The transportation industry faces problems when a system functionality cannot form per predictable patterns which are affected by external elements like traffic, human errors or accidents.
A.I. uses data to predict decisions appropriately and it has been implemented in a variety of ways where some of examples include
- public safety (e.g. tracking crime data in real time),
- autonomous vehicles (e.g. self-driven vehicles),
- pedestrian safety (e.g. tracking pedestrians/cyclists paths to minimize accidents),
- traffic patterns (e.g. causes of delays, reduction of traffic congestion) and
- corporate decision making (e.g. accurate prediction methods and forecasts).
Benefits of AI in transport:
The best fit of AI and transport somehow came naturally as adoption of these technologies can have a massive impact on the entire industry although the application of AI still varies across geographies.
Increased use of A.I. will ensure reduced labour costs while providing higher profits — fully automated fleets will be there to resolve an issue of long driving hours and breaks.
AI can also have a huge impact on safety and traffic accidents. Driving at night is a great issue and smart unmanned vehicles can significantly improve the problem. Auto-pilots or unmanned vehicles that can operate without a human can help the drivers to snooze without causing any traffic accidents.
Traffic management can also be more effective — AI methods enable us to forecast traffic by using traffic data and details about urban ongoing events as well as suggest alternative routes by automation.
Complex infrastructures and various elements within cooperation chains can be improved with the help of AI through e.g. optimal route schedule, minimal waiting time, traffic detection in real time for adjusting the routes etc.
Data analytics in logistics can also help upgrade transportation planning and increase safety in general.
There are many more benefits to list yet AI is still growing and the benefits will too.
