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<ol class="chapter"><li class="chapter-item expanded "><a href="../index.html"><strong aria-hidden="true">1.</strong> Overview</a></li><li class="chapter-item expanded "><a href="../howto/index.html"><strong aria-hidden="true">2.</strong> Instructions</a></li><li><ol class="section"><li class="chapter-item expanded "><a href="../howto/map_parking.html"><strong aria-hidden="true">2.1.</strong> How to map on-street parking</a></li><li class="chapter-item expanded "><a href="../howto/new_city.html"><strong aria-hidden="true">2.2.</strong> Importing a new city</a></li></ol></li><li class="chapter-item expanded "><a href="../how_it_works.html"><strong aria-hidden="true">3.</strong> How it works</a></li><li class="chapter-item expanded "><a href="../case_studies/index.html"><strong aria-hidden="true">4.</strong> Case studies</a></li><li><ol class="section"><li class="chapter-item expanded "><a href="../case_studies/lake_wash.html"><strong aria-hidden="true">4.1.</strong> Lake Washington Blvd Stay Healthy Street</a></li><li class="chapter-item expanded "><a href="../case_studies/west_seattle.html"><strong aria-hidden="true">4.2.</strong> West Seattle mitigations</a></li><li class="spacer"></li></ol></li><li class="chapter-item expanded "><a href="../dev/index.html"><strong aria-hidden="true">5.</strong> Developer guide</a></li><li><ol class="section"><li class="chapter-item expanded "><a href="../dev/misc_tricks.html"><strong aria-hidden="true">5.1.</strong> Misc developer tricks</a></li><li class="chapter-item expanded "><a href="../dev/api.html"><strong aria-hidden="true">5.2.</strong> API</a></li><li class="chapter-item expanded "><a href="../dev/testing.html"><strong aria-hidden="true">5.3.</strong> Testing</a></li><li class="chapter-item expanded "><a href="../dev/mass_import.html"><strong aria-hidden="true">5.4.</strong> Importing many maps</a></li><li class="chapter-item expanded "><a href="../dev/data.html"><strong aria-hidden="true">5.5.</strong> Data organization</a></li></ol></li><li class="chapter-item expanded "><a href="../map/index.html"><strong aria-hidden="true">6.</strong> Map model</a></li><li><ol class="section"><li class="chapter-item expanded "><a href="../map/details.html"><strong aria-hidden="true">6.1.</strong> Details</a></li><li class="chapter-item expanded "><a href="../map/importing/index.html"><strong aria-hidden="true">6.2.</strong> Importing</a></li><li><ol class="section"><li class="chapter-item expanded "><a href="../map/importing/convert_osm.html"><strong aria-hidden="true">6.2.1.</strong> convert_osm</a></li><li class="chapter-item expanded "><a href="../map/importing/geometry.html"><strong aria-hidden="true">6.2.2.</strong> Road/intersection geometry</a></li><li class="chapter-item expanded "><a href="../map/importing/rest.html"><strong aria-hidden="true">6.2.3.</strong> The rest</a></li><li class="chapter-item expanded "><a href="../map/importing/misc.html"><strong aria-hidden="true">6.2.4.</strong> Misc</a></li></ol></li><li class="chapter-item expanded "><a href="../map/edits.html"><strong aria-hidden="true">6.3.</strong> Live edits</a></li><li class="chapter-item expanded "><a href="../map/platform.html"><strong aria-hidden="true">6.4.</strong> Exporting</a></li></ol></li><li class="chapter-item expanded "><a href="../trafficsim/index.html"><strong aria-hidden="true">7.</strong> Traffic simulation</a></li><li><ol class="section"><li class="chapter-item expanded "><a href="../trafficsim/discrete_event.html" class="active"><strong aria-hidden="true">7.1.</strong> Discrete event simulation</a></li><li class="chapter-item expanded "><a href="../trafficsim/travel_demand.html"><strong aria-hidden="true">7.2.</strong> Travel demand</a></li><li class="chapter-item expanded "><a href="../trafficsim/gridlock.html"><strong aria-hidden="true">7.3.</strong> Gridlock</a></li><li class="chapter-item expanded "><a href="../trafficsim/trips.html"><strong aria-hidden="true">7.4.</strong> Multi-modal trips</a></li><li class="chapter-item expanded "><a href="../trafficsim/live_edits.html"><strong aria-hidden="true">7.5.</strong> Live edits</a></li><li class="chapter-item expanded "><a href="../trafficsim/parking.html"><strong aria-hidden="true">7.6.</strong> Parking</a></li><li class="spacer"></li></ol></li><li class="chapter-item expanded "><a href="../project/index.html"><strong aria-hidden="true">8.</strong> Project</a></li><li><ol class="section"><li class="chapter-item expanded "><a href="../project/roadmap.html"><strong aria-hidden="true">8.1.</strong> Roadmap</a></li><li class="chapter-item expanded "><a href="../project/motivations.html"><strong aria-hidden="true">8.2.</strong> Motivations</a></li><li class="chapter-item expanded "><a href="../project/history/index.html"><strong aria-hidden="true">8.3.</strong> History</a></li><li><ol class="section"><li class="chapter-item expanded "><a href="../project/history/backstory.html"><strong aria-hidden="true">8.3.1.</strong> Backstory</a></li><li class="chapter-item expanded "><a href="../project/history/year1.html"><strong aria-hidden="true">8.3.2.</strong> Year 1</a></li><li class="chapter-item expanded "><a href="../project/history/year2.html"><strong aria-hidden="true">8.3.3.</strong> Year 2</a></li><li class="chapter-item expanded "><a href="../project/history/year3.html"><strong aria-hidden="true">8.3.4.</strong> Year 3</a></li></ol></li><li class="chapter-item expanded "><a href="../project/CHANGELOG.html"><strong aria-hidden="true">8.4.</strong> Full CHANGELOG</a></li><li class="chapter-item expanded "><a href="../project/references.html"><strong aria-hidden="true">8.5.</strong> References</a></li><li class="chapter-item expanded "><a href="../project/collaborations.html"><strong aria-hidden="true">8.6.</strong> Collaborations</a></li></ol></li></ol>
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<h1 class="menu-title">A/B Street</h1>
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<h1><a class="header" href="#discrete-event-simulation" id="discrete-event-simulation">Discrete-event simulation</a></h1>
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<p>The traffic simulation models different agents (cars, bikes, buses, pedestrians,
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and intersections) over time. Agents don't constantly sense and react to the
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world every second; instead, they remain in some state until something
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interesting happens. This is a discrete-event architecture -- events are
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scheduled for some time in the future, and handling them changes the state of
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some agents. The core simulation loop simply processes events in order -- see
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<code>scheduler.rs</code> and the <code>step</code> method in <code>sim.rs</code>.</p>
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<h2><a class="header" href="#cars" id="cars">Cars</a></h2>
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<p>(Note: Cars, bikes, and buses are all modeled the same way -- bikes just have a
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max speed, and buses/bikes can use restricted lanes.)</p>
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<p>Cars move through a sequence of lanes and turns (movements through an
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intersection). They queue and can't over-take a slow lead vehicle. The main
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simplifying assumption in A/B Street is that cars can instantly accelerate and
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decelerate. This wouldn't model highway driving at all, where things like jam
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waves are important, but it's reasonable for in-city driving. The essence of
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scarcity is the capacity on lanes and the contention at intersections. What
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happens in between isn't vital to get exactly right.</p>
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<p>A car has a few states (<code>mechanics/car.rs</code>):</p>
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<ul>
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<li><strong>Crossing</strong> some distance of a lane/turn over some time interval</li>
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<li><strong>Queued</strong> behind another car on a lane/turn</li>
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<li><strong>WaitingToAdvance</strong> at the end of a lane, blocked on an intersection</li>
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<li>A few states where the car stays in one place: <strong>Parking</strong>, <strong>Unparking</strong>, and
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<strong>Idling</strong> (for buses at a stop)</li>
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</ul>
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<p>State transitions happen in <code>mechanics/driving.rs</code>. This is best explained by an
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example sequence:</p>
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<ul>
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<li>A car enters the Unparking state, taking a fixed 30s to exit a parking spot
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and enter the adjacent driving lane. The driving lane is blocked during this
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time, to mimic somebody pulling out from a parallel parking spot.</li>
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<li>The car is now fully somewhere on the driving lane. It enters the Crossing
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state, covering the remaining distance to the end of the road. The time
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interval is calculated assuming the car travels at the max speed limit of the
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road.</li>
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<li>After that time, the car checks if there's anybody in the queue before it.
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Nope? Then it attempts to initiate a turn through the intersection, but the
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stop sign says no, so the car enters the WaitingToAdvance state.</li>
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<li>Some time later, the stop sign wakes up the car. The car starts the turn,
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entering the Crossing state again.</li>
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<li>After finishing the turn, the car starts Crossing the next lane. When it's
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finished, it turns out there are a few cars ahead of it, so it enters the
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Queued state.</li>
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<li>When the lead vehicle directly in front of the car exits the lane, it wakes up
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the car, putting it in the Crossing state, starting at the appropriate
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following distance behind the lead vehicle. This prevents the car from
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immediately warping to the end of the lane when the lead vehicle is out of the
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way.</li>
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<li>And so on...</li>
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</ul>
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<h3><a class="header" href="#exact-positions" id="exact-positions">Exact positions</a></h3>
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<p>For a discrete-event simulation, we don't usually care exactly where on a lane a
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car is at some time. But we do need to know for drawing and for a few cases
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during simulation, such as determining when a bus is lined up with a bus stop in
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the middle of a lane. <code>mechanics/queue.rs</code> handles this, computing the distance
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of every car in a lane. For cars in the <code>Crossing</code> state, we linearly
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interpolate distance based on the current time. Of course, cars have to remain
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in order, so Queued cars are limited by the lead vehicle's position + the lead
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vehicle's length + a fixed following distance of 1m.</p>
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<p>Another case where we need to know exact positions of cars is to prevent the
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first vehicle on a lane from hitting the back of a car who just left the lane.
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All vehicles have length, and position is tracked by the front of the car. When
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a car's front leaves a lane, its back is still partly in the lane. Logically,
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the new lead car in the lane still needs to act like it's Queued. So each lane
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keeps a "laggy head", pointing to the car with its back partly in the lane.
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After the laggy head has made it sufficient distance along its new turn or lane,
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the laggy head on the old lane can be erased, unblocking the lead vehicle. This
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requires calculating exact distances and some occasionally expensive cases where
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we have to schedule frequent events to check when a laggy head is clear.</p>
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<h2><a class="header" href="#lane-changing" id="lane-changing">Lane-changing</a></h2>
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<p>Lane-changing (LCing) deserves special mention. A/B Street cheats by not
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allowing it on lanes themselves. Instead, at intersections, cars can perform
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turns that shift them over any number of lanes. These LCing turns conflict with
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other turns appropriately, so the contention is still modeled. Why do it this
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way? In a
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<a href="http://apps.cs.utexas.edu/tech_reports/reports/tr/TR-2157.pdf">previous project</a>,
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I tried opportunistic LCing. If a car had room to warp to the equivalent
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distance on the adjacent lane without causing a crash, it would start LCing,
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then take a fixed time to slide over, blocking both lanes throughout. This meant
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cars often failed to LC when they needed to, forcing them to reroute, botching
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their trip times. In many cases the cars would be permanently stuck, because
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pathfinding would return paths requiring LCing that couldn't be pulled off in
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practice due to really short roads. Why not try making the car slow down if
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needed? Eventually it might have to stop, which could lead to unrealistic
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gridlock. This LCing model was using a detailed discrete-time model with cars
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accelerating properly; maybe it's easier with A/B Street's simplified movement
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model.</p>
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<p>Currently in A/B Street, cars will pick the least backed-up lane when there's a
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choice. They make this decision once when they reach the front of a queue; look
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for <code>opportunistically_lanechange</code> in <code>router.rs</code>. The decision could be
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improved.</p>
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<h2><a class="header" href="#pedestrians" id="pedestrians">Pedestrians</a></h2>
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<p>Pedestrian modeling -- in <code>mechanics/walking.rs</code> is way simpler. Pedestrians
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don't need to queue on sidewalks; they can "ghost" through each other. In
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Seattle, there aren't huge crowds of people walking and slowing down, except for
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niche cases like Pike Place Market. So in A/B Street, the only scarce resource
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modeled is the time spent waiting to cross intersections.</p>
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<h2><a class="header" href="#intersections" id="intersections">Intersections</a></h2>
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<p>I need to flesh this section out. See <code>mechanics/intersections.rs</code> for how stop
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signs and traffic signals work. Two things I need to fix before making this
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section interesting:</p>
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<ul>
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<li>Only wake up relevant agents when a previous agent finishes a turn.</li>
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<li>Don't let an agent start a low-priority turn (like an unprotected left) if
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it'll force a high-priority vehicle approaching to wait. The approaching
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vehicle is still in the Crossing state, so we need to notify intersections
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ahead of time of intended turns and an ETA.</li>
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</ul>
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<p>One contributor to permanent gridlock is cars and bikes being stuck in an
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intersection, preventing conflicting turns from being performed. To help avoid
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this, one of the last checks that stop signs and traffic signals perform before
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accepting a new turn request is that the target lane has enough space for the
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new vehicle. This is "reserved" space, not necessarily currently occupied by
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vehicles in that lane. This accounts for other vehicles performing a turn bound
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for that lane. See <code>try_to_reserve_entry</code> in <code>mechanics/queue.rs</code>. When a car
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completely leaves a lane (determined by the "laggy head" described above), this
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space is freed, and blocked cars are woken up.</p>
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<h2><a class="header" href="#appendix-discrete-time-simulation" id="appendix-discrete-time-simulation">Appendix: discrete-time simulation</a></h2>
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<p>A/B Street's first traffic model was discrete-time, meaning that every agent
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reacted to the world every 0.1s. Cars had a more realistic kinematics model,
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accelerating to change speed and gradually come to a halt. Cars did a worst-case
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estimation of how far ahead they need to lookahead in order to satisfy different
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constraints:</p>
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<ul>
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<li>Don't exceed any speed limits</li>
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<li>Don't hit the lead vehicle (which might suddenly slam on its brakes)</li>
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<li>Stop at the end of a lane, unless the intersection says to go</li>
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</ul>
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<p>After fighting with this approach for a long time, I eventually scrapped it in
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favor of the simpler discrete-event model because:</p>
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<ul>
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<li>It's fundamentally slow; there's lots of busy work where cars in freeflow with
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nothing blocking them or stopped in a long queue constantly check to see if
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anything has changed.</li>
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<li>Figuring out the acceleration to apply for the next 0.1s in order to satisfy
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all of the constraints is really complicated. Floating point inaccuracies
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cause ugly edge cases with speeds that wind up slightly negative and with cars
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coming to a complete stop slightly past the end of a lane. I wound up storing
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the "intent" of an action to auto-correct these errors.</li>
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<li>The realism of having cars accelerate smoothly didn't add value to the core
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idea in A/B Street, which is to model points of contention like parking
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capacity and intersections. (This is the same reason why I don't model bike
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racks for parking bikes -- in Seattle, it's never hard to find something to
|
|
lock to -- this would be very different if Copenhagen was the target.)
|
|
Additionally, the kinematics model made silly assumptions about driving anyway
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|
-- cars would smash on their accelerators and brakes as hard as possible
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within all of the constraints.</li>
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