The growing development of self-driving systems utilize a variety of sensor-based technologies such as cameras, radar, LiDAR, GPS and machine learning algorithms to enable vehicles to operate in an environment where there may be some (but limited) human interaction. The self-driving systems collect and analyze vast amounts of environmental data in near real-time and generate vehicle operating decisions based upon this analysis. As such, autonomous technologies have had significant effects on the automotive industry, logistics companies, insurance providers and city planners.
While the regulatory and safety evaluations of fully autonomous vehicles continue to advance, semi-autonomous systems are currently changing how consumers think about purchasing vehicles and changing business models within the automotive industry. As such, understanding both the technology behind autonomous systems and the potential market changes created by these systems are key factors for any company or government agency interested in participating in the future of mobility.
1. Key Technologies That Enable Autonomous Systems
In order to provide safe and reliable operation, the autonomous systems must operate across all layers of a vehicle’s operating architecture; including perception, decision making and control.
The core technologies that support each of the layers include:
- Sensors such as LiDAR, Radar and Camera Technology
- AI-Powered Object Detection Algorithms
- Real-Time Mapping and Vehicle Localization
- Automatic Braking and Steering Controls
All of these technologies must work in unison in order for the autonomous system to function reliably and safely.
2. Safety and Regulatory Issues Associated with Autonomous Vehicles
Autonomous vehicles offer many benefits, one of the largest being the reduction of human error, which is the leading cause of accidents. However, safety validation of autonomous vehicles remains a complex issue.
Regulatory bodies, who are responsible for evaluating the safety of autonomous vehicles, evaluate a wide range of testing data related to safety issues. Additionally, regulatory bodies also assess liability and cyber security framework.
Key regulatory focus areas:
- Collision Avoidance Performance of Autonomous Vehicles
- Ability to Record Data from the Vehicle after a Collision or Other Incident to Review
- Cyber Security Protections to Prevent Unauthorized Access
- Determining Who is Responsible if an Autonomous Vehicle Malfunctions
Policymaker Decisions Will Determine How Quickly Autonomous Vehicles Are Adopted.
3. Economic Impacts of Autonomous Systems
Autonomous systems will have an economic impact on industries other than just the automotive manufacturing sector.
Some of the potential economic impacts of autonomous systems include:
- Reduced Logistics Costs Due to Autonomous Fleets
- Changes to Risk Models Used by Insurance Companies
- Transformed Ride-Sharing Services
- Redesign of Urban Infrastructure
Each of these areas presents opportunities for new revenue streams, but also creates new workforce challenges.
4. Trust and Acceptance of Autonomous Vehicles
The degree of trust consumers have regarding the safety of autonomous vehicles will ultimately dictate the rate at which autonomous vehicles are adopted into the marketplace.
Reliability and Transparency Regarding System Limitations and Safety Records of the Autonomous System Will Drive Public Acceptance.
Additionally, Consumers Will Evaluate Convenience Alongside Their Perceived Risk When Considering the Purchase of an Autonomous Vehicle.
Drivers of Adoption Include:
- Documented Proven Safety Data Regarding Autonomous Vehicles
- A Clear Explanation of System Limits
- Gradual Integration of Driver-Assist Features Into New Vehicle Purchases
- Lower Operational Costs
Ultimately, it is the level of trust that consumers have in autonomous vehicles that will determine the long-term scalability of the technology.
Conclusion
While the primary concern regarding the adoption of autonomous systems relates to safety and regulatory issues, the economic impact and consumer trust associated with autonomous systems will ultimately dictate the rate at which autonomous systems become part of the overall transportation infrastructure.
Therefore, the successful implementation of autonomous systems will depend upon the ability of developers to provide reliable and accurate integration, and to ensure that regulatory oversight is transparent and provides assurance to the public. Additionally, a successful transition to autonomous systems will require gradual adoption models that allow consumers to become accustomed to autonomous systems while also providing assurance that the autonomous system operates safely and reliably.