AI in Transport: From Smarter Journeys to Self-Driving Vehicles

Transport is already full of AI, and not only in self-driving cars.

• Navigation and traffic prediction: routes that adapt to congestion.
• Public transport planning: timetable and capacity forecasting.
• Ride-hailing and delivery: matching, pricing and routing.
• Fleet management: maintenance prediction and fuel efficiency.
• Smart traffic lights that adjust to flow.
• Parking and charging: finding spaces and chargers.
• Safety features: lane-keeping, collision warning and automatic braking.
• Logistics: warehouse and last-mile optimisation.

Vehicles are described by levels of automation, from basic driver assistance to full autonomy. Fully driverless services operate only in limited areas and conditions, while many consumer cars offer assistance that still requires the driver's attention.

• Rare, unusual situations (the "long tail") are hard to handle.
• Weather and road conditions.
• Liability: who is responsible after a crash?
• Regulation differs by country and city.
• Trust and transparency after incidents.
• Cybersecurity of connected vehicles.
• Jobs and communities affected by automation.

1. Understand what your car's assistance features actually do.
2. Stay alert with driver-assist systems and follow the manufacturer's rules.
3. Keep software updated.
4. Check privacy settings for location and driving data.

AI is already improving safety and efficiency on the roads. Full autonomy is progressing city by city, and human attention still matters for most vehicles today.