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94 level positioning. It is rated to operate with lateral error margins of less than 8 in (0.2 m) and a longitudinal error within 6.5 ft (2 m) with a 95% confidence interval, providing accurate reference for highway pilot and automated valet parking. Even when both GNSS and lane line detection are unavailable, the HD-MapBox can still enable vehicles to keep in lane for at least 400 m. RoboSense Lidar showcased its smart Lidar sensors, including its flagship RS-Lidar-M1, which is styled as the world’s first mass-produced automotive- grade MEMS solid-state Lidar. It also displayed Ruby Plus, a new 128-beam mechanical Lidar for the first time internationally. As of August 2021, the M1’s first mass production and delivery in a designated project with a vehicle manufacturer had been completed. The company also reported orders from automotive OEMs and related companies including BYD, GAC, WM Motor, Geely subsidiary Zeekr, Lotus Cars and Inceptio Technology. The Ruby Plus meanwhile has a diameter and height of 125 mm (down from its predecessor’s 166 x 148 mm) and power consumption has been reduced by 40% (from 45 to 27 W). RoboSense also showcased RS- Helios-5515, a new 32-beam Lidar custom made for Alibaba’s logistics robot Xiaomanlv, for the first time outside China. It features capabilities such as a customised FoV, long-range perception and near-field blind-spot elimination that traditional mechanical Lidars have yet to achieve. Its design has been configured to arrange lasers densely in the centre of its FoV, which is key to its perception and blind-spot reduction. Green Hills Software (GHS) announced the availability of its ROS 2- compatible development framework for safety- and security-critical transportation solutions, developed in collaboration with Apex.AI. It is a software platform that combines the safety and security of GHS’ Integrity RTOS with the latter’s Apex.OS, a fork of ROS 2 made real- time, deterministic and certified for safety- critical applications. The combined solution aims to give OEMs and Tier 1 suppliers a fast, low-cost path to production for their ROS- and ROS 2-based vehicle prototypes being developed for ADAS and autonomous driving, particularly regarding requirements for the highest levels of automotive safety, up to ISO 26262 ASIL-D. It is also intended to fill a gap that developers of safety-critical transportation systems face when trying to successfully migrate prototypes developed with ROS or ROS 2 to a production-focused real-time and safety-certified computing platform, and hence into series manufacturing that complies with the ISO 26262 automotive safety standard and ISO 21434 automotive cybersecurity standard. “The combination of Integrity RTOS with its ROS-aware development tools and C/C++ compilers provide the necessary foundation to the production- focused Apex.AI ROS 2 safety framework and middleware for today’s automated drive systems,” said Dan Mender at Green Hills Software. “Our collaboration with Apex.AI provides OEMs and their partners with a highly optimised ROS 2-based foundational software development platform that allows OEMs to focus on unique software-defined vehicle application differentiations.” Lilee Systems exhibited its new autonomous vehicle and fleet management software, as well as an ADA-compliant shuttle, its self-driving system, and a cloud-based platform enabled by Lilee SafeRide for remote monitoring and management. “We started developing self-driving systems in 2017, and we have received a commercial licence in Taiwan to operate our Autonomous Rapid Transit [ART] system on two regular bus lines near rail stations and schools to enhance the existing public transportation services,” said Jia-Ru Li. Lilee’s ART fleet management system uses AI edge computing for managing Lidar and vision processing, which connects via fibre to a centralised transport traffic control system. That in turn maintains connections with a vehicle’s onboard computers and connectivity systems via 5G, LTE or software-defined radio, as well as to an operations control centre via existing wi-fi or Ethernet where video feeds of intersections, live data from vehicle telematics or bus routes are monitored. April/May 2022 | Unmanned Systems Technology RoboSense showcased many solutions at its booth, including its RS-Lidar-M1 automotive-grade Lidar