Exploring the interplay between population profile and optimal routes in U.S. cities

Area of Science:

• Urban Science
• Network Analysis
• Computational Social Science

Background:

• Cities evolve with civilization, prioritizing efficient travel and cost reduction.
• Existing research explores urban road networks' properties but lacks clarity on car routes and population dynamics.
• Understanding the interplay between urban structure, population distribution, and transportation networks is crucial for city planning.

Purpose of the Study:

• To investigate the relationship between car routes and population distribution within urban structures.
• To identify fundamental principles shaping urban design through population-path optimization.

Main Methods:

• Utilized US Census city tracts' centers of mass as origins and destinations for route calculations.
• Calculated travel time, Euclidean distance, and travel distance for sixty major cities.
• Applied Weibull functions to model car journey distributions and developed a population point pattern model.

Main Results:

• The total sum of all routes follows a quantifiable urban law.
• Car journey distributions are accurately fitted by Weibull functions, highlighting the urban center's role in route optimization.
• A city classification system was established, and the population model aligns with the decreasing exponential density expression.

Conclusions:

• The urban center is pivotal in optimizing travel routes across diverse cities.
• Population distribution and path optimization significantly influence city structure.
• Findings offer novel insights into the foundational principles governing urban design and development.