[Hwang Miseon's Crisis Escape – Season 4] Autonomous driving is not abo...

[Image credit: AI-generated by the author]

[By Hwang Miseon, Columnist, Korea Lecturer News] When discussing autonomous driving technology, we tend to begin with questions of performance.

“How accurate is it?” “How safe is it?” These are the most common inquiries.

However, such questions fail to fully capture the essence of autonomous driving.

The core of this technology lies not in how well it performs, but in where it can operate—its range of applicability.

Autonomous driving systems are not designed to function under all conditions.

They operate properly only when a set of environmental and operational conditions are satisfied—such as road geometry, lane clarity, weather, time of day, speed range, and traffic conditions.

This set of conditions is defined as the Operational Design Domain (ODD).

ODD is not merely a list of operating conditions; it represents the boundary conditions within which the system can function reliably.

The problem arises when these boundaries are not clearly defined.

Within its defined conditions, an autonomous system can demonstrate a very high level of performance.

However, once those conditions are exceeded, the system can no longer guarantee the same level of reliability.

For example, in situations where visibility is reduced due to rain or fog, where lane markings are faded or unclear, or where unexpected events occur, the uncertainty in perception and decision-making increases rapidly.

At this point, the issue is not simply a degradation in performance.

Rather, the system undergoes a transition—from safe automation to a state of unpredictability—as the underlying assumptions of its operating environment collapse.

This characteristic is often interpreted as a limitation of the technology.

More precisely, it reflects a structural property of autonomous systems.

Autonomous driving is not a universal solution capable of handling all scenarios.

It is a conditional system that achieves full performance only within a defined set of constraints.

Therefore, the key question in evaluating autonomous driving is not

“How well does it perform?”

but rather,

“Up to where does it work?”

This question goes beyond performance evaluation—it defines both the applicability and the limits of the system.

Particularly at Level 4 and higher levels of automation, the definition of the ODD effectively becomes the definition of the system itself.

The roads it can operate on, the weather it can handle, and the speed ranges it supports—these factors simultaneously determine both its capability and its risk.

Ultimately, the advancement of autonomous driving technology is not achieved through performance improvements alone.

What matters more is the ability to clearly define and manage its boundaries.

Only when we precisely define where a technology works can we also understand where it becomes unsafe.

This is not merely a technical issue.

It is a fundamental criterion that directly influences safety, policy, and accountability.

Autonomous driving is not a perfect technology.

But when its boundaries are clearly understood and properly managed, it can become a system we can truly trust.

Columnist Profile

Hwang Miseon is a disaster safety instructor who has conducted on-site safety education for citizens and students. Based on repeated observations of “stoppages” and “concentrations” in training environments, she interprets disasters not as issues of individual behavior, but as problems of space and structure. She analyzes risks in everyday environments—such as hospitals, schools, public transportation, and performance venues—through movement paths, bottlenecks, guidance systems, and exit functionality. She is currently conducting research on evacuation structure analysis using microscopic pedestrian simulation.

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