This post originally appeared on Orphan Road.
This quarter I’m taking a travel demand forecasting class. It has been very theory heavy but luckily our final project is hands on. The goal of the project is to reduce emissions, total delays and VMT with a hypothetical city. The catch is that we have to do this with as little money as possible and oh by the way population and employment will increase by 50%.
Well today I slaved away in the dungeon, ie the CEE computer lab for a few hours and I got a good way through the project already. We have the authority to control where growth is located. My strategy was to increase the percent of intra-zonal (ie local trips, which are not loaded onto the regional transportation network) by focusing all growth in three TAZ’s one of which was the CBD. I also tried to balance housing and employment so all of the TAZ’s have a good balance. This included the smaller TAZs as well. These strategies are essentially what smart growth is all about. Put people closer together and close to everything they want.
I haven not made changes to the roadway or transit network yet but as you can see below smart growth principles have cut delay in half (even below current levels) and substantially reduced VMT. Emissions did not go down much because cold starts are the major cause of emissions and I didn’t cut down much on this yet.
Base / New / Change / Change%
Benefit:
VMT= 355242 / 249295/ -105948 / -29.82
Delay= 19010 / 778 / -18232 / -95.91
Emission= 0.85 / 0.81 / -0.04 / -4.58
Also look at the difference of intra-zonal trips and average travel times. This approach reduced the average trip travel time from 12 minutes to 5 minutes. Not to shabby! We’ll see what happens when I get the transit network working. I’ll post again when I complete this project.
Base
Total / Intra / Avg Time
HBW = 122673 / 39.81% / 13.08
HBO = 136416 / 64.48% / 8.04
NHB = 170281 / 66.29% / 14.69
TOT = 429370 / 58.15% / 12.12
New
Total / Intra / Avg Time
HBW = 122673 / 56.73% / 6.96
HBO = 136416 / 70.26% / 4.45
NHB = 170281 / 75.62% / 3.77
TOT = 429370 / 68.52% / 4.90
I show this just as an example. This is a hypothetical example and there were a lot of simplifications that went into the model.
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