AI in Transportation and Smart Mobility Training Course

Course overview

Transportation produces enormous streams of data: vehicle telematics, traffic sensors, ticketing, GPS traces, and demand signals. Artificial intelligence is what turns that data into routing decisions, congestion forecasts, predictive maintenance, and the perception systems behind automated driving. The result is a shift in how cities and operators move people and goods.

This course explains where AI genuinely adds value across transportation and smart mobility, and where its limits and risks lie. It covers AI in logistics and fleets, traffic prediction and congestion management, autonomous and connected vehicles, and the strategy that ties technology to sustainable mobility goals. It is built for professionals who need to understand and plan for these technologies rather than to code them.

Why this matters

Congestion, emissions, and rising demand are pressing on transport systems that cannot simply be built bigger. AI offers a way to get more from existing networks through better prediction, routing, and coordination, and it underpins the longer shift toward automated and connected vehicles.

Understanding these technologies matters because the decisions being made now, about data, infrastructure, and procurement, will shape mobility for decades. Professionals who grasp what AI can and cannot do can plan soundly and avoid both hype and missed opportunity. This course builds that judgment.

What you will be able to do afterwards

By the end of the course, participants should be able to:

• Explain how AI is applied across transportation and mobility.
• Describe AI use in fleet, logistics, and route optimization.
• Outline how traffic prediction and congestion management work.
• Discuss autonomous and connected vehicles and their constraints.
• Contribute to a sustainable smart-mobility strategy.

Course outline

Unit 1: AI and the future of transportation

The course opens with the landscape and what AI changes.

• Where AI fits across the transport system.
• The data that powers transport AI.
• Machine learning concepts in plain terms.
• Opportunities, limits, and realistic expectations.

Unit 2: AI for logistics and fleet optimization

This unit covers moving goods and managing vehicles.

• Route optimization and dynamic dispatch.
• Predictive maintenance from vehicle telematics.
• Demand forecasting for fleets and deliveries.
• Documented examples of AI in logistics.

Unit 3: Traffic prediction and congestion management

This unit covers keeping networks moving.

• Predicting traffic flow from sensor and probe data.
• Adaptive signal control and demand management.
• Incident detection and response.
• Integrating public transport and multimodal data.

Unit 4: Autonomous and connected vehicles

This unit covers the technology behind automated driving.

• Levels of vehicle automation and what each means.
• Perception, sensors, and decision systems.
• Vehicle-to-everything connectivity.
• Safety, liability, and regulatory questions.

Unit 5: Building sustainable smart-mobility strategies

The final unit ties technology to outcomes.

• Linking AI deployment to mobility and climate goals.
• Data governance, privacy, and ethics in mobility.
• Procurement and integration with existing systems.
• Building a realistic smart-mobility roadmap.

How the course is delivered

The course is led through structured explanation, documented case studies, and group discussion of how these technologies perform in practice. Participants examine real deployments, their results, and their limits, and work through the planning and governance questions they raise. It connects naturally to Designing and Implementing Smart Transportation Strategies for those focused on the planning side.

Who should attend

This course suits transport and mobility planners, fleet and logistics managers, city and infrastructure professionals, and technology and innovation staff in the transport sector. It works for those new to AI in transport and for experienced professionals who want a clearer, more critical view of what these tools deliver. A technical background is helpful but not required.

About EuroQuest International Training

EuroQuest International Training was founded in 2015 by a team with more than 25 years of combined experience in professional training. The institute has delivered over 1,000 courses to more than 15,000 participants, and is headquartered in Bratislava, Slovakia, with training hubs in Dubai, London, Barcelona, Istanbul, Vienna, Paris, and Geneva. Courses are designed and reviewed by practitioners and updated to reflect current practice in each field.

Frequently asked questions

Do I need a programming background to attend?

No. The course explains AI concepts in plain terms and focuses on application, planning, and governance rather than coding, so it suits planners, managers, and policy staff.

Does it cover self-driving cars?

Yes. A full unit covers autonomous and connected vehicles, including the levels of automation, the technology involved, and the safety and regulatory questions that remain open.

Is the focus on cities or on freight?

Both. The course covers urban traffic and public mobility alongside logistics and fleet optimization, since AI techniques and data challenges overlap across the two.

Related courses

• Fleet Management Optimization in Ground Transport
• The Future of Smart Transportation and Logistics Innovation
• AI Applications in Logistics Planning and Optimization
• Transportation Safety and Risk Prevention

Register for this course

To reserve a place or ask about scheduling and city options for the AI in Transportation and Smart Mobility course, use the registration and enquiry options on this page and the EuroQuest team will follow up with the details you need.