Method for estimating population OD matrix based on probe vehicles

KSCE Journal of Civil Engineering

Volumn 14, Issue 2, 2010, Pages 231-235

  Baek, Seungkirl ^a   Lim, Yongtaek ^b   Rhee, Sungmo ^c   Choi, Keechoo ^d  

^a Korea Highway Corporation   (South Korea)

^b Chonnam National University   (South Korea)

^c Seoul National University   (South Korea)

^d Ajou University   (South Korea)

Author keywords

Mathematical minimization program; OD estimation; Population OD matrix; Probe vehicle; Sampling ratio

Indexed keywords

DATA COLLECTION; LINK-FLOW; NEW APPROACHES; O-D MATRIX; OD ESTIMATION; ORIGIN DESTINATION; PROBE VEHICLES; ROUTE INFORMATION; SAMPLING RATIOS; TRAFFIC DATA; TRAFFIC VOLUMES; TRAVEL DEMAND FORECASTING;

ALGORITHMS; ESTIMATION; MATRIX ALGEBRA; MOBILE TELECOMMUNICATION SYSTEMS; PROBES; RADIO FREQUENCY IDENTIFICATION (RFID); SAMPLING; TRANSPORTATION ROUTES; VEHICLES;

POPULATION STATISTICS;

EID: 77649226963     PISSN: 12267988     EISSN: 19763808     Source Type: Journal    
DOI: 10.1007/s12205-010-0231-4     Document Type: Article

References (15)

1. Baek, S., Kim, H., and Shin, D. (2002). OD matrix estimation using link use proportion sample data as additional information. The Journal of Korean Society of Transportation, Vol. 20, No. 4, pp. 83-93.
2. Baek, S., Jung, S., Kim, H., and Choi, K. (2008) A methodology for expanding sample OD based on probe vehicle. The Journal of Korean Society of Transportation, Vol. 26, No. 2, pp. 135-145.
3. Bazaraa, M., Sherali, H. D., and Shetty, C. M. (2006) Nonlinear programming, theory and algorithms, 3rd ed., Wiley.
4. Bell, M. G. H. (1991). The estimation OD matrices constrained generalized least squares. Transportation Research 25B, pp. 13-22.
5. Cascetta, E. (1984). Estimation of trip matrices from traffic counts and survey and data: Generalized least squares estimator. Transportation Research 18B, pp. 289-299.
6. Cascetta, E. and Nguyen, S. (1988). A unified framework for estimating or updating OD matrices from traffic counts. Transportation Research 22B, pp. 437-455.
7. Hellinga, B. (1994). Estimating dynamic origin-destination demands from link and probe counts, PhD Dissertation, Queens University.
8. Kim, H. (2008). New dynamic travel demand modeling methods in advanced data collecting environments, PhD Dissertation, University of California, Irvine.
9. Kim, H., Baek, S., and Lim, Y. (2001). Origin-destination matrices estimated with a genetic algorithm from link traffic counts. Transportation Research Record 1771, pp. 156-163.
10. Kwon, J. and Varaiya, P. (2005). Real-time Estimation of origindestination matrices with partial trajectories from electronic toll congestion tag data. Transportation Research Record, No. 1923, pp. 119-126.
11. Maher, M. J. (1983). Inference on trip matrices from observations on link volumes: A Bayesian statistical approach. Transportation Research 17B, 435-447.
12. Spiess, H. (1987). A Maximum likelihood model for estimating OD matrices. Transportation Research 21B, pp. 395-412.
13. van Zuylen and Willumsen, G. (1980). The most likely trip matrix estimated from traffic counts. Transportation Research 14B, pp. 281-293.
14. Zhou, X. (2004). Dynamic origin-destination demand estimation and prediction for off-line and on-line dynamic traffic assignment operation, PhD Dissertation, University of Maryland, College Park.
15. Zhou, X. and Mahmassani, H. S. (2006). Dynamic origin-destination demand estimation using automatic vehicle identification data. IEEE Transactions on Intelligent Transportation Systems, Vol. 7, No. 1, pp. 105-114.