Abstract
Flow, speed, and density are the three primary characteristics of traffic and are used to describe various aspects of operations of a highway facility. When describing and assessing traffic operations, we are often concerned with the movement of a group of vehicles, or the traffic stream, rather than the movement of each vehicle. In those cases, it is more convenient to describe traffic operations in terms of macroscopic measures of traffic.
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References
Highway Capacity Manual, 7th Edition, Transportation Research Board, National Academies, Washington DC, 2022
Mendenhall, W. Wackerly, D. D., Scheaffer, R. L., “Mathematical Statistics with Applications”, Fourth Edition, PWS-KENT, 1990
FHWA Traffic Detector Handbook, Third Edition, Publication Number FHWA-HRT-06-108, October 2006
Gerlough D.L. and Huber M. J., “Traffic Flow Theory: A Monograph”, TRB Special Report 165, National Research Council, Washington, D.C., 1975
Daganzo, C.F., “Fundamentals of Transportation and Traffic Operations”, Pergamon, 1997
Edie, L.C. “Discussion of traffic stream measurements and definitions” Proc. 2nd Int. Symp. On the Theory of Traffic Flow, (J. Almond, editor), pp. 139–154, OECD, Paris, France.
Greenshields, B., A study of Traffic Capacity, Highway Research Board, Proceedings of the Annual Meeting of the Highway Research Board, Vol. 14, 1935, pages 448–477
Greenberg, H. (1959). “An Analysis of Traffic Flow.” Operations Research, Volume 7: 78–85.
Underwood, R.T. (1961). “Speed, Volume, and Density Relationships: Quality and Theory of Traffic Flow.” Yale Bureau of Highway Traffic: 141–188.
Pipes, L.A., “Car Following Models and the Fundamental Diagram of Road Traffic”, Transportation Research 1, (May 1967), 21–29.
Van Aerde, M. (1995). “Single regime speed-flow-density relationship for congested and uncongested highways.” Presented at the 74th TRB Annual Conference, Washington DC, Paper No. 950802.
Coifman, B., “Revisiting the empirical fundamental relationship” Transp. Res. Part B, Volume 68, October 2014, pp. 173–184, https://doi.org/10.1016/j.trb.2014.06.005
May, A.D., “Traffic Flow Fundamentals”, Prentice Hall, 1990
Roess, R. P., Prassas, E. S., McShane, W. R., “Traffic Engineering”, Fourth Edition, Pearson/Prentice Hall, 2011
Gazis, D. C., Herman, R., Potts, R. B., “Car-Following Theory of Steady State Flow”, Operations Research, Vol. 7, No. 4, 1959, pages 499–505
Blue, V.J. and Adler, J. L. (2001), Cellular automata microsimulation for modeling bi-directional pedestrian walkways, Transportation Research Part B: Methodological, Volume 35, Issue 3, March 2001, Pages 293–312
Helbing, D. and Molnár, P. Social force model for pedestrian dynamics, Phys. Rev. E 51, 4282–4286 (1995).
Fellendorf, M., Schönauer, R., Huang, W., Social Force based Vehicle Model for Two-Dimensional Spaces, Presented at the Transportation Research Boards 91st Annual Meeting, Washington, D.C., 2012.
Daganzo, C., “Urban gridlock: Macroscopic modeling and mitigation approaches”, Transportation Research Part B 41 (2007) 49–62.
Geroliminis, N., C.F. Daganzo “Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings” Transportation Research Part B 42 (2008) 759–770.
Aghamohammadi, R., J. A. Laval, Parameter estimation of the macroscopic fundamental diagram: A maximum likeligood approach” Transportation Research Part C: Emerging Technologies Volume 140, July 2022, https://doi.org/10.1016/j.trc.2022.103678
Knoop, V.L., D. DeJong, and S. Hoogendorn “Influence of Road Layout on Network Fundamental Diagram” Transportation Research Record: Journal of the Transportation Research Board Volume 2421, Issue 1. https://doi.org/10.3141/2421-03
Wierbos, M.J., V. L. Knoop, F. S. Hanseler, S. P., Hoogendoorn “Capacity, Capacity Drop, and Relation of Capacity to the Path Width in Bicycle Traffic” Transportation Research Record: Journal of the Transportation Research Board, Volume 2673, Issue 5, pp 693–702 https://doi.org/10.1177/0361198119840347
Wierbos, M.J., V. L. Knoop, B. Goni-Ros., S. P., Hoogendoorn “The Influence of Jam Density and Merging Cyclists on the Queue Discharge Rate” Journal of Advanced Transportation, Volume 2020, Article ID 9272845 https://doi.org/10.1155/2020/9272845
Wierbos, M.J., V. L. Knoop, F. S. Hanseler, S. P., Hoogendoorn “A macroscopic flow model for mixed bicycle–car traffic” Transportmetrica A: Transport Science, Volume 17, Issue 3, pp 340–355 https://doi.org/10.1080/23249935.2019.1708512
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Problems
Problems
-
1.
The following 15-min volumes have been collected at a four-leg unsignalized intersection.
Time intervals
Eastbound
Westbound
Northbound
Southbound
4:30–4:45
569
921
624
783
4:45–5:00
610
957
634
795
5:00–5:15
652
883
691
802
5:15–5:30
678
832
727
811
5:30–5:45
631
845
753
902
5:45–6:00
595
833
718
889
What is the peak 15-min period and what is the respective peak 15 min volume for the intersection? What is the peak hour and what is the respective 1-h volume? What is the PHF at this intersection during the evening peak period?
-
2.
For the headway data shown below, conduct the following analyses:
-
(a)
Plot the probability density function and the cumulative density function.
-
(b)
Determine the sample mean, mode, variance, and 85th percentile.
-
(c)
Estimate the hourly flow during the data collection.
-
(d)
Test the hypothesis that these data are from a negative exponential distribution.
-
(a)
Headway Data (in seconds) | |||||
4 | 5 | 11 | 3 | 14 | 22 |
1.5 | 14 | 182 | 20 | 13 | 8 |
8 | 22 | 16 | 10 | 10 | 23 |
16 | 7 | 4 | 12 | 5 | 2.5 |
4.5 | 12 | 2 | 5 | 5 | 2 |
2 | 8 | 8 | 1.5 | 3 | 24 |
3 | 22 | 25 | 4 | 2 | 25 |
2 | 3.5 | 14 | 3 | 3 | 8 |
19 | 24 | 5 | 12 | 21 | 7 |
10 | 8 | 40 | 38 | 18 | 21 |
17 | 13 | 19 | 28 | 19 | 12 |
23 | 6 | 15 | 39 | 5 | 4 |
31 | 2 | 2 | 17 | 5 | 3 |
9 | 3 | 6.5 | 3 | 2 | 15 |
5.5 | 4 | 28 | 12 | 2 | 23 |
17 | 5 | 12 | 26 | 6 | 19 |
42 | 1.5 | 8 | 39 | 29 | 3 |
29 | 12 | 7.5 | 18 | 17 | 8 |
19 | 9 | 13 | 31 | 7 | 27 |
20 | 4 | 34 | 15 | 3 | 20 |
8 | 2.5 | 4 | 4 | 31 | 15 |
2 | 12 | 15 | 4 | 8 | 17 |
-
3.
Conduct a literature review on statistical tests for distributions and summarize your findings. Describe which test is most appropriate for specific conditions.
-
4.
A study of freeway flow at a particular site has resulted in a calibrated speed–density relationship as follows:
$$ \mathrm{U}=65.4\ \left(1-0.0075\ \mathrm{K}\right) $$From this relationship:
-
(a)
Find the free-flow speed and jam density.
-
(b)
Derive equations describing flow vs speed and flow vs density.
-
(c)
Determine the capacity of the site mathematically.
-
(d)
Sketch the speed–density, flow–speed, and flow–density curves.
-
(e)
How does this relationship handle boundary conditions (minimal flow, capacity, and jam density conditions)?
-
(a)
-
5.
Conduct a literature review on traffic stream models and for each identified model, state the advantages and disadvantages.
-
6.
Collect or obtain speed–flow data from a freeway location and plot them. Discuss the location of the data collection site vs the plot obtained. Is your site located upstream or downstream of a bottleneck?
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Elefteriadou, L. (2024). Flow, Speed, and Density and Their Relationships. In: An Introduction to Traffic Flow Theory. Springer Optimization and Its Applications, vol 84. Springer, Cham. https://doi.org/10.1007/978-3-031-54030-1_3
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DOI: https://doi.org/10.1007/978-3-031-54030-1_3
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