Problem: Optimizing Traffic Flow Using Machine Learning Context: A city traffic department is experiencing severe traffic congestion during peak hours. They want to develop a machine learning model to optimize traffic signal timings across intersections to reduce congestion. Problem Statement The traffic department has provided: 1. Traffic sensor data: Real-time vehicle counts from cameras at 50 intersections in the city. 2. Historical traffic patterns: Average vehicle count per hour for the past year. 3. Signal timing logs: The timing sequences used at each intersection. Your task is to design a system that uses this data to optimize traffic light timings, minimizing the average waiting time per vehicle.

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
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Problem: Optimizing Traffic Flow Using Machine Learning
Context: A city traffic department is experiencing severe traffic congestion during peak hours. They
want to develop a machine learning model to optimize traffic signal timings across intersections to
reduce congestion.
Problem Statement
The traffic department has provided:
1. Traffic sensor data: Real-time vehicle counts from cameras at 50 intersections in the city.
2. Historical traffic patterns: Average vehicle count per hour for the past year.
3. Signal timing logs: The timing sequences used at each intersection.
Your task is to design a system that uses this data to optimize traffic light timings, minimizing the
average waiting time per vehicle.
Transcribed Image Text:Problem: Optimizing Traffic Flow Using Machine Learning Context: A city traffic department is experiencing severe traffic congestion during peak hours. They want to develop a machine learning model to optimize traffic signal timings across intersections to reduce congestion. Problem Statement The traffic department has provided: 1. Traffic sensor data: Real-time vehicle counts from cameras at 50 intersections in the city. 2. Historical traffic patterns: Average vehicle count per hour for the past year. 3. Signal timing logs: The timing sequences used at each intersection. Your task is to design a system that uses this data to optimize traffic light timings, minimizing the average waiting time per vehicle.
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