AI Is Crucial to the Future of Transportation

Advances in the field are likely to transform vehicles and mass transit

9 April 2018

Even though most cars produced today are not fully autonomous, our cars are becoming smarter all the time by employing sensors that can help stop the vehicle in case of an imminent crash, lane assist to keep the vehicle from veering off course, and backup cameras that alert drivers of nearby obstacles.

Artificial intelligence will play a huge role in our transportation systems—both in public transit and in the cars we own. Here are three ways AI is already affecting transportation.

Improved Urban Design

Urbanization is causing our roads to become increasingly congested, with the average number of people per car in Denver at 1.1, according to a Tech Crunch article. That’s several empty seats for every car‑which means more cars on the road and thus more traffic. If that weren’t bad enough, our environment is also being harmed. The use of private cars is now considered to be responsible for about 73 percent of urban air pollutants.

AI can help cities improve their public transportation systems and can encourage people to share rides. Sensors and cameras placed at intersections can detect traffic patterns and help transit companies devise smarter scheduling for buses and trains. The traffic data also can help them automatically increase toll prices when there’s more traffic on the road and determine where to designate high-occupancy vehicle (HOV) lanes for vehicles carrying two or more people.

Making Decisions on the Fly

New drivers can’t possibly prepare for all the situations they might face on the road. Even veteran drivers are in for a few surprises from time to time.

Fortunately, we are able to respond using our experience and common sense to make split-second decisions, often avoiding disaster. Autonomous vehicles cannot be that reliable without advances in machine learning—but those advances are right around the corner.

Machine learning is the phenomenon of AI to learn without being explicitly programmed for a task. Autonomous vehicles will be able to collect data during their everyday interactions, and learn based on those interactions.

The startup Braiq has designed software that learns a vehicle owner’s preferences over time. If the driver gets nervous when the car gets close to cyclists and pedestrians, for example, the system can adjust to maintain a safer distance.

In the future, an individual’s ride-sharing preference could be stored so that information is shared with an autonomous taxi on its way to pick him up.

Better Communication Between Cars and People

One of the growing pains of the autonomous vehicle industry is facing the fact that people communicate with one another in many different ways on the road. Whether it’s a raised hand, flashed lights, or simple eye contact, we interact with each other behind the wheel more than we might realize. Autonomous vehicles aren’t great at understanding human behavior, however, which can lead to accidents.

AI can help vehicles communicate with drivers and pedestrians during the transitional period, when some humans are still behind the wheel. Drive.ai is one startup that converts existing vehicles into fully autonomous ones, outfitting them with a large display to communicate with people on the road. For example, if the car detects a pedestrian in a crosswalk, its display can illuminate a message when it’s safe to cross.

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