Tracking vehicles from mobile phones has applications, among others, in traffic monitoring, location-based services, and personal navigation. We address the problem of tracking vehicles from received signal strength (RSS) sequences generated by mobile phones carried by passengers. A mobile phone periodically measures the RSS levels from the associated cell tower and several (six for GSM) strongest neighbor cell towers. Each such measurement is known as an RSS fingerprint. However, due to various effects, the contents of fingerprints may vary over time even when measured at the same location. These variations have two components. First is the fluctuation of the RSS levels. Second is the variation of the set of cell towers reported in fingerprints. The latter is not properly modeled by traditional methods. To address both components of variation, we propose a probabilistic model for RSS fingerprints that specifies for each gird-location in the area of interest, the distribution of the probability of observing any fingerprint at that location. We then use it as the observation model of a Dynamic Bayesian Network to track vehicles. Experiments on several roads demonstrate a 40% reduction in average error with our method compared to its traditional counterparts. Using RSS sequences of phone calls made by road users, our algorithm produced better travel-time estimates than comparison methods for a selected road segment with an average error of 13% with respect to travel-times computed through manual license plate recognition.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Complete Observation Model for Tracking Vehicles from Mobile Phone Signal Strengths and Its Potential in Travel-Time Estimation


    Contributors:


    Publication date :

    2016-09-01


    Size :

    513994 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Travel Time Information Service Utilising Mobile Phone Tracking

    Caj Holm / Mario Anžek / Slobodan Kaštela | DOAJ | 2004

    Free access

    Exploring strengths and weaknesses of mobility inference from mobile phone data vs. travel surveys

    Caceres, Noelia / Romero, L. M. / Benitez, Francisco G. | Taylor & Francis Verlag | 2020


    Signal intersection road travel time calculating method based on mobile phone switching data

    YANG FEI / DAI LU / YAO ZHENXING et al. | European Patent Office | 2016

    Free access


    Predicting travel time reliability using mobile phone GPS data

    Woodard, Dawn / Nogin, Galina / Koch, Paul et al. | Elsevier | 2016