如今，芯片供應商也在抓緊行動，便利自動駕駛汽車的到來。最近，恩智浦半導體公司（NXP Semiconductors）推出了一款BlueBox安全控制器，可承擔傳感器融合、數據分析及完成復雜聯網等任務。
據悉，恩智浦半導體去年成功收購飛思卡爾（Freescale），從而成為世界上最大的汽車半導體供應商，而后者在為恩智浦的系統供應所需的硅材料。恩智浦推出的新模塊表明，芯片生產商已經逐步開始在系統方面進行布局。去年，瑞薩公司（Renesas）也與多家合作伙伴組隊，并利用后者的傳感器等組件強化公司的自動駕駛平臺。
具體來說，安全系統能夠做出制動和轉向的決定，從而為自動駕駛的到來鋪平道路，而中央控制器則可收集來自多個傳感器的輸入，并將這些信息整合起來進行綜合分析。這些控制器通?？梢苑直孳囕v、行人和其他物體，然后判斷這些對象是否會影響車輛的行駛，以及可能帶來怎樣的影響。
恩智浦的BlueBox配備了2個處理器，可以整合不同渠道的數據輸入，并做出綜合判斷。其中，網絡設備可以承擔通信任務，而安全控制器則會整合來自攝像頭、雷達、激光雷達及車-車通信系統的數據輸入。系統的集中控制器配備了一塊RAM內存，功率需求相當低。
“BlueBox的處理速度高達90，000 DMIPS（每秒百萬條指令），而功耗卻不到40W，絕不會超出車輛的功率分配，”恩智浦汽車營銷經理Mark O’Donnell表示，“如今，汽車中的各種系統都要用電，這是一個大問題。”
BlueBox安全控制器配備了四核微處理器和硬件加速器。網絡芯片則比較大，共有八核。事實上，無論是計算能力的提升，還是向以太網的轉型均凸顯了一個現實：未來的中央計算機需要應對來自多個傳感器的輸入，處理海量數據。
“我們必須改變現有的網絡架構，從CAN和LIN轉向以太網，”恩智浦汽車業務CTO Lars Reger表示，“在一些高端車型中，車內電纜的重量比我還重，而以太網可以削減這部分重量。此外，我們還需要采用分域架構，這樣一旦信息娛樂系統遭到攻擊，威脅也不會蔓延至其他系統，而以太網就能夠幫我們實現這種架構，還允許我們增加更多的安全系統和網關。”
BLUEBOX是一個基于Linux的開放平臺。該系統經過專門設計，廠商和一級供應商的定制非常容易。Reger指出，廠商希望親自編寫自己的軟件，而不是依賴于神經網絡和“深度學習”等允許車輛隨著時間自己開發出一些規則的功能。
“車輛就算擁有與人類相仿的認知能力也并沒什么用，它不需要知道監測到的車輛是新車還是舊車，監測到的行人是男人還是女人。”Reger表示，“車輛需要的是一個高度可靠的判斷系統，能夠監測物體并進行分類。”
Reger還強調，法律環境將在自動系統和主動安全系統的逐漸推進中發揮關鍵作用。
Reger表示，“如果汽車生產商必須在法庭上解釋為什么車輛要左轉而不是右轉，他們肯定不能說這是車輛的神經網絡做出的決定。”
作者：Terry Costlow
來源：SAE汽車工程雜志
翻譯：SAE 中國辦公室
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New NXP system drives sensor fusion for autonomous vehicles
Silicon suppliers are stepping up to help facilitate progress in the road to autonomous driving. NXP Semiconductors has unveiled its BlueBox, which handles sensor fusion, analysis and complex networking.
NXP, which became the largest automotive semiconductor supplier last year by acquiring Freescale, provides all the silicon in the system. The module underscores chipmakers’ growing focus on systems. Last year, Renesas teamed up with a number of partners whose sensors and other components augment its autonomous driving platform.
As safety systems that make decisions on braking and steering pave the way for more autonomous driving, central controllers collect input from multiple sensors and stitch it together so it can be analyzed. These controllers will typically classify vehicles, pedestrians and other objects, then determine whether and how these objects impact the vehicle’s movement.
NXP’s BlueBox utilizes two main processors to fuse inputs and make decisions. A networking device handles communications while a safety controller combines inputs from cameras, radar, lidar and vehicle-to-vehicle communications. The centralized controller, which includes significant RAM, has fairly low power requirements.
“The box runs at 90,000 DMIPS (million instructions per second) and draws less than 40W, which fits the power budget of vehicles,” said Mark O’Donnell, the company's Automotive Marketing Manager. “Everything on the vehicle these days is power hungry, so that’s a big concern.”
The safety controller has four microprocessor cores and hardware accelerators. The networking chip is larger, with eight cores. That level of computing power and a shift to Ethernet highlight the huge volumes of data that will flow into a centralized computer that combines several sensor inputs.
“We’ve got to change the networking architecture, going from CAN and LIN to Ethernet,” said Lars Reger, NXP's Automotive CTO. “On high-end cars, the cabling weighs more than I do, Ethernet can help reduce that weight. We need domain architectures so if the infotainment branch is attacked, it doesn’t go any further. Ethernet enables this architecture and includes the ability to add security and gateways.”
The BlueBox is an open platform with Linux software. It’s designed for easy customization by OEMs and Tier 1s. Reger noted that OEMs will want to write their own software rather than relying on neural networks and 'deep learning,' which let the car develop some of its own rules over time.
“It does not help if the car has the same level of recognition that a person has; it’s not important to know whether a car is old or new or whether a pedestrian is male or female,” Reger said. “Vehicles just need a highly reliable and deterministic system that does object detection and object classification.”
He also addressed the legal climate that will play a critical role in the eventual rollout of autonomous and active safety systems.
“If a carmaker in court needs to defend why a car turned left instead of right, they don’t want to explain that a neural network made the decision,” Reger said.
Author: Terry Costlow
Source: SAE Automotive Engineering Magazine
恩智浦的BlueBox系統可以收集來自多個傳感器的數據，并綜合這些輸入從而做出安全決定。