Qualcomm Driving Data Platform Powers TomTom's HD Map Mapping Data Crowdsourcing Program for Autopilot

—Qualcomm Snapdragon 820Am automotive processor with precise positioning, in-vehicle machine learning, heterogeneous computing and connectivity

Help generate HD maps quickly and efficiently—

Barcelona, ​​February 27, 2017 - Qualcomm Incorporated (NASDAQ: QCOM) subsidiary Qualcomm Technologies, Inc. today announced that it is working with TomTom (TOM2), the world's leading navigation and mapping product company, to drive data using Qualcomm® The platform (Qualcomm® Drive Data Platform) supports high-definition map crowdsourcing to accelerate the future of autonomous driving. The Qualcomm Driving Data Platform utilizes a number of cutting-edge technologies to intelligently capture and analyze data from different vehicle sensors to make the vehicle smarter: determine its location, monitor and learn driving patterns, sense the surrounding environment and reliably and accurately perceive the information The world shares. TomTom's high-definition maps (including RoadDNA) are digital map-based products that are revolutionary and highly accurate, helping autopilots accurately position themselves on high-speed travel and help decide which driving route to take.

Traditional map development requires dedicated vehicles with professional-grade sensors to capture position, raw images, lidar and other data, then transfer the data back to the data center and store and process it in the data center. As cars become more connected and equipped with a range of sensors, a new approach to map development that complements traditional methods is possible.

The Qualcomm driving data platform uses the Qualcomm® SnapdragonTM 820Am automotive processor. Leveraging the precision positioning, in-vehicle machine learning, heterogeneous computing and connectivity capabilities of the Qualcomm driving data platform, TomTom and Qualcomm Technologies aim to add improved, scalable and cost-effective crowdsourcing models to high-definition mapping methods. . The new concept supports massively connected cars to “see” and “understand” the environment, traffic and road conditions they are in, and to support real-time information entry for maps and road updates.

"The feature-rich, highly accurate and frequently updated HD maps are critical to supporting the most cutting-edge applications envisioned by the automotive industry, especially for autonomous driving," said Willem Strijbosch, head of automated driving at TomTom. "We are working on Build a cloud platform to map and maintain high-definition maps that leverage a range of sources, including crowdsourced data from a large number of smart connected cars. We are excited to explore and leverage the connectivity and computing capabilities of the Qualcomm driving data platform to help shape the future Driving the world."

Nakul Duggal, vice president of product management at Qualcomm Technologies, Inc., said: "Qualcomm Technologies today demonstrated a low-cost, easy-to-integrate mapping solution for autonomous vehicles. The Qualcomm driving data platform offers several key technologies. Integrated into a cost-effective edge computing solution, which is a must for more secure, highly connected and smarter traffic. We are excited to be a high-definition map provider like TomTom, as well as automotive manufacturing. Business, shared travel service providers and the entire automotive industry provide these technologies."

For more information on the Qualcomm driving data platform, please visit the Qualcomm booth at World Mobile Congress (3E10 booth 3) or visit TIve. The World Mobile Congress will be held in Barcelona from February 27th to March 2nd.

The machine learning algorithm runs on the Snapdragon 820Am processor and is optimized with the Qualcomm® SnapdragonTM Neuroprocessing Engine Toolkit, which is designed to identify features such as traffic signs and lane markings and combine this information with precise positioning to generate functionality. Rich, highly accurate and lightweight map updates. It can automatically update real-time traffic conditions to navigation services using the X12 LTE modem integrated in the Snapdragon 820Am to help turn cars on the road into real-time sensors. Both object recognition and classification processing are performed on the heterogeneous core of the Opteron processor, eliminating the need to send raw video over the network and remove associated costs. The process runs on a local platform supported by Snapdragon 820Am and is further optimized through multiple iterations and then uploaded to the crowdsourcing cloud. The process generates real-time, high-definition maps that are continuously improved and highly accurate, enabling a safer, more advanced driving experience.

For more information on TomTom Maps supporting highly automated driving, please click here to download.

Qualcomm's technology drives the revolution in smartphones, connecting billions of people. We have made pioneering contributions in 3G and 4G, and are now leading the 5G road to a new era of intelligent networking terminals. Our products are transforming the automotive, computing, Internet of Things, health care, data center and other industries, and support millions of terminals connected to each other in unimagined ways. Qualcomm Incorporated includes the Technology Licensing Service (QTL) and most of our patent portfolio. Qualcomm Technologies, Inc. (QTI) is a wholly owned subsidiary of Qualcomm, which operates all of its engineering, research and development activities and all of its products and services with its subsidiaries, including our semiconductor business QCT. For more information, please visit Qualcomm's website, blog and Weibo.

TomTom Automotive is a trusted partner to the global automotive industry, providing innovative navigation technologies for the future. As the world's leading provider of networked navigation software, traffic information and digital real-time maps, we offer modular components to automotive OEMs to create competitive infotainment systems and provide technical support for future autonomous vehicles to look farther than sensors.

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