‘Matrix signs, rush-hour lanes and regulated slip roads more effective than anticipated’

News - 24 May 2016

Solutions to reduce traffic jams often involve more asphalt and tolls, while less attention is paid in public debate to measures such as matrix signs, rush-hour lanes and regulated entry on slip roads. Yet these measures may have more impact than first anticipated. As suggested by improved models which take account of unpredictable factors such as weather and fluctuating traffic flow. On Thursday 26 May, Simeon Calvert will be awarded his PhD at TU Delft for his work on the subject.

Traffic is constantly changing

Many drivers will recognise the phenomenon: one day traffic seems fine and the next day you wonder where all those extra cars have come from. Unpredictable elements in traffic may be influenced by the weather, or by incidents, or road works, and sometimes there’s no obvious reason. Moreover, each driver has a different way of driving: some stick close to the bumper ahead; others like to keep enough distance for an invisible truck. These unpredictable elements and fluctuations in traffic flows impact on traffic and queue formation.

Traffic management

Traffic management focuses on better use of road capacity to enable traffic to flow more smoothly. Matrix signs, rush-hour lanes, regulated slip roads and traffic information, for example. The effectiveness of these measures in cutting journey times may be affected by unpredictable elements and fluctuations.

To be able to assess the effectiveness of traffic management measures, Simeon Calvert developed models to improve journey time prediction. Instead of assessing journey times based on averages, such as the average traffic volume in a particular month, Calvert calculated on the basis of actual traffic volume and factors that might influence traffic flow.

More accurate

This improved method appeared to make traffic management more efficient. Calvert: “The old models used for predicting journey times underestimated positive outcomes. The calculations took no account of factors that might influence traffic flow. Taking these aspects into account when predicting journey times leads to more accurate predictions.”

Calvert investigated the effect of certain measures, such as regulated entry from slip roads, to improve traffic flow on the A20 motorway near Rotterdam. His models predicted that these measures would reduce traffic delays by thousands of hours.


These insights and methods can help Dutch traffic management authorities and other road users to offer better recommendations to reduce traffic problems. Calvert: “Building more infrastructure remains an option, but it is expensive and may have negative side effects, for example, it may attract even more traffic. I believe that we should start by looking at traffic management before resorting to more asphalt.”

More information
S.C. Calvert presents his doctoral thesis on Stochastic Macroscopic Analysis and Modelling for Traffic Management on 26 May 2016, at 09:30, TU Delft Aula
Contact: Simeon Calvert, +31 88-866 3314, s.c.calvert@tudelft.nl or simeon.calvert@tno.nl
Wendy Dallinga, Science Communication Adviser, +31 6-42572041, w.m.dallinga@tudelft.nl