Traffic Flow Optimization: Per-Lane Speed Ranges

An agent-based simulation demonstrating that per-lane speed ranges with enforced minimums produces dramatically better traffic flow than traditional single speed limits.

The Hypothesis

Traffic congestion isn't caused by high speeds—it's caused by speed variance. The slow driver in the fast lane creates cascading brake events and forces constant lane changes.

Proposed solution:

• Non-overlapping speed ranges per lane (55-65, 65-75, 75-85, 85-95 mph)
• Harsh enforcement of minimums (ticket slow drivers, tolerate fast drivers)
• License and vehicle certification tiers for higher-speed lane access

Results (Bay Area Projections)

Metric	Current	Proposed	Change
Throughput	1,175/hr	1,574/hr	+34%
Lane changes/car	7.49	0.46	-94%
Accident risk	9.06/1000	1.11/1000	-84%
Effective MPG	17.7	27.1	+53%

Annual Impact (SF Bay Area)

• $3.3 billion in benefits (time, fuel, safety)
• $1.8 billion in new government revenue
• 334 million gallons of fuel saved
• 3.3 million tons of CO2 reduced
• 84% fewer accidents
• 54x ROI on $62M implementation cost

Files

• traffic_model.py - Basic simulation comparing baseline vs proposed
• traffic_model_v2.py - Realistic model with mid-road exits and imperfect compliance
• traffic_results.png - Visualization of simulation results
• linkedin_post.md - Full writeup with revenue model and policy analysis

Running the Simulation

# Basic comparison
python3 traffic_model.py

# Realistic model with visualization
python3 traffic_model_v2.py

Requires: numpy, matplotlib

The Mechanism

1. Self-selection: Drivers sort by desired speed at entry
2. Structural enforcement: Can't enter faster lane below its minimum
3. Natural discipline: "Accelerate then merge left" becomes mandatory
4. Reduced variance: Within-lane speeds are uniform
5. Fewer lane changes: 94% reduction eliminates accordion effect

Revenue Model

The proposal increases government revenue:

• Un-speeding tickets (slow-traffic cameras): $660M/year
• License tier fees: $688M/year
• Vehicle certification: $488M/year
• Total: $1.8B/year (vs $280M current)

Plus creates $206M driving school market.

Why It Works

Accidents correlate with speed differential, not absolute speed. The current system optimizes for the wrong variable. A left lane where everyone goes 80 is safer than a left lane with cars going 60, 70, and 80 mixed together.

Author

Jeremy McEntire

License

MIT - Take it, use it, implement it. Credit appreciated but not required.