01558339

Component

https://doi.org/10.3141/2491-12

Long-term, regional travel demand models are essential tools used by planning organizations for resource management, project scheduling, and impact studies. Developed primarily at the macroscopic level, these tools lack sufficient detail to capture the influence of local geometry, dynamic traffic controls, or advanced transportation demand management strategies. To bridge the gap, a hybrid mesoscopic–microscopic model was developed. The core of the model, surrounding two light rail corridors in Minneapolis–Saint Paul, Minnesota (the Twin Cities), was developed at high resolution for microscopic simulation to capture the interaction between traffic signals, transit systems, and the road network. The remainder of the greater Twin Cities area was implemented according to the regional planning model (RPM) maintained by the Metropolitan Council. Interfacing the AIMSUN-based hybrid model with the CUBE-based RPM, the Twin Cities metro hybrid simulation was used to improve mode choice and traffic assignment iteratively to achieve a dynamic user equilibrium state. Significant lessons were learned about the effort needed to develop and to maintain such a model, with implications for future large-scale regional modeling.

01586813

15-5671

English

pp 107–116

2015

Transportation Research Record: Journal of the Transportation Research Board

9780309369275

Print

Figures (6) ; Maps; References (10) ; Tables (3)

Hybrid simulation; Lessons learned; Light rail transit; Mesoscopic traffic flow; Microscopic traffic flow; Regional planning; Traffic equilibrium; Traffic signal control systems; Traffic simulation

Minneapolis (Minnesota); Saint Paul (Minnesota); Twin Cities Metropolitan Area (Minnesota)

Highways; Operations and Traffic Management; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning; I73: Traffic Control

TRIS, TRB, ATRI

Dec 30 2014 1:54PM

• Analysis of Network Exit Functions for Various Urban Grid Network Configurations
• Capacity Drop: Relationship Between Speed in Congestion and the Queue Discharge Rate
• Comparative Analysis of Traffic State Estimation: Cumulative Counts-Based and Trajectory-Based Methods
• Driving Type Categorizing and Microscopic Simulation Model Calibration
• Empirical Study of Scooter–Vehicle Mixed Traffic Propagation on Urban Arterials
• Multiscale Traffic Flow Model Based on the Mesoscopic Lighthill–Whitham and Richards Models
• On Traffic Relaxation, Anticipation, and Hysteresis
• Real-Time Traffic Network State Prediction for Proactive Traffic Management: Simulation Experiments and Sensitivity Analysis
• Spatiotemporal Clustering of Urban Networks: Real Case Scenario in London
• Trajectory Data and Flow Characteristics of Mixed Traffic
• Use of Microsimulation for Examination of Macroscopic Fundamental Diagram Hysteresis Patterns for Hierarchical Urban Street Networks
• Vehicle Dynamics Model for Estimating Typical Vehicle Accelerations