NDLI: An arterial speed estimation model fusing data from stationary and mobile sensors

Content Provider	IEEE Xplore Digital Library
Author	Ruey Long Cheu Der-Horng Lee Chi Xie
Copyright Year	2001
Description	Author affiliation: Dept. of Civil Eng., Nat. Univ. of Singapore, Singapore (Ruey Long Cheu)
Abstract	This paper presents an arterial speed estimation model using data from two distinct sources: mobile probe vehicles and inductive loop detectors. The model consists of three modules: (1) the probe vehicle module which measures arterial speed using vehicles equipped with differential global positioning system receivers; (2) the loop detector module which estimates the link speed using loop detector data, incorporating traffic signal timing parameters; and (3) the data fusion module which uses a neural network to combine outputs from the above two modules to improve the speed estimation accuracy. The computational procedures of the three modules are presented. This paper presents a validation test of the model using a set of data generated from a calibrated simulation model. Our test results show that, the probe vehicle and loop detector modules are capable of making speed estimation with 2-RMSE of less than 3.20 km/h. Using a neural network to fuse the estimates from the two sources reduces the 2-RMSE to less than 1.32 km/h.
Starting Page	573
Ending Page	578
File Size	481813
Page Count	6
File Format	PDF
ISBN	0780371941
DOI	10.1109/ITSC.2001.948723
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-08-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vehicle detection Detectors Probes Vehicles Neural networks Testing Position measurement Velocity measurement Telecommunication traffic Traffic control
Content Type	Text
Resource Type	Article

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