Model controls

Assumptions

Monte Carlo drawsEnd yearNetwork participation shareHours per dayMiles per hourPrice per mile USDPlatform fee share

Advanced model inputs

Occupancy shareCar lifespan years

Full notebook configuration

Edit every range, deployment date, impact constant, and VMT setting as JSON.

{
  "yearsToSimulate": 2039,
  "numSimulations": 5000,
  "seed": 20300907,
  "daysPerWeek": 5.6,
  "hoursPerDay": 8,
  "milesPerHour": 13,
  "occupancyPct": 0.45,
  "networkParticipation": 0.25,
  "carLifespan": 9,
  "pricePerMile": 0.8,
  "pricePerMileAsia": 0.66,
  "platformFee": 0.25,
  "costsPerMile": 0.15,
  "growth": {
    "min": 0.4,
    "bear": 0.55,
    "bull": 0.7,
    "max": 0.8
  },
  "generalInputs": {
    "Price/Mile": {
      "min": 0.7,
      "bear": 0.8,
      "bull": 1.2,
      "max": 1.7
    },
    "Price/Mile Asia": {
      "min": 0.5,
      "bear": 0.66,
      "bull": 0.8,
      "max": 1.1
    },
    "Costs/Mile": {
      "min": 0.1,
      "bear": 0.15,
      "bull": 0.25,
      "max": 0.3
    },
    "Platform fee": {
      "min": 0.15,
      "bear": 0.25,
      "bull": 0.35,
      "max": 0.45
    },
    "Hours/day": {
      "min": 6,
      "bear": 8,
      "bull": 13,
      "max": 16
    },
    "Days/week": {
      "min": 4.5,
      "bear": 5.6,
      "bull": 6.5,
      "max": 7
    },
    "Miles/hour": {
      "min": 10,
      "bear": 13,
      "bull": 17,
      "max": 20
    },
    "% ocupacy": {
      "min": 0.35,
      "bear": 0.45,
      "bull": 0.65,
      "max": 0.69
    },
    "Network Participation": {
      "min": 0.2,
      "bear": 0.25,
      "bull": 0.35,
      "max": 0.4
    },
    "Car Lifespan": {
      "min": 8.5,
      "bear": 9,
      "bull": 11.5,
      "max": 13
    }
  },
  "growthByYear": {
    "2022": {
      "min": 0.4,
      "bear": 0.55,
      "bull": 0.7,
      "max": 0.8
    },
    "2023": {
      "min": 0.39,
      "bear": 0.5,
      "bull": 0.66,
      "max": 0.75
    },
    "2024": {
      "min": 0.37,
      "bear": 0.43,
      "bull": 0.6,
      "max": 0.65
    },
    "2025": {
      "min": 0.35,
      "bear": 0.4,
      "bull": 0.55,
      "max": 0.62
    },
    "2026": {
      "min": 0.3,
      "bear": 0.38,
      "bull": 0.49,
      "max": 0.55
    },
    "2027": {
      "min": 0.18,
      "bear": 0.25,
      "bull": 0.4,
      "max": 0.4
    },
    "2028": {
      "min": 0.11,
      "bear": 0.18,
      "bull": 0.31,
      "max": 0.35
    },
    "2029": {
      "min": 0.07,
      "bear": 0.12,
      "bull": 0.17,
      "max": 0.22
    },
    "2030": {
      "min": 0.05,
      "bear": 0.09,
      "bull": 0.15,
      "max": 0.2
    },
    "2031": {
      "min": 0.04,
      "bear": 0.08,
      "bull": 0.13,
      "max": 0.17
    },
    "2032": {
      "min": 0.035,
      "bear": 0.075,
      "bull": 0.1,
      "max": 0.15
    },
    "2033": {
      "min": 0.03,
      "bear": 0.07,
      "bull": 0.09,
      "max": 0.13
    },
    "2034": {
      "min": 0.025,
      "bear": 0.06,
      "bull": 0.08,
      "max": 0.1
    },
    "2035": {
      "min": 0.02,
      "bear": 0.05,
      "bull": 0.07,
      "max": 0.09
    },
    "2036": {
      "min": 0.015,
      "bear": 0.04,
      "bull": 0.06,
      "max": 0.08
    },
    "2037": {
      "min": 0.01,
      "bear": 0.03,
      "bull": 0.05,
      "max": 0.07
    },
    "2038": {
      "min": 0.005,
      "bear": 0.02,
      "bull": 0.04,
      "max": 0.06
    },
    "2039": {
      "min": 0.005,
      "bear": 0.01,
      "bull": 0.03,
      "max": 0.05
    }
  },
  "regionalDistribution": {
    "USA": {
      "min": 0.27,
      "bear": 0.3,
      "bull": 0.35,
      "max": 0.38
    },
    "Canada": {
      "min": 0.005,
      "bear": 0.008,
      "bull": 0.012,
      "max": 0.016
    },
    "Europe": {
      "min": 0.22,
      "bear": 0.25,
      "bull": 0.35,
      "max": 0.38
    },
    "China": {
      "min": 0.23,
      "bear": 0.265,
      "bull": 0.373,
      "max": 0.38
    },
    "APAC excl China": {
      "min": 0.01,
      "bear": 0.03,
      "bull": 0.065,
      "max": 0.072
    }
  },
  "regionalShares": {
    "USA": 0.3516998827667057,
    "Canada": 0.009378663540445486,
    "Europe": 0.2930832356389214,
    "China": 0.3106682297772567,
    "APAC excl China": 0.03516998827667057
  },
  "deploymentDates": {
    "USA": {
      "min": "01/09/2022",
      "bear": "01/07/2023",
      "bull": "01/10/2024",
      "max": "01/01/2029"
    },
    "Canada": {
      "min": "01/03/2023",
      "bear": "01/10/2023",
      "bull": "01/12/2024",
      "max": "01/01/2029"
    },
    "Europe": {
      "min": "01/08/2023",
      "bear": "01/08/2024",
      "bull": "01/12/2025",
      "max": "01/01/2030"
    },
    "China": {
      "min": "01/03/2023",
      "bear": "01/12/2023",
      "bull": "01/02/2025",
      "max": "01/01/2030"
    },
    "APAC excl China": {
      "min": "01/08/2023",
      "bear": "01/05/2024",
      "bull": "01/08/2025",
      "max": "01/01/2030"
    }
  },
  "impact": {
    "co2PerMile": {
      "Europe": {
        "ice": 395.721596,
        "ev": 133.897421
      },
      "USA": {
        "ice": 410.141318,
        "ev": 165.730245
      },
      "China": {
        "ice": 419.137551,
        "ev": 265.413012
      }
    },
    "co2Produced": {
      "USA": 4712770573,
      "Europe": 4946034489,
      "China": 10667887453
    },
    "alaCostPerGallon": 1.15,
    "usaMpg": 25.4,
    "carsUsa": 282800000,
    "avgMilesCar": 13476,
    "hoursInYear": 8760,
    "productivityPerHour": {
      "USA": 74.19,
      "Europe": 54.25,
      "China": 15,
      "Canada": 56.61
    },
    "gdpByRegion": {
      "USA": 20936600000000,
      "Europe": 15276468990000,
      "China": 14722730700000,
      "Canada": 1644037290000
    }
  },
  "vmt": {
    "enabled": true,
    "arimaOrder": [
      1,
      1,
      1
    ]
  }
}

Ready to run

Monte Carlo scenario analysis / 2022–2039

How much road can an autonomous fleet absorb?

A browser-based reconstruction of the thesis model. Adjust the operating assumptions, run the draws locally, and inspect the uncertainty band rather than a single forecast.

Run the reference model in your browser.

The first run creates the same scenario summaries as the thesis model, but keeps the work off the server and out of the UI thread.