DocumentCode :
2537103
Title :
Estimation of bus travel time incorporating dwell time for APTS applications
Author :
Padmanaban, R.P. ; Vanajakshi, Lelitha ; Subramanian, Shankar C.
Author_Institution :
Dept. of Civil Eng., Indian Inst. of Technol. Madras, Chennai, India
fYear :
2009
fDate :
3-5 June 2009
Firstpage :
955
Lastpage :
959
Abstract :
Congestion has become a serious problem in the context of urban transport around the world. As more and more vehicles are being introduced into the urban streets every year, the mode share of the public transportation sector is declining at an alarming rate. Particularly in developing countries, more people have moved to personalized mode since it is becoming easily affordable and the quality of service offered by the public transit is not improving. To attract more people, the public transit should provide a high level of quality service to the passengers. One way of achieving this is by using Advanced Public Transport Systems (APTS) applications such as providing accurate real-time bus arrival information to the passengers which will improve the service reliability of the public transit. Travel time prediction has been a well-renowned topic of research for years. However, studies which were model based and incorporating dwell times at bus stops explicitly for heterogeneous traffic conditions are limited. The present study tries to explicitly incorporate the bus stop delays associated with the total travel times of the buses under heterogeneous traffic conditions. This will help in obtaining a reliable algorithm which can be adopted for bus arrival time prediction under Indian conditions.
Keywords :
estimation theory; road vehicles; traffic information systems; transportation; advanced public transport system; bus arrival time prediction; bus stop delays; bus travel time estimation; heterogeneous traffic condition; passengers; public transit; public transportation sector; quality service; real-time bus arrival information; reliable algorithm; service reliability; urban streets; urban transport; vehicles; Delay effects; Filtering; Intelligent transportation systems; Kalman filters; Machine learning; Machine learning algorithms; Predictive models; Roads; Traffic control; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium, 2009 IEEE
Conference_Location :
Xi´an
ISSN :
1931-0587
Print_ISBN :
978-1-4244-3503-6
Electronic_ISBN :
1931-0587
Type :
conf
DOI :
10.1109/IVS.2009.5164409
Filename :
5164409
Link To Document :
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