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AI Transformation in Transport Industry

AI Transformation in Transport Industry
November 13, 2018

Co-Author: Surojit Neogi

Daily, people move across the city for hours using roads for school, college, business, and other reasons, including work. While moving around, it is preferable to opt for a safe mode of transport. Scientists and researchers have developed Artificial Intelligence (AI) to support transportation in the Manufacturing industry after putting in a lot of effort. In this blog we will focus on the contribution of AI in transport industry.

AI transformation refers to the ability of a machine to use its intelligence to excel in any situation the environment has to offer. This transformation is required for the industry to evolve in order to create superior customer experiences. ADAS (advanced driver-assistance systems) are using artificial intelligence as a key component in emerging autonomous drive platforms. There are many benefits from AI like alerts for bad road condition, detection of objects, detection of pedestrians, etc. based on camera-based vision. This blog post will explain some of the following in brief:

AI transformation refers to the ability of a machine to use its intelligence to excel in any situation the environment has to offer.

  • Vehicle-to-vehicle communication through ad-hoc network
  • AI inside the car for safety
  • Predictive maintenance
  • Traffic management

Vehicle-to-vehicle Communication through Ad-hoc Network

The automation using artificial intelligence is transforming transport within the city. As the communication among machines has developed with the help of IoT, each car will be part of an ad-hoc network and will be able to communicate with the other cars in the same ad-hoc network. This vehicle-to-vehicle communication will offer better safety to the customer as it dynamically calculates precisely the risk involved in applying brakes, as well as the resources available to the vehicle, such as how much amount of gas or battery in case of electric vehicles.

Vehicle-to-vehicle communication will offer better safety to the customer as it dynamically calculates precisely the risk

Ad-hoc Network

Pre-collision technology is another such use case where major manufactures (adopted by Ford and Hyundai) use AI algorithms to identify driver blind spots. The pre-collision system works with a radar system in the front of the vehicle, which emits radio waves to detect obstacles. Based on the data received, there are different ways of alerting the driver, including sounding an alarm. With the data, artificial intelligence also calculates the car’s distance, speed, relative velocity, exerts additional pressure on the braking system to slow down or stop the vehicle.

AI inside the Car for Safety

AI algorithm can now monitor the driver with cameras or sensors. It checks whether the driver’s eyes are open and also the position of his head. Moreover, it can alert the driver if the eyes are not focused on the road. AI ensures the safety of babies by sensing the presence of children in the child care seat. Additionally, it alerts the parents when they leave their children inside the car.

In autonomous ride sharing, AI can detect passenger occupancy along with the seat belt use to ensure the safety of passengers while the vehicle is on the move. At the same time, benefits of AI including alerting passengers on items, such as mobile phones and purses, which have been left behind in the vehicle. AI also has the capability to estimate the size of the airbag that has to be deployed in case of a collision.

Predictive Maintenance

AI can be used to help predict maintenance events and diagnose problems. A mechanic can use the predictive maintenance data from sensors for pinpointing problems. AI can be used to monitor the sensor data and send an alert for preventive maintenance. Preventive maintenance is done when the vehicle is still functioning but may break down (example: overheating of engine).

AI also can be used to detect the problems and malfunction of the software running in the vehicle.

Traffic management

AI will even recognize that a traffic jam ahead will likely cause you to be late for a meeting and offer to send a note about your delay. Machine learning is used to predict and prevent traffic jams. Researchers have been working on traffic management systems that would process complex data in order to advise on the best routes for drivers.

AI will even recognize that a traffic jam ahead will likely cause you to be late for a meeting and offer to send a note about your delay.

Future (One Example): Smart City by Ford

There is a city designed by Ford that accommodates AI-powered cars and trucks. The vehicles will be connected to each other and share the status so that AI can play a key role in preventing collisions and accidents.

Ford

Source:https://media.ford.com/content/fordmedia/fna/us/en/news/2018/01/09/ford-qualcomm.html

References:

https://interestingengineering.com/the-25-ways-ai-can-revolutionize-transportation-from-driverless-trains-to-smart-tracks

https://techcrunch.com/2018/05/24/the-ai-in-your-non-autonomous-car/

https://www.codementor.io/ashish1dev/autonomous-cars-and-artificial-intelligence-ai-adzk2yk4x

https://www.forbes.com/sites/default/files/images/inline-migration/bernardmarr/2017/11/06/the-future-of-the-transport-industry-iot-big-data-ai-and-autonomous-vehicles/#2cce639a1137

https://techcrunch.com/2018/05/24/the-ai-in-your-non-autonomous-car/