Limitpedsasi -

| Feature | Complete Streets | Limitpedsasi | |--------|----------------|---------------| | Approach | Idealistic, long-term | Pragmatic, incremental | | Budget | High | Low to medium | | Time to implement | Years | Weeks | | Main focus | All users equally | Pedestrians first, within constraints | | Adaptability | Low | High |

Limitpedsasi is not meant to replace Complete Streets but to complement it in cash-strapped or space-limited environments. limitpedsasi

The idea of "limiting" pedestrians seems counterintuitive in a walkable city. However, the Limitpedsasi approach is necessary for three primary reasons: Documentation, examples, benchmarks, CI, packaging

As AI and real-time traffic management mature, limitpedsasi could become fully automated. Imagine smart curbs that physically widen or narrow based on pedestrian density sensors. Or dynamic speed limits that drop automatically when more than five people are waiting to cross. sim = PedsSim.from_yaml("mall_scenario.yml"

Even without high tech, the philosophy of working creatively within limits will grow more relevant as cities face climate budgets, aging infrastructure, and rising pedestrian deaths.

During parades, marathons, or emergencies, sidewalks become congested. To prevent "pedestrian lock-up" (where density stops movement), authorities must limit entry to specific sidewalk segments.

let limiter = Limit::token_bucket(100, 10.0); // capacity 100, 10 tokens/sec
let permit = limiter.acquire(1).await?;
spawn(async move 
  let _p = permit; // holds permit until dropped
  // do work
);

lim = Limit.token_bucket(10, refill=1.0)
async with lim.acquire(1, timeout=5):
    await do_request()

sim = PedsSim.from_yaml("mall_scenario.yml", deterministic=True, seed=42)
sim.run(steps=10000)
sim.export_trajectory("out.json")