1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
//! An activity model creates "people" that follow a set schedule of activities through the day.
//! Each activity (like shopping, working, sleeping) lasts some time, and requires the person to go
//! somewhere at some time. This is an extremely simple activity model that just uses data inferred
//! from OSM.

use anyhow::Result;
use rand::seq::SliceRandom;
use rand::Rng;
use rand_xorshift::XorShiftRng;

use abstutil::{prettyprint_usize, Parallelism, Timer};
use geom::{Distance, Duration, Time};
use map_model::{BuildingID, BuildingType, Map, PathConstraints, PathRequest};

use crate::make::fork_rng;
use crate::{
    IndividTrip, PersonSpec, Scenario, ScenarioGenerator, TripEndpoint, TripMode, TripPurpose,
};

impl ScenarioGenerator {
    /// Designed in https://github.com/a-b-street/abstreet/issues/154
    pub fn proletariat_robot(map: &Map, rng: &mut XorShiftRng, timer: &mut Timer) -> Scenario {
        let mut residents: Vec<BuildingID> = Vec::new();
        let mut workers: Vec<BuildingID> = Vec::new();

        let mut num_bldg_residential = 0;
        let mut num_bldg_commercial = 0;
        let mut num_bldg_mixed_residential_commercial = 0;
        for b in map.all_buildings() {
            match b.bldg_type {
                BuildingType::Residential { num_residents, .. } => {
                    for _ in 0..num_residents {
                        residents.push(b.id);
                    }
                    num_bldg_residential += 1;
                }
                BuildingType::ResidentialCommercial(resident_cap, worker_cap) => {
                    for _ in 0..resident_cap {
                        residents.push(b.id);
                    }
                    for _ in 0..worker_cap {
                        workers.push(b.id);
                    }
                    num_bldg_mixed_residential_commercial += 1;
                }
                BuildingType::Commercial(worker_cap) => {
                    for _ in 0..worker_cap {
                        workers.push(b.id);
                    }
                    num_bldg_commercial += 1;
                }
                BuildingType::Empty => {}
            }
        }

        residents.shuffle(rng);
        workers.shuffle(rng);

        let mut s = Scenario::empty(map, "random people going to and from work");
        // Include all buses/trains
        s.only_seed_buses = None;

        let residents_cap = residents.len();
        let workers_cap = workers.len();

        // this saturation figure is an arbitrary guess - we assume that the number of trips will
        // scale as some factor of the people living and/or working on the map. A number of more
        // than 1.0 will primarily affect the number of "pass through" trips - people who neither
        // work nor live in the neighborhood.
        let trip_saturation = 1.2;
        let num_trips = (trip_saturation * (residents_cap + workers_cap) as f64) as usize;

        // bound probabilities to ensure we're getting some diversity of agents
        let lower_bound_prob = 0.05;
        let upper_bound_prob = 0.90;
        let prob_local_resident = if workers_cap == 0 {
            lower_bound_prob
        } else {
            f64::min(
                upper_bound_prob,
                f64::max(lower_bound_prob, residents_cap as f64 / num_trips as f64),
            )
        };
        let prob_local_worker = f64::min(
            upper_bound_prob,
            f64::max(lower_bound_prob, workers_cap as f64 / num_trips as f64),
        );

        debug!(
            "BUILDINGS - workplaces: {}, residences: {}, mixed: {}",
            prettyprint_usize(num_bldg_commercial),
            prettyprint_usize(num_bldg_residential),
            prettyprint_usize(num_bldg_mixed_residential_commercial)
        );
        debug!(
            "CAPACITY - workers_cap: {}, residents_cap: {}, prob_local_worker: {:.1}%, \
             prob_local_resident: {:.1}%",
            prettyprint_usize(workers_cap),
            prettyprint_usize(residents_cap),
            prob_local_worker * 100.,
            prob_local_resident * 100.
        );

        let mut num_trips_local = 0;
        let mut num_trips_commuting_in = 0;
        let mut num_trips_commuting_out = 0;
        let mut num_trips_passthru = 0;
        timer.start("create people");

        // Only consider two-way intersections, so the agent can return the same way
        // they came.
        // TODO: instead, if it's not a two-way border, we should find an intersection
        // an incoming border "near" the outgoing border, to allow a broader set of
        // realistic options.
        // TODO: prefer larger thoroughfares to better reflect reality.
        let commuter_borders: Vec<TripEndpoint> = map
            .all_outgoing_borders()
            .into_iter()
            .filter(|b| b.is_incoming_border())
            .map(|b| TripEndpoint::Border(b.id))
            .collect();
        assert!(!commuter_borders.is_empty());
        let person_params = (0..num_trips)
            .map(|_| {
                let (is_local_resident, is_local_worker) = (
                    rng.gen_bool(prob_local_resident),
                    rng.gen_bool(prob_local_worker),
                );
                let home = if is_local_resident {
                    if let Some(residence) = residents.pop() {
                        TripEndpoint::Bldg(residence)
                    } else {
                        *commuter_borders.choose(rng).unwrap()
                    }
                } else {
                    *commuter_borders.choose(rng).unwrap()
                };

                let work = if is_local_worker {
                    if let Some(workplace) = workers.pop() {
                        TripEndpoint::Bldg(workplace)
                    } else {
                        *commuter_borders.choose(rng).unwrap()
                    }
                } else {
                    *commuter_borders.choose(rng).unwrap()
                };

                match (&home, &work) {
                    (TripEndpoint::Bldg(_), TripEndpoint::Bldg(_)) => {
                        num_trips_local += 1;
                    }
                    (TripEndpoint::Bldg(_), TripEndpoint::Border(_)) => {
                        num_trips_commuting_out += 1;
                    }
                    (TripEndpoint::Border(_), TripEndpoint::Bldg(_)) => {
                        num_trips_commuting_in += 1;
                    }
                    (TripEndpoint::Border(_), TripEndpoint::Border(_)) => {
                        num_trips_passthru += 1;
                    }
                    (TripEndpoint::SuddenlyAppear(_), _) => unreachable!(),
                    (_, TripEndpoint::SuddenlyAppear(_)) => unreachable!(),
                };

                (home, work, fork_rng(rng))
            })
            .collect();

        s.people.extend(
            timer
                .parallelize(
                    "create people: making PersonSpec from endpoints",
                    Parallelism::Fastest,
                    person_params,
                    |(home, work, mut rng)| match create_prole(home, work, map, &mut rng) {
                        Ok(person) => Some(person),
                        Err(e) => {
                            trace!("Unable to create person. error: {}", e);
                            None
                        }
                    },
                )
                .into_iter()
                .flatten(),
        );

        timer.stop("create people");

        info!(
            "TRIPS - total: {}, local: {}, commuting_in: {}, commuting_out: {}, passthru: {}, \
             errored: {}, leftover_resident_capacity: {}, leftover_worker_capacity: {}",
            prettyprint_usize(num_trips),
            prettyprint_usize(num_trips_local),
            prettyprint_usize(num_trips_commuting_in),
            prettyprint_usize(num_trips_commuting_out),
            prettyprint_usize(num_trips_passthru),
            prettyprint_usize(num_trips - s.people.len()),
            prettyprint_usize(residents.len()),
            prettyprint_usize(workers.len()),
        );
        s
    }
}

fn create_prole(
    home: TripEndpoint,
    work: TripEndpoint,
    map: &Map,
    rng: &mut XorShiftRng,
) -> Result<PersonSpec> {
    if home == work {
        // TODO: handle edge-case of working and living in the same building...  maybe more likely
        // to go for a walk later in the day or something
        bail!("TODO: handle working and living in the same building");
    }

    let mode = match (&home, &work) {
        // commuting entirely within map
        (TripEndpoint::Bldg(home_bldg), TripEndpoint::Bldg(work_bldg)) => {
            // Decide mode based on walking distance. If the buildings aren't connected,
            // probably a bug in importing; just skip this person.
            let dist = if let Some(path) = PathRequest::between_buildings(
                map,
                *home_bldg,
                *work_bldg,
                PathConstraints::Pedestrian,
            )
            .and_then(|req| map.pathfind(req).ok())
            {
                path.total_length()
            } else {
                bail!("no path found");
            };

            // TODO If home or work is in an access-restricted zone (like a living street),
            // then probably don't drive there. Actually, it depends on the specific tagging;
            // access=no in the US usually means a gated community.
            select_trip_mode(dist, rng)
        }
        // if you exit or leave the map, we assume driving
        _ => TripMode::Drive,
    };

    // TODO This will cause a single morning and afternoon rush. Outside of these times,
    // it'll be really quiet. Probably want a normal distribution centered around these
    // peak times, but with a long tail.
    let mut depart_am = rand_time(
        rng,
        Time::START_OF_DAY + Duration::hours(7),
        Time::START_OF_DAY + Duration::hours(10),
    );
    let mut depart_pm = rand_time(
        rng,
        Time::START_OF_DAY + Duration::hours(17),
        Time::START_OF_DAY + Duration::hours(19),
    );

    if rng.gen_bool(0.1) {
        // hacky hack to get some background traffic
        depart_am = rand_time(
            rng,
            Time::START_OF_DAY + Duration::hours(0),
            Time::START_OF_DAY + Duration::hours(12),
        );
        depart_pm = rand_time(
            rng,
            Time::START_OF_DAY + Duration::hours(12),
            Time::START_OF_DAY + Duration::hours(24),
        );
    }

    Ok(PersonSpec {
        orig_id: None,
        origin: home,
        trips: vec![
            IndividTrip::new(depart_am, TripPurpose::Work, work, mode),
            IndividTrip::new(depart_pm, TripPurpose::Home, home, mode),
        ],
    })
}

fn select_trip_mode(distance: Distance, rng: &mut XorShiftRng) -> TripMode {
    // TODO Make this probabilistic
    // for example probability of walking currently has massive differences
    // at thresholds, it would be nicer to change this gradually
    // TODO - do not select based on distance but select one that is fastest/best in the
    // given situation excellent bus connection / plenty of parking /
    // cycleways / suitable rail connection all strongly influence
    // selected mode of transport, distance is not the sole influence
    // in some cities there may case where driving is only possible method
    // to get somewhere, even at a short distance

    // Always walk for really short trips
    if distance < Distance::miles(0.5) {
        return TripMode::Walk;
    }

    // Sometimes bike or walk for moderate trips
    if distance < Distance::miles(3.0) {
        if rng.gen_bool(0.15) {
            return TripMode::Bike;
        }
        if rng.gen_bool(0.05) {
            return TripMode::Walk;
        }
    }

    // For longer trips, maybe bike for dedicated cyclists
    if rng.gen_bool(0.005) {
        return TripMode::Bike;
    }
    // Try transit if available, or fallback to walking
    if rng.gen_bool(0.3) {
        return TripMode::Transit;
    }

    // Most of the time, just drive
    TripMode::Drive
}

fn rand_time(rng: &mut XorShiftRng, low: Time, high: Time) -> Time {
    assert!(high > low);
    Time::START_OF_DAY + Duration::seconds(rng.gen_range(low.inner_seconds()..high.inner_seconds()))
}