a-b-street / a-b-street/abstreet

Measuring risk exposure of pedestrians on crowded sidewalks

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Beschreibung

Currently, the width of sidewalks doesn't matter at all in the traffic simulation, because pedestrians don't collide with each other: https://a-b-street.github.io/docs/tech/trafficsim/discrete_event/index.html#starting-simple-pedestrians. That was an easy first thing to implement, and it's realistic enough in places without much foot traffic. But there are plenty of places where the volume of pedestrians far exceeds the capacity of the sidewalk. When that happens, people walk slower than they might wish to, and some people will step onto the street temporarily to try to dodge the crowd. In some cities, there are substantial collisions and fatalities as a result. So widening sidewalks is an interesting intervention to consider.

Sidewalks can be widened in A/B Street today. The next step is to model pedestrian behavior on crowded sidewalks better. The really cool thing to do would be consider a social force model, but a more realistic task is to measure "risk exposure" events on crowded sidewalks. Michael and I made these in #600 -- when something potentially risky happens, we record the time, place, and person experiencing it, and then we have existing dataviz to understand patterns (#607, #622).

# Detecting over-crowding events

![pedestrian_ghosts](https://user-images.githubusercontent.com/1664407/154490341-402b5aca-d9d1-4ef4-ae80-8f6ddd5a67de.gif)

When two pedestrians collide like this, let's check the width of the sidewalk, and consider emitting a "overcrowded sidewalk" event. In reality, people might slow down a bit, or maybe step into the street to dodge someone else. It also has a bit of a social distancing / COVID implication (https://www.sidewalkwidths.nyc/#13/40.67924/-73.94357).

I think there's likely an efficient way to detect these events by solving a simple linear equation when people enter/exit a sidewalk lane. Can think about that later.

# How this could be used

*If* we have a decent travel demand model, we can run a simulation, then look for hot-spots in the overcrowdedness risk exposure layer. Then widen sidewalks there, repeat the simulation, and expect to see the problem be reduced.

# Better sidewalk width data

All sidewalks in A/B Street are a fixed width right now, because there's practically never easy data about their width. But sometimes a city has open data with a full vectorized curb -- Seattle, London, Sao Paulo. Ultimately I'd like to use this to properly represent complex 2D space -- https://github.com/dabreegster/dabreegster.github.io/issues/2. But in the short term, we could try to use it to calculate an average sidewalk width and update the A/B Street representation.

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