Bayesian Route Choice Inference to Address Missed Bluetooth Detections

Simple item page
dc.contributor.authorGarrido Valenzuela, Francisco Orlando
dc.contributor.authorRaveau Feliú, Sebastián
dc.contributor.authorHerrera Maldonado, Juan Carlos
dc.date.accessioned2022-05-18T14:39:47Z
dc.date.available2022-05-18T14:39:47Z
dc.date.issued2020
dc.description.abstractBy installing wireless sensors such as Bluetooth or Wi-Fi at a specific set of intersections and/or roadways it is possible to detect the passage of vehicles equipped with these technologies. However, Wi-Fi or Bluetooth-equipped vehicles are not necessarily detected by every sensor they pass by, as the detection probability depends on several factors, such as weather, nearby infrastructure, or the vehicle's speed. To address this lack of perfect information, we propose a methodology to infer the most likely route used by a vehicle between two successive detections. The methodology consists of three stages. The first stage entails constructing a graph of the road network and the location of the sensors. The second stage consists of using the wireless data to calibrate the distribution of dwell time at each node and travel time for each link of the graph defined in the first stage. The third and final stage consists of convoluting node and link time distributions between successive detections to obtain an aggregate time distribution for each potential route. A Bayesian inference is then applied based on the travel time observed for each vehicle and the number of missed detections, to determine the probability of each alternative route. The methodology is tested through microsimulations, showing a prediction performance of over 90% in most favorable scenarios tested. When compared to a benchmark approach to infer routes, the proposed methodology provides better results when the network's sensory density is low and data available are reduced.
dc.fuente.origenIEEE
dc.identifier.doi10.1109/TITS.2020.3028804
dc.identifier.issn1558-0016
dc.identifier.urihttps://doi.org/10.1109/TITS.2020.3028804
dc.identifier.urihttps://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9228868
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/64156
dc.information.autorucEscuela de ingeniería ; Garrido Valenzuela, Francisco Orlando ; S/I ; 194046
dc.information.autorucEscuela de ingeniería ; Raveau Feliu, Sebastián ; S/I ; 141271
dc.information.autorucEscuela de ingeniería ; Herrera Maldonado, Juan Carlos ; S/I ; 3146
dc.issue.numero3
dc.language.isoen
dc.nota.accesoContenido parcial
dc.pagina.final1874
dc.pagina.inicio1865
dc.revistaIEEE Transactions on Intelligent Transportation Systems
dc.rightsacceso restringido
dc.subjectSensors
dc.subjectBluetooth
dc.subjectWireless fidelity
dc.subjectTrajectory
dc.subjectRoads
dc.subjectBayes methods
dc.subjectDirected graphs
dc.titleBayesian Route Choice Inference to Address Missed Bluetooth Detectionses_ES
dc.typeartículo
dc.volumen23
sipa.codpersvinculados194046
sipa.codpersvinculados141271
sipa.codpersvinculados3146
Files
Collections
Artículos de revistas