♦ Connectivity and Communication

MaaS relies heavily on real-time data exchange between vehicles, infrastructure, and users. Semiconductors power the onboard communication systems that allow vehicles to interact with each other and the broader transportation network, whether V2V (Vehicle-to-Vehicle) or V2I (Vehicle-to-Infrastructure) communication, these chips enable the seamless flow of information critical for safe and efficient Mobility.

For example:

• • Cellular modems: These semiconductor components enable vehicles to connect to cellular networks and exchange data with other vehicles, infrastructure, and users.
  • Ethernet controllers: These chips facilitate high-speed data communication between various vehicle systems, such as the infotainment system, sensors, and control units.
  • Wireless communication modules: These semiconductors enable vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication using technologies like Wi-Fi and Bluetooth.

♦ Sensors and Perception

Autonomous vehicles are a significant component of MaaS. To navigate and make decisions in real-time, these vehicles rely on an array of sensors, including LiDAR, radar, and cameras. Automotive semiconductors are at the core of these sensor technologies, processing vast amounts of data and enabling vehicles to “see” and respond to their environment.

For example:

• • LiDAR processors: These semiconductor chips are responsible for processing the data captured by LiDAR sensors, which use laser beams to measure distances and create detailed 3D maps of the vehicle’s surroundings.
  • Radar signal processors: These semiconductors analyze the radar signals received by the vehicle’s radar sensors to detect and track objects, such as other vehicles or pedestrians.
  • Image signal processors: These chips process the data from cameras installed in the vehicle, allowing it to recognize and interpret visual information, such as traffic signs or lane markings.

♦ Data Processing and AI

Artificial intelligence (AI) is a driving force behind MaaS, powering predictive maintenance, route optimization, and even ride-hailing algorithms. Automotive semiconductors are crucial in supporting the immense computational power required for AI-based decision-making processes in vehicles.

For example:

• • Central processing units (CPUs): These semiconductors are the main processing units in vehicles, responsible for executing complex algorithms and performing calculations required for AI-based decision-making processes.
  • Graphics processing units (GPUs): These chips accelerate the processing of graphical data and are often used in AI applications, such as computer vision algorithms used in autonomous driving.
  • Neural network accelerators: These specialized semiconductors are designed to accelerate the execution of neural network models used in AI applications, enabling faster and more efficient data processing.

♦ Cybersecurity

With the increased connectivity of vehicles in MaaS, the risk of cyberattacks also rises. Semiconductors are instrumental in providing robust security features to protect vehicles from potential threats and breaches. As the automotive industry continues to embrace connectivity and autonomous technologies, the demand for semiconductors with enhanced cybersecurity capabilities is surging.

For example :

• • Secure microcontrollers: These semiconductor components provide a secure environment for storing and executing sensitive software and cryptographic algorithms, protecting the vehicle’s systems from unauthorized access or tampering.
  • Intrusion detection systems: These chips monitor the vehicle’s network traffic and behavior to detect any suspicious activities or potential cyberattacks, triggering appropriate security measures.
  • Secure communication modules: These semiconductors ensure secure communication between different vehicle systems, preventing unauthorized access or interception of data transmitted within the vehicle.