The other day I was catching a bus home later at night, which made me acutely aware that I should not take the frequent daytime transit in Vancouver for granted. On the ride home I decided to dig into this and grab some transit data. We have played with transit data before, but since this was going to be the second time it was high time for a quick R package to standardize our efforts and simplify things for the next time around.
Two days ago we took a first look at motor vehicle traffic counts, now it is time to turn to pedestrian lights. Everyone knows the “beg buttons” that pedestrians need to push for the pedestrian signal to turn green. If you forget to push the pedestrian light might stay red even if parallel motor vehicle traffic has a green light, all in the name of efficiency of motor vehicle traffic.
School has started, and with it debate about people driving their kids to and from school is flaring up. And again people are questioning how much traffic is caused by this. As someone who bikes to school with his son every day I am keenly aware of the traffic mess around schools. But since I choose not to drive regularly, I don’t have a feeling for broader traffic patterns on non-school days to compare this too.
I have played with Mapzen’s Isochrone serivce in the past with a simple visualization of walksheds. Recently Mazen updated the isochrone API to allow for a more fine-grained selection of exactly what transit services to include or exclude in transit routing, and they created an amazing mobility explorer based on that. Partially motivated by chatting with two TransLink planners I decided to riff off of that and take a look at how well TransLink serves different parts of Vancouver.
Just saw a comment on the Pricetags blog pointing to a nice master’s thesis investigating various TOD metrics around skytrain stations. I got curious how the 2011 transit mode share compares to the earlier census years listed in the thesis. And how the mode share varies spatially. With CensusMapper at my finger tips and building on the visuals from the previous post this is an easy exercise. We again simply map our concentric circles around the stations, but this time we turn them into pie charts to show the commute to work mode share.