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243_018predictionAuto/Transportautonomous

Fleet turnover from human-driven to autonomous will take a very long time due to 10+ year avg car life

Predictor: Dara Khosrowshahi · ep#243 "Uber vs. Tesla, Robotaxi Timelines, and the End of Human Driving | Uber CEO Dara Khosrowshahi | #243" · source

Prior probability
60.0%
Current probability
44.4%
evolves via intake + LBP
Conviction
4/5
Signal quality
C
Resolution
pending
Window
2026-04-30 – 2030-11-30
Edges in / out
3 / 0
Tickers exposed
31

Prediction text

Fleet turnover from human-driven to autonomous will take a very long time due to 10+ year avg car life | there's going to be a huge inventory of existing cars. And the average life of a car in the US is over 10 years. So, it's going to take a very very long time.

Watch events: Waymo 1M rides/wk (end-2026); Tesla Robotaxi scaling; NHTSA AV rules

Verbatim quote

From episode "Uber vs. Tesla, Robotaxi Timelines, and the End of Human Driving | Uber CEO Dara Khosrowshahi | #243"
there's going to be a huge inventory of existing cars. And the average life of a car in the US is over 10 years. So, it's going to take a very very long time.

Predictor: Dara Khosrowshahi

κ + Brier as of 2026-05-22
κ (discount)
0.688
Brier
0.0105
excellent
Hits / Misses
2 / 0
of 3 resolved
Hit rate
66.7%
Calibration plot (stated vs observed)

Evidence about this node from Dara Khosrowshahi is multiplied by κ in /api/intake. Lower κ = less weight; floors at 0.10 (effectively silenced) and caps at 1.00 (full weight).

Reference class

Not linked

This node isn't linked to a reference class. The Bayesian update applies without outside-view blending.

Probability over time

5 prob_history rows
0%25%50%75%100%prior 60%2026-04-302026-05-032026-05-17
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 44.4%

Milestone chain

Pre-event signals (upstream prereqs + window checkpoints) → resolution event → downstream cascades. Status/dates update from linked nodes; re-derive nightly via scripts/ops/derive_milestones.py.
Leading chain: 2 fired ✓ · 5 pending
  1. 2026-03-27hitWaymo reaches 500K paid autonomous rides per week (Q1 2026)
    How: Waymo discloses ≥500,000 paid fully autonomous rides per week across ≥10 US cities
    Source: TechCrunch — Waymo's skyrocketing ridership in one chart (March 27, 2026)conf 99%
    Notes: HIT — but achieved via higher utilization per vehicle, not larger fleet. Confirms Khosrowshahi's slow-fleet-turnover thesis: fleet is ~3K vehicles serving 500K rides/week.
  2. 2026-04-30hitAV fleets reach 10-20% of trips in operating cities
    How: AV fleets account for 10-20% of trips in cities where they operate (SF, Phoenix, LA, Austin)
    Source: Mobisoft Infotech — Future of Ride-Hailing 2026conf 85%
    Notes: HIT — but city-level penetration is local, not national. Confirms 'huge inventory of existing cars' thesis nationally even with high local AV share.
  3. 2026-04-01 → 2026-12-31pendingWaymo fleet remains under 5K vehicles (vs ~250M US registered cars)
    How: Waymo + peer robotaxi total US fleet remains under 5,000 vehicles (vs ~250M registered passenger cars), confirming <0.002% fleet penetration
    Source: carboncredits.com — Waymo Hits 2,500 Robotaxis in US (December 2025: 3,067 vehicles)conf 85%
    Notes: Confirms fleet turnover is slow — the share-of-cars metric is microscopic even if share-of-rides grows fast in covered cities.
  4. 2027-02-13pendingQ1 window check-in (25%)
  5. 2027-11-30pendingQ2 window check-in (50%)
  6. 2028-09-15pendingQ3 window check-in (75%)
  7. 2026-06-01 → 2030-12-31pendingAverage vehicle age in US passenger fleet remains >12 years
    How: S&P Global Mobility / IHS Markit shows average US passenger vehicle age remains ≥12 years through end of decade
    Source: Anticipated — S&P Global Mobility annual reportsconf 85%
    Notes: Direct measurement of Khosrowshahi's '10+ year avg car life' thesis. Average US vehicle age was 12.6 years in 2024, climbing.
  8. 2029-01-01 → 2030-12-31pendingRobotaxi share of US rideshare market reaches ~8% (Goldman target)
    How: Robotaxis capture ~8% of US rideshare TAM with ~$7B annual revenue, per Goldman Sachs framework
    Source: Goldman Sachs robotaxi market model summary via Mobisoft Infotechconf 55%
    Notes: 8% by 2030 still leaves ~92% rideshare market human-driven — supports Khosrowshahi's slow-turnover thesis at the macro level.

What if this resolves?

Clamp this prediction TRUE or FALSE and run a counterfactual Gibbs sample. Surfaces the predictions whose marginals shift most under that assumption.
(live posterior: 44%)

Click a button to clamp this prediction and run a Gibbs sample. Returns the predictions whose marginals shift most. ~30s per run; ideal for stress-testing "if X resolves, what else moves?"

Evidence chain

Every probability update with full Bayesian provenance — chronological, latest first
LBP2026-05-17T02:00:01Z44.4%-1.7pp
Network propagation: 46.2% → 44.4%
5-iter LBP, residual 0.00689 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e607fa96
LBP2026-05-10T02:00:02Z46.2%-3.4pp
Network propagation: 49.6% → 46.2%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z49.6%-6.8pp
Network propagation: 56.4% → 49.6%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z56.4%-1.2pp
Network propagation: 57.6% → 56.4%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z57.6%-2.4pp
Network propagation: 60.0% → 57.6%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef

Network propagation neighbors

Top edges sorted by latest LBP cross-impact
All propagation →

Top incoming (parents)

Edges that influence THIS node's belief

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereqS_ROBOTAXI_MASS_2030
Robotaxi >10% urban miles by Nov 2030
30.0%0.6000.050-0.229
killerTK06
China-Taiwan Military Conflict
8.0%0.0500.600+0.112
killerTK11
Autonomous Regulatory Block (Level 4 Halt)
10.0%0.0500.600+0.101

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Ticker exposure

31 ticker(s) linked

Beneficiaries (24)

INVZWRDLIDRAEVAMBLYPONYOUSTVRRMAMBAAURAIOTHSAIMBGAFBIDUBMWYYGMGOOGLHMCIOTQCOMTMTSLAUBERVWAGY

Adverse (5)

MCYALLCINFPGRTRV

Prerequisites (3)

Predictions that must hit first
TypePredTitleDomainLag
prereqS_ROBOTAXI_MASS_2030Robotaxi >10% urban miles by Nov 2030robotaxi_deployment
killerTK11Autonomous Regulatory Block (Level 4 Halt)
killerTK06China-Taiwan Military Conflict

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "qty": ">10 years",
  "url": "https://www.youtube.com/watch?v=fzKVYNBg50E",
  "mode": "FORECAST",
  "role": "Guest-CEO",
  "context": "there's going to be a huge inventory of existing cars. And the average life of a car in the US is over 10 years. So, it's going to take a very very long time.",
  "verbatim": "there's going to be a huge inventory of existing cars. And the average life of a car in the US is over 10 years. So, it's going to take a very very long time.",
  "conv_cues": "going to take a very very long time",
  "direction": "HAPPEN",
  "timeframe": "Very very long time",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Waymo reaches 500K paid autonomous rides per week (Q1 2026)",
      "notes": "HIT — but achieved via higher utilization per vehicle, not larger fleet. Confirms Khosrowshahi's slow-fleet-turnover thesis: fleet is ~3K vehicles serving 500K rides/week.",
      "source": "TechCrunch — Waymo's skyrocketing ridership in one chart (March 27, 2026)",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -7,
      "source_id": null,
      "confidence": 0.99,
      "source_url": "https://techcrunch.com/2026/03/27/waymo-skyrocketing-ridership-in-one-chart/",
      "expected_date": "2026-03-27",
      "observed_date": "2026-03-27",
      "research_origin": "deep_research",
      "measurement_criterion": "Waymo discloses ≥500,000 paid fully autonomous rides per week across ≥10 US cities"
    },
    {
      "kind": "llm_post_event",
      "label": "AV fleets reach 10-20% of trips in operating cities",
      "notes": "HIT — but city-level penetration is local, not national. Confirms 'huge inventory of existing cars' thesis nationally even with high local AV share.",
      "source": "Mobisoft Infotech — Future of Ride-Hailing 2026",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -6,
      "source_id": null,
      "confidence": 0.85,
      "source_url": "https://mobisoftinfotech.com/resources/blog/future-of-ride-hailing-ai-ev-autonomous-2026",
      "expected_date": "2026-04-30",
      "observed_date": "2026-04-30",
      "research_origin": "deep_research",
      "measurement_criterion": "AV fleets account for 10-20% of trips in cities where they operate (SF, Phoenix, LA, Austin)"
    },
    {
      "kind": "llm_pre_event",
      "label": "Waymo fleet remains under 5K vehicles (vs ~250M US registered cars)",
      "notes": "Confirms fleet turnover is slow — the share-of-cars metric is microscopic even if share-of-rides grows fast in covered cities.",
      "source": "carboncredits.com — Waymo Hits 2,500 Robotaxis in US (December 2025: 3,067 vehicles)",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -5,
      "source_id": null,
      "confidence": 0.85,
      "source_url": "https://carboncredits.com/waymo-hits-2500-robotaxi-in-u-s-the-future-of-driverless-rides/",
      "expected_date": "2026-08-16",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2026-12-31",
        "from": "2026-04-01"
      },
      "measurement_criterion": "Waymo + peer robotaxi total US fleet remains under 5,000 vehicles (vs ~250M registered passenger cars), confirming <0.002% fleet penetration"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -4,
      "source_id": null,
      "expected_date": "2027-02-13",
      "observed_date": null
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -3,
      "source_id": null,
      "expected_date": "2027-11-30",
      "observed_date": null
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -2,
      "source_id": null,
      "expected_date": "2028
... (truncated)