Bluetooth as a traffic sensor for stream travel time estimation under Bogazici Bosporus conditions in Turkey

被引:15
作者
Erkan İ. [1 ]
Hastemoglu H. [1 ]
机构
[1] Faculty of Architecture, Suleyman Demirel University, Cunur, İsparta
来源
Journal of Modern Transportation | 2016年 / 24卷 / 3期
关键词
Istanbul traffic; Public transport; Traffic management; Traffic time estimation; Travel time;
D O I
10.1007/s40534-016-0101-y
中图分类号
学科分类号
摘要
Travel time estimation is an integral part of Intelligent Transportation Systems, and has been an important component in traffic management and operations for many years. Travel time, being spatial in nature, requires spatial sensors to measure it accurately. Bluetooth is emerging as a promising technology for the direct measurement of travel time, and is reported in a few studies from homogenous traffic conditions. At the same time, there have been no studies on the applicability of Bluetooth for travel time estimation in heterogeneous traffic seen in Istanbul and even that Turkey. Bluetooth data collected from a busy urban road in Istanbul city have been analyzed and the penetration rate was found to be about 5 %. Two wheelers and light motor vehicles have been detected using the Bluetooth sensor and the data have been extrapolated to estimate travel times of other classes of vehicles. The study developed linear relationships between speeds of different classes of vehicles through weighted linear regression methods and were used for the estimation of stream travel time. The results obtained were promising and show that Bluetooth is a cost-effective technology for estimation of travel time for heterogeneous traffic conditions. © 2016, The Author(s).
引用
收藏
页码:207 / 214
页数:7
相关论文
共 41 条
[1]  
Lin H.E., Zito R., Taylor M.A.P., A review of travel time prediction in transport and logistics, Proc East Asia Soc Transp Stud, 5, pp. 1433-1448, (2005)
[2]  
Soriguera Marti F., Rosas Diaz D.M., Abeijon Monjas D., Thorson Bofarull L., Robuste Anton F., Travel time estimation from multiple data sources, In: 11th world conference on transport research, (2007)
[3]  
Stiener A., An improved method for travel time estimation on long freeway sections. In: conference paper STRC 2008, 8th Swiss transport research conference, (2008)
[4]  
Haghani A., Hamedi M., Sadabadi K.F., Young S., Tarnoff P., Data collection of freeway travel time ground truth with Bluetooth sensors, no. 2160, transportation research record, transportation research board of the national academies, Washington, D.C, pp. 60-68, (2010)
[5]  
Young S., Bluetooth traffic monitoring technology: concept of operation and deployment guidelines, (2008)
[6]  
Coifman B., Kim S., Speed estimation and length based vehicle classification from freeway single-loop detectors, Transp Res Part C Emerg Technol, 17, pp. 349-364, (2009)
[7]  
Coifman B., Krishnamurthy S., Vehicle reidentification and travel time measurement across freeway junctions using the existing detector infrastructure, Transp Res Part C Emerg Technol, 15, 3, pp. 135-153, (2007)
[8]  
Bhaskar A., Qu M., Nantes A., Miska M., Chung E., Is bus overrepresented in Bluetooth MAC scanner data? Is MAC-ID really unique?, Int J Intell Transp Syst Res, 13, 2, pp. 119-130, (2015)
[9]  
Cortes C., Lavanya R., Oh J.S., Jayakrishnan R., General-purpose methodology for estimating link travel time with multiple-point detection of traffic, Transp Res Rec J Transp Res Board, 1802, pp. 181-189, (2002)
[10]  
Dailey D.J., A statistical algorithm for estimating speed from single loop volume and occupancy measurements, Transp Res Part B Methodol, 33, 5, pp. 313-322, (1999)