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Delphi, Mobileye to Unveil Automated Driving System

The two companies announce plans to showcase their turnkey, fully integrated automated driving solution next month during CES 2017.

by Staff
December 7, 2016
Delphi, Mobileye to Unveil Automated Driving System

Photo courtesy of Delphi.

2 min to read


Photo courtesy of Delphi.

Delphi Automotive and Mobileye plan to demonstrate their automated driving system during the Consumer Electronics Show (CES), scheduled for Jan. 5-8 in Las Vegas.

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The two companies this past summer formed a partnership to jointly develop a complete SAE Level 4/5 automated driving solution. Delphi is a leader in automated driving software, sensors, and systems integration. Mobileye is a leader in computer vision systems, mapping, localization, and machine learning focused on the automotive domain.

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The 6.3-mile demonstration drive, held as part of CES 2017, will showcase Delphi and Mobileye’s Centralized Sensing Localization and Planning (CSLP) automated driving system. CSLP will be ready for production by 2019, the companies said. 

“Three factors will separate the leader from the pack in the race to offer driverless vehicles by 2019 — best-in-class perception sensors such as cameras, radar and LiDAR, automotive experience and computer processing speed,” said Glen De Vos, vice president of services for Delphi. “We will demonstrate the capability of the CSLP solution in our intensive drive at CES 2017 in Las Vegas.”

The Las Vegas drive will tackle everyday driving challenges such as highway merges, congested city streets with pedestrians and cyclists, and a tunnel.

The 2019 CLSP system will feature several advanced technologies, including:

  • Localization capability to ensure the vehicle knows its location within 10 cm, even without GPS connectivity

  • Free space detection to help the car navigate complex lane splits or areas lacking lane markings

  • 360-degree pedestrian sensing

  • 3D vehicle detection to identify vehicles at any angle. This technology can detect partial cars by identifying vehicles based on overall shape, and can detect by wheel movement if a car is stationary or parked. Such capability is critical for urban environments with unusually angled intersections. The technology also enables lateral turning vehicle detection critical for intersections.

  • Path and motion planning to allow the car to behave more human-like in its driving behavior and determine the best path forward.  

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