mirror of
https://github.com/a-b-street/abstreet.git
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39f5d50fcd
City names are now disambiguated by a two-letter country code. This commit handles almost everything needed to make this transition. Main next steps are fixing up map edits automatically and making the city picker UI understand the extra level of hierarchy. A little bit of fallout: lakeslice gridlocks again; this regression is actually from the recent traffic signal changes, but I'm just now regenerating everything. Will fix soon.
103 lines
3.6 KiB
Python
Executable File
103 lines
3.6 KiB
Python
Executable File
#!/usr/bin/python3
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# This example runs a scenario, finds roads with high driver throughput, then
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# establishes a per-hour cap.
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#
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# Before running this script, start the API server:
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#
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# > cargo run --release --bin headless -- --port=1234 --alerts=silence
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#
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# You may need to install https://requests.readthedocs.io
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# Keep this script formatted with autopep8 -i
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import abst_helpers
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from abst_helpers import get
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from abst_helpers import post
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import argparse
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import sys
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import time
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument('--api', default='http://localhost:1234')
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parser.add_argument('--country_code', default='us')
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parser.add_argument('--city_name', default='seattle')
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parser.add_argument('--map_name', default='montlake')
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parser.add_argument('--hours', type=int, default=24)
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parser.add_argument('--cap_pct', type=int, default=80)
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parser.add_argument('--rounds', type=int, default=10)
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parser.add_argument('--cap_all_roads', type=bool, default=True)
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args = parser.parse_args()
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print('Simulating {} hours of data/system/{}/{}/scenarios/{}/weekday.bin'.format(
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args.hours, args.country_code, args.city_name, args.map_name))
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baseline = abst_helpers.run_sim(args)
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edits = get(args, '/map/get-edits').json()
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for _ in range(args.rounds):
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print('')
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print('{} roads have a cap'.format(len(edits['commands'])))
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experiment = abst_helpers.run_sim(args, edits=edits)
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baseline.compare(experiment)
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print('{:,} trips changed due to the caps'.format(
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len(experiment.capped_trips)))
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if args.cap_all_roads:
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edits['commands'] = cap_all_roads(args)
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# Individual cap per road; don't merge adjacent roads that happen to have the same cap.
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edits['merge_zones'] = False
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else:
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# Cap the busiest road
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busiest_road, thruput = find_busiest_road(args)
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cmd = get(args, '/map/get-edit-road-command',
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params={'id': busiest_road}).json()
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cmd['ChangeRoad']['new']['access_restrictions']['cap_vehicles_per_hour'] = int(
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(args.cap_pct / 100.0) * thruput)
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edits['commands'].append(cmd)
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# Write the final edits
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f = open('cap_edits.json', 'w')
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f.write(get(args, '/map/get-edits').text)
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f.close()
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# Find the road with the most car traffic in any one hour period
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def find_busiest_road(args):
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thruput = get(
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args, '/data/get-road-thruput').json()['counts']
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max_key = None
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max_value = 0
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for r, agent, hr, count in thruput:
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if agent == 'Car':
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if count > max_value:
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max_key = (r, hr)
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max_value = count
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print('Busiest road is #{}, with {} cars crossing during hour {}'.format(
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max_key[0], max_value, max_key[1]))
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return (max_key[0], max_value)
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# Cap all roads to some percent of their max throughput over any one hour period
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def cap_all_roads(args):
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thruput = get(
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args, '/data/get-road-thruput').json()['counts']
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max_per_road = {}
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for r, agent, hr, count in thruput:
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if agent == 'Car':
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if r not in max_per_road or count > max_per_road[r]:
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max_per_road[r] = count
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commands = []
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for r, count in max_per_road.items():
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cap = int((args.cap_pct / 100.0) * count)
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# Don't go too low
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if cap > 10:
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cmd = get(args, '/map/get-edit-road-command',
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params={'id': r}).json()
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cmd['ChangeRoad']['new']['access_restrictions']['cap_vehicles_per_hour'] = cap
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commands.append(cmd)
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return commands
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if __name__ == '__main__':
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main()
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