카카오모빌리티, 물리적 AI 레벨 4 자율주행 로드맵 상세화

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#ai 서비스 #모빌리티데이터 #심야자율택시 #자율주행 #카카오모빌리티 #강남 #모빌리티 #이벤트
원문 출처: AI News · Genesis Park에서 요약 및 분석

요약

카카오모빌리티는 물리적 AI 전략의 일환으로 레벨4 자율주행 기술을 자체 개발한다는 계획을 세웠다. 김진규 카카오모빌리티 피지컬AI사업부장 부사장이 서울 코엑스에서 열린 2026 월드IT쇼 컨퍼런스에서 로드맵을 발표하고 있다. 그의 세션은 구축된 자율주행 서비스에 중점을 두었습니다. […] 물리적 AI를 위한 레벨 4 자율주행 로드맵을 자세히 설명하는 카카오모빌리티 포스트가 AI 뉴스에 처음 등장했습니다.

본문

Kakao Mobility has set out plans to develop Level 4 autonomous driving technologies in-house as part of its physical AI strategy. Kim Jin-kyu, vice president and head of Kakao Mobility’s Physical AI division, presented the roadmap at the 2026 World IT Show conference at COEX in Seoul. His session focused on autonomous driving services built around mobility platforms in the physical AI era. The event was held under the title “Beyond Idea, Into Action: AI moves Reality,” with 460 companies and organisations from 17 countries taking part, according to Yonhap. South Korea’s Ministry of Science and ICT also described the event as linked to a wider physical AI transition, where AI is applied to physical industrial fields. Kim said Kakao Mobility is working to combine autonomous driving technologies with physical infrastructure as part of its mobility strategy in Korea, and aims to establish an open autonomous driving ecosystem to support local competitiveness. Level 4 autonomy refers to systems that can handle driving in limited service areas without requiring passengers to monitor the road or take control, according to the US National Highway Traffic Safety Administration. Such systems are typically deployed in defined service areas, like autonomous taxi zones or fixed districts. Level 4 roadmap Kakao Mobility’s Level 4 roadmap is built around three technology areas: machine learning models, vehicle redundancy, and validation systems. The company is developing machine learning models designed to handle perception, decision-making, and control without human input. These functions cover how an autonomous vehicle reads its surroundings, makes driving decisions, and controls movement. Kakao Mobility also plans to use vehicle architectures with redundant systems, allowing core functions to continue operating if an important component fails. Its validation platform will combine virtual simulations with real-world driving data. The system is intended to support testing, performance improvement, and quality checks as the company develops autonomous driving services. Safety and control systems Kakao Mobility is also building an integrated safety management platform for autonomous vehicles. One component is the Autonomous Vehicle Visualizer, a 3D visualisation tool that shares a vehicle’s field of view in real time and allows passengers to monitor driving conditions. The tool is designed to show what the vehicle is detecting during operation. It shows passengers the vehicle’s driving context during a ride. The company plans to add a 24-hour control centre and an anomaly detection system using vision-language models. These systems are intended to support real-time context analysis, remote intervention, and emergency response. The planned control centre would monitor autonomous driving services after deployment. Kakao Mobility said the anomaly detection system will use vision-language models, but it did not provide details on model architecture or performance. Open ecosystem plan Kakao Mobility also outlined plans to share selected technology assets with companies, startups and manufacturers working on autonomous driving. The assets include large-scale autonomous driving datasets, high-definition (HD) maps, and platform APIs for ride-hailing and dispatch. HD maps support autonomous driving by providing detailed road information used for localisation and driving decisions. The company said the asset-sharing plan would allow other industry participants to develop autonomous driving technologies without building all the underlying infrastructure independently. Kakao Mobility also plans to share operational resources, including fleet management systems and on-site response abilities. These are part of the company’s plan to support an open domestic autonomous driving ecosystem. Gangnam service data The company pointed to its late-night autonomous vehicle service in Seoul’s Gangnam district as one example of its current work. The service is available through the Kakao T platform, where users can access autonomous driving services with existing mobility options. The Gangnam late-night autonomous taxi service recorded 7,754 rides from its launch on September 26, 2024, to February 28, 2026, according to the Seoul Metropolitan Government. The city said no accidents were attributed to autonomous driving technology during that period, and the service averaged about 24 trips per operating day. The service moved from a free pilot to paid operation in April 2026. Seoul also expanded the fleet from three vehicles to seven, excluding two reserve vehicles. The service can be called through Kakao T using either the Seoul Autonomous Car icon or the regular taxi-hailing menu. Kakao T groups multiple mobility services in one app, including taxi, navigation and vehicle-related services. The Gangnam service is accessed through Kakao Mobility’s existing mobility platform. (Photo by Hyundai Motor Group) See also: Hyundai expands into robotics and ph

Genesis Park 편집팀이 AI를 활용하여 작성한 분석입니다. 원문은 출처 링크를 통해 확인할 수 있습니다.

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