"""
Autonomous Vehicle Adoption Index — Track AV deployment, regulatory progress,
key companies, and adoption metrics using public data sources.
Roadmap #394.
"""
import datetime
from typing import Dict, List, Optional
AV_COMPANIES = [
{"name": "Waymo", "parent": "Alphabet", "level": 4, "status": "commercial", "cities": ["Phoenix", "San Francisco", "Los Angeles", "Austin"], "rides_per_week_est": 150000},
{"name": "Cruise", "parent": "GM", "level": 4, "status": "suspended", "cities": [], "rides_per_week_est": 0},
{"name": "Tesla FSD", "parent": "Tesla", "ticker": "TSLA", "level": 3, "status": "beta", "cities": ["nationwide_US"], "rides_per_week_est": None},
{"name": "Baidu Apollo", "parent": "Baidu", "ticker": "BIDU", "level": 4, "status": "commercial", "cities": ["Beijing", "Wuhan", "Shenzhen"], "rides_per_week_est": 80000},
{"name": "Pony.ai", "parent": None, "ticker": "PONY", "level": 4, "status": "commercial", "cities": ["Beijing", "Guangzhou"], "rides_per_week_est": 20000},
{"name": "Mobileye", "parent": "Intel", "ticker": "MBLY", "level": 3, "status": "testing", "cities": ["Munich", "Detroit"], "rides_per_week_est": 0},
{"name": "Aurora", "parent": None, "ticker": "AUR", "level": 4, "status": "commercial_trucking", "cities": ["Dallas-Houston corridor"], "rides_per_week_est": 5000},
{"name": "Zoox", "parent": "Amazon", "level": 4, "status": "testing", "cities": ["Las Vegas", "Foster City"], "rides_per_week_est": 0},
{"name": "Nuro", "parent": None, "level": 4, "status": "commercial_delivery", "cities": ["Houston", "Mountain View"], "rides_per_week_est": 3000},
]
REGULATORY_STATUS = [
{"jurisdiction": "California", "robotaxi_permitted": True, "trucking_permitted": True, "notes": "Post-Cruise review ongoing"},
{"jurisdiction": "Arizona", "robotaxi_permitted": True, "trucking_permitted": True, "notes": "Most permissive US state"},
{"jurisdiction": "Texas", "robotaxi_permitted": True, "trucking_permitted": True, "notes": "No special AV permit required"},
{"jurisdiction": "China", "robotaxi_permitted": True, "trucking_permitted": True, "notes": "City-by-city permits, 20+ cities"},
{"jurisdiction": "EU", "robotaxi_permitted": False, "trucking_permitted": False, "notes": "Framework expected 2026"},
{"jurisdiction": "UK", "robotaxi_permitted": False, "trucking_permitted": False, "notes": "Automated Vehicles Act 2024"},
]
def get_av_landscape() -> Dict:
"""Get overview of autonomous vehicle industry — companies, status, regulations."""
commercial = [c for c in AV_COMPANIES if "commercial" in c["status"]]
total_rides = sum(c["rides_per_week_est"] or 0 for c in AV_COMPANIES)
public_tickers = [{"name": c["name"], "ticker": c.get("ticker")} for c in AV_COMPANIES if c.get("ticker")]
return {
"total_companies": len(AV_COMPANIES),
"commercial_operators": len(commercial),
"est_weekly_rides_global": total_rides,
"public_tickers": public_tickers,
"regulatory_summary": REGULATORY_STATUS,
"companies": AV_COMPANIES,
}
def get_company_detail(name: str) -> Optional[Dict]:
"""Get detailed info on a specific AV company."""
for c in AV_COMPANIES:
if c["name"].lower() == name.lower():
return c
return None
def get_adoption_metrics() -> Dict:
"""Calculate aggregate adoption metrics for the AV sector."""
total_cities = set()
for c in AV_COMPANIES:
for city in c.get("cities", []):
if city != "nationwide_US":
total_cities.add(city)
commercial = [c for c in AV_COMPANIES if "commercial" in c["status"]]
total_weekly = sum(c["rides_per_week_est"] or 0 for c in AV_COMPANIES)
return {
"unique_cities_with_av": len(total_cities),
"commercial_operators": len(commercial),
"est_weekly_autonomous_rides": total_weekly,
"est_annual_rides": total_weekly * 52,
"jurisdictions_permitting_robotaxi": sum(1 for r in REGULATORY_STATUS if r["robotaxi_permitted"]),
}
