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Traffic Monitoring using Road Side Sensors: Modeling and Estimation
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In many modern societies, different sensors have started to penetrate life in many new ways.Examples include personal devices for monitoring health and well-being, supervision and power distribution in the smart grid, or smart farming that takesweather and soil conditions into account to efficiently cultivate fields. In order to obtain the desired data, such sensor systems requirewell-designed signal processing algorithms that infer the parameters of interest from the measured quantities. In this thesis, algorithms for traffic monitoring using road side sensors are proposed. Thesensors considered are a combination of an accelerometer measuring road surfacewaves and a magnetometer measuring magnetic disturbances, both caused by vehicles passing the sensors.The research problems addressed are: (1) the feasibility of using road surface waves fortraffic monitoring, (2) the modeling of road surface waves, and (3) combining the measurements of the accelerometer and the magnetometer.These three problems are addressed in the six research papers composing this thesis. First, it is shown that it is indeed viable to exploit road surface waves for estimating vehicle parameters and research challenges are identified by analyzing a first field test. Based on these conclusions, it is shown how to model waves in pavements using system identification and a semi-parametric wave propagation model. Furthermore, an efficient algorithm for estimating the driving direction using magnetometers only is proposed and evaluated. Finally, it is shown how to combine the two sensors. First, an iterative particle smootherbased system identification algorithm is used to jointly estimate the vehicle trajectory as wellas unknown parameters in the system model. Second, a multi-rate particle filter is proposed where unknown parameters are treated through marginalization.Based on the work in this thesis, future research directions are proposed. These include the improvement of some of the models to address problems encountered in the trajectory estimation and tracking algorithms aswell as further development of the estimation methods to make them more efficient and take prior information and constraints into account.

Place, publisher, year, edition, pages
Luleå tekniska universitet, 2014.
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
National Category
Control Engineering
Research subject
Control Engineering
URN: urn:nbn:se:ltu:diva-17161Local ID: 1f6310b8-4729-4026-8c0a-8e0007ce77bcISBN: 978-91-7439-956-1 (print)ISBN: 978-91-7439-957-8 (electronic)OAI: diva2:990160
Godkänd; 2014; 20140411 (rolhos); Nedanstående person kommer att disputera för avläggande av teknologie doktorsexamen. Namn: Roland Hostettler Ämne: Reglerteknik/Automatic Control Avhandling: Traffic Monitoring using Road Side Sensors: Modeling and Estimation Opponent: Professor Thomas Schön, Avd för systemteknik, Institutionen för informationsteknologi, Uppsala universitet, Ordförande: Biträdande professor Wolfgang Birk, Avd för system och interaktion, Institutionen för system- och rymdteknik, Luleå tekniska universitet Tid: Onsdag den 18 juni 2014, kl 09.00 Plats: A1545, Luleå tekniska universitetAvailable from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved

Open Access in DiVA

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