Smart City Gnosys

Smart city article details

Title	Towards The Next Generation Intelligent Transportation System: A Vehicle Detection And Counting Framework For Undisciplined Traffic Conditions
ID_Doc	58424
Authors	Ahmed S.H.; Raza M.; Kazmi M.; Mehdi S.S.; Rehman I.; Qazi S.A.
Year	2023
Published	Neural Network World, 33, 3
DOI	http://dx.doi.org/10.14311/NNW.2023.33.011
Abstract	Modern development in deep learning and computer vision techniques, intelligent transportation system (ITS) has emerged as a useful tool for building a traffic infrastructure in smart cities. Previously, several computer vision techniques have been proposed for vehicle recognition, which were limited in handling undisciplined, dense and laneless traffic conditions. Moreover, these frameworks did not incorporate many of the local vehicle configurations common in South Asian countries such as Pakistan, Bangladesh, and India. Considering the limitations of previous frameworks, this paper presents efficient vehicle detection and counting model for undisciplined conditions including dense and laneless traffic, occulusion cases and diverse range of local vehicles. A dataset of more than 2400 images of vehicles has been collected comprising of six new categories of local vehicles, and considering undisciplined traffic conditions to ensure robustness in vehicle detection and counting system. Transfer learning based technique has been used, using faster R-CNN model with Inception V2 as underlying architecture. The experimental results show a precision of 86.14% in terms of mAP. The work finds its application in South Asian contexts as more smart cities are formed in this region. The proposed framework will enable traffic monitoring with higher reliability, accuracy and granularity, contributing in having next-generation ITS. © 2023 Institute of Computer Science. All rights reserved.
Author Keywords	computer vision; image classification; intelligent transportation systems; recurrent neural networks; transfer learning; vehicle detection

Similar Articles

Id	Similarity	Authors	Title	Published
17847	0.901	Sisaudia V.; Giri S.K.	Deep Learning Based Novel Vehicle Detection And Counting System	7th International Conference on Communication and Electronics Systems, ICCES 2022 - Proceedings (2022)
60905	0.898	Kejriwal R.; Ritika H.J.; Arora A.; Mohana	Vehicle Detection And Counting Using Deep Learning Basedyolo And Deep Sort Algorithm For Urban Traffic Management System	2022 1st International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2022 (2022)
5776	0.896	Lucking M.; Rivera E.; Kohout L.; Zimmermann C.; Polad D.; Stork W.	A Video-Based Vehicle Counting System Using An Embedded Device In Realistic Traffic Conditions	IEEE World Forum on Internet of Things, WF-IoT 2020 - Symposium Proceedings (2020)
51587	0.895	Lingani G.M.; Rawat D.B.; Garuba M.	Smart Traffic Management System Using Deep Learning For Smart City Applications	2019 IEEE 9th Annual Computing and Communication Workshop and Conference, CCWC 2019 (2019)
44480	0.894	Srikanth M.; Krishna N.S.V.S.S.J.; Krishna S.J.S.; Irfan S.; Venkat T.G.	Real-Time Vehicle Detection And Road Condition Prediction For Smart Urban Areas	Proceedings of the 4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024 (2024)
7402	0.891	Ghosh A.; Sabuj M.S.; Sonet H.H.; Shatabda S.; Farid D.M.	An Adaptive Video-Based Vehicle Detection, Classification, Counting, And Speed-Measurement System For Real-Time Traffic Data Collection	Proceedings of 2019 IEEE Region 10 Symposium, TENSYMP 2019 (2019)
60924	0.89	Sharma P.; Singh A.; Singh K.K.; Dhull A.	Vehicle Identification Using Modified Region Based Convolution Network For Intelligent Transportation System	Multimedia Tools and Applications, 81, 24 (2022)
24007	0.889	Kumari S.; Kumar T.	Enhancing The Capabilities Of Traffic Surveillance System By Integration Of Intelligent Vehicle Classification Technique	Multimedia Tools and Applications (2025)
60898	0.889	Alsanabani A.A.; Ahmed M.A.; Al Smadi A.M.	Vehicle Counting Using Detecting-Tracking Combinations: A Comparative Analysis	ACM International Conference Proceeding Series, PartF168342 (2020)
61087	0.888	Mirthubashini J.; Santhi V.	Video Based Vehicle Counting Using Deep Learning Algorithms	2020 6th International Conference on Advanced Computing and Communication Systems, ICACCS 2020 (2020)