Hacking the Underground Autonomous Street Racing Sceneby@garrettkinsman
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2,291 reads

Hacking the Underground Autonomous Street Racing Scene

by Garrett KinsmanJuly 28th, 2017
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<span>We</span> travel to Cambridge Massachusetts, where an underground scene of renegades are tearing up the backroads. Multi-million dollar Bitcoin wagers and terabyte data dumps are fueling a new scene of street racing.

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Students are hacking cars, pushing their vehicles and algorithms to the limits.

Nvidia’s Drive PX 2 supercomputer is used to fuel a new kind of street race

We travel to Cambridge Massachusetts, where an underground scene of renegades are tearing up the backroads. Multi-million dollar Bitcoin wagers and terabyte data dumps are fueling a new scene of street racing.

With the advent of advanced driver assist (ADAS) in modern cars, (for example lane keeping and self-parking), autonomous driving has opened to the masses. Standard ADAS, paired with open source software like, Udacity, and Baidu’s Apollo is giving hackers complete control over their vehicles.

A new breed of street racer is taking over, consisting of computer science majors despondent in the age of Snapchat dog filters, heartless Tinder dates, and dormroom binge drinking. Like the slicked back hot rod culture of the 1950s, a unique subculture is getting their adrenaline fix behind the wheel.

I met with “Sean” at 11am on sunday. Sean’s name has been changed for obvious reasons. He’s a student, finishing a degree in CS, and from what I’ve been told, the mastermind behind this entire operation.

What he was about to show me was a highly illegal operation. He told me later that the risk was worth it, “This is something no one has ever done before. Like Silk Road or Cryptocurrency, this is a technology that changes everything.” A completely new sport is emerging from this unnamed group’s lines of code.

Sean flicked a cigarette outside a nondescript, run down industrial building in Cambridge, Massachusetts. He keyed us in, and led me through a door beside a steel garage door.

Daft Punk thumped through a dimly lit hallway, ending in an open space. It looked like an old mechanics shop, 1970s bulletin boards now sported photos of cars and clippings from Wired Magazine.

Three cars in various orders of assembly lay gleaming before me. Half a dozen students worked feverishly. Marijuana wafted from the vape-pen of someone coding next to a car.

It took five weeks to get the introduction to even get in here, and the engineering students barely noticed I was there.

Sean kissed his girlfriend and showed me his Acura. Cans of Rockstar energy and cigarrette buts littered the floor. A server rack covered the back wall. Ethernet cables of all color littered the ceiling, snaking out from the server rack.

He walked me to his heavily modified car. The hood was open, but other than that, one couldn’t see anything special about the car. It was the ultimate sleeper. The guy smoking hash on his laptop was dubbed “Einstein”. He wrote several of the machine learning algorithms that took open source software and supercharged it. His black Macbook had a cable running into a custom designed T-Box, plugged directly into the CAN interface of the car.

Any one of these engineers could have 6 figure salaries at Google, Uber, or any one of the dozens of companies pouring billions into the self driving car race. Instead they were doing doing this, pushing AV technology far beyond anyone else.

“Something happens when you completely deregulate something,” Sean explained, “It moves it maximum speed.” In his case, the team was working around regulation. By now a few of the engineers had looked up at the stranger in their oasis of code and cars and hashish. I asked how Sean funded the venture and he remained silent. I changed tone, asking how this all began.

“It started with the release of an AV source code being put on github,” He explained, looking down into the rebuilt engine of the Acura, “The damn code ran on a OnePlus 3 smartphone. It was too easy I had to give it a try.”

Sean is referring to’s release of OpenPilot. The controversial and classically brash San Francisco startup is using the 820 GPU in a smartphone to capture data, and control a car. The DIY kit plugs into the vehicle’s CAN interface, which controls acceleration and steering.

“So we screwed around with that, pushing it to it’s limits,” Sean explained, “Until some douche in a Mustang shot by me going 150,” he kicked an empty can of Rockstar on the floor, “That’s when this crazy idea hit me. What if we can drive better than any human ever could?” Sean had a way of pulling you into his words that couldn’t quite be conveyed. Over the past 8 months he got together a crack team of CS majors, gearheads, druggies, bassheads, and true innovators. All of them happened to be pretty good at Deep Learning.

After 6 months of reverse engineering other people’s code, and finally building their own, they were ready for their first race.

Sean sat behind the wheel of his “coded out”, white Acura. He pointed to two cameras in the corners of the window, along with the existing ADAS camera. “You’ve got to believe in the code,” He said almost religiously, setting his hands on the steering wheel, “She’s a machine that is truly self aware, and has to be treated with respect.”

In the trunk of the car, two Nvidia PX supercomputers, with respective cooling systems were nestled into the back. The steering controller had to be swapped out for one with higher torque, and the VCU completely remapped.

I asked Sean again, sitting in the passenger seat now, how he funded everything. He looked over at the server rack, then back to me, “Let’s just say… I made a lot of money with Bitcoin. The savings from that are enough to put a wager on a race larger than anyone before.” He looked me in the eye, “Enough on that.”

We are living in an age of nondescript Bitcoin millionaires. Kids who mined or coded something stupid-clever in their teens, and end up completely set by the time they’re in university.

He climbed out of the car, “So now that you know we’re not full of it, I’ll send you an email when we race.”

I asked when.

Sean laughed and glanced back at the server rack, “When the rest of the wagers have been made.” Ushering me out, I took one last look at the “coded out” cars in the shop. They looked almost boring from the outside.

I asked one final question, why he let me see all of this.

Sean was about to open the door to the street when he paused for a moment, “Because,” thinking, “We’re making history. These vehicles are gaining consciousness and I want the world to see it.” I couldn’t even tell that the cars behind me were unique.

It would not be for a few weeks that an email arrived from a random address in my inbox. It simply said a time and a place, which turned out to be a library, along with “Don’t be late :)”

I boarded the next flight from from SFO to Logan, leaving my South Boston AirBnb at just past 3am. It was July in Boston, and the summer nights were warm and pleasant. It reminded me of screwing around in high school, hopping barbed wire fences and drinking stolen alcohol.

We met at the public library on the outskirts of Boston. Sean was waiting for me in his Acura. A few tiny cameras had been added in the back windows, along with a police cruiser style laptop holder, “Man your Lyft driver is slow. Hop in.”

On his Macbook, Google Earth was open, showing a traced route of my cab ride extending about a mile from where we sat.

“Don’t be offended, I grabbed you IMEI when we met weeks ago. The Brits call em IMSI Catchers, the feds, Stingrays. We use em to track cops.” Sean explained that every cop car has either a radio repeater, or a cop with a cell phone. The software defined radio (SDR) required to track IMEIs could easily be bought from China for a few hundred bucks. Each of the racecars had an SDR, and their signals triangulated to pinpoint police.

I did not ask, but a fast enough SDR could be used to jam most police signals, including their cell phones. Sean turned down the brightness of the screen and checked his watch, a glowing Rolex GMT. The Acura started without him touching a control, the headlights turned on, the engine revved. We were on our way.

A map appeared on the Macbook showing two other cars, along with a view around the car. It was eerie and surreal watching the car’s sensors compile a 3D view of the night around us.

“We’re heading to Vermont,” Sean said quietly, he pressed a button on a Motorola radio hidden near the ignition. “Einstein, you pushed the latest build? I want to give it a go before 4G drops out.” Sean grabbed the wheel while he car updated to the latest firmware, and he laid back in his seat again.

We didn’t speak much, just a few radio checks. Like he said, 4G became spotty, and eventually we were on our own. Once we were into Vermont, we joined the other two cars. They flashed their high beams behind us in excitement.

Sean flicked off the car headlights, the other cars followed suit. Our world was submerged in darkness, driving at over 80mph, we hadn’t even reached first light.

Sean began laughing into the radio, “Einstein, the Five-Eight link is working great”. On screen, the perceptual awareness of our vehicle had expanded threefold. He looked at me by the light of his macbook, keeping his eyes off the invisible road ahead, “Who needs headlights when you have RAW camera data?”

The Macbook displayed an enormous, god’s eye view of the road ahead and behind. Each car was sharing data over a 150Mbps V2V Wi-Fi link, pulling enough data to drive in the dark. The cars didn’t even flinch.

By first light we were deep into the forests of Vermont. For some reason, my Verizon phone wasn’t getting any signal. Lush forests and hills surrounded the highway, the sun peeked over the horizon.

Everyone pulled over and stopped, jumping onto their cars and sipping coffee from a thermos. Sean had his gold Pixel phone out. Four guys and three girls stood around the cars, hugging campus hoodies and their lovers.

“Ladies and Gentleman,” he looked at each of the forward vehicle cameras. He paused, looking surprised while reading his phone, “The wagers have been set!” He looked each one of his team members in the eye, “Four thousand two hundred Bitcoin,” One of the engineers spit out his coffee, “will be the prize for this race. We have people all over Earth wagering over one hundred and fifty thousand Bitcoin on this!” He paused, “This is unprecedented.”

For reference, in July 2017, the value of 150,000 BTC is well over $1 Billion USD. A bit less if properly laundered.

Everyone was quiet for a moment. “The funds,” Sean continued, “Have been collected, mixed, and are awaiting distribution.” He turned off the screen, holding his phone up, then checked his watch, “To those of you watching this live via satellite, the time is 10:17 UTC,” He was staring into the camera of his car now, “And this just might be the greatest wager in the history of auto racing.”

Sean was dangerously alive with energy. He said quietly, calmly, and quickly, “Let the race begin!” Einstein lit up a joint and passed it to a girl with dreadlocks. Sean kissed his girlfriend, who rode in another car. Everyone was silent for a moment.

The next few moments are difficult to remember. I recall climbing into Sean’s coded out Acura and thinking, this is complete madness. I tightened my race harness.

Everyone lined up along the highway. Sean’s car stood last, and he calmly did a radio check, a police scan, and checked the satellite internet connection.

“Syncing clocks…. Mark!” He hit enter. A countdown timer appeared in the command prompt of our vehicle.

There are moments in your life where reality distorts and you are thrust by incredible acceleration into a completely new world. A tremendous noise erupted from all around. The road was cast into light as three tricked out, coded up supercars passed from 0–60mph in less than 4 seconds. I looked back to the blur of tire smoke, as my body pressed into the racing seat.

The laptop’s screen before me was cut in half, showing a 3D map around the car, and a hypnotic swirl of code. Billions of possibilities were analyzed and thrown away. The outcomes deemed acceptable were converted via fiber optic into explosions of gasoline, pressing the seat into my back.

Before I could blink, the cars were up to 100Mph. I rocked side to side in my 5 point harness seat. Sean was ecstatic, with his hands behind his head. We neared 150Mph, drifting into the hilly turns. If the code failed now, it would be too late to do anything. Why worry one’s self?

The other cars would drive quite literally a few inches ahead. Every moment seemed we would crash to our death, but the computers found that risk perfectly acceptable.

Perhaps the engine noise was the most hypnotic. Each gear shift was artistic, the way the vehicle committed to its turns was enigmatic. I wanted more.

The onscreen map showed several possible trajectories, one turned green. We shot past the car ahead, around a blind turn. A minivan driving head on blared it headlights! Our car swerved, losing traction, and corrected without a hitch.

I was beginning to feel nauseous. Sean swore out loud, this is what he lived for. This is also what he would die for, at least at this rate.

Making great attempts to hold my stomach, we dove into deadly hairpin turns at over 100mph. I found the computers knew how to drift. The engine began to redline as we accelerated into a straightaway.

Something strange happened. Sean’s car centered itself across the dashed center line. The car ahead moved to the right. Behind us, the last car moved into the space beside. Instead of blocking the way, Sean’s car was letting the others pass.

The cars weren’t programmed to compete with one another, but work together, pushing their specs to the max. They were making way for each other to see which car could be pushed the hardest.

Wild vibration shook our car. The cars besides us struggled to maintain straight, as the wheels vibrated side to side. The speedometer read 160, the satellite link read closer to 200.

On the map, a turn appeared. The car began analyzing millions of trajectories, taking longer than usual to pick a path. Sean was breathing heavily now, sweat ran down his face, “What are you gonna to do baby? What are you going to do?”

It was a game of chicken, to see which car would make way for the other to turn first.

The computer committed, throwing our bodies into the turn.


Sean and I met a few weeks after the race, at Philz coffee in Palo Alto. Oddly enough the building was owned by Palantir, a symbol of for-profit, big-data mass surveillance. Sean felt right at home, sipping a mint mojito, wearing reflective Ray-Ban sunglasses. The team had been disbanded, most of the members had graduated. Sean moved as far away as he could from the icy winters of New England.

That race had left each member a multi millionaire. Besides the winning prize, each member took a substantial cut of the bets made globally. Not a single person had to work another day in their lives, yet almost all of them had either joined a company, or were building their own.

I knew it would be my last meeting with Sean. We joked about the race, and conversed on where the technology was heading. He explained that most of the current AV software was rule based. The systems that would learn on their own, without any human input would win in the end. “It’s not a game of rules, it a game of learning.”

I asked him what next.

“Well, I’ve got more ‘coin than god. And an algorithm better than Google. What do I do now?” Sean sipped his coffee. He looked at me with a smirk, then up to the security camera in the corner, “Find a way to make it seem like I pay taxes!”

X Garrett Kinsman Writes Technology out of San Francisco and Bangalore India.

This unfortunately is a work of fiction