Researchers shorten waiting time at the bus stop

Monday 13 May 19
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Contact

Evelien van der Hurk
Associate Professor
DTU Management
+45 45 25 48 21

Contact

Allan Larsen
Professor, Deputy Head of Division, Head of Section
DTU Management
+45 45 25 60 73

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About operations analysis

Operations analysis is a mathematical approach to optimizing large and complex systems, and is often used in production and route planning. It is a vital tool used in relation to a wide range of practical and scientific problems.

Operations analysis combines mathematical modelling, heuristic searches, and machine learning. 

Traffic researchers have developed algorithms that optimize timetables and reduce waiting times for public transport.

By Lotte Krull

DTU researchers have developed algorithms that can optimize public transport timetables and reduce waiting times at stops.

Short waiting times are an important factor in how people perceive public transport, according to Evelien van der Hurk, a researcher at DTU Management’s group for traffic modelling and planning in the optimization of public transport.

“We know that passengers experience waiting time as three times longer than if they spend the same time in the bus or train. So it will improve how people experience public transport if waiting time, in particular, can be minimized,” says Evelien van der Hurk. She notes that it is vital for public transport to be perceived as an attractive solution if society wishes to prevent more and more people choosing to drive. More automobiles will mean more pollution and more congestion on roads:

“Public transport has to be part of society’s transport solutions. We need to travel in groups if we want to have a sustainable future and cities that are pleasant to live in.” 

Bus timetables have special potential

Bus timetables, in particular, hold potential that could benefit passengers, the researcher notes:

“Bus routes are not as fixed as train, metro, and light rail traffic, which has to follow the tracks. Busses also carry fewer passengers at a time, so their routes can be more easily adapted to where passengers need to get on and off,” says Evelien van der Hurk.

The algorithms have been developed as part of the Integrated Public Transport Optimization and Planning (IPTOP) project, one of the partners in which is Movia. Movia is represented by Timetable Manager Poul Bayer, who is familiar with the challenges of optimization and minimizing waiting time.

“Optimizing timetables is a complex task, where waiting time is one of the factors. It can no doubt be supported by tools that help the planner make the right choices,” says Poul Bayer.

Finding the best solution

The optimization is being done using operational analysis (see fact box) which requires calculations, analyses, and mathematical models, and large amounts of data on passenger numbers, trip lengths, routes etc.

“Optimization means finding the best solution. But first you have to define what you mean by the ‘best solution’. There is also a budget that has to be met. How much money can you spend? This has both political and user-related elements, which mathematics cannot address,” explains Evelien van der Hurk.

She also notes that the time it takes to find the optimal timetables is an important factor:

“It’s important that the algorithms help to find the solutions quickly. It’s not much use to have an optimal timetable in ten years’ time, if it is based on data on the needs and travel habits of passengers in 2019.”

Dynamic timetables

The algorithms the DTU researchers have developed for timetable optimization can work out a good timetable in just a few hours. This process normally takes weeks or even months. Fast algorithms also make it possible to create dynamic timetables, so that public transport adapts more flexibly to the needs of passengers, special events, and variations in the seasons and weather conditions.

Movia’s timetable manager looks forward to implementing the researchers’ work.

“The results we have seen presented so far look very interesting. We look forward to using the results in an operational form, so that we can benefit from them in our planning and translate our knowledge into better service for customers,” says Poul Bayer.

 

 

 

About the IPTOP project

  • Timetable optimization is part of the IPTOP (Integrated Public Transport Optimization and Planning) research project.
  • DTU is working with MIT, DSB, the Danish Transport Authority, Banedanmark, Movia, Rapidis, Erasmus University Rotterdam, Hong Kong Polytechnic University, and others.
  • IPTOP is being financed by Innovation Fund Denmark
  • The project ends in 2019.

Read more about the IPTOP project