Scribble is a haptic interface lets you draw your way through traffic. In an environment where fully automated vehicles are becoming the expectation for the next step in transportation, Scribble provides a friendly alternative that allows you to guide your car around, while the automation makes decisions on how to actually steer the car around obstacles.
The driver is guided by haptic feedback that alerts them about the road conditions or obstacles ahead. The project was conceived by [Felix Ros] for his master’s thesis at Eindhoven University, featured a five bar linkage that moves with two lateral degrees of freedom, commonly used for drawing robots.
The code run on an Arduino DUE control over serial by a program made in Open Frameworks that communicates with a Unity 3D driving simulator over UDP. Fellow graduate student [Frank van Valeknhoef]’s Haptic Engines are used as the actuators, outputting the position and a variable force.
The forward kinematics algorithms were based on a clock and weather plotter by SAP, sharing the same servo and drawing arm assembly. The left and right actuators update based on the desired angle, calculating the proper angles needed to achieve the correct position.
While automated vehicles may be able to travel efficiently from one destination to the next, they can’t necessarily wander off course to explore new places. Scribble takes back some of that freedom and allows drivers to decide for themselves where they want to be. It’s an interesting take at inserting the human back into the driver’s seat in automated cars.
Continue reading “Steering By Touch And Haptic Feedback”
Part of the fun of watching action movies is imagining yourself as the main character, always going on exciting adventures and, of course, being accompanied by the perfect soundtrack to score the excitement and drama of your life. While having an orchestra follow you around might not always be practical, [P1kachu] at least figured out how to get some musical orchestration to sync up with how he drives his car, Fast-and-Furious style.
The idea is pretty straightforward: when [P1kachu] drives his car calmly and slowly, the music that the infotainment system plays is cool and reserved. But when he drops the hammer, the music changes to something more aggressive and in line with the new driving style. While first iterations of his project used the CAN bus, he moved to Japan and bought an old Subaru that doesn’t have CAN. The new project works on something similar called Subaru Select Monitor v1 (SSM1), but still gets the job done pretty well.
The hardware uses an Asus Tinkerboard and a Raspberry Pi with the 7″ screen, and a shield that can interface with CAN (and later with SSM1). The new music is selected by sensing pedal position, allowing him to more easily trigger the aggressive mode that his previous iterations did. Those were done using vehicle speed as a trigger, which proved to be ineffective at producing the desired results. Of course, there are many other things that you can do with CAN bus besides switching up the music in your car.
Continue reading “Adaptive Infotainment Plays Tunes To Match Your Dangerous Driving”
I think I can sum up the difference between those of us who regularly visit Hackaday and the world of non-hackers. As a case study, here is a story about how necessity is the mother of invention and the people who invent.
Hackaday has overlap with sites like Pinterest and Instructables but there is one vital difference, we choose to create something new and beautiful with the materials at hand. Often these tools and techniques are very simple. We look to make things elegant by reducing the unnecessary clutter, not adding glitter. If something could be built with a 555 timer we will let you know. If there is a better choice for a processor, we will tell you.
My first real work commute was a forty-minute eastward drive every morning and a forty-minute westward drive every evening. This route pointed my car directly into the sun twice a day. Staring into a miasma of incandescent plasma for an hour and a half a day isn’t fun, and probably isn’t safe, but we can fix that.
Continue reading “What Makes A Hacker”
In a previous article, I discussed LEDs in general and their properties. In this write-up, I want to give some examples of driving LEDs and comparing a few of the most commonly used methods. There is no “one size fits all” but I will try and generalize as much as possible. The idea is to be able to effectively control the brightness of the LED and prolong their life while doing it. An efficient driver can make all the difference if you plan to deploy them for the long-haul. Let’s take a look at the problem and then discuss the solutions. Continue reading “Control Thy LED”
For all the complexity involved in driving, it becomes second nature to respond to pedestrians, environmental conditions, even the basic rules of the road. When it comes to AI, teaching machine learning algorithms how to drive in a virtual world makes sense when the real one is packed full of squishy humans and other potential catastrophes. So, why not use the wildly successful virtual world of Grand Theft Auto V to teach machine learning programs to operate a vehicle?
The hard problem with this approach is getting a large enough sample for the machine learning to be viable. The idea is this: the virtual world provides a far more efficient solution to supplying enough data to these programs compared to the time-consuming task of annotating object data from real-world images. In addition to scaling up the amount of data, researchers can manipulate weather, traffic, pedestrians and more to create complex conditions with which to train AI.
It’s pretty easy to teach the “rules of the road” — we do with 16-year-olds all the time. But those earliest drivers have already spent a lifetime observing the real world and watching parents drive. The virtual world inside GTA V is fantastically realistic. Humans are great pattern recognizers and fickle gamers would cry foul at anything that doesn’t analog real life. What we’re left with is a near-perfect source of test cases for machine learning to be applied to the hard part of self-drive: understanding the vastly variable world every vehicle encounters.
A team of researchers from Intel Labs and Darmstadt University in Germany created a program that automatically indexes the virtual world (as seen above), creating useful data for a machine learning program to consume. This isn’t a complete substitute for real-world experience mind you, but the freedom to make a few mistakes before putting an AI behind the wheel of a vehicle has the potential to speed up development of autonomous vehicles. Read the paper the team published Playing for Data: Ground Truth from Video Games.
Continue reading “Grand Theft Auto V Used To Teach Self-Driving AI”
[j3tstream] wanted an easier way to monitor traffic on the roads in his area. Specifically, he wanted to monitor the roads from his car while driving. That meant it needed to be easy to use, and not too distracting.
[j3tstream] figured he could use a Raspberry Pi to run the system. This would make things easy since he’d have a full Linux system at his disposal. The Pi is relatively low power, so it’s run from a car cigarette lighter adapter. [j3tstream] did have to add a custom power button to the Pi. This allows the system to boot up and shut down gracefully, preventing system files from being corrupted.
After searching eBay, [j3tstream] found an inexpensive 3.2″ TFT LCD touchscreen display that would work nicely for displaying the traffic data. The display was easy to get working with the Pi. [j3tstream] used the Raspbian linux distribution. His project page includes a link to download a Raspbian image that already includes the necessary modules to work with the LCD screen. Once the image is loaded, all that needs to be done is to calibrate the screen using built-in operating system functions.
The system still needed a data connection. To make things simple and inexpensive, [j3tstream] used a USB WiFi dongle. The Pi then connects to a WiFi hot spot built into his 4G mobile phone. To view the traffic map, [j3tstream] just connects to a website that displays traffic for his area.
The last steps were to automate as much as possible. After all, you don’t want to be fumbling with a little touch screen while driving. [j3tstream] made some edits to the LXDE autostart file. These changes automatically load a browser in full screen mode to the traffic website. Now when [j3tstream] boots up his Pi, it automatically connects to his WiFi hotspot and loads up local traffic maps.
[Cmonaco3’s] girlfriend wanted a better way to control her iPod when driving. She didn’t want to take her eyes of the road and asked him if he could help. He ended up building a heads up display which reads out track information and offers a few simple buttons for control.
The display includes controls for track forward, track back, and play/pause. Those buttons, along with the LCD screen, mount on the windshield using a suction cup. This way the driver doesn’t have to completely remove focus from the road to control the iPod which is sitting in the passenger’s seat.
To accomplish this [Cmonaco] used a dock connector breakout board for communication between an Arduino and the iPod. The Arduino pulls song information to be displayed on the graphic LCD screen, and sends commands to the iPod when it detects a button push. See a quick demo of the setup after the break.
Continue reading “Heads Up Controls For Your IPod”