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자율주행 맵 산업 분석(2024년)
Autonomous Driving Map Industry Report,2024
상품코드 : 1400761
리서치사 : ResearchInChina
발행일 : 2023년 12월
페이지 정보 : 영문 270 Pages
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한글목차

HD 지도의 자격에 대한 감독이 엄격해지면서 지도 수집 비용, 업데이트 빈도, 커버리지 등의 문제가 부각되고 있습니다. 도시용 NOA(Navigation on Autopilot) 붐이 일고 있는 가운데, 2023년에는 '경량 지도'형 지능형 운전 솔루션이 화두로 떠오르고 있습니다. 이 솔루션은 오프라인 HD 맵에 대한 의존도를 낮춰 HD 맵 개발에 도전장을 내밀고 있습니다.

자율주행의 개발 과정에서 인간과 기계의 협동 운전이 일정 기간 중 존재한다는 것을 알 수 있습니다. 이 단계에서 필요한 지도가 반드시 HD 지도일 필요는 없습니다. 서로 다른 지도의 보완적인 특성을 통합한 멀티소스 지도가 이 단계의 자율주행 요구에 더 적합할 수 있습니다.

차세대 자율주행 지도 개발, 각 조직과 기업은 어떻게 대응할 것인가?

정부: HD 지도의 측량-매핑 A급 자격을 강화하는 한편, ADAS 지도와 B급 측량-매핑 자격 심사를 강화합니다.

OEM: 내비게이션용 전자지도 측량 및 매핑 A급 자격에 대한 관련 부문의 심사가 엄격해짐에 따라 OEM은 측량 및 매핑 A급 자격을 도입하는 것을 자제하고 있습니다. 현재 일부 OEM은 실시간 지도 제작에 신경망 모델 알고리즘을 사용하여 오프라인 HD 지도에 대한 의존도를 낮추고 있으며, Tesla, Li Auto, Xpeng, Huawei의 ADS 지원 모델이 그 대표적인 예입니다.

지도 프로바이더: 시장 수요를 충족시키기 위해 SD 데이터, HD 데이터, LD 데이터 등을 하나의 지도에 통합하여 내비게이션의 연속성을 보장하는 '경량화 지도' 솔루션을 발표했습니다. 일례로 텐센트는 '3-in-one' 지능형 운전 지도를 발표한 후 지도 프로바이더, 자동차 제조업체, 자율주행 기업 및 기타 기업의 협력 구축을 지원하는 '지능형 운전 클라우드 지도'를 선보였습니다.

"경량 지도" 솔루션에 적극적인 것은 주로 신흥 자동차 제조업체들입니다. 그 이유 중 하나는 그들이 도시 지역의 NOA 기능을 매우 빠르게 구현하고 있으며, HD 지도가 그들의 관련 요구에 부응하지 못하기 때문입니다.

세계 및 중국의 자율주행 맵 시장·산업에 대해 분석하고, 기술 개요 및 관련 규제·기준, 기술·시장 최신 상황(탑재 대수·보급률, 기술의 활용 동향 등), 향후 기술개발·활용 시나리오나 시장 성장의 방향성, 주요 기업의 개요와 주력 제품, 등의 정보를 정리하여 전해드립니다.

목차

제1장 자율주행 맵에 관한 정책·기준·규제의 현황

제2장 자율주행 맵 시장의 현황

제3장 HD 맵 시장의 현황

제4장 OEM의 지능형 운전 맵 애플리케이션 레이아웃

제5장 국내계·외자계 맵 프로바이더

제6장 HD 맵 기술 기업

KSA
영문 목차

영문목차

As the supervision of HD map qualifications tightens, issues such as map collection cost, update frequency, and coverage stand out. Amid the boom of urban NOA, the "lightweight map" intelligent driving solution has become a hot topic in 2023. This solution lessens the dependence on offline HD maps, posing a challenge to the development of HD maps.

From the development process of autonomous driving, it can be seen that human-machine co-driving will exist for a period of time. The need for maps in this phase is not necessarily HD maps. Multi-source maps that integrate the complementary characteristics of different maps may be more suitable for the needs of autonomous driving in this phase.

How do players respond to the development of new-generation autonomous driving maps?

Government: while tightening the Class A qualification for HD map surveying and mapping, work to enhance the review of ADAS maps and Class B surveying and mapping qualification.

In June 2023, the Map Technology Review Center of the Ministry of Natural Resources announced the phased progress in review of ADAS maps of ordinary urban roads across China, and allowed companies to submit ADAS maps of nationwide ordinary urban roads for review in batches. Currently, NavInfo's approved nationwide urban ADAS map data have covered 120 cities in 30 provinces; Baidu Maps has ADAS maps of 134 cities approved.

OEMs: relevant departments' stricter review of the Class A qualification for navigation electronic map surveying and mapping has discouraged OEMs to deploy the Class A qualification for map surveying and mapping. At present, some OEMs use neural network model algorithms for real-time mapping and lower reliance on offline HD maps, and the ADS-enabled models of Tesla, Li Auto, Xpeng, and Huawei are typical cases; some other OEMs prefer stability, and obtain surveying and mapping qualifications by way of applying for Class B qualification or establishing new joint ventures with map providers. For example, GAC together with its partners such as Nanjing Institute of Surveying, Mapping and Geotechnical Surveying Co., Ltd. co-funded "Guangdong Guangqi Yutu Equity Investment Partnership (Limited Partnership)"; Anhui NIO Smart Mobility Technology Co., Ltd., a subsidiary of NIO, applied for the Class A qualification for Internet map services.

Map providers: to meet the market demand, they launch "lightweight map" solutions, putting SD data, HD data, LD data, etc. on one map to ensure the continuity of navigation. One example is Tencent which introduced the "Intelligent Driving Cloud Map" to support the cooperative construction by map providers, automakers, autonomous driving companies and other players, after launching its "three-in-one" intelligent driving map.

Emerging carmakers take the lead in launching "lightweight map" solutions.

At present, OEMs' solutions that do not rely on HD maps don't mean that they do not use maps at all, but subtract elements from HD maps or add them to navigation maps instead.

It is mainly emerging carmakers that are more active in "lightweight map" solutions. One reason is that they implement urban NOA functions very quickly, and HD maps fail to answer their relevant needs.

Xpeng

In the first half of 2023, Xpeng started developing intelligent driving solutions based on SD maps. NGP that uses HD maps or does not use adopts the same technology stack. The only difference is that the original HD map input is replaced by the navigation map input, and the understanding of navigation information in real-time perception.

Xpeng's solution that does not use HD maps has the advantages of 4 to 10 times faster generalization speed, completely solving the problem of data freshness, reducing costs, and popularizing intelligent driving, compared with the solution using HD maps.

The "no offline HD map" solution implemented by Xpeng relies on XNet to build a "HD map" in real time.

Li Auto

Li Auto has launched urban NOA in 2023. This solution does not rely on HD maps. It aims to construct the features of intersections to assist in real-time perception and mapping. In a word, road sections are "unmapped", and intersections are mapped by crowdsourcing.

Li Auto is now promoting the NPN solution, hoping to solve the problem of online map updates.

In terms of OEMs' solutions, despite less dependence on HD maps, the "lightweight map" solution has higher requirements for vehicle perception and algorithms.

Conventional map providers launch lightweight autonomous driving map solutions to meet demand.

The voice of OEMs to "not rely on HD maps" is growing ever louder. To cater to the market demand, conventional map providers also make changes, trying hard to solve the three enduring problems of HD maps: update frequency, coverage area, and cost, and launching map products that more fit in with the current needs of autonomous driving.

Baidu

In July 2023, Baidu MapAuto 6.5, a human-machine co-driving map, was launched. It is a full 3D lane-level map and also an all-scenario human-machine co-driving map. It can provide three types of data: SD, LD and HD. Wherein, SD data has covered the whole country and is currently available on 10 million vehicles. Baidu's LD lightweight map data service consists of lane-level topology, complex scene geometry, experience layer, and dynamic information layer, allowing for daily update.

Amap

The new HQ Live MAP, launched in June 2023, combines the merits of HD MAP and SD MAP. In spite of a lower accuracy than HD MAP (absolute accuracy: 50cm, relative accuracy: 10cm), HQ Live MAP is enough for ADAS scenarios (highway and urban expressway scenarios: absolute accuracy of 1m, and relative accuracy of 30cm; ordinary urban road scenarios: relative accuracy of 1m), and it also simplifies unnecessary map elements in ordinary urban road scenarios, further reducing production and deployment costs.

Tencent

The latest Intelligent Driving Cloud Map, released in September 2023, enables fully cloud-based autonomous driving maps, supports element-level and minute-level online updates, and allows for the cooperative construction by map providers, automakers, autonomous driving companies and other players.

Tencent Intelligent Driving Cloud Map features scalable multi-layer forms, covering basic map layer, update element layer, ODD dynamic layer, driving experience layer and operation layer. Automakers can flexibly configure and manage the layers as they need, and build a data-driven operation platform suitable for themselves by combining it with their own data layer.

Autonomous Driving Map Industry Report,2024 highlights the following:

Autonomous driving map (formulation of policies, regulations, standards, etc.);

Vehicle map amid the development of urban NOA (development direction, coping strategies of conventional map providers, main types of maps used in urban NOA, etc.);

HD map (market status, market size, company pattern, business model, development challenges, etc.);

Application scenarios of intelligent driving map (high-speed autonomous driving of passenger cars, low-speed parking, autonomous human carrying, autonomous object carrying, etc.);

Major Chinese and foreign map providers (map product series, new product layout, product application cooperation, etc.);

HD map technology companies (technology layout, new technology R&D, etc.).

Table of Contents

1 Status Quo of Policies, Standards and Regulations Concerning Autonomous Driving Map

2 Status Quo of Autonomous Driving Map Market

3 Status Quo of HD Map Market

4 Intelligent Driving Map Application Layout of OEMs

5 Chinese and Foreign Map Providers

6 HD Map Technology Companies

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