Trends in Auto Tech (part 2)

List of driver assistance features available today

Advanced Driver Assistance Systems (ADAS) enable enhanced situational awareness and vehicle control for easier and safer driving experience.

Most ADAS includes a combination of sensors (cameras, radar systems, ultrasounds, LIDAR and GPS) and artificial intelligence software (computer vision based on deep learning algorithms).

While Tesla think that laser is not the ‘sauce’ for autonomous driving, others like Google argument that in low-lighting conditions where cameras alone do not work, LIDAR is required.

Part 1 of this blog post covered problem and emerging solutions, industry transition, and investments in Auto Tech. In Part 2, you can find the list of technologies and features:

NON-INTERVENTION are the features that only monitor and warn drivers without controlling any part of the vehicle.

Forward Collision Warning (FCW): Alertsthe drivers to a potential collision with a vehicle detected ahead. Uses cameras, radar, or laser (or some combination thereof) to scan the road ahead and to alert the driver if the distance to a vehicle ahead is closing too quickly. The systems alert the driver with an audible, haptic (touch), and/or visual cue. According to the NHTSA, out of the 6 million car accidents that happen on U.S. roads every year, over 40% of them (2.5 million) are rear-end collisions. FCW alone reduced rear-end striking crash involvement rates by 23%.

Lane Departure Warning (LDW): Alerts drivers when their vehicle is about to unintentionally cross into another lane with a visual and audio or sensory cue. A small front camera detect the distance of road surface markings and then analyzes that information to determine if the vehicle is about to drift across said markings. If the turn signal is not activated when this happens, the driver is alerted by a visual warning and an audible tone or a vibration. In 2015, nearly 13,000 people died in single-vehicle run-off-road, head-on, and sideswipe crashes where a passenger vehicle left the lane unintentionally

High Speed Warning (HSW): Alert driver when speeding. Coordinates the car’s position, via GPS, with a database of speed limit information to alert drivers if they’re speeding. This helps drivers maintain a safe driving speed.

Blind Spot Monitor: alerts drivers when there may be something located in their blind spot.

Rear Cross Traffic Alert: provides an alert to the driver that traffic is approaching from the left or right when the vehicle is in reverse.

Traffic-sign recognition (TSR): the vehicle is able to recognize the traffic signs put on the road e.g. “red traffic light” or “school area” or “turn ahead”, and alert driver in case speed or directions is not appropriate.

INTERVENTION are the features that in addition to monitor and warn, also control the braking, and steering of the vehicle.

Autonomous Emergency Break (AEB): Automatically activates the vehicle’s brake, to some degree, when necessary. Use sensors, cameras, radar, and LIDAR to detect an impending vehicle collision. Systems vary from pre-charging brakes, slowing the vehicle to lessen damage or even stop the vehicle before a collision occurs. FCW with AEB reduced rear-end striking crash involvement rates by 39%

Collision Avoidance Assist (CAA): Helps the driver steer around an obstacle in a critical situation. Uses data from the two radar sensors and the front camera to calculate a suitable evasive maneuver corridor. After a warning, it applies a slight steering torque.

Lane Keeping Assist (LKA): Acts to automatically move the vehicle back into the lane. The car will either apply the brakes on the opposite front wheel or use steering input to make the correction. A driver who simply forgot to use the turn signal can easily overcome this by actively steering the car in the desired direction. In model year 2017, lane departure warning was available on 63% of new U.S. passenger vehicle series equipment (5% as standard and 57% as optional)

Speed Limiter (SL): Limits driving speed to a value set by the driver. When the preset limit is reached, the vehicle gently throttles the speed down. The speed limit is not exceeded even if the driver applies more pressure to the accelerator pedal. Europe will require carmakers to install speed limiters from 2022 in all new cars. Safety campaigners described the move as one of the biggest leaps forward in 50 years and said it could save 25,000 lives by 2037.

Adaptive Cruise Control (ACC): Automatically speeds up and slows down your car to keep a set following distance relative to the car ahead. Provides some limited braking. A radar and cameras read cars in front of you in your lane. Then the car increase or decrease your car’s speed to maintain a following distance that you set. Advanced versions can even slow and stop your car in traffic jams, then accelerate for you.

Pedestrian Detection (PD): can detect pedestrians who walk into the road in front of the car, warn the driver — and automatically apply full braking power if the driver does not respond in time. 6,227 pedestrians were killed on U.S. roads in 2018, the highest number in nearly three decades. In Europe, 14% of all traffic fatalities are pedestrians.

Park Assist: Helps guide you into a parallel parking spot after searching and finding a viable option. It automatically steer the car but doesn’t brake or shift gears.

Other: Surround view, Remote Control Parking, Park Distance Control, Back-up Camera…

If you car still doesn’t have those safety features, there are mobile apps available that provide basic safety warnings: download Wavyn Beta to try Forward Collision Warnings (FCW) and High Speed Warnings (HSW) on you Android phone.

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Trends in Auto Tech (part 1)

I spent the last two months working from Saint Petersburg in Russia where I had the opportunity to engage with a great community of Python and Data Science engineers. I was greatly surprised by the rich social and networking activities they organize in a weekly basis: from conferences, formal talks, and global meetups with a few hundred attendees, to more informal drinkups and breakfast meetups.

This blog post is a summary of my talk about ‘Trends in Auto Tech’ at one of those events. You can find the slides and video at the end.

Problem and emerging solutions

Road traffic crashes are the leading cause of death among 15-29 years old population. Even though we have seen a lot of improvements on safety since the first car was manufactured 100+ years ago, there is still a lot of work ahead to reduce the more than 3,000 current deaths per day.

Recently, more computer power has accelerated the use of artificial neural networks. This has led to software programming getting seriously into the car industry in two forms: 1) Semi-Autonomous Vehicles or Assisted Driver Assistance Systems (ADAS), and 2) Fully Autonomous Vehicles. ADAS are the technologies based on camera and sensors that help the driver in the driving process. An example of this is Tesla Autopilot. The autopilot capability is able to keep the car on the track, break, accelerate and steer the wheel as appropriate, however it requires the driver to be in control all the time in the case is needed. Autonomous is when the car is able to drive without a driver. It’s a full driverless car. This means the largest transition ever in the car industry for both business and adoption perspectives (read 3 Ways To Speed Up The Adoption Of Autonomous Vehicles).

Industry transition

In the past couple of decades, the software development has been disrupting few industries. The Internet, Mobile, and Video Streaming have changed completely retail, banking, telecom, transportation, and entertainment businesses. Customers just love the easy to use, rapidly evolving, consistency and seamless experience across devices.

The car industry has remained vertical in the past, where just car manufacturers and suppliers built the entire end-to-end experience, according to a study from McKinsey. Today, customers demand a more horizontal model with participation from tech companies and third-party creators. They want a car with features that get updated over-the-air every week, that can play a podcast that continues at home, and learns from users habits to reduce the number of interactions. Even car owners with expensive built-in navigation systems, use Google Maps or Waze on their iPhones while driving.

Cars could become soon phones with wheels, and most businesses and use cases around the car would change forever. This will be a great opportunity for startups able to blend software with great customers experience, and for looking-forward car designers to let them use the car’s resources safely.

Investments

Investors are looking into auto tech startups for their ability to use software to improve safety, convenience, and efficiency in cars.

In addition to connected vehicle/driving data, fleet telematics, vehicle-to-vehicle communication, and auto cybersecurity, the more promising area is assisted and autonomous driving. According to CBInsights, investments deals in auto tech private companies already counted for more than $4B in 2017 and keep growing, most of the localized in a few regions.

Some examples of these deals are NuTonomy, a robo-taxi service in Singapore, Drive.ai that creates AI software for autonomous vehicles using deep learning, and FiveAI that build software for urban mobility in public transport.

Stay tuned for the second part of this post to learn more about trends in auto tech technologies and use cases.

Trends in Auto Tech by Rafael Marañón, CEO at Wavyn

[Video] https://youtu.be/DxbSTcPlnQ4

[Slides] https://www.slideshare.net/rmaranon/trends-in-auto-tech

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3 Ways To Speed Up The Adoption Of Autonomous Vehicles

Three-quarters (78%) of Americans are afraid to ride in a self-driving vehicle. According to the survey, they explain that by trusting themselves more than the technology, feeling the new car advances are too new and unproven, that it is also annoying and last, but not the least- not willing to pay extra for it.

How can we transition smoothly to self-driving cars?

Overcome Phycological Challenges

Latest research indicates that ethical dilemmas, overreactions to accidents, and the opacity of the cars’ decision-making algorithms can delay the adoption of self-driving cars. Nobody wants to buy a car that would sacrifice passengers to save pedestrians lives.

The role of media is not always helping as the video of accidents go viral, showing how unreliable can be the new technology.

In order to help, more transparency and familiarity with highly automated car technologies can help customers to change their mental models and build trust. Early adopters would have this as an opportunity to show off responsibility and commitment to reduce total number of road accidents you find out if visit Heninger Garrison Davis for more information. You can test your mental model in the MIT Moral Machine website.

Start with driving assistants

Self-driving cars promise many benefits. However, it will take many years to reach the masses. As today, new car buyers can enjoy from $20K active automobile safety features such as collision avoidance or lane keeping assist. You won’t be able to watch a movie while in a traffic jam, but they will prevent up to 40% of the rear-end car crashes according to a Insurance Institute for Highway Safety (IIHS) report.

Still, only half of car models include those features as standard. Customers have to make the hard decision to add them for at least $1K at the risk of turning them off later if they don’t like. Notice that not everyone is yet comfortable with a car computer controlling the break and steering wheel. And that makes drivers more likely to adopt only-alert type of driving assistance features like forward collision or lane departure warning.

The good news for driver assistance technologies that doesn’t require intervention, is that can also be integrated in old cars. This is a great motivation for software and consumer electronics startups that can now target to a billion car market operating without any type of driving assistant technology.

Excellent Driving Experience (DX)

Noisy driver assistance is a big complain. While useful at the beginning, it become annoying over time, to the point you end up switching it off permanently (an IIHS study found that two-thirds of drivers turned off the lane departure warning). Designers has the challenging job to create enjoable and safety driving experiences in an environment where the number of software features will increasing rapidly.

Like other mobile apps personalize our experience based on our usage, we may expect very soon our car to sense what route I’m taking, if I’m driving sleepy, or with other passengers and set alerts accordingly so it doesn’t bother and keep me aware.

If we want those feature become more a life-saver than annoying ‘turn signal nanny’, as designers we need understand drivers mood and behavior, and provide a balanced flexibility and warnings for the technology to become a trusted buddy driver.

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