As the automotive industry evolves, so does the technology that propels it, namely generative AI. Autonomous driving represents a significant leap forward in this evolution, promising to redefine our roadways. This guide explores autonomous driving – explaining what it is, how it works, the challenges, the benefits, and more.
What is autonomous driving?
Defined by the Society of Automotive Engineers (SAE), autonomous driving includes six levels of driving automation, ranging from minimal to total automation. These levels have been widely adopted by various regulatory bodies, including the U.S. Department of Transportation, and detailed by the National Highway Traffic Safety Administration in their publication, Levels of Automation.
The six levels of driving automation range from Level 0 (Momentary Assistance), where the human driver performs all driving tasks with limited assistance in the form of warnings, alerts, and emergency safety interventions, to Level 5 (Full Automation), where no human intervention is required at any time during the driving process. Levels 1 (Driver Assistance) and 2 (Additional Driver Assistance) involve some automated features like steering or acceleration controls but require significant human driver engagement. Level 3 (Conditional Automation) allows the vehicle to manage all aspects of driving in certain conditions, though human override is still needed. Level 4 (High Automation) enables the vehicle to operate independently in most scenarios without any human intervention, but it may be limited to specific locations, environments, or conditions.
To clearly understand autonomous driving, it’s crucial to understand that autonomous and automated driving are not synonymous. While an automated car operates under specific commands and drives within those parameters, a fully autonomous vehicle can make decisions and operate independently, akin to having self-awareness. Furthermore, the term “self-driving” is often used interchangeably with autonomous; however, a self-driving car typically requires a human passenger to intervene if necessary, making it less independent than a fully autonomous vehicle.
How does autonomous driving work?
Autonomous vehicles function through a complex network of sensors, machine learning systems, actuators, algorithms, and processors that, together, execute sophisticated software. These vehicles are equipped with multiple types of sensors to create a detailed map of their surroundings in real-time. The sensor types include:
- Radar Sensors: Track the position of nearby cars.
- Video Cameras: Identify traffic signals, read road signs, and monitor other vehicles, along with pedestrians and animals.
- Lidar Sensors: Utilize light pulses to measure distances and detect road edges and lane markings.
The software processes sensor data in real-time to navigate paths and control the vehicle's mechanics like acceleration, braking, and steering. Simultaneously, the software integrates hard-coded rules, obstacle avoidance algorithms, predictive modeling, and object recognition to make autonomous navigation possible.
Current Challenges of Autonomous Driving
Despite advancements, autonomous driving still faces many challenges:
- Lidar and Radar Signal Interference: How do autonomous vehicles perform in environments with multiple similar systems? Can the existing radio frequency spectrum support widespread adoption without signal interference?
- Weather and Road Conditions: Autonomous sensors must reliably detect and interpret road signs and lane markings under all weather conditions. How effective are these technologies in rain, snow, or on dirty roads?
- Complex Travel Conditions: How do autonomous vehicles perform in diverse traffic conditions, such as congested roads or mixed traffic environments involving both autonomous and human-driven vehicles?
- Laws and Regulations: With autonomous driving regulations increasingly governed at the state level in the U.S., how will the differences affect drivers crossing state lines? How will the potential variance in regulations in the U.S. affect development across the globe?
- Liability and Insurance: Determining liability in accidents involving autonomous vehicles is complex. Who is held accountable–the owner, passenger, or manufacturer?
- Human Factors: Human drivers often rely on non-verbal cues and subtle forms of communication for split-second and often life-saving decision-making. Can autonomous vehicles replicate these human-like judgments?
What are the benefits of autonomous driving?
The potential benefits of autonomous driving extend well beyond mere convenience:
- Increased Independency: Autonomous driving offers mobility solutions for individuals unable to drive, such as the elderly, disabled, or young.
- Environmental Impact: By optimizing driving patterns and decreasing idle times, autonomous vehicles could reduce CO2 emissions.
- Reduced Congestion: Autonomous vehicles might lower overall traffic congestion through efficient route and traffic management.
- Economic Efficiency: Autonomous vehicles have the potential to decrease vehicle and infrastructure costs significantly by opening up new possibilities for ride-sharing.
- Urban Design: With autonomous vehicles and advanced ride-share programs, urban landscapes may see a reduced need for parking spaces and enhanced walkability.
Discover Encora's Digital Solutions for Automotive Industry
As the automotive industry continues to shift towards connected, electric, and autonomous vehicles, Encora is at the forefront of providing innovative digital engineering solutions. From developing engaging infotainment systems to leading the charge in Advanced Driver Assitance (ADAS), Encora’s contributions are setting new standards in automotive technology.
To learn more about how Encora can drive your company’s automotive innovations, speak with an expert today.
