TY - GEN
T1 - Development of an effective travel time prediction method using modified moving average approach
AU - Chowdhury, Nihad Karim
AU - Nath, Rudra Pratap Deb
AU - Lee, Hyunjo
AU - Chang, Jaewoo
PY - 2009/12/4
Y1 - 2009/12/4
N2 - Prediction of travel time on road network has emerged as a crucial research issue in intelligent transportation system (ITS). Travel time prediction provides information that may allow travelers to change their routes as well as departure time. To provide accurate travel time for travelers is the key challenge in this research area. In this paper, we formulate two new methods which are based on moving average can deal with this kind of challenge. In conventional moving average approach, data may lose at the beginning and end of a series. It may sometimes generate cycles or other movements that are not present in the original data. Our proposed modified method can strongly tackle those kinds of uneven presence of extreme values. We compare the proposed methods with the existing prediction methods like Switching method [10] and NBC method [11]. It is also revealed that proposed methods can reduce error significantly in compared with other existing methods.
AB - Prediction of travel time on road network has emerged as a crucial research issue in intelligent transportation system (ITS). Travel time prediction provides information that may allow travelers to change their routes as well as departure time. To provide accurate travel time for travelers is the key challenge in this research area. In this paper, we formulate two new methods which are based on moving average can deal with this kind of challenge. In conventional moving average approach, data may lose at the beginning and end of a series. It may sometimes generate cycles or other movements that are not present in the original data. Our proposed modified method can strongly tackle those kinds of uneven presence of extreme values. We compare the proposed methods with the existing prediction methods like Switching method [10] and NBC method [11]. It is also revealed that proposed methods can reduce error significantly in compared with other existing methods.
KW - Intelligent transportation system
KW - Moving average
KW - NBC method
KW - Switching method
KW - Travel time prediction
UR - http://www.scopus.com/inward/record.url?scp=70849118580&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04595-0_16
DO - 10.1007/978-3-642-04595-0_16
M3 - Article in proceeding
AN - SCOPUS:70849118580
SN - 3642045944
SN - 9783642045943
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 130
EP - 138
BT - Knowledge-Based and Intelligent Information and Engineering Systems - 13th International Conference, KES 2009, Proceedings
T2 - 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2009
Y2 - 28 September 2009 through 30 September 2009
ER -