The traffic industry has invested in an extensive infrastructure for vehicle detection and speed estimation. This paper describes how these sensors can be enhanced to measure not only the presence and speed of a vehicle but also its acceleration and travel time. While acceleration of vehicles is of independent interest, knowledge of the acceleration of a vehicle can also be used to normalize vehicular signatures to increase significantly the probability of successfully reidentifying vehicles to generate travel time estimates. In this paper, the acceleration correction for vehicle reidentification is developed and analyzed in terms of the percentage of vehicles correctly matched and in the framework of a communication system's receiver operating characteristic. The percentage of vehicles correctly matched for the travel time estimation is increased from 55.1% when only the speed of the passing vehicles is used to 64.5% and the acceleration estimates are also used.
Get full access to this article
View all access options for this article.
References
1.
NdoyeM., TottenV., CarterB., BullockD. M., and KrogmeierJ. V.Vehicle Detector Signature Processing and Vehicle Reidentification for Travel Time Estimation. Presented at 87th Annual Meeting of the Transportation Research Board, Washington, D.C., 2008.
2.
RobertsonH., HummerJ., and NelsonD.ITE Manual of Transportation Engineering Studies.Prentice Hall, Upper Saddle River, N.J., 1994.
3.
LiR., RoseG., and SarviM.Evaluation of Speed-Based Travel Time Estimation Models. ASCE Journal of Transportation Engineering, Vol. 132, No. 7, 2006, pp. 540–547.
4.
MalinovskiyY., WuY.-J., WangY., and LeeU. K.Field Experiments on Bluetooth-Based Travel Time Data Collection. Presented at 89th Annual Meeting of the Transportation Research Board, Washington, D.C., 2010.
5.
SchaeferM. C.License Plate Matching Surveys: Practical Issues and Statistical Considerations. Institute of Transportation Engineers Journal, Vol. 58, No. 7, 1988, pp. 37–42.
6.
CayfordR.Characteristics of Cell Phone Probe Technologies and Field Testing of Very High Volume Probe System. Presented at 89th Annual Meeting of the Transportation Research Board, Washington, D.C., 2010.
7.
WassonJ. S., SturdevantJ. R., and BullockD. M.Real-Time Travel Time Estimates Using Media Access Control Address Matching. Institute of Transportation Engineers Journal, Vol. 78, No. 6, 2008, pp. 20–23.
8.
BrennanT. M., ErnstJ. M., BullockD. M., KrogmeierJ. V., and MartchoukM.Influence of Vertical Sensor Placement on Data Collection Efficiency from Bluetooth MAC Address Collection Devices. ASCE Journal of Transportation Engineering, Vol. 136, No. 12, 2010, pp. 1104–1109.
9.
PfoserD., BrakatsoulasS., BroshP., UmlauftM., TryfonaN., and TsironisG.Dynamic Travel Time Provision for Road Networks. Proc., 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Irvine, Calif., November 2008.
10.
PuW., LinJ., and LongL.Estimation of Urban Street Segment Travel Time Using Buses as Real-Time Speed Probes. Presented at 89th Annual of Meeting of the Transportation Research Board, Washington, D.C., 2010.
11.
van ZuylenH. J., ZhengF., and ChenY.An Investigation of Urban Link Travel Time Estimation Based on Field Sparse Probe Vehicle Data. Presented at 89th Annual Meeting of the Transportation Research Board, Washington, D.C., 2010.
12.
QuirogaC., and BullockD.Travel Time Studies with Global Positioning and Geographic Information Systems: An Integrated Methodology. Transportation Research Part C, Vol. 6, Nos. 1-2, 1998, pp. 101–127.
13.
López-ValcarceR., MosqueraC., and Pérez-GonzálezF.Estimation of Road Vehicle Speed Using Two Omnidirectional Microphones: A Maximum Likelihood Approach. EURASIP Journal on Applied Signal Processing, Vol. 2004, No. 8, 2004, pp. 1059–1077.
14.
HaouiA., KavalerR., and VaraiyaP.Wireless Magnetic Sensors for Traffic Surveillance. Transportation Research Part C, Vol. 16, No. 3, 2008, 2007, pp. 294–306.
15.
DayC. M., PremachandraH., BrennenT. M.Jr., SturdevantJ. R., and BullockD. M.Operational Evaluation of Wireless Magnetometer Vehicle Detectors at Signalized Intersection. In Transportation Research Record: Journal of the Transportation Research Board, No. 2192, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 11–23.
16.
CoifmanB., and KrishnamurthyS.Vehicle Reidentification and Travel Time Measurement Across Freeway Junctions Using the Existing Detector Infrastructure. Transportation Research Part C, Vol. 15, No. 3, 2007, pp. 135–153.
17.
OrcuttL. H., and AlKadriM. Y.Overcoming Roadblocks to Innovation: Three Case Studies at the California Department of Transportation. In Transportation Research Record: Journal of the Transportation Research Board, No. 2109, Transportation Research Board of the National Academies, Washington, D.C., 2009, pp. 65–73.
18.
KwongK., KavalerR., RajagopalR., and VaraiyaP. P.Practical Scheme for Arterial Travel Time Estimation Based on Vehicle Reidentification Using Wireless Sensors. Presented at 88th Annual Meeting of the Transportation Research Board, Washington, D.C., 2009.
19.
ErnstJ. M., KrogmeierJ. V., and BullockD. M.Non-Linear Compensation of Vehicle Signatures Captured from Electromagnetic Sensors with Application to Vehicle Re-identification. Presented at 13th International IEEE Conference on Intelligent Transportation Systems, Madeira Island, Portugal, Sept. 19–22, 2010.
20.
TokA. Y. C.Correcting Acceleration-Distorted Inductive Signatures to Improve Traffic Information. Presented at 89th Annual Meeting of the Transportation Research Board, Washington, D.C., 2010.
21.
LuzE., MimbelaY., and KleinL. A.Summary of Vehicle Detection and Surveillance Technologies Used in Intelligent Transportation Systems. Technical report. Intelligent Transportation Systems Joint Program Office, FHWA, U.S. Department of Transportation, 2000.
22.
CheungS. Y., ColeriS., DundarB., GaneshS., TanC.-W., and VaraiyaP.Traffic Measurement and Vehicle Classification with Single Magnetic Sensor. In Transportation Research Record: Journal of the Transportation Research Board, No. 1917, Transportation Research Board of the National Academies, Washington, D.C., 2005, pp. 173–181.
23.
Abdel-RahimA., and DixonM. P.Automated Measurement of Approach Delay at Signalized Intersections: Vehicle-Event-Based Method. Presented at 88th Annual Meeting of the Transportation Research Board, Washington, D.C., 2009.
24.
ZhaoN., YuL., ZhaoH., GuoJ., and WenH.Analysis of Traffic Flow Characteristics on Ring Road Expressways in Beijing Using Floating Car Data and Remote Traffic Microwave Sensor Data. In Transportation Research Record: Journal of the Transportation Research Board, No. 2124, Transportation Research Board of the National Academies, Washington, D.C., 2009, pp. 178–185.
25.
KayS. M.Fundamentals of Statistical Signal Processing: Detection Theory.Prentice-Hall, Upper Saddle River, N.J., 1993.
26.
ErnstJ. M., NdoyeM., KrogmeierJ. V., and BullockD. M.Maximum-Likelihood Speed Estimation Using Vehicle-Induced Magnetic Signatures. Presented at 12th International IEEE Conference on Intelligent Transportation Systems, St. Louis, Mo., Oct. 3–7, 2009.
