很多企業的最高管理者都非常熱衷于宣傳自己的公司已經擁有了各種技術，并且從理論上講，這些技術可以讓他們的公司在不久的將來推出自動駕駛汽車。但是，坦白說，這其中至少有一個領域需要的不僅僅是深層次的技術知識，這里面還需要“表面”上的技術支持。
只有對路面狀況具有全面了解和足夠重視，自動駕駛汽車的智能系統才能識別道路上可能對汽車行駛造成影響的各種因素，小到某條小路上的坑洼起伏，大至高速公路上的裂縫，從而確保整個行駛過程不受到任何影響，從而避免可能出現的災難性后果。
rFpro模擬器軟件公司技術主管Chris Hoyle表示，要實現這個目標，需要開展全面綜合的測試項目，其中需要動用由OEM提供的覆蓋所有市場路面的先進掃描技術。為法拉利F1賽車操作提供專業技術（詳見http://articles.sae.org/13603/）的rFpro公司，正致力于針對這一難題研究解決方案。而它的獨門秘籍就是將精確度與全新的省時系統結合起來。
“自動駕駛測試項目的全部需求才剛開始為人所知，” Hoyle表示。“但實現這些需求的專業技術現在就能研發，而且這些技術帶來的信息對提高當今汽車的安全性能同樣重要。”
Hoyle解釋道，越來越多的新車都是為了滿足國際市場的需求而設計的，因此最好從一開始便選擇最佳的設計，但這一目標對目前的汽車制造商而言非常困難。若在研發后期才根據不同市場的偏好和特點對車輛進行修改，那么付出的代價一定是高昂的。因此所有制造商都盡早開始測試，以避免這些問題。
在使用全球性研發平臺的過程中，各個地區的路面特征各不相同，這是個讓人頭疼的問題，這是因為只有在原型車生產出來之后，才能進行有效的測試。Hoyle 表示，“駕駛員在環（DIL，Driver In the Loop）模擬器可以讓一名人類駕駛員早在實體的原型車制作出來之前，便在虛擬環境中體驗汽車的行駛狀況；然而該系統的有效性需要獲得路面細節信息的支持，而這些信息直到今天為止都沒有人可以提供。”
但Hoyle表示，rFpro公司已經開發出了一套解決方案：“rFpro現在能使用全新的路面掃描技術來建立數字路面模型，而且建模的精確度和速度都達到了前所未有的水平。我們可以捕捉信息，并再現各種路面間的區別，比如一段因霜凍而受損的底特律高速公路、平坦的德國干線道路、瑞士阿爾卑斯的山路或其他各種路面。”
這一技術進步使得汽車制造商無論身處世界何處，都能在逼真的虛擬環境中評估汽車底盤對任何道路類型的反應。 “而且他們不必離開辦公室就能做到這一點” Hoyle說。
rFpro在數字路面建模技術上取得的突破開始于一個創舉。它擯棄了傳統的單脈沖激光LIDAR“渡越時間”掃描技術，代之以逐步發出一連串分離激光信號的全新掃描技術。傳統技術要求每個信號返回之后才能發出下一個信號，而全新的受控逐步發射技術允許信號重疊，這提高了數據捕捉的速度、數量和質量。
“新技術可提供相當于傳統技術50倍精度的信息細節，準確度也顯著提高；它的掃描速度也更快，因此掃描儀可以隨著正常車速運作，而非傳統的緩慢爬行，” Hoyle表示。“這意味著不僅可以掃描更長的路段，而且在白天也可以工作，且不會干擾到其他道路使用者。”
為了覆蓋全球的道路類型，rFpro與各個地區的掃描技術公司開展了合作。這些公司都將最新的逐步掃描技術加入到他們在rFpro的道路勘測項目中所使用的系統。
這項新技術有效縮短了研發時間，從而大大降低了研發成本。
新技術的精確程度可以在這些數字中體現：“采樣”每隔5毫米（0.2英寸）可進行一次路面“采樣”，精度可達1毫米（0.04英寸）以內。
Hoyle表示，越來越多的汽車制造商希望rFpro捕捉數據，并再現他們最喜歡的測試道路條件：“2012年我們為100公里以上的路面建立了數字模型，2014年為1000公里以上，而今年我們打算建造3000公里左右的模型。”
Hoyle還說，信息量的增加讓rFpro轉向云端處理和存儲技術。云技術不僅擁有無限的成長空間，而且成百上千的CPU內核可以同時進行數據處理，這進一步縮短了時間。“過去制造商使用的模擬器都改編自航空航天業的模擬器，但是為了充分發揮數字建模價值，必須專門為汽車行業開發最先進的模擬器。”
從今年起，rFpro與幾家大型OEM展開合作，共同開發自動駕駛汽車的高級駕駛輔助系統。盡管Hoyle不愿推測在2020年前是否有可能實現自動駕駛的商業化生產，但一些公司已將這一年設為其開發目標達成的時間。
汽車行業的最新進展（例如共享平臺和自動駕駛汽車）使得虛擬測試變得越來越重要。
Hoyle表示，rFpro的TerrainServer軟件目前已獲得北美、亞洲和歐洲眾多OEM客戶的青睞，而大多數F1賽車和NASCAR團隊也已加入其中。只有將數字路徑（道路）表面模型與諸如輪胎接觸面的其他方面相結合，加上信息實時處理技術的開發，才能實現精準的汽車動態模擬。這種能力的實時提供，對DIL測試至關重要。
Road-surface modeling aims to support autonomous driving
Some chief executives are enthusiastically fond of stating that their companies already possess much of the technology that would, in theory, allow them to introduce autonomous vehicles in the very near future. However, there is at least one area that is likely to require not just in-depth knowledge but, quite literally, superficial knowledge.
It is to acquire a total understanding and appreciation of road surfaces that would allow an autonomously operated vehicle’s intelligent systems to recognize and appreciate the potential effects on a vehicle of anything from mild camber changes and potholes on a minor road, to cracks on a freeway, and to ensure that none would cause a possibly catastrophic effect that could endanger a whole high-speed convoy.
To achieve this will involve very comprehensive test programs incorporating the use of advanced surface scanning technology of roads in all markets served by an OEM, said Chris Hoyle, Technical Director of simulator software specialist rFpro. The company, which has technology links with Ferrari's F1 operation (seehttp://articles.sae.org/13603/), is majoring on the creation of solutions to the challenge. And it is doing so by combining accuracy with new time saving systems.
“The needs of autonomous driving test programs are only now starting to be fully understood,” said Hoyle. “But meeting those needs can be achieved via expertise that can be gained now, providing equally significant information to make current vehicles safer.”
Hoyle explains that as increasing numbers of new vehicles are designed to suit global markets, making the optimum design choices at the outset has become essential but is now far more challenging for vehicle manufacturers. Revisions to a vehicle to suit individual market tastes and conditions late in a development program are so costly that manufacturers aim to avoid such issues by testing as early as possible.
Pronounced regional differences in road-surface characteristics are a known headache for use of global platforms because effective testing is currently only possible after representative prototype vehicles are available, stated Hoyle. “Driver-in-the-loop (DIL) simulators provide a solution by allowing a human driver to experience the vehicle’s behavior in a virtual environment long before physical prototypes exist; however, to be effective they need a level of road-surface detail that has been unavailable until now.”
However, Hoyle says his company has developed a solution: “New surface scanning technology is being utilized by rFpro to produce digital road models with unprecedented accuracy and speed. We can capture and reproduce the differences between a frost-damaged Detroit highway, a smooth German autobahn, a Swiss alpine pass, or any other surface.”
This advance means vehicle manufacturers located anywhere in the world can evaluate their vehicle’s chassis response to any road type in a realistic virtual environment, he claims: “And they can do so without leaving the office.”
The breakthrough in digital road modeling developed by rFpro starts with replacing the usual single pulse laser LIDAR “time-of-flight” scanning process with new scanning technology that uses a number of separate, phased laser signals. Instead of waiting for each signal to return before firing the next one, the controlled phasing allows the signals to be overlapped, increasing the speed, quantity, and quality of data captured.
“The new process provides up to 50 times the level of detail with greater accuracy than ever before; it’s also faster, which allows the scanners to drive at normal road speeds rather than at a crawl,” said Hoyle. “This makes it realistic to scan much longer sections of a chosen route, even during the day, without impeding other road users.”
To provide global coverage, the company works with a core group of regionally located scanning partners, all of whom have now added the latest phase-based scanning capability to the systems they use for rFpro’s road surveys.
Because it reduces development time, the new technology has the potential to make a significant reduction in costs.
Accuracy is such that a road surface can be “sampled” every 5 mm (0.2 in) with a precision down to less than 1 mm (0.04 in).
Growing numbers of vehicle manufacturers are asking for their favorite test routes to be captured and reproduced, according to Hoyle: “For example, in 2012 we built just over 100 km of digital road models; in 2014, it was more than 1000 km, and this year we expect to build approximately 3000 km.”
He added that the increasing volumes of data have led rFpro to switch to cloud-based processing and storage, providing almost limitless scope for further growth and enabling hundreds of CPU cores to work simultaneously on data processing, further reducing timescales: “Traditionally, manufacturers have used simulators adapted from the aerospace industry, but to get the most from these digital road models it is essential to use state-of-the-art, purpose built automotive simulators.”
This year, rFpro has begun working with several major OEMs on advanced driver assistance systems for autonomous vehicles, although Hoyle will not comment on the likelihood of the commercialization of autonomous vehicles by 2020, a timescale for which that some companies are aiming.
Current developments in the automotive industry, such as the growing use of shared platforms and autonomous vehicles, are increasing the importance of virtual testing.
The company’s TerrainServer software is currently being used by OEMs in North America, Asia, and Europe as well as by most of the F1 and NASCAR teams, stated Hoyle. It takes the digital track (or road) surface model together with other inputs including tire contact patches, and processes the information in real time, to achieve accurate vehicle dynamic simulations. Hoyle explained that the real-time aspect of this capability is essential for DIL testing.
rFpro's的新技術可以按每隔5毫米的距離對路面進行掃描，精度可達1毫米以內。
圖上顯示的是路面掃描的常規狀態。
rFpro 技術主管Chris Hoyle聲稱，較之從前，這項新技術可提供多達50倍的路面信息，精確度也更高。