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.
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
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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