[구태완 테크 칼럼] GORE: What보다는 Why에 집중한 요구사항 분석

목표 지향 요구공학(GORE)은 단순히 기능 나열이 아닌 그 기능의 존재 이유와 목표, 그리고 그 이유가 사람과 조직의 가치에 어떻게 연결되는지를 생각하게 해 준다. 이 글은 요구사항 작성에서 “왜”를 묻는 중요성을 짚는다.

2026-01-02 온라인기사

Apex.AI-QNX, 결정론적 AI 가속 위한 플랫폼 호환 발표
Apex.OS와 QNX SDP 8.0 간 호환 ··· 양산 수준 자율·로봇 시스템 개발 지원 

에이펙스에이아이와 QNX가 자율·로봇 시스템을 위한 결정론적 AI 가속을 목표로 협력에 나섰다. Apex.OS가 QNX SDP 8.0과 호환되면서, 고성능 AI와 안전 인증이 가능한 실시간 실행을 동시에 갖춘 양산 수준 플랫폼 구현이 가능해졌다.

2026-01-02 온라인기사

Fog doesn’t hide sensors - it hides operations
DeepFusion AI revisits autonomous driving through 4D imaging radar

Autonomous driving changes the question the moment it enters real-world operations—not whether it can see better, but whether it can keep going even when it cannot see. On this, SungHun Yu, CEO of DeepFusion AI, speaks through the lens of 4D imaging radar and RF-domain deep learning.

2026년 01월호 지면기사

DeepFusion AI, 4D 이미징 레이다로 다시 묻는 자율주행
안개는 센서를 가리지 않는다, ‘운영’을 가린다

자율주행이 실제 운영 단계로 들어가는 순간 질문은 바뀐다. 더 잘 보느냐가 아니라 보이지 않는 순간에도 멈추지 않을 수 있느냐로. 이에 대해 4D 이미징 레이다와 전파계 딥러닝과 함께 DeepFusion AI의 유승훈 CEO가 말한다.

🎧2026년 01월호 지면기사

자동차 SW 신뢰성을 위한 동기화된 타이밍 측정의 중요성

나노초 단위로 얽힌 태스크와 이벤트를 정확히 측정하고 동기화하지 못한다면, 소프트웨어의 안전성은 검증될 수 없다. 이 글은 자동차 소프트웨어 신뢰성을 입증하기 위한 동기화된 타이밍 측정의 중요성을 살펴본다.

2026년 01월호 지면기사

벡터 HIL Farm, 고객사 CT 팩토리 구축으로 SDV 시대 선도
“테스트 환경의 패러다임을 바꿨다” 

벡터의 HIL Farm은 현대모비스 CT 팩토리 구축에 적용돼 자율주행 소프트웨어 검증 효율과 품질을 동시에 높였다. 현대모비스 김민태 책임연구원은 “CT 팩토리 구축을 통해 SW 개발 효율과 품질 확보 방식이 크게 개선됐다”고 말했다. 

2026년 01월호 지면기사

The Real Question in China’s Intelligent Driving: Not Speed, but Boundaries
China’s AI & Autonomous Driving Debate Shifts From “Faster” to “Where the Line Is”

I attended the International Summit on Connected Vehicles at Automechanika Shanghai. When people imagine discussions in China’s automotive industry, they often expect an expansionist narrative—“faster, bigger, more.” But this panel was different. If you follow the discussion closely, you hear maturity, strategy, and a sober willingness to confront risk behind the overwhelming pace. The panelists did not frame AI and autonomous driving around the possibilities of technology, but around the boundaries of technology—where systems should and should not be trusted. The conversation was driven by fundamental questions: safety responsibility across Level 2 and Level 3+, the risks of probabilistic models, and the problem of user misuse. They also spoke candidly about real implementation challenges: the optimal balance between simulation and public-road testing, emotion-aware multimodal interaction, fail-safe design, and redundancy.

2026년 01월호 지면기사

Why Track Testing Is Becoming Critical Again for Advanced ADAS and Autonomous Driving

As China accelerates the commercialization of advanced autonomous driving, limitations in existing validation frameworks—based on standardized tracks and public-road testing—are becoming increasingly apparent. These approaches are struggling to cope with the complexity of real urban environments. At the International Summit on Connected Vehicles held during Automechanika Shanghai, Professor Xiong Lu of Tongji University emphasized that track testing is once again emerging as a critical pillar in autonomous driving validation.

2026년 01월호 지면기사

Robotaxis Are Not About Technology — They’re About Operations
Pony.ai and the New Order of Autonomous Commercialization

Waymo continues to set the benchmark for “the safest autonomous driving,” expanding city by city with a strong focus on technology and validation. Cruise pursued rapid scaling, but the large-scale pullback following its 2023 accident exposed the limits of that strategy. Pony.ai, by contrast, is redefining robotaxis as an industrial system, placing cost structure, operational capability, and full lifecycle management at the center of commercialization. At Automechanika Shanghai, Pony.ai Vice President Wang Qiang emphasized that the future of autonomous driving rests not on technological novelty alone, but on practical realities—operations, cost, and end-to-end system design. Not the performance of a single vehicle, but the ability to operate thousands simultaneously. Not a single trip, but a lifecycle spanning vehicle introduction, operation, and retirement. This is where Pony.ai is outlining what it takes for autonomous driving to become a true industry.

2026년 01월호 지면기사

Automechanika Shanghai 2025 and What Comes After ‘China for China’:
A Supply Chain That Is Complete - and Not Complete at All

China - has it really “completed everything”? Throughout a week at Automechanika Shanghai 2025, walking through countless booths and crowds, I kept turning this question over in my mind. Now that the phrase “China for China” has hardened into a fixed narrative, Shanghai seemed almost to whisper a different sentence: the supply chain is complete, and yet still not complete. That is the story this show is trying to tell - and perhaps, its wish as well.

2026년 01월호 지면기사