Vehicle Detection System for Smart Crosswalks Using Sensors and Machine Learning

Jose Manuel Lozano Dominguez, Faroq Al-Tam, Tomas De J.Mateo Sanguino, Noelia Correia

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddTrafodion Cynhadledd (Nid-Cyfnodolyn fathau)

7 Dyfyniadau (Scopus)

Crynodeb

Cities are transforming into smart areas thanks to several key technologies involving artificial intelligence (AI), 5G or big data aimed at improving the lives of their inhabitants with new services (e.g., transport systems, including road safety). In this field, the paper describes how to improve vehicle detection through several machine learning techniques applied to smart crosswalks. As a main advantage, this approach avoids readjusting labels in classic fuzzy classifiers that typically depends on the system location and road conditions. To address this, various AI methods were evaluated with data taken from real traffic pertaining to roads in Spain and Portugal. The machine learning techniques were random forest (RF), extremely randomized trees (extra-tree), deep reinforcement learning (DRL), time series forecasting (TSF), multi-layer perceptron (MLP), k-nearest neighbor (KNN) and logistic regression (LR). The results were validated through a receiver operating characteristic (ROC) analysis, obtaining the best performance in RF with a true positive rate (TPR) of 96.82%, false positive rate (FPR) of 1.73% and accuracy (ACC) of 97.85%. This was followed by DRL and TSF, while MLP and LR presented the worst outcomes.

Iaith wreiddiolSaesneg
Teitl18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021
CyhoeddwrIEEE Press
Tudalennau984-991
Nifer y tudalennau8
ISBN (Electronig)9781665414937
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 21 Mai 2021
DigwyddiadSystems, Signals and Devices - Monastir, Tiwnisia
Hyd: 22 Maw 202125 Maw 2021
Rhif y gynhadledd: 18

Cyfres gyhoeddiadau

Enw18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021

Cynhadledd

CynhadleddSystems, Signals and Devices
Teitl crynoSSD-2021
Gwlad/TiriogaethTiwnisia
DinasMonastir
Cyfnod22 Maw 202125 Maw 2021

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