Autonomous Vehicles: Perhaps the most prominent example of AI in transportation, self-driving vehicles leverage AI for object detection, path planning, and decision making. Autonomous vehicles can greatly improve safety and efficiency on the roads.

AI-Based Traffic Management Systems: AI can analyze real-time traffic data to optimize signal timings, manage traffic flow, and reduce congestion. It can also predict traffic conditions and suggest alternative routes to drivers.

Predictive Maintenance for Vehicles: AI can analyze data from various sensors in a vehicle to predict maintenance needs before a breakdown occurs. This can reduce downtime and costs associated with vehicle maintenance.

AI-Powered Logistics and Supply Chain Management: AI can optimize route planning for logistics companies, taking into account factors such as traffic, fuel costs, and delivery times. It can also predict demand and manage inventory in the supply chain.

Autonomous Drones for Delivery: AI can be used to develop autonomous drones for delivery of goods, particularly in hard-to-reach areas. These drones can navigate their environment, avoid obstacles, and ensure safe and efficient delivery.

AI in Railways: AI can improve safety and efficiency in railways. It can predict maintenance needs for tracks and trains, optimize schedules, manage traffic, and improve safety through advanced monitoring and anomaly detection.

AI-Powered Ride-Sharing Platforms: AI plays a critical role in ride-sharing platforms like Uber and Lyft, matching drivers with riders, determining prices based on demand and supply, and optimizing routes.

AI for Maritime Navigation: AI can assist in maritime navigation, predicting weather and sea conditions, optimizing routes, and even assisting in autonomous operation of ships.

AI in Aviation: AI can be used in various aspects of aviation, such as predictive maintenance of aircraft, optimizing routes, managing air traffic, and even assisting in autonomous operation of aircraft.

AI for Public Transportation: AI can enhance public transportation systems, optimizing routes and schedules, predicting maintenance needs for vehicles, and improving passenger information systems.

While AI can greatly enhance the efficiency, safety, and environmental sustainability of transportation, its implementation also involves challenges such as cybersecurity, data privacy, and the need for regulatory frameworks for autonomous vehicles.