01456595

Component

http://www.trb.org/Publications/Blurbs/168134.aspx

This article discusses applications of artificial intelligence (AI) methods to urban travel demand forecasting. The article begins with an historical overview of urban travel demand forecasting. The discussion takes two perspectives: concepts perspective (i.e., how certain AI concepts could improve the current state of practice), and a methods perspective (i.e., which AI methods could be applied and how).

01456594

English

pp 86-92

2012-11

Transportation Research Circular

Web

Figures; References

Artificial intelligence; Forecasting; Travel demand; Urban travel

Data and Information Technology; Highways; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Dec 10 2012 3:32PM

• Advantages and Limitations of Artificial Intelligence
• Agent-Based Modeling and Simulation
• Analysis of Public Transportation Planning and Operations
• Artificial Intelligence and Microscopic Traffic Simulation Models: Applications to Parameter Calibration and Origin–Destination Estimation
• Design and Construction of Transportation Infrastructure
• Difference Between Artificial Intelligence and Traditional Methods
• Neural Networks for Travel Time Prediction on Interrupted Flow Facilities
• Ramp Metering
• Short-Term Traffic and Travel Time Prediction Models
• Traffic Signal Timing and Optimization
• Transportation Safety Analysis
• Transportation Security
• Travel Behavior Research