AAA estimates the total cost of driving at ~$0.37/mile. To save $5600/year @ 20000 miles they would have to cut ~$0.28/mile off the cost, or get down into the $0.09/mile range. Consumer reports puts current electric vehicles at ~$0.035/mile of energy costs, giving providers $0.055/mile to cover liability, consumables, financing, etc.
It is certainly tight, but seems doable.
First thing, this is a good article even if I disagree with the central assertion. I think that is worth pointing out because the vast majority aren't these days.
Next, I had never heard of the term "passenger economy" or if I did, I took it the wrong way and thought it was about infotainment systems in the backs of headrests or something that would sell Intel CPUs. Maybe I'm still not understanding the term as Intel wants me to but I think it's the perfect term to cover all the changes to transportation that are going to happen.
Finally, I like GM and think it's the 2nd best player in the market for general purpose SDC. I think their acquisition of Cruse was a master stroke for the company and I think they have a very good EV strategy. I'm not sure any of that matters as far as "winning" the autonomous car race goes though whatever that means. I think they will be a player and get a big chunk of the market which in my book is "success". Given how few cars are needed to get past a tipping point, I don't see manufacturing being a big deal short term. I think it's a long term plus because you can build very specific very high quality cars and drive costs down. I think it gets GM into the game, it secure success.
Musk has said, "Five or six years from now I think we'll be able to achieve true autonomous driving where you could literally get in the car, go to sleep and wake up at your destination," but there are still skeptics who think the "we" refers to humanity, not Tesla, and that he's actually talking about Google. So getting that cleared up would be one question.
How incredibly irresponsible to test that on a public road. The exact same thing could have been accomplished on a test track without actually endangering other drivers. These guys seem like real assholes.
edit: Looks like someone on HN reported them to the cops. https://news.ycombinator.com/item?id=9921557
Maybe this is what you meant to say, without the anti-American bias.
“Stupidity cannot be cured. Stupidity is the only universal capital crime; the sentence is death. There is no appeal, and execution is carried out automatically and without pity.” -- Robert Heinlein
> Warning to Silicon Valley: Automaking is hard
Yes, obviously Tesla has no idea how hard it is to make cars, what with their Model S scoring 103/100 as Consumer Reports' best car ever.
And Tesla has done that on a shoestring.
> "It will be a huge money loser," Lutz predicted.
Apple and Google have something like $200 billion in cash - literally hundreds of times more than Tesla. They could buy every automaker on Earth outright if they felt like it. If they want to acquire the capacity to build cars, they can afford to do so.
And remember, these comments are coming from Bob Lutz - the CEO who captained GM into bankruptcy in 2008-2009. If it hadn't been bailed out by the federal government, he would be famous for ruining what had once been one of the largest companies in the world.
Gifs
Android version
This project was written in java and took me a few months. I'd be happy to answer any questions you might have.
My understanding is that Mobileye are concurrently working on three different autonomous driving systems - single camera (as on Tesla's right now), a three camera system and an eight camera system intended for full autonomy.
At an earnings call in Nov 2015 Mobileye stated: >"We are on track with four launches of the front-sensing trifocal camera configuration to support highly autonomous driving. And we are on track with two launches of an eight camera 360 degree awareness system design to support fully autonomous driving. And all the above, our plan for the 2016 to 2019 timeframe as will occur in parallel rather than one following the other."
So we will have a better idea of Tesla's autonomy plans when we know what Mobileye system they are putting on the vehicles. If any of the vehicles have the 8 camera system then this might indicate that those vehicles will be intended to be fully autonomous at some point. Likewise the three camera system might indicate that the vehicles at some point might have NHTSA Level 3 capability for highway driving say. I am speculating here - but have provided my reasoning.
Regulators WANT self-driving cars, which reduce road deaths and increase traffic efficiency. California will allow self-driving cars without wheels or pedals on public roads by May 1 (120 days after new regulations are passed later this year).
According to this they have already mapped it >Google employees have driven the Lexus SUV out on Kirkland’s roads for the past few weeks, collecting key data on the location of lane markers, traffic signals, curb heights, and more that will help the vehicle drive on its own. Now, the car is ready to drive itself, though there will be a Google employee on board who can take over if needed.
It's an open source host file blocker for Android, called AdAway https://f-droid.org/repository/browse/?fdid=org.adaway . Interestingly it also blocks ads from free apps and Spotify commercials. Needs root obviously, you can uninstall it after modifying the hosts. Very effective as it has no performance loss and by definition is undetectable. Only minus is that unblocking an ad can only be done manually.
I'd suggest checking out the syllabus to this nanodegree. https://www.udacity.com/course/self-driving-car-engineer-nanodegree--nd013
​
On the other hand, if you are a mechanical engineer, it might be easier to be hired as a mechanical engineer. It might make sense to read about some of the various lidar companies and their products.
The problem is - while the first of the SDCs will be within the decade, they're unlikely to reach mass market saturation for at least 20-30 years, and could be delayed further due to unfriendly regulation or litigation from incumbents. It's been "the year of the electric car" or "the year of alternative energy" for decades now, and even traditional hybrids are still in the single digits of market penetration.
Even if it was a service like Uber taking over car ownership, it would have to still come down dramatically in price. At the moment, UberX's rates in my city are $1 pickup fee + $0.15/minute + $1.10/mile. According to http://www.consumerreports.org/cro/2012/12/what-that-car-really-costs-to-own/index.htm - an average car driven about 12,000 miles per year like a Honda Accord costs about $8,000/year. That same 12,000 miles with Uber would be $16,800 ignoring the pickup fee and assuming an average speed of 30 Mph (for the per-minute charge).
> My 2016 Kia can sense cross rear traffic with its sensor suite.
> 2016 Kia can sense cross rear traffic
yeah but that uses two radar mounted on the inside of both side bumpers. tesla only uses one forward radar and their ultrasonic is unreliable.
http://www.consumerreports.org/cro/magazine/2015/04/cars-that-can-save-your-life/index.htm
I believe that this is the call they are referring to (SeekingAlpha - free registration).
This is the relevant language from that call: "In spite of our autonomous driving initiatives, Mobileye is in a closing phases of two strategic projects to partner our customers to create level four fully autonomous driving."
My guess is that this squirly language can be translated as them offering "Level 4 fully autonomous driving", i.e. no driver standby necessary, on highways between 2019 and 2021.
consumer reports actually recommends that parents break the tradition of teens driving old cars, specifically cars without airbags and stability control http://www.consumerreports.org/cro/news/2014/12/why-teens-shouldn-t-drive-old-cars/index.htm
> Unless the problem of charging time is solved, electric cars make more sense for individuals than for fleet vehicles. Individuals don't want to spend all day in the car, so the car naturally has some convenient idle time during which it can recharge.
The Model S can be recharged to 80% capacity in 30 minutes using their 120 kwh Supercharger stations. This is a solved problem. Tesla even gives the patents away (high voltage DC bypassing the onboard chargers).
The per mile costs for electric vehicles are too low to ignore, compared to a quick refill time.
> The pure electric Nissan Leaf costs just 3.5 cents a mile based on the national average of 11 cents/kWh of electricity. That's less than half of what it costs to drive the most fuel-efficient four-door car we've tested, the Toyota Prius.
Note that 11 cents/kWH is on the high side, and an entity purchasing megawatts of power at a time would get much lower rates. Some utilities offer power as low as 1 cent/kWH between midnight and 5am when demand is at its lowest but base load can't be throttled back.
I've been doing this for months through the chffr app. Get a good phone mount and download from one of these links:
Google app: https://play.google.com/store/apps/details?id=ai.comma.chffr
Apple app: https://itunes.apple.com/us/app/dash-train-self-driving-cars/id1146683979?ls=1&mt=8
Well written article - thanks for posting. Given part of the article discussion revolves around sensor and algorithm limitations, what do folks think about the sensor suites required to get to the fully autonomous vehicle? Is a camera truly enough (eventually)? How's about lidar + radar? Do we need additional sensors like high resolution radar or ground penetrating radar to make self-driving vehicles accident free?
>Delphi purchased nuTonomy for $400 million in October this year
I just looked up Delphi's stock quote, and it turns out yesterday Delphi split into two companies. Delphi will be in the legacy powertrain business, and Aptiv (APTV) will be in the business of electric and self-driving vehicles.
Is this one of the few self-driving investment pure plays on public markets? Do you think it's a good one?
Little of this has really been formally decided yet. The first generation of driverless consumer cars will still have steering wheels and pedals, so there will be plenty of feedback about when consumers use the manual controls and how to address those situations before the controls get removed entirely. Robotaxis and other vehicles may have their controls removed, though, like the pedestrian shuttle that was posted here earlier.
>Preventing(or slowing) regulations that enable autonomous vehicle development and deployment is unacceptable and immoral.
Typically government regulations are defined as being restrictive.
If you support regulations, it means you favor restrictions that may limit the testing, development, and deployment of AVs. If you oppose regulations, it means you oppose those restrictions, ie you think there should be minimal or no limits to the testing, development, and deployment of AVs.
So it sounds like you oppose regulations, is that right? And you also characterize them as unacceptable and immoral? Why the strong language?
When a human looks at a paper map, we get a 2d image, which we mentally convert into a more representative format. A string of black dots turns into "oh, that's a road", a symbol turns into "this must be a freeway", etc.
Map databases already contain this data in its representative format. This is because that's the easiest way to store it and edit it; if you need to remove a road, you don't need to take a virtual eraser and carefully extract it from a pixel grid, you just remove the road from the database and regenerate the pixel grid.
There's no reason for autonomous vehicles to (1) start with the representative model, (2) convert it into a pixel grid, and (3) convert that back into a representative model. So, while they include mapping data, it is not included in the form of a 2d image, but in the form of a large database of roads, intersections, etc.
> If they don't, how to they represent geographical information instead?
Check out OpenStreetMap.org, which has export options. I'm certainly not going to claim they're all in exactly this format, because they aren't, but this is a rough approximation of how it's possible for them to work. A quick cursory scan over output .xml suggests that it consists of a large set of "nodes" defined in latitude and longitude coordinates, with roads and addresses then defined in terms of those nodes.
The exact on-vehicle format is probably derived from their canonical database; its format will depend on what the implementer needs, and may change dramatically between one version of the software and another.
>Waymo could spin up a ride sharing app for Android and iOS in a month. They probably already have one.
Yes, they have one. It's on a pilot stage in the Bay Area.
Well, technically is not 100% the same as Uber, but the difference between Uber and carpooling is pretty small from a software point of view.
I have, yes. It's a great supplement to a lot of data that DOTs try to capture, and great for near-real-time applications. And unlike their parent company Google (or Alphabet), they've been really good about exchanging data with DOTs via their Connected Citizens Program.
> he most immediate need will be for signals in congested urban areas
Have you been using Waze? They do great "real-time" traffic data without local communication stations (all via phone & cloud).
"real-time", because it's up-to-the-minute and not up-to-the-second.
Beside normal engineering in a car, a bit more sensor, control and communication will be required. All these field are very dependent on computer science, electrical science, complex adaptive systems and math so these are also options.
So any engineering degree from data to mechanical engineering is useful if you want to be part of developing SDC. I'm studying Systems Control and Mechantronics and almost everything we learn seems useful for SDCs, especially Sensor Fusion, MPC, Mechatronics and Supervisory Control. Just wish I also got to study some deep learning and I should have the whole kid.
For a good intro to the problem you should check out this course: https://www.udacity.com/course/cs373
It isn't the computer that needs to be all that complex, it is the sensors.
That LIDAR sensor is so expensive because it outputs a stream of usable information. That takes a significant amount of processing but it is done in the sensor rather than in the computer.
That is true in a lot of things these days. Rather than one big computer doing everything each part may have a micrcontroller/s specially programmed to do one job well, then all the parts "talk" to a "brain" computer that runs the system. This is good because you can make things modular and upgrade/replace parts without needing to replace the whole system. Also it allows you to add redundant systems for failover protection.
On a side note Sebastian Thrun has a course up on Udacity teaching how to program in python most of the concepts for a driverless car/autonomous robot.
https://www.udacity.com/course/cs373
I'm taking that course myself it is fun so far.
>Or should I just start looking for companies doing work on this and apply right away?
This is just my opinion and it isn't meant to insult you at all, but I think at this stage it might be too late to go to school to learn this in order to bring it about faster. I think that the expertise to solve this in already in place and adding more won't bring it about any faster.
Instead I think it is time to work on finding ways to increase adoption once the tech is in production. Study urban areas and build models that clearly show specific benefits to specific urban areas. Make these models as realistic as possible by including AVs and human drivers in realistic proportions and how these proportions can change over time. Conceive of new business models that rely on AVs, or show how existing businesses can benefit from switching to AVs.
I think the effort to get AVs to be adopted will be much greater than the effort to develop the technology. There is a lot of inertia (social, government, etc) to overcome.
Apart from that if you are interested in studying it from a programing perspective this is free:
https://www.udacity.com/course/viewer#!/c-cs373/l-48739381/m-48735024
> ... it's very uncommon for the big players from the earlier generation to make it through to the new world. How many of you are using a Kodak camera, for example?
Brad's understands the technology well, but he has this weird tendency to get into "disruptive technology" and predict the fall of the the automakers. I think he's a little too influenced by <em>The Innovator's Dilemma</em> and recent history, especially considering that there are many companies that have survived "disruption" by continuing to make steady, incremental improvements (Canon, Nikon, Fujifilm). You don't have to be first on every technology.
It's based on a LeEco X720 (also know as LeEco Le Pro3). That's the same phone as the EON Gold was based on. Sadly the Snapdragon 821 it contains is getting quite old, and doesn't have any neural net accelerators for example.
Your background is great. If you wanted to fine-tune it to be SDC focused a good approach that doesn't involve school/employment would be to get some experience with some open source autonomy projects. AV stacks like apollo, autoware, comma are great, as are av simulators like carla and lgsvl. Courses like https://www.udacity.com/course/self-driving-car-engineer-nanodegree--nd0013 are good too.
But they aren't required for any reasonaboe recruiter. You might stand out a bit more, but the kind of experience you get from a few months messing around with open source software isn't going to outshine your web dev and navy experience. Probably the biggest contribution to selling yourself as an SDC candidate is proving you'll enjoy the work instead of just thinking you will.
I think your first few predictions are optimistic but reasonable. You go off the rails at #12. If SDCs are available in 2019, and no one ever bought a human-driven car again, it would still take almost 10 years for 50% of the cars to be SDC.
People still use rotary phones, rabbit ears, newspapers and ham radios. Obsolete technologies can be surprisingly resilient, especially ones that people have an emotional attachment to. I could see some highways having SDC-only lanes with a high speed limit within 10 years of SDCs being generally available, but I doubt that existing roads will be restricted from human drivers that soon.
2030 is way too soon for human-driven cars to be restricted on all public roads. Maybe the last new mass market human-driven car will be produced in the 2030's, but even that feels optimistic to me. Human-driven cars will be legal almost everywhere for at least 10 years after the last new one is produced.
My guess is around 2050 is when all public roads will be restricted to SDCs. That's when the real fun starts.
I love these sorts of questions and would love to see more of them on this sub. Thank you, /u/deeplearninglex
If you haven't already, I'd recommend checking out Udacity's free Apollo course, and Oliver Cameron's discussion of Prediction as the next frontier in SDCs.
Same here, but it works for me. I did, though, find an excerpt of the story on MarketWatch.
uhhh Wut?
>Population in the world is currently (2018-2019) growing at a rate of around 1.07% per year (down from 1.09% in 2018, 1.12% in 2017 and 1.14% in 2016). The current average population increase is estimated at 82 million people per year.
Existing self-driving cars, with their rather extensive spatial mapping sensor suite, already have superhuman spatial awareness. They can definitely be set up to avoid deer. A self-driving car actively tracks position and velocity of all visible cars in a certain radius around it. In dense city traffic, a self-driving Google car might actively track 50 other cars. This is a feat that no human driver can pull off.
To give you an idea of what's possible with existing technology: you could set things up to detect, track and avoid drivers that exhibit erratic/drunken behavior, for example, before they come near you. This is generally impossible for a human driver: we're talking of identifying a drunk driver 5 cars behind you, 3 lanes over, hidden in between other cars. That's what the technology can do today.
If the sensors will pick up a dear, the car's software can be certainly set up to execute avoidance maneuvers. Any deer detection capability, similar to the tracking of other targets, will be vastly superior to anything a human can pull off.
Deer are a human driver's worst nightmare - that bicycle could have avoided that dear, had it had a self-driving system. As for self-driving cars, if it's remotely possible to detect and avoid the deer, the car will do it.
TL;DR: A self-driving car is to other cars and large animals as an AEW&C/AWACS plane is to other planes.
Scala is mostly for big data analysis.
Most deep learning libraries use Python. If you want to learn deep learning I suggest looking on YouTube for Gilbert Strangs Linear Algebra course, then looking at Andrew Ngs Coursera course.
Have you looked at the Udacity course for self driving car engineer as well?
https://www.udacity.com/course/self-driving-car-engineer-nanodegree--nd013
> Google’s new prototype, by the way, is built in Michigan. Google has not said who but common speculation names not a major car company, but one of their big suppliers.
>The problem is - while the first of the SDCs will be within the decade, they're unlikely to reach mass market saturation for at least 20-30 years, and could be delayed further due to unfriendly regulation or litigation from incumbents. It's been "the year of the electric car" or "the year of alternative energy" for decades now, and even traditional hybrids are still in the single digits of market penetration.
I somewhat agree. There are a lot of people here who vastly underestimate how long it takes for technologies to fully conquer markets. But there have been times in history when technology penetrated relatively quickly, smartphones come to mind. With my suggestion of inter city SDC mini buses, that should be a possibility relatively shortly after SDCs come online. I forget which country it is, but it's already a reality today, except with human drivers.
>Even if it was a service like Uber taking over car ownership, it would have to still come down dramatically in price. At the moment, UberX's rates in my city are $1 pickup fee + $0.15/minute + $1.10/mile. According to http://www.consumerreports.org/cro/2012/12/what-that-car-really-costs-to-own/index.htm - an average car driven about 12,000 miles per year like a Honda Accord costs about $8,000/year.
In theory the price cut would come from two places. First you wouldn't need to pay a driver, especially useful when there are no passengers in the car. Second SDCs are known to be up to 30% more efficient drivers in terms of gas use.
Personally I'm planning to buy an SDC, and it's looking like Tesla might be first.
> handcrafted AI for autonomous vehicles will be surpassed by machine learning systems
I think we're probably already at that point. Universities are likely still doing manual learning, but I think Google and Tesla are using machine learning systems. For example, I just came across this guy who's main background is machine learning "Predictive Control."
It was actually based upon regulations.
> "The speed restriction [of 25 mph] falls into this classification of the Neighborhood Electric Vehicle," a sub-classification of the Low-Speed Vehicle that operates in mixed-used environments, said Susan Shaheen, co-director of the Transportation Sustainability Research Center at the University of California, Berkeley.
via http://www.cnet.com/news/even-limited-to-25-mph-googles-car-will-arrive-faster-than-you-think/
They claim 5 million in the US. Some are not through human error. 2008 I think.
Edit: According to this The US totals the same amount of cars in one year as the world produces in one month...roughly :)
>They were near-universal by 2010, just three years after the launch of the original iPhone.
Smartphones had a 22% market share worldwide in 2010. And one third of those where Symbian phones, which people that believe the iPhone was the first smartphone didn't even consider those to be smartphones.
http://www.quirksmode.org/blog/archives/2011/02/smartphone_sale.html
If you are talking about the US, in Q4 2010 there were 234 million total mobile owners, but only 63.2 million smartphone owners.
So, you see, not even close to near-universal.
Sure, smartphone adoption was way faster than many other historical examples of previous technology, but not as fast as many people think.
He's got a few other concepts on LinkedIn, e.g. I-beam layout with pods that can eject in a crash.
I'm intrigued by alternative vehicle designs possible with full automation. He seems very into high-speed, high-performance vehicles.
That is exactly the intention of this dataset, unlabeled videos good for self-supervised learning and testing, free and easy to use by millions of people.
We have too many labeled datasets that are not generic enough, and most SDC research is just limiting their testing to them.
You mention Berkeley DeepDrive which is great, but it is just 1100 hours of driving from a single area. Have tried to use it? Did you see results from it? Please share them.
My approach is to build self-supervised algorithms (even non deep learning based) which should work on any unlabeled video, and test (even manually) them on as many videos as possible.
Check my Twitter and LinkedIn messages if you'll like to learn more about this approach, they are linked in this SDC presentation: https://slides.com/mslavescu
Autoware (used by a few startups) is the most complete open source SDC platform, but has one important limitation, it cannot be used without a detailed 3D map, which is built with a fairly expensive LIDAR, which is required for navigation also.
OpenPilot (initiated by Comma) is just LKAS (neural net based) and ACC (radar based) running on a phone and requires to inject CAN messages to emulate commands from the LKAS and ACC installed by the car manufacturer.
Apollo advances fast, but their perception still requires expensive LIDAR, like Autoware.
Now we got more simulators and visualization tools, which is great, we just need to evaluate and consolidate them.
At this point there are no complete open source solutions, affordable or safe enough to be used at scale, they are good just for tinkering.
My focus in http://ossdc.org is to build a set of open source smart cameras (similar with Mobileye, but with stereo) that would bring down the cost of perception (with accurate 3D reconstruction) and follow Toyota's Guardian approach to offer assisted technology, instead of actually driving the car.
Using boards like Ultra96 we can make flexible, affordable and feature rich smart cameras with less than $500 per stereo camera.
See more details in my SDC presentation here: https://slides.com/mslavescu
And join me in my endeavor if you have experience with FPGA and computer vision.
What car do you plan to use?
Check the sensors pages on my recent SDC presentation at (click on images for related articles): https://slides.com/mslavescu
Do you plan to open source any of your work?
Join the discussions on OSSDC.org Slack at http://join.ossdc.org
Very good highlights!
See my recent overview of SDC (will add more ongoing content), my view is that ML based approach needs to be changed to achieve robustness and generality (AutoML may help achieve that faster): https://slides.com/mslavescu
While driving today I recorded a test video, I just posted on YouTube and launched a mini challenge with prizes, see the details here: https://www.linkedin.com/feed/update/urn:li:activity:6501259381554978816
No, there is no other technology. But it's all about ambition and what people think are the problems. And German car companies are not really interested in autonomous cars, as their entire narrative is around the driver. Then the regulators and agencies are also way too risk averse, too afraid of somebody getting into an accident and then they are getting blamed for recklessly giving them a test license. And then there is a totally wrong understanding that you need connectivity and 5G and vehicle-to-vehicle or vehicle-to-infratsructure communication with tons of stuff built into roads etc. and that is a totally wrong understanding.
You can read more on my German-language blog and the German book with the same title to understand more.
uBlock Origin works with either Kiwi Browser or Firefox on Android.
If you have been visiting this reddit-forum, you may have read some of my articles and seen videos of autonomous vehicles that I encounter in Silicon Valley. Well, my site has been the result of a book that - two years after the German book came out - is now available in English, with updated and new content.
The Last Driver's License Holder Has Already Been Born is available today, my publisher is McGrawHill. The book covers autonomous, electric, shared driving and connectivity, and most importantly, discusses the ramifications for cities, jobs, access individual mobility and much more. Because I live in the San Francisco Bay Area - a.k.a Silicon Valley - the hotbed of many of those developments, I spoke to many of the companies and experts, which might give you an interesting insight in the whole world of new mobility. The book's available at Amazon and any bookstore!
as /u/david_ranch_dressing said, specifically this one: https://www.amazon.com/Arteck-Universal-Rotation-Windshield-Smartphone/dp/B01MAYNX9T/ref=pd_lpo_sbs_107_t_0?_encoding=UTF8&psc=1&refRID=GQXRRQQ5P2XN02P1M2P1
This drone can carry a payload of 15 pounds for 40 minutes. That's more than five 2Liters of soda. It weights 42 pounds and cost half of a new car.
I think we could be doing this today if people weren't worried about legal hurdles/liabilities.
Nature's review:
> Humanity hovers at a momentous technological crossroads, declares engineer Vivek Wadhwa. 'Exponential' advances seeping into every cranny of life could propel us towards utopia or dystopia — Star Trek or Mad Max, as he puts it. Writing with Alex Salkever, Wadhwa ranges over applications from genome editing and the Internet of Things to artificial intelligence, weighing up their potential for risk and the universality of any benefits. Readers may not all share his enthusiasm for autonomous vehicles, but his pointed analyses of the coming transformations add nuance to the debate.
Here's the Amazon page: https://www.amazon.com/Driver-Driverless-Car-Technology-Choices/dp/1626569711/
The Driver in the Driverless Car: How Our Technology Choices Will Create the Future by Vivek Wadhwa, Alex Salkever
You should focus on developing meaningful career assets. Understanding the theory or having exposure through data entry won't be enough. This book has helped me understand that building my own robot is the only sure-fire way to get hired onto one of those teams.
If you haven't slept enough but need to drive, keep some caffeine pills in your car. You can also pull over and get coffee. I'd prefer to skip spending extra for crappy coffee to just get caffeine. Each pill is about 1.5 cups of coffee. If it's a shorter drive, take half. Doesn't make me jittery or anything but I also drink a fair amount of coffee.
> For instance construction sites would be required to install a small sensor that tells all cArs in the area to avoid that spot.
Use WeatherSignal to help 1 day?
https://play.google.com/store/apps/details?id=com.opensignal.weathersignal&hl=en
>WeatherSignal uses native phone sensors to measure local atmospheric conditions, which are then displayed on our live-updating weather map.
>Join the world's largest crowdsourced weather project.
You can report when it rains.
That's some hefty cooperation though.