How Edge AI Could Be The Future Of Transportation

People need accurate and relevant information quickly in today’s fast-paced world. Artificial intelligence (AI) tools can often provide it, especially due to advancements in edge AI solutions. Since edge computing enables processing data closer to its source, it facilitates near-real-time responses. The transportation industry relies on giving people prompt, correct information. As people travel to destinations for time-sensitive work obligations, urgent medical care or long-awaited reunions with loved ones, they need dependable details. Here are some fascinating ways that progress in edge AI can make travel safer, more efficient and increasingly pleasant.

Ensuring That E-Scooter Riders Travel Responsibly

Image: Daniel von Appen on Unsplash

E-scooters have recently become extremely popular, and it didn’t take long for people to develop mixed feelings about them. Some people without cars or access to nearby public transportation options rely on these to get around conveniently for reasonable prices. However, many urban residents and workers complained that e-scooter riders caused sidewalk congestion and often carelessly abandoned their scooters in random locations after using them. Spin, a subsidiary of the Ford Motor Company, specializes in e-scooter transportation. It recently partnered with Drover AI, which offers high-tech solutions for last-mile transportation. The collaboration resulted in an edge computing-based system that combines a camera, onboard computing power and a sensor array.

The setup can detect if riders engage in prohibited behavior — such as traveling on the sidewalk, which many cities forbid. It also gives users real-time information by showing them the best routes with the most bike lanes. Such data leads to smoother, law-abiding travel, since cities that allow smart scooter use restrict them to areas for bicycles. Spin is also looking at ways to make scooters a safer way of getting around. Like how many cars alert drivers who move out of their lanes or nearly collide with obstacles, the company intends to use this technology to warn scooter riders who are going the wrong way or need to adjust their speed due to changing conditions.

Improving Vehicle Routing During Congested Periods

Image: Henry Perks on Unsplash

The most readily available methods of monitoring traffic congestion currently involve using GPS cellular data from smartphones. However, this approach falls short because it assumes — sometimes incorrectly — that all data comes from moving cars. German artist Simon Weckert faked a Google Maps traffic jam by placing 100 smartphones in a wagon and pulling it along a planned route. Moreover, the time required to collect, process and analyze such data often means the information is outdated by the time people see it. TidalWave uses a different approach. It’s a joint project from Cubic Transportation Systems’ Trafficware and SWIM.ai.

The product provides traffic location and intersection details with high resolution and accurate live data. TidalWave uses edge AI and machine learning to provide the information less than a second after intersection changes happen. Professionals can then rely on captured intersection and traffic light data to optimize travel routes for drivers. Additionally, TidalWave allows predicting driver behavior. Nine U.S. cities and counties currently use the technology — including Las Vegas, Nev., and Palo Alto, Calif. Transportation officials in more than a dozen others will roll it out soon.

Image: David Preston from Unsplash‌‌

Life often presents people with an overwhelming number of choices, which leads to a problem called analysis paralysis. When people have too much data, they may overanalyze it and never narrow down the options enough to pick one. AI can help by suggesting which selections people will like based on their past actions or what similar users have done. For example, Taco Bell’s 5 million app users got personalized menus after an AI upgrade.

Such personalization could help travelers explore their surroundings in new places, too. Getting engrossed in travel guides can cause information overload. Most people can recall at least a few experiences of learning about must-see attractions only after coming home from their destinations. Welcome is an AI app that builds a personalized itinerary for people before or after they travel somewhere. It uses their reactions to the various options to create a schedule, including attractions other users chose and ones they may like based on their previous feedback. Since the AI features real-time location awareness, it can recommend nearby sights and experiences. The app allows users to select transportation preferences, such as walking or taking a Lyft, too.

Removing the Hassles From Renting a Car or Operating a Rental Business

Image: Coastr

Many people find frustration in the inefficient process of renting a car. They can probably recall instances of sleepily deplaning from a red-eye flight, finding the car rental desks and wearily waiting in line to get details about the available vehicles and go over paperwork.

Coastr is a Scottish company aiming to upend the existing car rental model. It recently announced a contactless rental system that relies partially on AI edge computing. For example, professionals in the rental car sector can see real-time analytics about any vehicle in their fleet, getting details about its battery health, location and need for maintenance.

Additionally, Coastr helps businesses reduce risk. Its real-time, onboard data collection options alert fleet owners to collisions, giving them vital information for making insurance claims. There is also a vehicle immobilization feature for car rental business representatives to activate when suspecting theft or other malicious behavior. The company helps customers with a user-friendly, cloud-based booking system, too. People can log in and select vehicles, then access them without keys. An accompanying app also has biometric capabilities to verify a person’s identity and documentation.

Edge AI Will Keep Improving Transportation

These examples show why edge AI is such a pioneering and beneficial technology for the transportation sector. As more entities adopt the technology or become interested in it, the use cases will grow. Then, everyone who travels for any reason can benefit.

Shannon Flynn is a technology freelancer with over two years in the technology industry. She is the Managing Editor at ReHack.com and has written for sites like TechDayHQ, Finovate, and Innovation & Technology Today. Follow ReHack on Twitter to read more of Shannon's work

Edge AI to Usher in a New Era of Transportation

Ensuring That E-Scooter Riders Travel Responsibly

Improving Vehicle Routing During Congested Periods

Removing the Hassles From Renting a Car or Operating a Rental Business

Edge AI Will Keep Improving Transportation

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