SEA:ME Partnership

• SEA:ME Partnerships
  • Introduction
  • What is a software defined vehicle (SdV)?
    • Project areas in SdV
      • Vehicle Control System
      • Autonomous driving technology
      • Human-machine interface (HMI)
      • Cybersecurity
      • Electrification
      • Data Analytics
      • Intelligent Transportation Systems (ITS)
      • Mobility-as-a-Service (MaaS)
      • Connected Vehicles
      • Smart Cities
  • Emerging Plans with Partners
    • Microsoft
    • CARIAD
    • MBition
    • T-Systems
    • Bosch
    • Capgemini
    • Digiteq Automotive
    • MicroNova
    • Eclipse Foundation

Introduction

SEA:ME (Software Engineering in Automotive & Mobility Ecosystems) is an open educational program that provides learners with the skills and knowledge needed to excel in the field of automotive software engineering. The program is designed for learners of all backgrounds, including high school students, apprenticeships students, university students, and industry professionals. It includes different learning modules (courses), simulation platforms, case studies, and open data sets, as well as project-based learning experiences and networking events. SEA:ME leverages open educational resources and platforms to create a more accessible and equitable learning experience, while also fostering collaboration and innovation in the field. By completing the program, learners will be equipped with the skills and knowledge needed to excel in the rapidly evolving field of SdM and SdV, and will be prepared for careers in this exciting and dynamic industry.

What is a software defined vehicle (SdV)?

A software-defined vehicle (SdV) is a vehicle where key functions are controlled through software, including engine management, brakes, and steering. This concept creates a connected, customizable vehicle, enabling remote updates, diagnostics, and data collection. It integrates technologies like V2V communication, AI, and cloud computing, revolutionizing vehicle design, efficiency, and safety, especially for electric and autonomous vehicles. SdV is a driving force for innovation in the automotive industry.

Project areas in SdV

Introducing the concept of software-defined vehicles in educational projects can be a great way to help learners understand the importance of software in modern vehicles and the role it plays in shaping the future of transportation.

1. Vehicle Control System: This includes developing software and hardware solutions for vehicle control systems such as propulsion, braking, steering, and suspension systems. The control systems play a crucial role in ensuring the safety and performance of the vehicle, especially in autonomous driving scenarios.
2. Autonomous driving technology: This includes developing software and hardware solutions for autonomous vehicles, such as perception systems, decision-making algorithms, and control systems.
3. Human-machine interface (HMI): This involves developing user interfaces and interaction systems for vehicles that allow drivers and passengers to interact with the vehicle's software and hardware systems.
4. Cybersecurity: This includes developing security solutions to protect SdV systems from cyber-attacks and ensuring the safety and privacy of passengers.
5. Electrification: This involves developing software and hardware solutions for electric and hybrid vehicles, such as battery management systems and charging infrastructure.
6. Data analytics: This involves analyzing data generated by SdV systems to improve vehicle performance, safety, and efficiency.
7. Intelligent Transportation Systems (ITS): Using sensors, cameras, and other technologies to collect data on traffic flow, congestion, and other factors to optimize transportation networks.
8. Mobility-as-a-Service (MaaS): Providing users with a comprehensive and integrated digital platform for accessing various modes of transportation, including public transit, ride-sharing, bike-sharing, and more.
9. Connected Vehicles: Integrating vehicles with digital platforms and networks to enable communication between vehicles, infrastructure, and other devices, improving safety, and efficiency.
10. Smart Cities

Vehicle Control System

1. Building a simple vehicle control system
   • Requirements: Students will build a simple vehicle control system using an Arduino microcontroller and various sensors such as accelerometers and gyroscopes. The system will be able to read sensor data and control a small model vehicle through different maneuvers. The project will also involve programming the control system to manage vehicle dynamics such as traction control and anti-lock braking.
   • Timeline: 4-6 weeks
   • Skills: Basic programming skills, knowledge of sensors and control systems, understanding of vehicle dynamics.
2. Designing a modular vehicle control system
   • Requirements: Students will design a modular vehicle control system that can be customized and expanded for different vehicle types and use cases. The system will include hardware modules for different functions such as engine control, braking, and steering, as well as a software framework for managing the modules and integrating with other vehicle systems. The project will involve designing and testing the hardware modules, as well as programming the software framework.
   • Timeline: 12-16 weeks
   • Skills: Basic electronics and programming skills, understanding of vehicle systems, ability to design and test modular hardware systems.

Autonomous driving technology

1. Building a self-driving model car
   • Requirements: Students will build a self-driving model car using a Raspberry Pi and various sensors such as cameras and LIDAR. The car will be programmed to navigate a simple obstacle course using machine learning algorithms such as deep neural networks. The project will also involve designing and testing control systems for vehicle dynamics and safety.
   • Timeline: 8-12 weeks
   • Skills: Basic programming skills, knowledge of machine learning algorithms and sensor integration, understanding of vehicle dynamics and safety.
2. Developing a simulation platform for autonomous vehicles
   • Requirements: Students will develop a simulation platform for testing and validating autonomous driving algorithms. The platform will include realistic models of vehicles, roads, and traffic scenarios, as well as tools for generating and analyzing data from simulated test runs. The project will involve designing and implementing the simulation platform, as well as testing and validating different autonomous driving algorithms.
   • Timeline: 16-20 weeks
   • Skills: Advanced programming skills, knowledge of simulation and modeling techniques, understanding of autonomous driving algorithms and sensor integration.
3. Testing an autonomous shuttle service in a controlled environment
   • Requirements: Students will test an autonomous shuttle service in a controlled environment, such as a closed campus or parking lot. Students will analyze the performance of the autonomous shuttle, and identify areas for improvement.
   • Potential Timeline: 3-4 months
   • Skillset: Testing and evaluation, data analysis, statistical modeling, programming, user research

Human-machine interface (HMI)

1. Designing an intuitive HMI for a semi-autonomous vehicle
   • Description: In this project, students will design an HMI for a semi-autonomous vehicle that is both intuitive and easy to use. They will need to consider factors such as user experience, safety, and accessibility, and design a system that can be easily adapted to different driving scenarios. Students will need to create wireframes, mockups, and prototypes of their HMI design, and test it in a simulated environment.
   • Timeline: 6-8 weeks
   • Skillset: User experience design, human factors engineering, software prototyping, simulation testing
2. Developing a voice-controlled HMI for a smart vehicle
   • Description: In this project, students will develop a voice-controlled HMI for a smart vehicle that can be used to perform various functions such as navigation, entertainment, and climate control. Students will need to design a natural language processing system that can understand spoken commands and respond appropriately, and integrate it with the vehicle's existing systems. They will also need to test the system in a simulated environment and fine-tune it based on user feedback.
   • Timeline: 8-10 weeks
   • Skillset: Natural language processing, machine learning, software development, testing and optimization
3. Designing an augmented reality HMI for a connected vehicle
   • Description: In this project, students will design an augmented reality HMI for a connected vehicle that provides drivers with real-time information about their surroundings. They will need to create a system that overlays digital information on top of the real-world environment, and can be used for navigation, safety, and entertainment purposes. Students will need to create a proof-of-concept prototype of their HMI design, and test it in a simulated environment.
   • Timeline: 10-12 weeks
   • Skillset: Augmented reality development, user experience design, software prototyping, simulation testing

Cybersecurity

1. Implementing a secure communication protocol for a connected vehicle *