Arcology Simulation Framework

Project Summary: Optimization and simulation framework to analyze transit-oriented designs

Mass Transit Paradigms: Commercial Aviation

Ground Transit establishes Feeder-and-Trunk model

Vehicle Sharing Options and Concepts

Personal Rapid Transit Systems struggle along

Transit Oriented Design should drive development of more efficient mass transit

Denser cities are more efficient per capita

Arcologies and Compact Cities pack functionality

A Metropolitan complex should maximize diversity

Mass Transit Optimization Key Capabilities

Mass Transit Optimization Model Elements

Conceptual Model of a Station

Transit Optimization Input / Output Variables

Transit Optimization Constraints

Multiple Objectives prioritized by weights: Obj 1 >> Obj 2 >> Obj 3 >> Obj 4

Transit Modes: timing, capacity, and optimization parameters tuned to represent:

Optimized Schedule Verified by Simulation (the second half)

Simulation Component Diagram

Commuter Transit Model Class Structure

Commuter Transit Model System Activity Diagram

Verification and Validation

Parametric Analysis Scenarios

1D Rail Passenger Metrics Response to uniform random demand pulse

1D Rail Vehicle Metrics Operating cost & efficiency

Factorial Experiments Design

Passenger view of Sequential vs. Express routing with respect to Vehicle Capacity

Fleet Operator view of Sequential vs. Express routing with respect to Vehicle Capacity

Passenger view of Sequential vs. Express routing with respect to Station Berth Capacity

Fleet Operator view of Sequential vs. Express routing with respect to Station Berth Capacity

Conclusion: This tool can do interesting things

Future Work: Model feature completion

Future Work: Scalability

Discussion