Application of Probe-Vehicle Data for Real-Time Traffic-State Estimation and Short-Term Travel-Time Prediction on a Freeway
-
- Chumchoke Nanthawichit
- Transportation and Traffic Systems, Graduate School of Engineering, Hokkaido University, Kita-13, Nishi-8, Kita-ku, Sapporo 060-8628, Japan
-
- Takashi Nakatsuji
- Transportation and Traffic Systems, Graduate School of Engineering, Hokkaido University, Kita-13, Nishi-8, Kita-ku, Sapporo 060-8628, Japan
-
- Hironori Suzuki
- Transportation and Traffic Systems, Graduate School of Engineering, Hokkaido University, Kita-13, Nishi-8, Kita-ku, Sapporo 060-8628, Japan
説明
<jats:p> Traffic information from probe vehicles has great potential for improving the estimation accuracy of traffic situations, especially where no traffic detector is installed. A method for dealing with probe data along with conventional detector data to estimate traffic states is proposed. The probe data were integrated into the observation equation of the Kalman filter, in which state equations are represented by a macroscopic traffic-flow model. Estimated states were updated with information from both stationary detectors and probe vehicles. The method was tested under several traffic conditions by using hypothetical data, giving considerably improved estimation results compared to those estimated without probe data. Finally, the application of the proposed method was extended to the estimation and short-term prediction of travel time. Travel times were obtained indirectly through the conversion of speeds estimated or predicted by the proposed method. Experimental results show that the performance of travel-time estimation or prediction is comparable to that of some existing methods. </jats:p>
収録刊行物
-
- Transportation Research Record: Journal of the Transportation Research Board
-
Transportation Research Record: Journal of the Transportation Research Board 1855 (1), 49-59, 2003-01
SAGE Publications
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1360574095931533312
-
- NII論文ID
- 30027081288
-
- DOI
- 10.3141/1855-06
-
- ISSN
- 21694052
- 03611981
-
- データソース種別
-
- Crossref
- CiNii Articles