In Development: Quanser's Self-Driving Car Research Studio - Quanser (2024)

Back Then…

In the late 2000s, there were no iPhones, no YouTube, no Arduinos or Raspberry Pi’s, the DotCom bubble was still growing, Google was still a new thing. You had to pay hundreds of dollars for a C compiler, and 90% of internet users were still on dial-up. Nevertheless, as an enthusiastic fourth-year engineering student working on my capstone project, anything was possible.

In Development: Quanser's Self-Driving Car Research Studio - Quanser (1)

With three other team members, we were determined to demonstrate the possibilities of an automated highway system with 1/10 scale model cars. We were using cutting edge technology, but our project goals were quite different from what we think of as an autonomous car today – full scale or model.

The car followed a line using an array of six photodetectors connected to a microcontroller which ran a fuzzy logic engine we hand-coded in assembly. Speed limit “signs” were read with a simple implementation of a barcode scanner. Our high-level planning processor managed inter-car communications using an infrared serial connection (WiFi was too expensive) and it used a decision tree to coordinate vehicle actions. Every PCB had to be built from scratch, and every cable had to be made by hand. That was eight months of work.

And now…

In Development: Quanser's Self-Driving Car Research Studio - Quanser (2)

Fast forward to 2019. I am now employed at Quanser. Early this year, we started talking about developing a new platform for researchers to study self-driving cars. As a first proof of concept, I dug out my vehicles from 19 years prior, ripped out all the electronics, and replaced them with a webcam, Raspberry Pi, and our QUARC Real-Time Control Software. We recreated 8 months of work in 2 days.

The idea of automated highway systems is valid now more than ever. The Highway 401 in Ontario is the busiest highway in the world, with more than half a million cars travelling on it every day, and far exceeding its design capacity. If we can take the humans out of the loop, even just on the highways, we could increase the traffic density and speed while reducing fuel consumption.

As this video by Johnathan Sprinkle at the University of Arizona demonstrates, even a small number of autonomous vehicles integrated with regular drivers can help to increase average travel speeds while reducing fuel consumption:

Helping Researchers Develop the Perfect Autonomous Car

So how do you make a perfect autonomous car? We don’t know, but we do have the expertise to provide researchers with a powerful and flexible platform for them to test their ideas. On the side, we’re going to test some of our own ideas too! Over the last six months, we have been hard at work developing our QCar platform.

If you are interested in this subject, stay tuned for my blog post series. Over the next few months, I plan to post regular updates about our progress and show you where we’re heading. Today, I’m going to start with focusing on the hardware aspects of our QCar.

The QCar Hardware

In Development: Quanser's Self-Driving Car Research Studio - Quanser (3)

After many months of prototyping, we are happy to announce that we have just built our first alpha version! An alpha version means that all the fundamental design goals are now functional and we have solved all the technical challenges to turn this into a product. We still have a couple more iterations before it is ready for manufacturing and we lock down the design, but in the meantime we’re well into our software and applications development.

Serious GPU Power for Real-time Image Processing

At the core of the QCar, NVidia Jetson TX2 plugs into a custom PCB. For a small, mobile platform, this is some serious GPU power which supports real-time image processing and AI functions. As part of the supporting architecture, we have implemented a USB 3.0 hub so that researchers can add a variety of high speed devices. Included with the QCar will be an Intel RealSense D435 depth camera that will make use of the USB 3.

Vision and Navigation

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Another key aspect of the supporting architecture is a high speed CSI interface. The QCar will include 4 onboard, wide angle, CSI color cameras to give you 360 degrees of vision. These cameras can stream their data directly to the onboard GPU so you can get almost 4K resolution at 10 bits per pixel per camera. Alternatively, you can switch to lower resolutions and get 120fps! With the direct interface into the GPU, you can leverage the power of the CUDA cores with minimal latency.

We’ve also added a 2D LIDAR on top for 360 degree ranging. This can either enhance your visual processing with the CSI cameras, or you can navigate solely with LIDAR alone. We’ve already taken care of some of the basic functions of LIDAR processing so you can get smart-interpolated data in fixed or variable length arrays, or you can just get the raw data if you prefer to start there and build up.

Exploring the Use of Audio

One of our more experimental features at the moment is adding stereo microphones. This adds another dimension to sensor fusion. Could this be used to determine the surface material your car is currently travelling on and change the control response as a result? Could a response to audio cues of an emergency vehicle be formulated before it is visible? Could honking horns be spatially located to identify a future threat? To build on this area of exploration, our developers have also added a speaker to the vehicle to add to the possible vehicle response to of an impending threat.

Signals and Lights

In Development: Quanser's Self-Driving Car Research Studio - Quanser (5)

On top of brake lights, turn signals, and reverse indicators, QCar also has headlights. Driving at night adds another facet to processing the driving environment. The field of view becomes more restricted at night using only headlights, image data becomes noisier, color information is more restricted, and oncoming traffic and street lights can create new challenges. With the QCar, you can test your image processing routines work under different lighting conditions to test the robustness of your algorithms, or try dynamically switching your processing models.

Before our society reaches a fully autonomous transportation infrastructure, self-driving cars will need to interact with those unpredictable human drivers. Since the processor can directly control all the lights, it’s just a small clip of code to correlate your signals with a game controller. We envision test scenarios where fully autonomous QCars interact with one or more human-driven QCars. By using cameras to evaluate the brake and turn signals of the human-driven vehicles, AI routines on the autonomous cars can try to evaluate the intentions of the human drivers.

And There’s More

To round things out, we also have an encoder on the motor and current measurements so you can estimate the power consumption to quantify the efficiency of driving. The 9-axis inertial measurement unit can work in combination with optical flow and encoder measurements for dead reckoning in the absence of external tracking systems. And the LCD screen gives you the current IP address and battery levels and you can even write your own messages to the screen.

In Development: Quanser's Self-Driving Car Research Studio - Quanser (6)

Not Enough? Customize!

Although we’ve tried to think up a lot of use cases, we know you will want to do more and customize the vehicles for your specific research. You can plug a keyboard, mouse, and HDMI cable directly into the vehicle so you have direct access to the Ubuntu operating system. We provide user-accessible communication ports for SPI, I2C, CAN bus, serial, Ethernet, and USB 3 ports so you can add more sensors and cameras. There are also general purpose digital IO, 4 user encoder channels with full quadrature decoding, and special PWM outputs that support general purpose PWM, standard servo PWM, DShot, Oneshot, and multishot. You could instrument each wheel on the vehicle if you like, or build a robot arm on top! Let us know in the comments below what you would like to do with a scale model of an autonomous research car!

Next time, I’ll tell you about the exciting software advancements we’re working on to support your research! Talk to you next month.

In Development: Quanser's Self-Driving Car Research Studio - Quanser (2024)

FAQs

What are the core moral dilemmas involved in the programming of driverless cars? ›

The ethical dilemmas faced by AV programmers primarily deal with exceptional driving situations – instances where the car cannot at the same time fulfill its obligations to all road users and its passengers.

What problem is self-driving cars solving? ›

In addition to making our roads safer, these capabilities are hoped to eliminate stop-and-go traffic, increasing road capacity, and optimising traffic flow. Overall, the prediction is that autonomous vehicles will reduce traffic congestion. But just how realistic a future this is remains unclear.

What is a major motivation in developing a self-driving car? ›

Higher levels of autonomy have the potential to reduce risky and dangerous driver behaviors. The greatest promise may be reducing the devastation of impaired driving, which causes approximately one-third of road fatalities today.

Are self-driving cars a good or bad idea research paper? ›

Self-driving technology in general is becoming increasingly common and could revolutionize our transportation system. Also, self-driving cars are on their way of being legal, but they still are not trusted enough to be used in real life due to a lack of their safety.

What is the main idea of self-driving cars? ›

An autonomous car is a vehicle capable of sensing its environment and operating without human involvement. A human passenger is not required to take control of the vehicle at any time, nor is a human passenger required to be present in the vehicle at all.

What is the argument for self-driving cars? ›

Automation can help reduce the number of crashes on our roads. Government data identifies driver behavior or error as a factor in 94 percent of crashes, and self-driving vehicles can help reduce driver error. Higher levels of autonomy have the potential to reduce risky and dangerous driver behaviors.

What is the main reason that self-driving cars fail? ›

Many AV crashes occur because self-driving technology doesn't correctly identify roadway obstacles. Automakers continually strive to update these systems to prevent further wrecks.

What is the biggest challenge for self-driving cars? ›

Current Challenges in Autonomous Vehicle Development
  • Safety and Reliability Concerns. ...
  • Regulatory and Legal Issues. ...
  • Technological Changes and Ethical Challenges. ...
  • Scalability and Infrastructure Adaptation. ...
  • Public Perception and Consumer Acceptance. ...
  • Data Security and Privacy Concerns.
Jan 10, 2024

Are self-driving cars pros and cons? ›

The pros and cons of the self-driving car revolution
  • Con: Machines are not as smart as humans. ...
  • Pro: Self-driving cars could make our roads safer. ...
  • Con: They could cause privacy and security concerns. ...
  • Pro: They could mark the end of parking problems. ...
  • Con: They could cause job losses.
Mar 8, 2023

What is one of the biggest benefits from self-driving cars? ›

1. Enhanced Road Safety. One of the most significant advantages of autonomous cars is their potential to make our roads safer. Human error is a leading cause of accidents, with factors like distracted driving, impaired judgment, and fatigue contributing to a large number of collisions.

What are some possible ethical problems with self-driving cars? ›

One important but often overlooked ethical issue raised by autonomous vehicles is whether they should be programmed to avoid hitting animals, and if so, which ones. All vertebrates, and some invertebrates, are sentient beings, liable to suffer if hit but not killed instantly.

How self-driving cars will impact society? ›

They could reduce the economic burden of traffic jams and vehicle accidents, but could contribute to a coming unemployment crisis and cause economic instability. AVs could also change the way urban land is used by freeing up valuable urban land, which could then be used for the public good.

What are the negative effects of self-driving cars? ›

A malicious attacker could find and exploit security holes in any number of complex systems to take over a car or even cause it to crash purposefully. Furthermore, driverless cars of the future will likely be networked in order to communicate with each other and send and receive data about other vehicles on the road.

Will self-driving cars be a positive or negative development? ›

Once they are fully developed, self-driving cars will potentially have a huge positive impact on our safety and lifestyle. The high-tech vision system has the potential to outperform humans in detecting dangerous situations. Unlike distracted or drunk drivers, self-driving cars always operate at their maximum ability.

Are self-driving cars bad for the environment? ›

The computers needed to run self-driving cars could pose a serious threat to the environment. They could ultimately produce more greenhouse gas emissions per year than Argentina currently does, new research suggests. Fossil fuel-guzzling cars spew out billions of tonnes of carbon dioxide.

What are the moral issues of self-driving cars? ›

Another concern is that autonomous vehicles could be used for nefarious purposes, such as being used as part of a terrorist attack. Additionally, there are worries that criminals could use these vehicles to get away from the scene of a crime or to transport illegal substances.

What moral challenge will the developers of self-driving cars face when designing them for the international market? ›

Program the Car to Make an Impartial Decision

Some also argue that the best way for a self-driving car is to make an impartial decision in case of accidents. They must not discriminate between humans based on age, gender, or other parameters. They should always make a decision that causes the least impact.

What are some concerns of driverless car technology? ›

What aspect of self-driving cars concerns you the most?
  • Safety. 36%
  • Technology malfunction. 27%
  • Reliability. 9%
  • Cost. 8%
  • N/A: I don't have any concerns over self-driving cars. 7%
  • Hacking. 6%
  • Long-term lifespan. 3%
  • Privacy. 2%
Feb 13, 2024

What is an example of a moral dilemma? ›

Moral dilemmas are not uncommon when organizations and individuals are working to satisfy competing interests, or when personal morals and professional obligations are directly opposed. An example would be a devout Catholic that marries, has children, and later discovers that their spouse is abusing one of them.

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