無人駕駛領域又要放大招了。一家名不見經傳的初創(chuàng)公司正在研究一種新型的無人駕駛技術，據(jù)這家公司稱，該技術能讓汽車利用“常識”，在不可控的環(huán)境中像人類一樣駕駛。

在無人駕駛領域，多數(shù)公司的研究重點是如何改進傳感器、感知和控制技術。而iSee公司的CEO趙一彪表示，他的公司開發(fā)的機器人，將是業(yè)內第一個能夠真正理解路面上發(fā)生了什么的機器人程序。

大約一年前，趙一彪與麻省理工學院的實驗室伙伴克里斯·貝克和科技創(chuàng)業(yè)人黛比·于（音譯）一同創(chuàng)辦了這家公司。該公司也獲得了麻省理工學院的風投機構The Engine的資助。

趙一彪上周在接受《財富》雜志的電話采訪時表示：“我們知道，‘看到’不等于‘理解’。目前，汽車已經實現(xiàn)了‘看到’，但它們并不能真的理解究竟發(fā)生了什么，別人在想什么，以及別人的意圖是什么。”

而iSee公司則為汽車程序提供了一種特殊算法，使汽車可以在開放環(huán)境中與人類協(xié)作。該系統(tǒng)有兩個主要組成部分：深度學習和常識引擎。

系統(tǒng)的深度學習部分與Waymo和Uber的現(xiàn)有技術大同小異。所謂深度學習，是指如果你對某件事練習得足夠多，你就能下意識地做到它。對于人類來說，正是快速的下意識思考，才使你在駕駛時能夠同時完成多個操作。而對于無人駕駛技術，也正是這種深度學習，才使得汽車能始終保持在自己的車道里行駛。

然而當你遇到特殊路況，你就需要推理和有意識的思考了。比如在高速公路上會車、變換車道或通過十字路口時，你都要預測其他車輛的活動，有時甚至要跟其他司機“談判”，有時也得考慮其他可能性，以求安全通過。

趙一彪表示：“作為一個人類司機，我們會有意識地思考那些可能發(fā)生的情形，這是因為我們的頭腦中有一個‘常識引擎’，因此，哪怕遇見一些從未見過的情形，我們也同樣有能力去應對它?！?/p>

而無人駕駛汽車的常識引擎，則同樣可以讓汽車基于常識和過往的經驗來應對新情況。

趙一彪介紹道，這個獨有的常識引擎能幫助汽車“真正理解現(xiàn)在發(fā)生了什么，并且預測接下來兩秒鐘里，他們可能會做什么?！边@樣一來，機器人就能“在需要與環(huán)境中的其他司機進行交流甚至談判時，做出安全的、策略性的決策?！?/p>

趙一彪三人在大約一年前建立了這個算法，并制作了一個模擬器。然后他們想到，為什么不在一臺真正的汽車上做實驗呢？黛比·于大方地借出了自己的一臺混動SUV作為實驗用車。

回憶起2017年冬天他們在車庫里工作的經歷時，趙一彪笑道：“我們只花了兩周時間，就讓那輛車實現(xiàn)了自動駕駛。這是一次非常有趣的經歷。”

第一次實驗成功后，iSee的程序又經過了多次修改完善。這個團隊不僅利用模擬器進行測試，也在美國的多個州通過有人駕駛汽車實測了系統(tǒng)在真實路況中的表現(xiàn)。

這種技術使機器人得以流暢地與人類協(xié)作。雖然該技術在無人駕駛領域之外也有應用潛力，不過趙一彪表示，目前iSee將主要專注于無人駕駛領域。

“我們認為，無人駕駛是一個新興市場，所有人都在朝著這個目標努力。而且現(xiàn)在市場已經準備好了，客戶也已經準備好了，缺的只是實現(xiàn)它的技術，所以我們的當務之急，是讓這個‘殺手級應用’能夠管用。未來我們也可以將它擴展到其他應用上?！?/p>

隨著常識引擎在技術上取得成功，iSee公司也希望它能被廣泛接受——至少不要像行業(yè)領袖Waymo那樣遭到車主的嫌棄。據(jù)稱，自從Waymo在亞利桑那州投入測試以來，已因其過于保守的駕駛風格遭到了很多人類司機的不滿。

對此趙一彪表示：“我認為這正是這個領域的一個公開挑戰(zhàn)。我覺得對于常識理解的核心部分，現(xiàn)在連Waymo和Uber這些公司也沒有搞明白，而我們正是專注于這一塊的，我認為它將是讓無人駕駛系統(tǒng)真正適應真實路況的一項關鍵技術?！?/p>

不過，這個目標什么時候才能實現(xiàn)呢？趙一彪表示：“它已經發(fā)生了，它不是未來，而是現(xiàn)在?！保ㄘ敻恢形木W）

譯者：樸成奎

A little-known name in the world of autonomous driving is paving the way for a new type of self-driving car—one that can use “common sense,” as the company calls it, to navigate an uncontrolled environment.

While most companies developing self-driving cars are focused on improving sensors, perception, and control, iSee CEO Yibiao Zhao says his company is the first to work on creating a robot that can really understand what’s going on.

Zhao founded iSee just about a year ago along with Chris Baker, his lab partner at the Massachusetts Institute of Technology, and Debbie Yu, who has a history with tech startups. The three are supported by MIT’s venture capital firm, The Engine, in Cambridge, Mass.

“We know that seeing is not equivalent to understanding,” Zhao told Fortune in a phone call last week. “Currently cars can see, but they cannot really understand what’s really going on and what other people are thinking, and what are the other people’s intentions.”

With iSee, the cars’ programming has a special algorithm allowing it to collaborate with humans in an open environment. The system has two components: deep learning and the common sense engine.

Deep learning is something other companies like Waymo and Uber have already established; it’s the notion that if you practice something enough, you’ll be able to do it unconsciously. In humans, it’s the fast, subconscious thinking that allows you to multitask while driving. In self-driving cars, it’s the type of learning that lets a car remain within a lane.

When you get to an obstacle, however, you’ll need reasoning, or conscious thinking. When you merge on the highway, change lanes, or come to an intersection, you need to predict the actions of other cars, negotiate with them, and consider different possibilities in order to make a safe decision.

As a human driver, “we’ll consciously think about those types of possible parallel futures,” says Zhao. “That is enabled by our common sense engine in our mind, and that gives us the ability to handle some new scenario that we never encountered before.”

In a self-driving car, the common sense engine allows it to navigate new situations based on a handful of past experiences and general knowledge.

This component, unique to iSee, helps the car to “truly understand what is going on, and to predict what they might do in the next two seconds,” says Zhao. This lets the robot “make safe and strategic decisions when they need to interact or even negotiate with the other drivers in the environment,” he says.

Once Zhao, Baker, and Yu had this algorithm established and passed through a simulator about a year ago, they figured “why not” try it on a real car, says Zhao. Yu generously agreed to let her car, a hybrid SUV, serve as guinea pig.

“We spent just two weeks, and we made the car driving,” says Zhao, laughing as he recalls how cold it was working in the garage in the winter of 2017. “It was a very fun experience.”

Since the success of that first experiment, iSee has gone through multiple variations of programming. The team tests their system with both a simulation engine and manned cars driving in multiple states.

This kind of technology, allowing robots to work fluidly with humans, has potential outside the industry of autonomous cars, but Zhao says iSee is focused on self-driving cars for now.

“We believe the self-driving car is the emerging market. Everyone is working so hard towards it, and the market is ready, the customer is ready,” he says. “What is lacking is this enabling technology, so we want to make this killer application work first. In the future, we can extend it to other applications.”

With the success of the common sense engine, iSee hopes to become widely accepted—without the controversies that have surrounded industry leaders like Waymo, which is reportedly hated by its human neighbors in Arizona due to the cars’ overly-conservative driving.

“I think that’s the open challenge in the field,” says Zhao. “There’s one single piece—that is this core part of the common sense understanding—and I think even Waymo and Uber, those companies, haven’t figured it out yet. We are laser focusing on that and I think that can be the enabling technology to make it really work well in a real-world scenario.”

How soon will that be? “It’s already happening,” says Zhao. “It’s not the future. It’s now.”