Tag Archives: Traffic Modelling

Melbourne Railway network map

Faster Trains by Skipping and Closing Stations

As Melbournes train lines increase their frequency to keep up with demand the passengers certainly appreciate the shorter waiting time and less crowding, but could we do even better? Although a few years old the train station patronage data from PTV allows some insights into how passengers as getting to the stations and from that we can estimate what effect station closures or timetable changes might have on the network. Continue reading Faster Trains by Skipping and Closing Stations

cars, pedestrians, bicycles, all mingling in street

Pedestrian Crossings another win for Motorised Transport

A good question from the crowd is always worth investigation and one that didn’t have an answer immediately to hand was: how much is traffic slowed by a pedestrian crossing? So here is a quick set of numbers for an example crossing comparing the typical treatments to each other. Continue reading Pedestrian Crossings another win for Motorised Transport

intersection of Hardware Lane with Bourke Street

Unbundling for Walking

Armed with a model of vehicle interaction rates and the relative risk they present to each other it is possible to explore how shifting transport between modes would impact safety. Here we turn a focus on pedestrians and the impacts improvements in safety or segregation would have. Continue reading Unbundling for Walking

bicycle route sign

Unbundling for Cycling

The question was posed, how much mode share would non motorised transport need before we see an overall reduction in the road toll? With non motorised transport currently more dangerous per distance travelled than motorised transport any small shifts away from cars to bicycles or walking would result in an increase in the road toll, how can it be made safer? Continue reading Unbundling for Cycling

complicated looking equation

Unhiding Unbundling

From the previous look at fatality rates a simple linear model shows that increasing use of transport modes that pose the least threat to others (namely walking and cycling) would increase the total road toll as they as so vulnerable to the disproportionately dangerous motorised modes. The limitations of a first order model make it fail to predict the obvious extremely low road toll if all motorised traffic were to be eliminated and only non motorised modes remained. Thus a second order model that includes the relative rates of modes interactions on each other is needed and presented here. Continue reading Unhiding Unbundling

taxis ignoring all road markings

Detector Perception

Continue reading Detector Perception


Cyclists clog the streets

Continue reading Cyclists clog the streets

car broken down on highway

How not to Merge

Continue reading How not to Merge


Hiding in the Gap

Continue reading Hiding in the Gap


Speed Step

Continue reading Speed Step