Passenger Transport Systems: planning and operation incorporating behavior and uncertainty – Spring 2024


28 February, 13 March, 27 March, 10 April 2024


10.00 – 16.00 h.




Dr. Rolf van Lieshout and Dr. Yongqiu Zhu




1 (participating only) – 4 (participating + passing the assignment)

Course fee:

Free for TRAIL/Beta/ERIM/OML members, others please contact the TRAIL office


see below


After completing this course, students will be able to:

  • Conceptualize research problems from the area of passenger transportation along the dimension of strategic – tactical – real-time, incorporating traveler behavior and uncertainty in demand and/or supply.
  • Devise and discuss basic principles of different methodological approaches to solving passenger transport related problems, such as graph representation, (robust) optimization, stochastic programming, heuristics, simulation, and reinforcement learning.
  • Motivate modelling choices, position them in relation to alternative approaches and examine their suitability and shortcomings.
  • Develop a research proposal addressing a scientific research problem in the domain of passenger transport systems, incorporating concepts and methods pertaining to behavior and uncertainty.

Course description:

Passenger transport systems are complex systems that undergo significant service, technological, and organizational transformations. This course provides a synthesis of the public transport planning process – from strategic through tactical and operational planning to real-time management and related methodological concepts. For each planning level, the course introduces the relevant practical problems, the traditional approaches of handling the problems, as well as the extensions addressing more realistic factors such as dynamic passenger behavior and uncertainties rising from demand and/or supply. Developments in integrating these problems and approaches will be discussed, as well as the emerging technologies (reinforcement learning) of addressing those problems.


During the course of the course, students will work on their final assignments in groups of 2-3 students. Each group will work on a research problem based on a pre-defined list of potential topics or related to their PhD project, subject to an approval by course leaders. Students will develop a conceptual framework, formulate their problem using a selected approach, discuss their modelling choices and their limitations and provide a proof of concept or small-scale demonstration.


Day 1: Course intro + Line planning: traditional approaches (Rolf, 2hr) + Delay management & Disruption management: traditional approaches + Assignment intro (Yongqiu, 2hr) + Student presentations on PhD projects (Yongqiu + Rolf, 1hr)

Day 2: Line planning: extensions (Rolf, 1.5hr) + Delay management & Disruption management: extensions (Yongqiu, 1.5hr) + Workshop format (students start to work on concept research proposals, Yongqiu + Rolf, 2hr)

Day 3: Timetable design: traditional approaches (Rolf, 1.5hr) + Timetable design: extensions (Yongqiu, 1.5hr)  + Workshop format (students start to work on concept research proposals, Yongqiu + Rolf, 2hr)

Day 4: Integrated planning (Rolf, 1hr) + Reinforcement learning in delay management (Yongqiu, 1hr) + Student presentations of concept research proposal (Yongqiu + Rolf + Expert Panel, 3hr)



Course material:

Relevant review papers:

Desaulniers G. and Hickman M.D. (2007). Chapter 2 Public Transit. Handbooks in Operations Research and Management Science, Vol. 14, pp. 69-127.

Ibarra-Rojas O.J., Delgado F., Giesen R. And Munoz J.C. (2015). Planning, operation, and control  of bus transport systems” A literature review. Transportation Research Part B: Methodological, Vol. 77, pp. 38-75.

Additional reading material will be provided in relation to each lecture/module.


Course Registration form

Member of research school: