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【分析レポート:技術】自律走行自動車の高確度・リアルタイムマップ

High Accuracy and Real-time Maps for Autonomous Vehicles

Technology Analysis | AN-2266 | 2Q 2016

 

出版社 出版年月価格
ABI Research
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2016年4月お問い合わせください

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Autonomous and fully driverless vehicles will require high accuracy maps enabling precise positioning within lanes based on reference points on 3D models of the road environment. Additionally, maps will need to be updated continuously with real-time information about traffic, roadworks, and any other relevant information needed for anticipating and planning the path ahead and emulate human driving. These requirements can only be met by crowdsourcing sensor data from  vehicles on the road, transforming both the way maps are generated and the entire ecosystem involved in the creation of maps, with new players like car OEMs, Tier1 players, and software vendors already showing interest.

This report discusses in detail the characteristics of driverless maps, production processes, the players involved and their solutions, issues and challenges, and new pricing and business models. It also provides in-depth information about crowdsourcing technology, including hybrid approaches and the role of 5G.  
 



目次

Table of Contents

1. THE ROLE OF MAPS FOR ADAS, AUTONOMOUS, AND DRIVERLESS VEHICLES1.1. ADAS, Autonomous, and Driverless Vehicles

1.2. Maps as High-accuracy, 3D-positioning References for Localization
1.3. Map-as-a-sensor (MaaS)
1.4. Humanized Driving
1.5. Real-time Maps and Vehicle-to-vehicle Communication

2. DIGITAL MAPS FOR DRIVERLESS CARS: CHARACTERISTICS AND TECHNOLOGIES2.1. Characteristics and Requirements

2.2. Corporate Mapmaking versus Community Input and Sensor Data Crowdsourcing
2.3. Camera / Radar versus Lidar Sensors
2.4. On-board versus Cloud-based Maps
2.5. The Future of Digital Maps in the Driverless Vehicle Era

3. DIGITAL MAP VENDORS AND PLAYERS3.1. TomTom

3.2. HERE (Daimler, BMW, and Audi Consortium)
3.3. Google
3.4. Baidu
3.5. Zenrin
3.6. Toyota
3.7. Mobileye, GM, VW, and Nissan
3.8. HARMAN
3.9. Continental
3.10. Apple
3.11. Uber

4. ISSUES AND CHALLENGES4.1. Lack of Standards

4.2. Fragmentation and the Lack of Cooperation within the Automotive Industry
4.3. Technological Uncertainty
4.4. Liability Concerns
 

 

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プレスリリース

[プレスリリース原文]

Vehicle Sensor Crowdsourcing to Transform the Digital Map Ecosystem in Preparation for the Driverless Era


LONDON, UNITED KINGDOM - 07 Apr 2016
ABI Research, the leader in transformative technology innovation market intelligence, finds that highly accurate, real-time maps are an essential next step as the automotive industry steers toward the future of fully driverless cars. All autonomous and driverless vehicle maps will need to combine accuracy, environmental models, and real-time attributes allowing positional and temporal awareness.  

“Crowdsourcing is crucial,” says Dominique Bonte, Managing Director and Vice President at ABI Research. “As connected vehicles include more low-cost, high-resolution sensors, cars will capture and upload this data to a central, cloud-based repository so that automotive companies, such as HERE, can crowdsource the information to build highly accurate, real-time precision maps. This is fueled by the rapid adoption of a wide range of active safety systems with more than 94 million longitudinal assistance ADAS systems expected to ship in 2026.”

The new 3D, dynamic maps will provide a complementary data set to ADAS sensors for an overall smoother driving experience. Whereas sensors provide real-time visibility on a vehicle’s immediate vicinity for last-minute obstacle detection and collision avoidance, maps extend this visibility to allow vehicles to anticipate those situations long before the sensors would even have to detect them.

“Humans managed to learn how to drive without maps, which leaves many wondering why driverless vehicles can’t do the same,” continues Bonte. “The short answer is: they can. But there is still an inherent need for reliability and robustness, which can only be achieved by building redundancy into autonomous vehicle technology. Maps will work in harmony with ADAS sensors to dramatically improve overall accuracy and predictability.”

The battle for controlling crowdsourced driverless HD map technology is heating up. Daimler, jointly owning HERE with BMW and Audi, confirmed talks with Amazon and Microsoft to join the consortium. Mobileye signed agreements with GM, VW, and Nissan to use its Road Experience Management (REM) mapping platform. And at the GPU Technology Conference (GTC), NVIDIA announced its new HD mapping approach based on its DRIVE™ PX machine vision hardware platform. Car OEM Toyota also announced its own mapping platform, working with mapping supplier Zenrin in Japan.

ABI Research argues that the biggest challenge for the new mapping paradigm is the lack of standards coupled with high levels of fragmentation in the automotive industry. Despite HERE’s efforts to assemble the industry around its Sensor Integration Standard for real-time map attributes, many players, like ADAS vendor Mobileye, are vying to play a role in map data crowdsourcing and proposing and/or imposing their own proprietary approaches.

“The industry needs to set standards, if only for the fact that standards readily allow vehicles to exchange real-time map attributes between each other,” concludes Bonte. “In the early stages, new players introducing their own solutions might actually fuel innovation and accelerate adoption of crowdsourced map technology. But in the long term, economies of scale and a maturing market environment will require the adoption of standards and open platform approaches.”

These findings are part of ABI Research’s Automotive Safety and Autonomous Driving Service, which includes research reports, market data, insights, and competitive assessments.
 

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