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Citation |
Stewart JA, Rakha H, Van Aerde M. Transp. Res. Rec. 1995; 1494: 1-10. |
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Copyright |
(Copyright © 1995, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing) |
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DOI |
unavailable |
PMID |
unavailable |
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Abstract |
To determine the speed-flow relationship for a highway section, a number of parameters must be estimated. These include free speed, speed at capacity, capacity, and jam density. Because of fluctuations in demand, variations in driver behavior, and geometric and environmental conditions, these parameter values may vary both spatially for different stations and temporally for different days. To use these speed-flow relationships to estimate link travel times or diversion capacities, or for incident detection algorithms, these spatial and temporal variations in the speed-flow relationships need to be quantified so that accurate estimates of the relevant traffic parameters can be made. This work presents a statistical analysis of the variability of free speed estimates for 24 stations along a section of I-4 in Orlando, Florida during a 4-month period. This analysis is a first step in performing similar analyses of capacity, speed at capacity, and jam density. In the analysis presented in this work, it was found that free speed estimates along I-4 had a standard deviation of 4.7 km/hr and were most dependent on the location at which they were observed. This location factor explained 60% of the sum of squared errors. Minor variations in free speed from one day to another were overshadowed by these spatial differences and accounted for approximately 6% of the sum of squared errors. These two findings suggest that on this freeway section there is little loss in accuracy if many days of data are aggregated for a specific location, but a great loss in accuracy if many locations are averaged for the same day. There is also little to be gained by estimating day-of-the-week specific free speeds. Language: en |
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Keywords |
Data acquisition; Speed; Highway engineering; Highway traffic control; Ecosystems; Transportation routes; Highway systems; Statistical methods; Parameter estimation |