1.4 Vehicle architectures
11 min read•august 21, 2024
Vehicle architectures form the foundation of autonomous systems, integrating structural, mechanical, and electronic elements. Understanding these components is crucial for implementing self-driving capabilities, as each subsystem plays a vital role in supporting autonomous functions and ensuring safe operation.
From chassis design to sensor integration, drive-by-wire systems, and advanced software architectures, autonomous vehicle platforms require careful consideration of numerous factors. Redundancy, fault tolerance, and robust communication networks are essential for creating reliable and safe autonomous vehicles.
Components of vehicle architecture
- Vehicle architecture forms the foundation for autonomous systems integration, encompassing structural, mechanical, and electronic elements
- Understanding these components is crucial for designing and implementing self-driving capabilities in vehicles
- Each subsystem plays a vital role in supporting autonomous functions and ensuring safe, efficient operation
Chassis and frame
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- Provides structural support and rigidity for the entire vehicle
- Influences vehicle dynamics, handling, and safety performance
- Designed to accommodate , computers, and other autonomous driving components
- Materials used include high-strength steel, aluminum, and carbon fiber composites
- Crash safety structures integrated to protect occupants and critical systems
Powertrain systems
- Encompasses engine, transmission, driveshaft, and differential components
- Electric powertrains gaining popularity in autonomous vehicles due to efficiency and control precision
- Hybrid systems combine internal combustion engines with electric motors for extended range
- Power delivery systems optimized for smooth acceleration and deceleration in autonomous mode
- Advanced engine control units (ECUs) interface with autonomous driving systems for coordinated operation
Electrical and electronic systems
- Central nervous system of autonomous vehicles, managing power distribution and data communication
- High-voltage systems for electric powertrains and low-voltage systems for electronics and sensors
- Advanced battery management systems ensure optimal performance and longevity
- Electromagnetic compatibility (EMC) considerations crucial for preventing interference between systems
- Redundant power supplies and fail-safe circuits enhance reliability and safety
Safety systems
- Active safety features include electronic stability control, anti-lock braking systems, and traction control
- Passive safety systems comprise airbags, seatbelts, and crumple zones
- Advanced driver assistance systems (ADAS) form the basis for higher levels of autonomy
- Lane departure warning
- Adaptive cruise control
- Automatic emergency braking
- Sensor fusion algorithms integrate data from multiple sources for comprehensive safety coverage
- Fault detection and isolation systems continuously monitor critical components
Comfort and convenience features
- Climate control systems with multi-zone capabilities and air quality management
- Infotainment systems providing entertainment, navigation, and vehicle status information
- Adjustable seating with memory functions and massage capabilities
- Ambient lighting and sound systems for personalized cabin atmosphere
- Autonomous parking assist and summon features for added convenience
Autonomous vehicle platforms
Purpose-built vs retrofitted designs
- Purpose-built platforms optimize vehicle architecture for autonomous operation from the ground up
- Streamlined sensor integration
- Optimized space utilization for computing hardware
- Enhanced structural design for sensor placement and protection
- Retrofitted designs adapt existing vehicle platforms for autonomous capabilities
- Cost-effective for testing and initial deployment
- Challenges in sensor placement and system integration
- Limited optimization of vehicle dynamics for autonomous operation
- Trade-offs between development time, cost, and performance influence platform choice
Sensor integration challenges
- Achieving 360-degree sensor coverage without compromising vehicle aesthetics or aerodynamics
- Ensuring sensor cleanliness and functionality in various weather conditions
- Managing electromagnetic interference between multiple sensor types
- Calibration and alignment of sensors for accurate data fusion
- Balancing sensor redundancy with cost and complexity considerations
Computing hardware requirements
- High-performance processors (CPUs) and graphics processing units (GPUs) for real-time data processing
- Field-programmable gate arrays (FPGAs) for specialized, low- operations
- Artificial intelligence accelerators for neural network inference
- Robust storage systems for mapping data and software updates
- Cooling systems to maintain optimal operating temperatures for computing hardware
Power management considerations
- Balancing power consumption of sensors, computers, and with vehicle range
- Implementing intelligent power management strategies to optimize energy usage
- Designing high-capacity, fast-charging battery systems for electric autonomous vehicles
- Ensuring uninterrupted power supply to critical systems during various driving conditions
- Developing energy harvesting technologies to supplement power requirements
Drive-by-wire systems
Steering control
- Replaces mechanical linkages with electronic control systems
- Electric power steering (EPS) actuators provide precise steering control
- Feedback mechanisms simulate road feel for human drivers when necessary
- Multiple redundant control paths ensure system reliability
- Variable steering ratios adapt to different driving conditions and speeds
Braking control
- Electro-hydraulic or fully electric brake-by-wire systems replace traditional hydraulic brakes
- Individual wheel braking control for enhanced stability and maneuverability
- Regenerative braking integration for energy recovery in electric and hybrid vehicles
- Fail-safe mechanisms ensure braking capability in case of system failure
- Adaptive braking force distribution based on road conditions and vehicle dynamics
Throttle control
- Electronic throttle control (ETC) replaces mechanical linkages to the engine
- Precise control of engine power output for smooth acceleration and efficient operation
- Integration with traction control and stability systems for enhanced vehicle dynamics
- Multiple sensor inputs for redundancy and fault detection
- Calibration algorithms optimize throttle response for different driving modes
Shift-by-wire technology
- Replaces mechanical transmission linkages with electronic controls
- Enables seamless integration with autonomous driving systems for optimal gear selection
- Supports advanced transmission technologies (Continuously Variable Transmission, dual-clutch)
- Enhances interior design flexibility by eliminating traditional gear shifters
- Implements safety interlocks to prevent unintended gear engagement
Sensor suite integration
Lidar placement and coverage
- Roof-mounted lidar provides long-range, 360-degree point cloud data
- Multiple smaller lidars integrated into bumpers and sides for close-range detection
- Solid-state lidar technologies enable sleeker integration into vehicle body panels
- Overlapping fields of view ensure comprehensive coverage and redundancy
- Cooling systems maintain optimal operating temperatures for lidar sensors
Camera array configuration
- Forward-facing cameras for lane detection, traffic sign recognition, and object identification
- Side-view cameras replace traditional mirrors and aid in lane change decisions
- Rear-view cameras assist in parking and provide additional situational awareness
- Surround-view camera systems create a bird's-eye view for low-speed maneuvering
- High dynamic range (HDR) and infrared cameras enhance performance in challenging lighting conditions
Radar and ultrasonic sensors
- Long-range radar sensors mounted in the front and rear for adaptive cruise control and collision avoidance
- Short-range radar sensors in vehicle corners for blind spot detection and cross-traffic alerts
- Ultrasonic sensors in bumpers facilitate precise parking assistance and low-speed obstacle detection
- Radar sensors provide reliable object detection in adverse weather conditions
- Fusion of radar and other sensor data enhances object classification and tracking accuracy
GPS and IMU integration
- High-precision GPS receivers for accurate global positioning
- Inertial Measurement Units (IMUs) provide data on vehicle acceleration, orientation, and angular velocity
- Sensor fusion algorithms combine GPS and IMU data for robust localization
- Real-time kinematic (RTK) GPS enhances positioning accuracy to centimeter-level precision
- Dead reckoning capabilities maintain localization when GPS signals are unavailable
Redundancy and fault tolerance
Backup systems for critical functions
- Redundant steering actuators ensure continued steering control in case of primary system failure
- Secondary braking systems (hydraulic or electric) provide failsafe stopping capability
- Backup power supplies maintain critical systems operation during main power interruptions
- Duplicate sensor arrays enable continued perception if primary sensors malfunction
- Redundant communication channels ensure uninterrupted connectivity for safety-critical functions
Fail-safe mechanisms
- Graceful degradation strategies allow continued operation with reduced functionality
- System isolation protocols prevent fault propagation across critical subsystems
- Mechanical overrides enable manual control in case of complete electronic system failure
- Watchdog timers monitor system responsiveness and trigger safe states when necessary
- Fault containment regions limit the impact of hardware or software failures
System health monitoring
- Continuous self-diagnostic routines assess the status of all critical components
- Real-time performance metrics track system efficiency and detect anomalies
- Predictive maintenance algorithms anticipate potential failures before they occur
- Logging and black box systems record vehicle data for post-incident analysis
- Remote monitoring capabilities allow fleet operators to track vehicle health in real-time
Vehicle network architecture
CAN bus systems
- provides robust, low-cost communication for vehicle subsystems
- Multi-master, message-based protocol allows efficient data exchange between ECUs
- Prioritization mechanisms ensure critical messages are transmitted without delay
- Fault-tolerant design with error detection and automatic retransmission capabilities
- Widely adopted standard in automotive industry, supporting legacy integration
Ethernet-based networks
- Automotive Ethernet offers high- communication for data-intensive autonomous systems
- Supports speeds up to 10 Gbps, enabling real-time sensor data transmission and processing
- Allows for switched network topologies, improving scalability and flexibility
- Audio Video Bridging (AVB) and Time-Sensitive Networking (TSN) extensions enhance real-time performance
- Facilitates integration of consumer electronics and infotainment systems
Time-sensitive networking (TSN)
- IEEE 802.1 standards-based technology ensuring deterministic, low-latency communication
- Time synchronization protocols maintain precise timing across distributed systems
- Traffic shaping and scheduling mechanisms guarantee bandwidth for critical data streams
- Frame preemption allows high-priority messages to interrupt lower-priority transmissions
- Enables convergence of real-time control traffic and best-effort data on a single network
Software architecture
Operating system choices
- Real-time operating systems (RTOS) provide deterministic performance for safety-critical functions
- Linux-based systems offer flexibility and extensive software ecosystem support
- Hypervisor technologies enable isolation between safety-critical and non-critical software components
- (AUTomotive Open System ARchitecture) standardizes software architecture across different platforms
- Virtualization techniques allow multiple operating systems to run concurrently on shared hardware
Middleware frameworks
- Robot Operating System (ROS) facilitates modular development of autonomous driving software
- Data Distribution Service (DDS) enables scalable, real-time data sharing between distributed components
- AUTOSAR Adaptive Platform provides standardized APIs for high-performance computing applications
- Inter-Process Communication (IPC) mechanisms ensure efficient data exchange between software modules
- Middleware abstracts hardware differences, enabling software portability across vehicle platforms
Application layer design
- Perception stack processes sensor data to create a comprehensive world model
- Planning and decision-making modules determine optimal vehicle behavior and trajectories
- Control algorithms translate high-level decisions into low-level actuator commands
- Localization and mapping systems maintain accurate vehicle positioning and environmental awareness
- Human-machine interface applications manage user interactions and display relevant information
Human-machine interface
Displays and controls
- Head-up displays (HUDs) project critical information onto the windshield, minimizing driver distraction
- Large touchscreen interfaces provide access to vehicle settings, navigation, and infotainment features
- Digital instrument clusters offer customizable information displays and adaptable layouts
- Steering wheel-mounted controls allow quick access to frequently used functions
- Gesture recognition systems enable intuitive control of certain vehicle features
Voice command systems
- Natural language processing enables conversational interactions with vehicle systems
- Multi-language support caters to diverse user bases and international markets
- Context-aware voice commands interpret user intent based on current vehicle state and location
- Integration with virtual assistants (Google Assistant, Amazon Alexa) expands functionality
- Noise cancellation and beamforming technologies improve voice recognition accuracy in noisy environments
Haptic feedback mechanisms
- Vibration alerts in steering wheel or seat provide non-visual warnings to the driver
- Force feedback in controls simulates traditional mechanical feel for enhanced user experience
- Tactile displays enable interaction with touchscreens without visual focus
- Programmable texture surfaces create dynamic, context-sensitive control interfaces
- Haptic pedestrian detection systems enhance safety for visually impaired individuals
Energy management
Battery systems for EVs
- High-capacity lithium-ion battery packs provide energy storage for electric powertrains
- Battery management systems (BMS) optimize charging, discharging, and thermal management
- Cell balancing techniques extend battery life and maintain consistent performance
- Fast-charging capabilities reduce downtime for autonomous electric vehicle fleets
- Vehicle-to-grid (V2G) technologies enable bidirectional power flow for grid stabilization
Hybrid powertrain architectures
- Series hybrids use an internal combustion engine solely as a generator for the electric drive system
- Parallel hybrids allow both the engine and electric motor to drive the wheels directly
- Power-split hybrids combine elements of series and parallel designs for optimal efficiency
- Plug-in hybrid electric vehicles (PHEVs) offer extended electric-only range with backup combustion power
- Mild hybrid systems provide electric assist and regenerative braking with minimal added complexity
Regenerative braking integration
- Converts kinetic energy into electrical energy during deceleration, improving overall efficiency
- Blended braking systems seamlessly transition between regenerative and friction braking
- Adaptive regeneration strategies optimize energy recovery based on driving conditions and battery state
- User-selectable regeneration modes allow customization of braking feel and energy recovery intensity
- Integration with stability control systems ensures safe operation during low-traction conditions
Connectivity and communication
V2X capabilities
- Vehicle-to-Vehicle (V2V) communication enables cooperative awareness and collision avoidance
- Vehicle-to-Infrastructure (V2I) systems interact with traffic signals and road signs for improved traffic flow
- Vehicle-to-Pedestrian (V2P) technologies enhance safety for vulnerable road users
- Vehicle-to-Network (V2N) connectivity provides access to cloud services and real-time traffic information
- Dedicated Short-Range Communications (DSRC) and Cellular V2X (C-V2X) are competing standards for V2X implementation
Cellular and Wi-Fi integration
- 5G cellular networks offer high-bandwidth, low-latency connectivity for autonomous vehicles
- Wi-Fi hotspots provide internet access for passengers and enable local data offloading
- Cellular fallback ensures continued connectivity in areas with limited Wi-Fi coverage
- Multi-network load balancing optimizes data transmission across available connections
- Software-defined radios enable flexible adaptation to different wireless standards
Over-the-air update systems
- Secure, remote software updates for vehicle systems and autonomous driving algorithms
- Differential updates minimize data transfer and reduce update times
- Rollback capabilities ensure system integrity in case of update failures
- Staged deployment strategies allow gradual rollout of updates across vehicle fleets
- Separate update channels for critical systems and non-essential features
Modularity and scalability
Standardized interfaces
- Hardware abstraction layers enable software portability across different vehicle platforms
- Standardized sensor interfaces facilitate easy integration of new or upgraded sensors
- Modular power distribution systems allow flexible configuration of electrical components
- Unified data formats and communication protocols simplify integration of third-party systems
- Standardized diagnostic interfaces enable consistent maintenance and troubleshooting procedures
Upgradeable components
- Modular sensor packages allow easy replacement or upgrade of individual sensors
- Plug-and-play compute modules enable processing power upgrades without major redesigns
- Swappable battery systems facilitate quick energy storage upgrades or replacements
- Software-defined functionality allows feature upgrades through over-the-air updates
- Modular interior components enable customization and updates to the user interface
Platform sharing across models
- Common electrical architectures shared across multiple vehicle models reduce development costs
- Scalable autonomous driving platforms adapt to different vehicle sizes and types
- Shared sensor suites with model-specific calibrations optimize performance for each vehicle
- Unified software stacks with vehicle-specific parameters streamline development and maintenance
- Standardized integration points for autonomous systems facilitate rapid deployment across model lines
Regulatory compliance
Safety standards adherence
- Compliance with functional safety standard for road vehicles
- Implementation of SOTIF (Safety Of The Intended Functionality) principles for autonomous systems
- Adherence to FMVSS (Federal Motor Vehicle Safety Standards) regulations in the United States
- Compliance with UN-ECE regulations for international markets
- Regular safety assessments and certifications to maintain regulatory compliance
Emissions control systems
- Integration of advanced catalytic converters and particulate filters for ICE vehicles
- Zero-emission vehicle (ZEV) technologies for electric and fuel cell vehicles
- On-board diagnostics (OBD) systems monitor emissions performance in real-time
- Compliance with region-specific emissions standards (Euro 6, Tier 3, LEV III)
- Adaptive emissions control strategies optimize performance across various driving conditions
Cybersecurity measures
- Implementation of automotive-specific cybersecurity standards (ISO/SAE 21434)
- Secure boot processes ensure integrity of vehicle software at startup
- Intrusion detection and prevention systems (IDPS) monitor for and block potential cyber attacks
- Hardware security modules (HSMs) provide secure key storage and cryptographic operations
- Regular security audits and penetration testing to identify and address vulnerabilities
Key Terms to Review (18)
Actuators: Actuators are mechanical devices that convert energy into motion, serving as the critical components that enable a system to perform specific actions. In the context of vehicle architectures, actuators are essential for controlling various systems such as steering, braking, and throttle control. They play a vital role in enhancing the functionality and responsiveness of autonomous vehicles by translating electronic signals into physical movement.
AUTOSAR: AUTOSAR, or Automotive Open System Architecture, is a global development partnership of automotive stakeholders aimed at creating a standardized software architecture for vehicle systems. This framework allows for modular design and helps ensure compatibility between different vehicle components, enabling easier integration of complex software and hardware. AUTOSAR facilitates collaboration among various manufacturers and suppliers, making it crucial for advancing vehicle architectures, sensor fusion techniques, and fault detection systems.
Bandwidth: Bandwidth refers to the maximum rate of data transfer across a network or communication channel, often measured in bits per second (bps). In the context of autonomous vehicles, bandwidth is crucial for ensuring that various systems can communicate effectively and efficiently, allowing real-time data exchange between sensors, control units, and external systems. It influences the overall performance and responsiveness of vehicle architectures, control systems, drive-by-wire technologies, and cloud computing capabilities.
Camera Data: Camera data refers to the information captured by cameras used in autonomous vehicles, including images and video that help the vehicle perceive its environment. This data is essential for tasks such as object detection, lane recognition, and traffic sign identification, allowing the vehicle to navigate safely and efficiently. The accuracy and quality of camera data are critical for the vehicle's decision-making processes and overall performance in various driving conditions.
Centralized Architecture: Centralized architecture refers to a design approach in which all computing processes and decision-making functionalities are concentrated in a single, central unit or server. This structure allows for streamlined communication and control over various subsystems, which is particularly vital for managing complex systems like autonomous vehicles. By using a centralized system, data can be processed more efficiently, and coordination among different vehicle components can be maintained seamlessly.
Control System: A control system is a set of devices or algorithms that manage, command, direct, or regulate the behavior of other systems or devices. This encompasses a wide variety of applications including feedback loops that continuously adjust system parameters to achieve desired outcomes, particularly in dynamic environments like vehicles. Within vehicle architectures, control systems are essential for ensuring stability, responsiveness, and safety of autonomous functions.
Controller area network (CAN): The controller area network (CAN) is a robust vehicle bus standard designed to facilitate communication among various electronic components in a vehicle without a host computer. This protocol is crucial for the efficient transfer of data between the numerous controllers that manage functions like engine control, safety systems, and infotainment, enabling real-time communication and synchronization among these systems. Its architecture supports both high-speed data transfer and reliability, making it essential for modern automotive applications.
Distributed Architecture: Distributed architecture refers to a system design where components are located on different networked computers, communicating and coordinating their actions by passing messages. This approach allows for improved scalability, redundancy, and flexibility within a vehicle's systems, making it particularly relevant in the context of advanced vehicle architectures, such as those used in autonomous vehicles. By distributing functionalities across multiple nodes, the system can handle failures more gracefully and adapt to changing operational demands more effectively.
Edge Computing: Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, enhancing response times and saving bandwidth. This approach is crucial for autonomous vehicles as it enables real-time processing of data from various sensors, reducing latency and improving the decision-making capabilities of the vehicle in dynamic environments.
Hardware-in-the-loop simulation: Hardware-in-the-loop simulation (HIL) is a testing method used in the development and validation of complex systems, where real hardware components are integrated with simulated software models to evaluate performance. This approach allows engineers to test the interactions between hardware and software in real-time, making it essential for ensuring that embedded systems function correctly within their operational environments.
ISO 26262: ISO 26262 is an international standard for functional safety in the automotive industry, specifically addressing the safety of electrical and electronic systems within vehicles. It provides a framework for ensuring that these systems operate reliably and can mitigate risks, which is crucial as vehicles become increasingly autonomous and complex.
Latency: Latency refers to the time delay between a stimulus and the response to that stimulus, often measured in milliseconds. In the context of autonomous vehicles, latency is critical as it affects how quickly systems can process data from sensors, make decisions, and execute actions, impacting overall vehicle performance and safety.
Lidar data: Lidar data refers to the information collected by Light Detection and Ranging (LiDAR) technology, which uses laser light to measure distances and create precise, three-dimensional maps of the environment. This technology is crucial for understanding the surroundings of autonomous vehicles, as it provides detailed information about objects, terrain, and other features in real time, enabling better navigation and obstacle detection.
Machine Learning: Machine learning is a branch of artificial intelligence that involves the development of algorithms and statistical models that enable computers to perform specific tasks without using explicit instructions, relying instead on patterns and inference. This technology is crucial for the advancement of autonomous vehicles, as it allows these systems to learn from data, improve their performance over time, and make real-time decisions based on sensory inputs.
Modular design: Modular design is an approach that breaks down a system into smaller, self-contained units or modules that can be independently created, modified, or replaced. This concept allows for flexibility, easier maintenance, and improved scalability within complex systems like vehicles. In vehicle architectures, modular design promotes efficient integration of various components, enabling manufacturers to adapt to new technologies and changing market demands without overhauling the entire system.
Perception System: A perception system is a collection of sensors and algorithms that enable an autonomous vehicle to gather, interpret, and understand data from its environment. This system plays a crucial role in identifying obstacles, lane markings, pedestrians, and other vehicles, allowing the vehicle to make informed decisions. It integrates various sensing technologies such as cameras, LiDAR, radar, and ultrasonic sensors to create a comprehensive understanding of the surroundings.
Sensors: Sensors are devices that detect changes in the environment and convert these changes into signals that can be read and interpreted by other systems. They play a critical role in autonomous vehicles by providing real-time data about the vehicle's surroundings, which is essential for safe navigation and operation. The integration of various sensors allows for improved vehicle architectures, precise drive-by-wire systems, and effective vehicle-to-infrastructure communication.
Vehicle-to-everything (v2x): Vehicle-to-everything (V2X) refers to the communication technology that allows vehicles to interact with various entities around them, including other vehicles, infrastructure, pedestrians, and the cloud. This technology aims to enhance road safety, improve traffic efficiency, and enable new applications in autonomous driving. V2X plays a crucial role in integrating vehicles into smart transportation systems and relies on advanced communication methods to facilitate these interactions.