The objectives of the study were to develop a predictive algorithm for freeway congestion and to investigate and evaluate the current TSMC definition of freeway congestion or 'bottleneck' conditions. Data were collected along a section of the I-5 mainline northbound beginning at Downtown Station 108 and ending at Montlake Terrace Station 193 using two approaches: (1) time series modeling, and (2) pattern recognition. A pattern recognition approach was used to identify the best criteria for 'bottleneck' definition and also to identify the best criteria for predicting 'bottleneck' conditions. The time period for collection was 2:30 to 6:30 p.m. with a data time interval of 20 seconds.
Freeway Congestion Prediction
1995
88 pages
Report
No indication
English
A study of freeway traffic congestion
TIBKAT | 1964
|Potential Freeway Congestion Severity Measure: Impact of Continuous Congestion Patterns
British Library Online Contents | 2009
|Potential Freeway Congestion Severity Measure: Impact of Continuous Congestion Patterns
Online Contents | 2009
|Estimating the Probability of Freeway Congestion Recurrence
Transportation Research Record | 1998
|