Delphi launches driverless pilot program in Singapore, aims for Level 4 operation by 2019

RSS_Auto_Poster

Well-known member
Delphi launches driverless pilot program in Singapore, aims for Level 4 operation by 2019

Written by Lindsay Brooke
4475.jpg

Delphi Automotive on August 1 announced an extensive autonomous-vehicle pilot program in Singapore, aimed at demonstrating cloud-based fully automated mobility on demand (AMoD) capability "at the [SAE] Level 4 performance level" by late 2019, said Glen DeVos, Vice President of Delphi"s Business Services Unit based in Mountain View, CA. Operational capability is expected by 2022. Delphi is partnering with the Singapore government"s Land Transport Authority (LTA) on the multi-phase project. The initial phase, to be conducted through 2019, will involve a fleet of six modified production vehicles operating at low speed on fixed routes in the island nation"s "one north" area, a business park that is currently serving as a test bed for autonomous-vehicle development, DeVos explained in a recent media briefing. Engineers acting as "safety drivers" will accompany select commuters during the first pilot phase. The program"s second phase "will use a true purpose-built, autonomous mobility-on-demand vehicle," DeVos said essentially driverless taxi-pods that can be summoned by customers. When completed the program "will show we have the complete ecosystem" and durability, including data analytics and reaction by the end consumer," he said. Delphi will announce an additional pilot in North America later this year and will also replicate the program in Europe. The second-phase bespoke vehicle will require automated door operation to easily accomodate passengers with physical disabilities, DeVos explained. Delphi President and CEO Kevin Clark said in a statement that the AMoD project will demonstrate his company"s prowess in automated software, multi-modal sensor technology and systems integration while showcasing Singapore"s leadership in connected-vehicle and autonomous infrastructure. Since 2014 the Singapore Autonomous Vehicle Initiative (SAVI) has increased autonomous-vehicle research and test-bedding with various industry partners. CTO Jeff Owens noted that the Singapore program will leverage technologies used in the first-ever coast-to-coast U.S. autonomous drive conducted by Delphi in 2015. That project used an Audi SQ5 platform and was a significant step in creating what Owens called "an end-to-end solution" for new mobility markets. The trans-U.S. drive "caught Singapore"s attention," noted DeVos. The Singapore LTA is studying ways to assist commuters in their daily round trip from home to mass-transit station to workplace. Offering on-demand automated vehicles on a 24/7 basis for what planners call "the first mile" and "last mile" of the typical commute would, they believe, increase use of mass transit systems and reduce overall traffic congestion and vehicle emissions in the process. "It"s not easy to get to mass transit in Singapore so people take taxies, increasing congestion in the process," DeVos asserted. He added that Delphi intends the service to include good and services in addition to people. Delphi is conducting its own mapping for the three highly controlled routes included in the Singapore project. The company is still finalizing its "five or six" supplier-partners, including that for the cloud platform. The team could include Mobileye, said DeVos. The effort "could possibly lead to a production-intent mapping service," he said. Mapping the 7 to 8 km (4.3 to 4.9 mi) of each of the three routes to a 30-cm (12-in) level of accuracy consumed 4 to 6 weeks of time, including data compilation. Delphi had not yet revealed OEM and models of the initial test-fleet vehicles at the time this article was published. "With AMoD, the cost of the trip goes down significantly," DeVos said. "We expect this project will prove our [autonomous] technology is robust and that consumers will use it."



Date written: 31-Jul-2016 09:05 EDT

More of this article on the SAE International Website

ID: 4475
 
Back
Top