Self-driving is currently the Holy Grail in the automotive world, with a number of companies racing to build general-purpose autonomous vehicles that can get from point A to point B with no user input. While no one has brought one to market yet, at least one has promised this feature and had customers pay for it, but continually moved the goalposts for delivery due to how challenging this problem turns out to be. But it doesn’t need to be that hard or expensive to solve, at least in some situations.
The situation in question is driving on a single stretch of highway, and only focuses on steering, so it doesn’t handle the accelerator or brake pedal input. The highway is driven normally, using a webcam to take images of the route and an Arduino to capture data about the steering angle. The idea here is that with enough training the Arduino could eventually steer the car. But first some math needs to happen on the training data since the steering wheel is almost always not turning the car, so the Arduino knows that actual steering events aren’t just statistical anomalies. After the training, the system does a surprisingly good job at “driving” based on this data, and does it on a budget not much larger than laptop, microcontroller, and webcam.
Admittedly, this project was a proof-of-concept to investigate machine learning, neural networks, and other statistical algorithms used in these sorts of systems, and doesn’t actually drive any cars on any roadways. Even the creator says he wouldn’t trust it himself, but that he was pleasantly surprised by the results of such a simple system. It could also be expanded out to handle brake and accelerator pedals with separate neural networks as well. It’s not our first budget-friendly self-driving system, either. This one makes it happen with the enormous computing resources of a single Android smartphone.
Continue reading “Full Self-Driving, On A Budget”
One of the best things about open source software is that, instead of being lost to the ravages of time like older proprietary software, anyone can dust off an old open source program and bring it up to the modern era. PyOBD, a python tool for interfacing with the OBD system in modern vehicles, was in just such a state with its latest version still being written in Python 2 which hasn’t had support in over three years. [barracuda-fsh] rewrote the entire program for Python 3 and included a few other upgrades to it as well.
Key feature updates with this version besides being completely rewritten in Python 3 include enhanced support for OBD-II commands as well as automating the detection of the vehicle’s computer capabilities. This makes the program much more plug-and-play than it would have been in the past. PyOBD now also includes the python-OBD library for handling the actual communication with the vehicle, while PyOBD provides the GUI for configuring and visualizing the data given to it from the vehicle. An ELM327 adapter is required.
With options for Mac, Windows, or Linux, most users will be able to make use of this software package provided they have the necessary ELM327 adapter to connect to their vehicle. OBD is a great tool as passenger vehicles become increasingly computer-driven as well, but there are some concerns surrounding privacy and security in some of the latest and proposed versions of the standard.
When looking the modify a passenger vehicle, the Controller Area Network (CAN) bus is a pretty easy target. In modern vehicles it has access to most of the on-board systems — everything from the climate control to the instrument cluster and often even the throttle, braking, and steering systems. With as versatile as the CAN bus is, though, it’s not the right tool for every job. There’s also the Media Oriented Systems Transport (MOST) bus which is increasingly found in automotive systems to handle multimedia such as streaming music to the stereo. To access that system you’ll need to approach it slightly differently as [Rhys] demonstrates.
[Rhys] has been working on replacing the dated head unit in his Jaguar, and began by investigating the CAN bus. He got almost everything working with replacement hardware except the stereo, which is where the MOST bus comes into play. It provides a much higher bandwidth than the CAN bus can accommodate but with almost no documentation it was difficult to interact with at first. With the help of a Raspberry Pi and a lot of testing he is able to get the stereo working again with a much more modern-looking touchscreen for control. It is also able to do things like change CDs in the car’s CD player, gather song information from the CD to display on the panel, and can perform other functions of the infotainment center.
For more detailed information on the MOST bus, [Rhys] also maintains a website where he puts his discoveries and other information he finds about this system. Unfortunately car stereo systems in modern vehicles can get pretty complicated these days, but adapting car stereos in older vehicles to modern technology carries some interesting challenges as well.
Continue reading “Get MOST Into Your Pi”
As the old saying goes, there’s no such thing as a lock that can’t be picked. However, it seems like there are plenty of examples of car manufacturers that refuse to add these metaphorical locks to their cars at all — especially when it comes to securing the electronic systems of vehicles. Plenty of modern cars are essentially begging to be attacked as a result of such poor practices as unencrypted CAN busses and easily spoofed wireless keyfobs. But even if your car comes from a manufacturer that takes basic security precautions, you still might want to check out this project from the University of Michigan that is attempting to add another layer of security to cars.
The security system works like many others, by waiting for the user to input a code. The main innovation here is that the code is actually a series of voltage fluctuations that are caused by doing things like turning on the headlights or activating the windshield wipers. This is actually the secondary input method, though; there is also a control pad that can mimic these voltage fluctuations as well without having to perform obvious inputs to the vehicle’s electrical system. But, if the control pad isn’t available then turning on switches and lights to input the code is still available for the driver. The control unit for this device is hidden away, and disables things like the starter motor until it sees these voltage fluctuations.
One of the major selling points for a system like this is the fact that it doesn’t require anything more complicated than access to the vehicle’s 12 volt electrical system to function. While there are some flaws with the design, it’s an innovative approach to car security that, when paired with a common-sense approach to securing modern car technology, could add some valuable peace-of-mind to vehicle ownership in areas prone to car theft. It could even alleviate the problem of cars being stolen via their headlights.
Continue reading “Car Security System Monitors Tiny Voltage Fluctuations”
Toyota is going through a bit of a Kodak moment right now, being that like the film giant they absolutely blundered the adoption of a revolutionary technology. In Kodak’s case it was the adoption of the digital camera which they nearly completely ignored; Toyota is now becoming similarly infamous for refusing to take part in the electric car boom, instead placing all of their faith in hybrid drivetrains and hydrogen fuel cell technologies. Whether or not Toyota can wake up in time to avoid a complete Kodak-style collapse remains to be seen, but they have been making some amazing claims about battery technology that is at least raising some eyebrows. Continue reading “Toyota Makes Grand Promises On Battery Tech”
One of the most common ways of measuring the speed of a vehicle is by using radar, which typically involves generating radio waves, directing them at a moving vehicle, and measuring the various ways that they return to the device. This is a tried-and-true method, but can be expensive and technically complex. [GeeDub] wanted an easier way of measuring vehicles passing by his home, so he switched to using sonar instead to measure speeds based on the sounds the cars generate themselves.
The method he is using is similar to passive sonar in submarines, which can locate objects underwater based on the sounds they produce. After a false start attempting to measure Doppler shift, he switched to time correlation using two microphones, essentially using stereo audio input to detect subtle differences in arrival times of various sounds to detect the positions of passing vehicles. Doing this fast enough and extrapolating the data gathered, speed information can be calculated. For the data gathering and calculation, [GeeDub] is using a Raspberry Pi to help keep costs down, and some further configuration of the microphones and their power supplies were also needed to ensure quality audio was gathered.
With the system in place in a window, it detected around 9,000 vehicles over a three-day period. The software generates a normal distribution of vehicle speeds for this time, with the distribution centered on around 35 MPH, slightly above the posted speed limit of 30. As long as there’s a clear line of sight to the road using this system it’s just as effective as some other passive systems we’ve seen to measure vehicle speed. Of course, active speed measurement systems are not out of the realm of possibility if you’re willing to spend a little more.
Almost all entry-level physics courses, and even some well into a degree program, will have the student make some assumptions in order to avoid some complex topics later on. Most commonly this is something to the effect of “ignore the effects of wind resistance” which can make an otherwise simple question in math several orders of magnitude more difficult. At some point, though, wind resistance can’t be ignored any more like when building this remote-controlled car designed for extremely high speeds.
[Indeterminate Design] has been working on this project for a while now, and it’s quite a bit beyond the design of most other RC cars we’ve seen before. The design took into account extreme aerodynamics to help the car generate not only the downforce needed to keep the tires in contact with the ground, but to keep the car stable in high-speed turns thanks to its custom 3D printed body. There is a suite of high-speed sensors on board as well which help control the vehicle including four-wheel independent torque vectoring, allowing for precise control of each wheel. During initial tests the car has demonstrated its ability to corner at 2.6 lateral G, a 250% increase in corning speed over the same car without the aid of aerodynamics.
We’ve linked the playlist to the entire build log above, but be sure to take a look at the video linked after the break which goes into detail about the car’s aerodynamic design specifically. [Indeterminate Design] notes that it’s still very early in the car’s development, but has already exceeded the original expectations for the build. There are also some scaled-up vehicles capable of transporting people which have gone to extremes in aerodynamic design to take a look at as well.
Continue reading “Remote-Controlled Hypercar Slices Through Air”