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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.

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.

Principles of Information Systems (MindTap Course List)
Principles of Information Systems (MindTap Course List)
13th Edition
ISBN:9781305971776
Author:Ralph Stair, George Reynolds
Publisher:Ralph Stair, George Reynolds
Chapter9: Business Intelligence And Analytics
Section: Chapter Questions
Problem 3CTQ1
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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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