pith:MPRZQYZX
The Robotaxi Placement Problem: Minimizing Expected ETA for Stochastic Demand
Sampling robotaxi locations from the demand distribution provides a randomized 2-approximation for minimizing expected rider wait times.
arxiv:2605.15745 v1 · 2026-05-15 · cs.DS · cs.CC
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Record completeness
Claims
Sampling robotaxi locations independently according to the demand distribution yields a randomized 2-approximation algorithm for the robotaxi placement problem.
The demand distribution over rider locations is known in advance and can be sampled from independently for each of the k riders (section on randomized algorithm and empirical evaluation).
Introduces the k-robotaxi placement problem on metric spaces, gives a randomized 2-approximation by independent sampling from demand, proves inapproximability via max-coverage reduction, provides exact DP on trees, and shows variance-reduced random placement works well empirically.
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Receipt and verification
| First computed | 2026-05-20T00:01:15.972915Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
63e39863374b54b5ae42028c763254c6e10e5f594d78f5949614c4b724b2b4f8
Aliases
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/MPRZQYZXJNKLLLSCAKGHMMSUY3 \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 63e39863374b54b5ae42028c763254c6e10e5f594d78f5949614c4b724b2b4f8
Canonical record JSON
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