Vision, Radar, Laser, and Ultrasound
2.2 Vision Sensors: Cameras, Types, Operation, and Applications
2.3 Radar Sensors: Technology, Frequency Bands, and Range
2.4 Laser Sensors: LiDAR in Motorcycles, Advantages, and Challenges
2.5 Ultrasound Sensors: Applications in Motorcycles and Operation
2.6 Sensor Integration: ADAS System Architecture
2.7 Technical Characteristics of Sensors: Resolution, Accuracy, and Sensitivity
2.8 Considerations for Mounting and Placing Sensors on Motorcycles
2.9 Sensor Calibration: Methods and Equipment
2.20 Impact of Environmental Conditions on Sensor Performance
3.3 Introduction to ADAS Systems in Motorcycles: Components and Operation
3.2 Troubleshooting ADAS Sensor Faults: Techniques and Tools
3.3 Calibration of ADAS Sensors: Procedures and Equipment
3.4 Preventive Maintenance of ADAS Systems: Routines and Protocols
3.5 Repairing ADAS Systems: Troubleshooting Common Problems
3.6 Driver Assistance Systems: Functions and Applications
3.7 Interpreting Fault Codes: Analysis and Solutions
3.8 Using Diagnostic Software: Operation and Application
3.9 Safety and Precautions in ADAS Repair
3.30 Updating and Maintaining Software in ADAS Systems
4.4 ADAS System Design for Motorcycles: Principles and Initial Considerations
4.2 Selection and Configuration of ADAS Sensors: Types, Location, and Specifications
4.3 Operation of ADAS Systems: Rider Interaction and Real-Time Functions
4.4 Optimizing ADAS Performance: Adjustments and Customization for Different Conditions
4.5 Development of ADAS Test and Validation Protocols
4.6 Integrating ADAS into Motorcycle Design: Aesthetics, Ergonomics, and Functionality
4.7 ADAS Software and Firmware: Development and Updating
4.8 Data Analysis and Feedback: Continuous System Improvement
4.9 ADAS Simulation and Modeling: Design and Evaluation Tools
4.40 Case Studies: Practical Applications and Examples of ADAS Design and Optimization
5.5 Introduction to ADAS Systems in Motorcycles
5.5 ADAS Sensors: Types and Operation
5.3 ADAS Functions: Adaptive Cruise Control (ACC)
5.4 ADAS Functions: Automatic Emergency Braking (AEB)
5.5 ADAS Functions: Blind Spot Detection (BSD)
5.6 ADAS Functions: Lane Keeping Assist (LKA)
5.7 Sensor and Function Integration
5.8 Sensor Calibration: Methods and Tools
5.9 Basic Troubleshooting of ADAS Systems
5.50 Safety and Legal Considerations
6.6 ADAS Components and Architecture in Motorcycles: Sensors, Control Modules, and Communication Networks
6.2 ADAS System Design: Component Selection and Motorcycle Integration
6.3 ADAS System Calibration: Specific Procedures and Tools
6.4 ADAS Fault Diagnosis: Error Codes, Tests, and Solutions
6.5 Radar and LiDAR Systems: Operation, Applications, and Calibration
6.6 Vision Cameras and Sensors: Technology, Functions, and Calibration
6.7 Ultrasonic Sensors: Applications in ADAS and Calibration
6.8 Advanced Stability and Traction Control Systems
6.9 ADAS System Performance Testing and Validation
6.60 Safety Considerations and Regulations for Motorcycle ADAS
- Hands-on methodology: test-before-you-trust, design reviews, failure analysis, compliance evidence.
- Software (depending on licenses/partners): MATLAB/Simulink, Python (NumPy/SciPy), OpenVSP, SU2/OpenFOAM, Nastran/Abaqus, AMESim/Modelica, acoustics tools, planning toolchains DO-178C.
- SEIUM Laboratories: scale rotor bench, vibrations/acoustics, EMC/Lightning pre-compliance, HIL/SIL for AFCS, data acquisition with strain gauging.
- Standards and compliance: EN 9100, 17025, ISO 27001, GDPR.
Capstone-type projects
Admissions, fees, and scholarships
- Profile: Background in Computer Engineering, Mathematics, Statistics, or related fields; practical experience in NLP and valued information retrieval systems.
- Documentation: Updated CV, academic transcript, SOP/statement of purpose, project examples or code (optional).
- Process: Application → Technical evaluation of profile and experience → Technical interview → Review of case studies → Final decision → Enrollment.
- Fees:
- Single payment: 10% discount.
- Payment in 3 installments: No fees; 30% upon registration + 2 equal monthly payments of the remaining 35%.
Monthly payment: available with a 7% commission on the total; annual review.
Scholarships: based on academic merit, financial need, and promoting inclusion; agreements with companies in the sector for partial or full scholarships.
See “Calendar & Calls for Applications,” “Scholarships & Grants,” and “Fees & Financing” in the SEIUM mega-menu.
Do you have any questions?
Our team is ready to help you. Contact us, and we will respond as soon as possible.
F. A. Q
Frequently asked questions
Yes, we have international certification
Yes: experimental models, real data, applied simulations, professional environments, real case studies.
It is not mandatory. We offer leveling tracks and tutoring.
Completely. It covers e-propulsion, integration, and emerging regulations (SC-VTOL).
Recommended. There are also internal challenges and consortiums.
Yes. Online/hybrid modality with planned labs and visa support (see “Visa & Residence”).