Sample Size Reduction Method Based on Data Fusion for Freeways with Fixed Detectors

Abstract

This research investigates the required minimum number of probe vehicles (PVs) necessary to report the real-time travel speed and travel time with the desired statistical accuracy for freeways equipped with fixed detectors. The field data used were collected from the Freeway Performance Measurement System from 7:00 to 10:00 a.m. on May 28, 2014, during a typical weekday. With corridor information and traffic volume data, this study uses VISSIM to create simulation scenarios to generate PV data and loop data for further analysis. Then the average relative errors of travel time by setting are compared with various PV percentages in traffic on different links. The least squares errors of the fused speed data are also compared with the PV and loop data. Through analysis, the study reaches the following results. When the probe sample size reaches a certain level (3% in the testing environment), the estimated errors are reduced gently with the increasing number of PVs. To ensure that the link is traversed by at least one PV in one sample interval, at least 5-min, 5- to 10-min, and 20- to 25-min sampling intervals are required when the PV percentages are 3%, 2%, and 1%, respectively. The fusion of PV data and loop data can increase the accuracy of estimation results. About 3% of PVs are sufficient to collect highly accurate data for general freeways; 2% is enough to obtain the same or higher accuracy for the same road with fixed detectors.

Get full access to this article

View all access options for this article.

References

Ran

, Rouphail

N. M.

, Tarko

, and Boyce

Toward a Class of Link Travel Time Functions for Dynamic Assignment Models on Signalized Networks. Transportation Research Part B, Vol. 31, No. 4, 1997, pp. 277–290.

Cohen

, Bosseboeuf

J.L.

, and Schwab

Probe Vehicle Sample Sizes for Travel Time Estimation on Equipped Motorways. Road Transport Information and Control, Conference Publication No. 486, March 19–21, 2002, London, pp. 172–176.

Robertson

H.D.

, Hummer

J.E.

, and Nelson

D.C.

Manual of Transportation Engineering Studies. Prentice Hall, Englewood Cliffs, N.J., 1994.

Quiroga

C.A.

, and Darcy

Development of CMS Monitoring Procedures. Louisiana Transportation Research Center, 1998.

Quiroga

C.A.

, and Bullock

Determination of Sample Size for Travel Time Studies. ITE Journal, Vol. 68, No. 8, 1998, pp. 92–98.

, Zhu

, van Gelder

B. H. W.

, Nagle

, and Tuttle

Reconsideration of Sample Size Requirements for Field Traffic Data Collection with Global Positioning System Devices. In Transportation Research Record: Journal of the Transportation Research Board, No. 1804, Transportation Research Board of the National Academies, Washington, D.C., 2002, pp. 17–22.

Cheu

R.L.

, Xie

, and Lee

Probe Vehicle Population and Sample Size for Arterial Speed Estimation. Computer-Aided Civil and Infrastructure Engineering, Vol. 17, No. 1, 2002, pp. 53–60.

Chen

, and Chien

S. I. J.

Determining the Number of Probe Vehicles for Freeway Travel Time Estimation by Microscopic Simulation. In Transportation Research Record: Journal of the Transportation Research Board, No. 1719, TRB, National Research Council, Washington, D.C., 2000, pp. 61–68.

, McCormack

E.D.

, and Wang

Processing Commercial Global Positioning System Data to Develop a Web-Based Truck Performance Measures Program. In Transportation Research Record: Journal of the Transportation Research Board, No. 2246, Transportation Research Board of the National Academies, Washington, D.C., 2011, pp. 92–100.

10.

, and McDonald

Determining the Sample Size of Probe Vehicles. Proceedings of the ICE—Transport, Vol. 160, No. 4, 2007, pp. 201–205.

11.

Boyce

, Hicks

, and Sen

In-Vehicle Navigation System Requirements for Monitoring Link Travel Time in a Dynamic Route Guidance System. Presented at 70th Annual Meeting of the Transportation Research Board, Washington, D.C., 1991.

12.

Turner

S.M.

, and Holdener

D.J.

Probe Vehicle Sample Sizes for Real-Time Information: The Houston Experience. IEEE, Vehicle Navigation and Information System Conference, Seattle, Washington, 1995, pp. 3–10.

13.

Srinivasan

K.K.

, and Jovanis

P.P.

Determination of Number of Probe Vehicles Required for Reliable Travel Time Measurement in Urban Network. In Transportation Research Record 1537, TRB, National Research Council, Washington, D.C., 1996, pp. 15–22.

14.

Green

M.W.

, Fontaine

M.D.

, and Smith

B.L.

Investigation of Dynamic Probe Sample Requirements for Traffic Condition Monitoring. In Transportation Research Record: Journal of the Transportation Research Board, No. 1870, Transportation Research Board of the National Academies, Washington, D.C., 2004, pp. 55–61.

15.

Cetin

, List

G.F.

, and Zhou

Factors Affecting Minimum Number of Probes Required for Reliable Estimation of Travel Time. In Transportation Research Record: Journal of the Transportation Research Board, No. 1917, Transportation Research Board of the National Academies, Washington, D.C., 2005, pp. 37–44.

16.

Nezamuddin

, Crunkleton

, and Tarnoff

P.J.

Speed Distribution Profile of Traffic Data and Sample Size Estimation. Presented at 88th Annual Meeting of the Transportation Research Board, Washington, D.C., 2009.

17.

Jiang

, Gang

, and Cai

Impact of Probe Vehicles Sample Size on Link Travel Time Estimation. IEEE Intelligent Transportation Systems Conference Proceedings, Toronto, Ontario, Canada, 2006, pp. 505–509.

18.

Wunderlich

K.E.

, Harding

J. A.

, Van Aerde

, and Hellinga

Macro-Level Traffic Simulation and Case Study Development for IVHS System Architecture Evaluation. Proc., ITS America 1995 Annual Meeting, Washington, D.C., 1995, pp. 875–886.

19.

Dai

, Ferman

M.A.

, and Roesser

R.P.

A Simulation Evaluation of a Real-Time Traffic Information System Using Probe Vehicles. Intelligent Transportation Systems, 2003 Proceedings, Vol. 1, 2003, pp. 475–480.

20.

Hong

, Zhang

, Wei

, Li

, and Ren

Spatial and Temporal Analysis of Probe Vehicle-Based Sampling for Real-time Traffic Information System. Proc., 2007 IEEE Intelligent Vehicles Symposium, Istanbul, Turkey, June 13–15, 2007, pp. 1234–1239.

21.

Zhao

, Kong

Q.-J.

, Xia

, and Liu

Sample Size Analysis of GPS Probe Vehicles for Urban Traffic State Estimation. 14th International IEEE Conference on Intelligent Transportation Systems, Washington, D.C., Oct. 5–7, 2011, pp. 272–276.

22.

Devore

L. J.

Probability and Statistics for Engineering and the Sciences, 7th ed. Cengage Learning, 2007.

23.

Turner

S.M.

, Eisele

W. L.

, Benz

R.J.

, and Holdener

D.J.

Travel Time Data Collection Handbook. Research Report 07470-1F. FHWA-PL-98-035. FHWA, Washington, D.C., 1998.

24.

Choe

, Skabardonis

, and Varaiya

Freeway Performance Measurement System: Operational Analysis Tool. In Transportation Research Record: Journal of the Transportation Research Board, No. 1811, Transportation Research Board of the National Academies, Washington, D.C., 2002, pp. 67–75.

25.

Bachmann

, Roorda

M. J.

, Abdulhai

, and Moshiri

Fusing a Bluetooth Traffic Monitoring System with Loop Detector Data for Improved Freeway Traffic Speed Estimation. Journal of Intelligent Transportation Systems, Vol. 17, No. 2, 2013, pp. 152–164.