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European and North American Advanced Driver Assistance Systems (ADAS) and High Definition (HD) Mapping Market, 2018 Updated Research Available
Start-ups, With Their Innovative Business Model Will End the Dominance of Traditional Map Developers
09-Apr-2019
North America
Market Research
ME85-01-00-00-00
AU01822-NA-MR_23010
In today’s world, while robots have the capability to do some things more efficiently than humans, humans are still much wiser when it comes to real-time decision-making capability. One such application that comes to light is driving and navigation. For example, decisions, such as stopping the vehicle at the right place, watching for a traffic signal at the intersection, or avoiding a split at the last minute, which humans take for granted, are still much harder for robots to make.
In the near future, when cars start driving themselves, they will have to ‘see’ what is around them to maneuver leaving no room for errors. To achieve this, vehicles will not only rely on sensors but will also require machine-readable maps of the world, containing accurate and precise road information. Autonomous vehicles will use sensors to make driving decisions on the fly, but vehicle sensors cannot observe everything all the time. Vehicle sensors can be blinded by corners, other vehicles, or bad weather conditions. Even though the sensors may notice an obstacle, they may not do so early enough to make decisions. In addition, lanes and signs may be missing on the road or knocked over or hidden by bushes, and therefore, can go undetected by sensors. Such accidents will be averted when sensor data will be combined with map data.
Research Highlights
This research service provides an overview of the mapping market along with the differentiation between the types of maps and levels of autonomy that they will support. In addition to the overview, the study covers the components and attributes of ADAS and HD maps, which will help an autonomous vehicle to operate safely.
In conjunction with different processes of mapping, major HD map developers have been segmented on the basis of the mapping process they follow and compared on the basis of various assessment criteria, such as localization accuracy, the technology used for developing HD maps and needed by customers, current partnerships, and cost of acquiring the solution for a customer.
Key Issues Addressed
- How will ADAS and HD maps enable safe operation of an autonomous vehicle?
- How are ADAS maps different than HD maps, and why will HD maps replace ADAS maps for L4 and L5 autonomy?
- What are the different processes that traditional map makers and start-ups follow to build HD maps?
- Which are the different solutions offered by map-making companies, and how do they fare against each other?
- Which are the OEMs and other customers that these HD map developers have partnered with, for development and testing?
Levels of Autonomy and Maps
HD Mapping Segments
Comparative Analysis—End-to-end Base Maps and Updates
Comparative Analysis—Crowdsourced Data Collection for Updates
Comparative Analysis—In-house Maps With Full Stack AV Software
Key Conclusions
Research Scope
Research Aims and Objectives
Key Questions this Study will Answer
Research Methodology
SAE Definitions
Parameters to Compare Profiles
SD, ADAS, and HD Maps
Autonomous Vehicles and ADAS and HD Maps
Elements of HD Maps
HD Mapping Process
HD Mapping Tools
Importance of an HD Base Map
Segmentation of Mapping Companies
End-to-end Mapping Companies
Crowdsourced Mapping Companies
In-house Mapping Companies
HERE Overview
HERE Overview (continued)
TomTom Overview
TomTom Overview (continued)
Civil Maps Overview
Civil Maps Overview (continued)
CARMERA Overview
CARMERA Overview (continued)
Sanborn Map Company Overview
Sanborn Map Company Overview (continued)
Voxelmaps Overview
Voxelmaps Overview (continued)
Mobileye Overview
Mobileye Overview (continued)
DeepMap Overview
DeepMap Overview (continued)
Mapper.ai Overview
Mapper.ai Overview (continued)
Mapbox Overview
Mapbox Overview (continued)
Waymo Overview
Waymo Overview (continued)
Oxbotica Overview
Oxbotica Overview (continued)
Drive.ai Overview
Drive.ai Overview (continued)
Growth Opportunity—Investments and Partnerships from OEMs/TSPs
Strategic Imperatives for Success and Growth
Key Conclusions
The Last Word—3 Big Predictions
Legal Disclaimer
Market Engineering Methodology
Abbreviations and Acronyms Used
List of Exhibits
List of Exhibits (continued)
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