Disappearing Traffic Studies

“Disappearing traffic, also sometimes referred to as suppressed traffic or traffic evaporation, relates to the observation that when highway capacity is reduced (typically due to provision of lanes for buses, street-running trams or bicycles, wider pavements (sidewalks), pedestrianisation, closures for road maintenance, or natural disasters) some proportion of the traffic disappears, resulting in fewer problems of congestion than had been expected.” (source)

Induced demand” is the “build-it-and-they-will-come” theory of driving.

What’s Up With That: Building Bigger Roads Actually Makes Traffic Worse

Disappearing Traffic? The Story So Far

Shrinking Roads Shrinks Traffic

World Bank’s Induced Traffic and Induced Demand Study

Charles Siegel: From induced demand to reduced demand

I Am Induced Demand (and So Can You)!

“additional lanes fly in the face of everything we’ve learned about induced demand”

Road Space Reallocation; Roadway Design and Management To Support Transportation Alternatives

What cities should do about traffic congestion

Congestion Costing Critique: Critical Evaluation of the ‘Urban Mobility Report’

Smart Congestion Relief: Comprehensive Analysis Of Traffic Congestion Costs and Congestion Reduction Benefits

Changing Travel Demand: Implications for Transport Planning

Miscellaneous Studies

TTI’s Rider 42 (Mobility Investment Priorities)

CAMPO’s Local Traffic Counts: click here & click here

TxDOT’s Traffic Maps

Estimates of AADT: Quantifying the Uncertainty

TTI’s Simulation Model Performance Evaluation for Congested Freeway Operations

TTI’s Dynamic Traffic Flow Modeling for Incident Detection and Short-term Congestion Prediction

TTI’s Travel Forecasting Program for model input

CTR’s The Texas Mobile Load Simulator: Accelerated Simulation of Real Traffic

CTR’s Using Real Time Traveler Demand Data to Optimize Commuter Rail Feeder Systems

CTR’s Understanding Emerging Commuting Trends in a Weekly Travel Decision Frame: Implications for Mega Region Transportation Planning

CTR’s Quantifying Travel Time Variability in Transportation Networks

CTR’s Examining the Role of Trip Length in Commuter Decisions to Use Public Transportation

CTR’s Microsimulation of Household and Firm Behaviors: Couple Models of Land Use and Travel Demand in Austin, Texas

Texas Facilities Commission’s 2010 Parking Usage Study

Dr. Chandra R. Bhat (Director, Center for Transportation Research, UT)

Travel Behavior Modeling/Travel Demand Modeling

Socio-Demographics and Land-Use Modeling

Sustainable Urban Design and Physical Activity

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