Predictive Speed Regulation to Prevent Phantom Traffic Jams
Feature: Predictive Speed Regulation to Prevent Phantom Traffic Jams
Problem:
When one vehicle hard-brakes on a highway, it creates a backward-traveling shockwave. Due to human reaction times, vehicles behind brake even harder — causing a dead-stop jam with no actual obstruction. These "phantom jams" cause thousands of rear-end collisions yearly.
Proposed Solution:
Waze already collects real-time GPS telemetry from millions of drivers. If the system detects a sudden velocity drop, it could instantly push a "Reduce speed to 60 km/h" advisory to drivers further back — absorbing the shockwave before it cascades.
I Built a Working Simulation:
I've created an open-source Python simulation using the Intelligent Driver Model (IDM) physics that proves this works:
Without intervention: 11/15 vehicles reach dead stop
With V2Cloud warning: Zero vehicles stopped, shockwave fully absorbed
Effectiveness drops sharply above 1.5s latency — Waze's existing infrastructure is fast enough
GitHub (full code + demo): https://github.com/san342147/v2cloud-traffic-optimization
Video demo: https://www.linkedin.com/in/[YOUR-LINKEDIN-URL]
No new hardware required. No V2V sensors. Just an algorithm upgrade to Waze's existing real-time traffic engine.
I'm a B.Tech AIML student from Chennai, India and would love to discuss this further with the Waze engineering team.
SANTHOSH A 241501185
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