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dc.contributor.authorDavis, Blake
dc.contributor.authorJi, Ang
dc.contributor.authorLiu, Bichen
dc.contributor.authorLevinson, David M.
dc.date.accessioned2019-11-11
dc.date.available2019-11-11
dc.date.issued2019-11-11
dc.identifier.urihttps://hdl.handle.net/2123/21344
dc.description.abstractThis paper explores the potential of moving array ‘probes’ to collect traffic data. This application simulates the prospect of mining environmental data on traffic conditions to present a cheap and potentially widespread source of traffic conditions. Based on three different simulations, we measure the magnitude and trends of probe error (comparing the probe’s ‘subjective’ or time-weighted perception with an ‘objective’ observer) in density, speed, and flow in order to validate the proposed model and compare the results with loop detectors. From these simulations, several conclusions were reached. A single probe’s error follows a double hump trend due to an interplay between the factors of traffic heterogeneity and shockwaves. Reduced visibility of the single probe does not proportionately increase the error. Multiple probes do not tend to increase accuracy significantly, which suggests that the data will be still useful even if probes are sparsely distributed. Finally, probes can measure the conditions of oncoming traffic more accurately than concurrent traffic. Further research is expected to consider more complex road networks and develop methods to improve the accuracy of moving array samples.en_AU
dc.language.isoen_AUen_AU
dc.subjectAutonomous vehiclesen_AU
dc.subjectprobesen_AU
dc.subjecttraffic state estimationen_AU
dc.subjectfloating car dataen_AU
dc.titleMoving Array Traffic Probesen_AU
dc.typeWorking Paperen_AU
dc.subject.asrcFoR::090507 - Transport Engineeringen_AU
dc.type.pubtypePre-printen_AU
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