AI APU Cyber & AI Original

How Soon Will We Be Moving Around in AI-Enabled Vehicles?

Pinterest LinkedIn Tumblr

Elon Musk, who is working to revolutionize transportation through his Tesla electric car company and the CEO of his rocket-producing SpaceX company, predicts that with advancements in artificial intelligence (AI), vehicles will be fully autonomous in 10 years. The question is, are we ready for this transformative creation both ethically and tactically?

What Is AI?

First, it is important to note that AI is defined as helping machines think and act like humans. Using this definition, AI is already incorporated in vehicles in some fashion. If you’ve used cruise control, GPS, or power steering, all of these technologies incorporate AI self-driving technology using machine learning.

Likewise, AI capabilities go beyond vehicles to include remote-controlled drones, helicopters, and unmanned vehicles. Equipped with navigation systems, AI can enable almost any machine to operate autonomously.

Self-Driving Vehicles Are a Mainstay in the Automobile Industry

AI in vehicles is not new. Self-driving vehicles have been discussed for the past 100 years. There are robotaxis to take you to your destination. Amazon delivers packages using driverless vehicles. AI with machine learning can outthink humans and perform faster and more efficiently in most situations.

Statistics prove that humans make mistakes while driving, engage in poor driving behavior like drinking and driving, text while driving, and make poor decisions. As a result, more than 32,000 deaths and over two million injuries occur each year as a result of motor vehicle crashes.

So while it is true that autonomous vehicles can reduce auto accidents, the shift to such vehicles will take time. For one reason, it takes years to design a vehicle. So incorporating AI will not be an overnight adoption. While there are several companies, like Waymo and Comma AI, that are making advances in AI, mainstream AI incorporation will require adoption by large companies as well as new widespread regulation.

Is Building More Roads the Answer?

The prevailing thought to address vehicular movement in fast-growing emerging cities was to build more roads. But in geographic areas where expansion is not possible, a new plan of action is needed. The Biden administration recently unveiled its infrastructure plan, which goes beyond fixing roads and bridges and updating airports and highways. The plan also includes building a network of electric charging stations, incorporating AI into vehicles and creating a national broadband network.

Five Levels of Automation Defined

There are five levels of automation that contribute to developing a fully autonomous vehicle:

Level 1 — cruise control

Level 2 — partial automation

Level 3 — conditional automation

Level 4 — high automation

Level 5 — full automation

What does Level 5 look like?  In some cases, AI-scheduled commutes will greatly reduce traffic congestion. Imagine receiving an alert to let you know when to start your commute home to maximize vehicle efficiency and to reduce overall commuting times.

In rural areas, drivers of fully equipped AI vehicles can get approval to drive up to 130 mph in emergencies because there are no other vehicles within a 50-mile radius. With internet connectivity in autonomous vehicles, commuters can be more productive by working while traveling to and from the office. AI can improve point-to-point transportation and deliveries. In addition, modern entertainment will make autonomous transportation more enjoyable for passengers.

Creating a Driverless World

What will a driverless world look like? Musk says his fleet of driverless cars can effortlessly navigate through residential streets and superhighways, eliminating the need for a human driver. So-called Sunday (slow) drivers will be a thing of the past as predictable GPS systems will provide accurate speeds and travel times despite slow drivers, construction sites, or road accidents.

However, most companies that are beta-testing autonomous vehicles still require a human behind the wheel to override the system if need be. So it’s important to distinguish between driver assistance vehicles and driverless vehicles.

AI Can Lead to New Ways to Travel

The vast majority of our transportation system involves vehicles. However, AI can create a new form of travel.

For example, Israel’s biggest defense contractor is experimenting with suspended linked magnetic pods to carry passengers, an advanced version of the high-speed monorail or maglev train system that hovers above the ground. The pods can detach, which creates flying vehicles and new HOV lanes in the sky.

Buses can be re-engineered to straddle multiple lanes and ride above traditional vehicles, creating a new elevated lane for mass transportation. Collective and individual at the same time, magnetic pods can rapidly move individuals to their specific destinations.

With AI, large cities and rural communities alike can create 3D transportation networks to alter the flow of traffic. Algorithms will determine traffic flow. During a crisis, they can institute contraflow, an evacuation procedure that promptly resets all traffic to move in one direction and avoid the crisis area.

And while many urban areas have a commuter rail system, interconnected subway systems can create a new way to travel between large cities where surface space is unavailable to lay tracks.

The Ethics of AI in Autonomous Vehicles

Autonomous vehicles pose some ethical considerations. Here are 10 key topics to consider:

  1. If machines can drive cars better than humans, should driving be outlawed?
  2. If commutes are eliminated, should the daily work hours and work week be adjusted?
  3. What changes must legacy automakers make to adjust to AI advances?
  4. Do humans still need to learn how to drive if they are using autonomous vehicles?
  5. Will traditional vehicles be eliminated all together?
  6. How long will it take to fully replace current vehicles with AI-enabled vehicles?
  7. Is there a need for a global oversight body to monitor the shift to autonomous vehicles?
  8. Should AI technology be standardized for all vehicles?
  9. How are maps updated in real time for heavy traffic, construction, and accidents?
  10. How is data shared among vehicles, law enforcement, and state/national official networks?

Real-Time Visual Recognition Is Essential

Autonomous vehicles will require some kind of visual recognition system and installed AI must fully understand its environment to make decisions in real time. In order for a vehicle to be autonomous, despite the ethical considerations, it must know as much about its surroundings in real time as a human driver.

Most companies use Light Detection and Ranging (Lidar), a surveying measure that uses a laser to determine the distance to a target. But Lidar cannot tell the difference between items, such as a cardboard box on the road or a vehicle. Lidar can create 3D maps for both day and night driving; however, it does not work in extreme cold, snow or heavy rain.

In contrast, there are companies that use cameras for environmental awareness because they are low cost and can be installed in a vehicle. Tesla vehicles uses cameras and forward-facing radar to determine its surroundings during daylight hours.

AI proponents agree that self-driving vehicles are safer, more sustainable and faster. AI can improve traditional vehicle movement and free up space for alternative modes of transportation like walking, scooters, and biking.

We will all have to decide how these new vehicles will be used and who is truly in control. For now, both people and vehicles are needed for efficient transportation, and the trend continues toward empowering AI to make human-like decisions.

Dr. Kandis Y. Boyd Wyatt, PMP, is an award-winning author, presenter, and professor with nearly 30 years of experience in science, technology, engineering, arts, and math (STEAM). She is the creator of the Professor S.T.E.A.M. Children’s Book Series, which brings tomorrow’s concepts to future leaders today. A global speaker, STEAM advocate, and STEM communicator, she holds a B.S. in meteorology and an M.S. in meteorology and water resources from Iowa State University, as well as a D.P.A. in public administration from Nova Southeastern University. She is a faculty member in Transportation and Logistics for the Wallace E. Boston School of Business and specializes in artificial intelligence (AI) in transportation, education, and technology.

Comments are closed.