[1] Y. Agarwal, K. Jain, and O. Karabasoglu, “Smart vehicle monitoring and assistance using cloud computing in vehicular Ad Hoc networks,” Int. J. Transp. Sci. Technol., vol. 7, no. 1, pp. 60–73, 2018, doi: 10.1016/j.ijtst.2017.12.001.

[2] M. Agbali, C. Trillo, T. Fernando, I. A. Ibrahim, and Y. Arayici, “Conceptual Smart City KPI Model: A System Dynamics Modelling Approach,” Proc. 2nd World Conf. Smart Trends Syst. Secur. Sustain. WorldS4 2018, pp. 158–162, 2019, doi: 10.1109/WorldS4.2018.8611565.

[3] S. H. Ahmed, M. A. Yaqub, S. H. Bouk, and D. Kim, “Towards content-centric traffic ticketing in VANETs: An application perspective,” Int. Conf. Ubiquitous Futur. Networks, ICUFN, vol. 2015-Augus, pp. 237–239, 2015, doi: 10.1109/ICUFN.2015.7182541.

[4] G. Aisyah and P. Bestari, “Implementation E-Tilang in Bandung to Increase Awareness of Cross as Moral Law Passed Citizenship (Civic Virtue),” vol. 251, no. 22, pp. 664–667, 2018, doi: 10.2991/acec-18.2018.148.

[5] Z. Al-Ars, S. van der Vlugt, P. Jääskeläinen, and F. van der Linden, “ALMARVI System Solution for Image and Video Processing in Healthcare, Surveillance and Mobile Applications,” J. Signal Process. Syst., vol. 91, no. 1, pp. 1–7, 2019, doi: 10.1007/s11265-018-1423-2.

[6] Z. Allam and P. Newman, “Redefining the Smart City: Culture, Metabolism and Governance,” Smart Cities, vol. 1, no. 1, pp. 4–25, 2018, doi: 10.3390/smartcities1010002.

[7] B. A. Alpatov, P. V. Babayan, and M. D. Ershov, “Vehicle detection and counting system for real-time traffic surveillance,” 2018 7th Mediterr. Conf. Embed. Comput. MECO 2018 - Incl. ECYPS 2018, Proc., no. June, pp. 1–4, 2018, doi: 10.1109/MECO.2018.8406017.

[8] A. A. Ambardekar and T. Advisor, “Efficient Vehicle Tracking and Classification for an Automated Traffic Surveillance System,” 2007.

[9] M. Angelidou, A. Psaltoglou, N. Komninos, C. Kakderi, P. Tsarchopoulos, and A. Panori, “Enhancing sustainable urban development through smart city applications,” J. Sci. Technol. Policy Manag., vol. 9, no. 2, pp. 146–169, 2018, doi: 10.1108/JSTPM-05-2017-0016.

[10] A. Appathurai, R. Sundarasekar, C. Raja, E. J. Alex, C. A. Palagan, and A. Nithya, “An Efficient Optimal Neural Network-Based Moving Vehicle Detection in Traffic Video Surveillance System,” Circuits, Syst. Signal Process., vol. 39, no. 2, pp. 734–756, 2020, doi: 10.1007/s00034-019-01224-9.

[11] P. April Insani, “Mewujudkan Kota Responsif Melalui Smart City,” PUBLISIA (Jurnal Ilmu Adm. Publik), vol. 2, no. Smart City, pp. 25–31, 2017.

[12] P. Bellavista, F. Caselli, A. Corradi, and L. Foschini, “Cooperative vehicular traffic monitoring in realistic low penetration scenarios: The COLOMBO experience,” Sensors (Switzerland), vol. 18, no. 3, 2018, doi: 10.3390/s18030822.

[13] T. Berglund, A. Brodnik, H. Jonsson, M. Staffanson, and I. Söderkvist, “Planning smooth and obstacle-avoiding B-spline paths for autonomous mining vehicles,” IEEE Trans. Autom. Sci. Eng., vol. 7, no. 1, pp. 167–172, 2010, doi: 10.1109/TASE.2009.2015886.

[14] T. M. A.-U.-H. Bhuiyan, M. Das, and M. S. R. Sajib, “Computer vision based traffic monitoring and analyzing from on-road videos,” Glob. J. Comput. Sci. Technol., vol. 19, no. 2, 2019.

[15] A. Bondy, D. Sheslow, and L. T. Garcia, “An investigation of children’s fears and their mothers’ fears,” J. Psychopathol. Behav. Assess., vol. 7, no. 1, pp. 1–12, 1985, doi: 10.1007/BF00961842.

[16] C. L. Bottasso, D. Leonello, and B. Savini, “Path planning for autonomous vehicles by trajectory smoothing using motion primitives,” IEEE Trans. Control Syst. Technol., vol. 16, no. 6, pp. 1152–1168, 2008, doi: 10.1109/TCST.2008.917870.

[17] P. Cardullo and R. Kitchin, “Being a ‘citizen’ in the smart city: up and down the scaffold of smart citizen participation in Dublin, Ireland,” GeoJournal, vol. 84, no. 1, 2019, doi: 10.1007/s10708-018-9845-8.

[18] J. Chang, L. Wang, G. Meng, S. Xiang, and C. Pan, “Vision-based occlusion handling and vehicle classification for traffic surveillance systems,” IEEE Intell. Transp. Syst. Mag., vol. 10, no. 2, pp. 80–92, 2018, doi: 10.1109/MITS.2018.2806619.

[19] S. Chaudhuri and U. Dayal, “Data warehousing and OLAP for decision support,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 1341, pp. 33–34, 1997, doi: 10.1007/3-540-63792-3_6.

[20] S. Chaudhuri and U. Dayal, “An Overview of Data Warehousing and OLAP Technology,” SIGMOD Rec. (ACM Spec. Interes. Gr. Manag. Data), vol. 26, no. 1, pp. 65–74, 1997, doi: 10.1145/248603.248616.

[21] J. W. Choi, R. Curry, and G. Elkaim, “Path planning based on bézier curve for autonomous ground vehicles,” Proc. - Adv. Electr. Electron. Eng. - IAENG Spec. Ed. World Congr. Eng. Comput. Sci. 2008, WCECS 2008, no. 2, pp. 158–166, 2008, doi: 10.1109/WCECS.2008.27.

[22] G. Corraro, F. Corraro, E. De Lellis, and L. Garbarino, “Flight tests of ADS-B traffic advisory system (ATAS) and performance comparison with other surveillance systems,” AIAA Aerosp. Sci. Meet. 2018, no. 210059, 2018, doi: 10.2514/6.2018-0286.

[23] R. Cowley, S. Joss, and Y. Dayot, “The smart city and its publics: insights from across six UK cities,” Urban Res. Pract., vol. 11, no. 1, pp. 53–77, 2018, doi: 10.1080/17535069.2017.1293150.

[24] M. Desai and A. Phadke, “Internet of Things based vehicle monitoring system,” IFIP Int. Conf. Wirel. Opt. Commun. Networks, WOCN, pp. 1–3, 2017, doi: 10.1109/WOCN.2017.8065840.

[25] N. K. Dewi et al., “Konsep Aplikasi E-Dakwah Untuk Generasi Milenial Jakarta penting dalam menyiarkan agama Islam . Dengan media dakwah yang tepat maka akan bisa menyiarkan agama Islam dengan maksimal dengan media dakwah yang tepat suatu konsep dalam berdakwah dengan E-Dakwah digunakan untuk generasi milenial Jakarta akan bisa ikut ke dalam syiar agama Islam yang harus terus dijalankan di masa Gambar 1 Metode Penelitian penjelasan di bawah ini?: a . Tinjauan Pustaka studi tinjauan pustaka ( Putr

[26] N. K. Dewi, I. Mulyana, A. S. Putra, and F. R. Radita, “Tampilan Konsep Robot Penjaga Toko Di Kombinasikan Dengan Pengendalian Virtual Reality (VR) Jarak Jauh,” J. IKRA-ITH Inform., vol. 5, no. 1, pp. 33–38, 2021, [Online]. Available: https://journals.upi-yai.ac.id/index.php/ikraith-informatika/article/view/911/702.

[27] N. K. Dewi and A. S. Putra, “PENERIMAAN KARYAWAN BARU DENGAN,” vol. 6, no. 2, pp. 154–160, 2020.

[28] T. Durand, X. He, I. Pop, and L. Robinault, Utilizing deep object detector for video surveillance indexing and retrieval, vol. 11296 LNCS. Springer International Publishing, 2019.

[29] M. A. Elliott, C. J. Baughan, and B. F. Sexton, “Errors and violations in relation to motorcyclists’ crash risk,” Accid. Anal. Prev., vol. 39, no. 3, pp. 491–499, 2007, doi: 10.1016/j.aap.2006.08.012.

[30] J. Gao and H. Tembine, “Distributed Mean-Field-Type Filters for Traffic Networks,” IEEE Trans. Intell. Transp. Syst., vol. 20, no. 2, pp. 507–521, 2019, doi: 10.1109/TITS.2018.2816811.

[31] B. Garau, A. Alvarez, and G. Oliver, “Path planning of autonomous underwater vehicles in current fields with complex spatial variability: An A* approach,” Proc. - IEEE Int. Conf. Robot. Autom., vol. 2005, no. April, pp. 194–198, 2005, doi: 10.1109/ROBOT.2005.1570118.

[32] S. Gardens and P. E. A. Hofsass, “United States Patent (19),” no. 19, 1995.

[33] K. Garg, N. Ramakrishnan, A. Prakash, and T. Srikanthan, “Rapid and Robust Background Modeling Technique for Low-Cost Road Traffic Surveillance Systems,” IEEE Trans. Intell. Transp. Syst., vol. 21, no. 5, pp. 2204–2215, 2020, doi: 10.1109/TITS.2019.2917560.

[34] P. Giannakeris, V. Kaltsa, K. Avgerinakis, A. Briassouli, S. Vrochidis, and I. Kompatsiaris, “Speed estimation and abnormality detection from surveillance cameras,” IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. Work., vol. 2018-June, pp. 93–99, 2018, doi: 10.1109/CVPRW.2018.00020.

[35] M. G. Gnoni, A. Rollo, and P. Tundo, “A smart model for urban ticketing based on RFID applications,” IEEM 2009 - IEEE Int. Conf. Ind. Eng. Eng. Manag., pp. 2353–2357, 2009, doi: 10.1109/IEEM.2009.5373004.

[36] E. Guerra, “Planning for Cars That Drive Themselves: Metropolitan Planning Organizations, Regional Transportation Plans, and Autonomous Vehicles,” J. Plan. Educ. Res., vol. 36, no. 2, pp. 210–224, 2016, doi: 10.1177/0739456X15613591.

[37] G. Guido, V. Gallelli, D. Rogano, and A. Vitale, “Evaluating the accuracy of vehicle tracking data obtained from Unmanned Aerial Vehicles,” Int. J. Transp. Sci. Technol., vol. 5, no. 3, pp. 136–151, 2016, doi: 10.1016/j.ijtst.2016.12.001.

[38] G. Guido, A. Vitale, F. F. Saccomanno, V. Astarita, and V. Giofrè, “Vehicle Tracking System based on Videotaping Data,” Procedia - Soc. Behav. Sci., vol. 111, pp. 1123–1132, 2014, doi: 10.1016/j.sbspro.2014.01.147.

[39] H. Gunawan and Lynawati, “Analisis Penerimaan Teknologi ‘Smart City’ Kota Purwokerto Dengan Model Technology Acceptance Model (TAM),” Konf. Nas. Sist. Inf., pp. 129–134, 2018, [Online]. Available: http://jurnal.atmaluhur.ac.id/index.php/knsi2018/article/view/347/272.

[40] C. El Hatri and J. Boumhidi, “Fuzzy deep learning based urban traffic incident detection,” 2017 Intell. Syst. Comput. Vision, ISCV 2017, 2017, doi: 10.1109/ISACV.2017.8054903.

[41] Hanok Mandaku, “Studi Penerapan Intelligent Transportation System ( Its ),” vol. 04, no. 1, 2010

[42] J. Z. Hernández, S. Ossowski, and A. García-Serrano, “Multiagent architectures for intelligent traffic management systems,” Transp. Res. Part C Emerg. Technol., vol. 10, no. 5–6, pp. 473–506, 2002, doi: 10.1016/S0968-090X(02)00032-3.

[43] J. I. Hernández-Vega, E. R. Varela, N. H. Romero, C. Hernández-Santos, J. L. S. Cuevas, and D. G. P. Gorham, Internet of things (IoT) for monitoring air pollutants with an unmanned aerial vehicle (UAV) in a smart city, vol. 213. Springer International Publishing, 2018.

[44] G. T. S. Ho, Y. P. Tsang, C. H. Wu, W. H. Wong, and K. L. Choy, “A computer vision-based roadside occupation surveillance system for intelligent transport in smart cities,” Sensors (Switzerland), vol. 19, no. 8, 2019, doi: 10.3390/s19081796.

[45] Y. Huang, Z. Liu, M. Jiang, X. Yu, and X. Ding, “Cost-Effective Vehicle Type Recognition in Surveillance Images with Deep Active Learning and Web Data,” IEEE Trans. Intell. Transp. Syst., vol. 21, no. 1, pp. 79–86, 2020, doi: 10.1109/TITS.2018.2888698.

[46] N. K. Jain, R. K. Saini, and P. Mittal, A review on traffic monitoring system techniques, vol. 742. Springer Singapore, 2019.

[47] José Miguel Cisneros Herreros and Germán Peñalva Moreno, “Article in Press Article in Press,” GEF Bull. Biosci., vol. 1, no. 1, pp. 1–6, 2010, doi: 10.1016/j.jinf.2020.02.020.

[48] R. Kala and K. Warwick, “Motion planning of autonomous vehicles in a non-autonomous vehicle environment without speed lanes,” Eng. Appl. Artif. Intell., vol. 26, no. 5–6, pp. 1588–1601, 2013, doi: 10.1016/j.engappai.2013.02.001.

[49] Kenny, “United States Patent (19) 11 Patent Number: 5,348,136,” no. 19, pp. 1992–1995, 1993.

[50] H. J. Kim, “Vehicle detection and speed estimation for automated traffic surveillance systems at nighttime,” Teh. Vjesn., vol. 26, no. 1, pp. 87–94, 2019, doi: 10.17559/TV-20170827091448.

[51] K. J. Kim, P. K. Kim, Y. S. Chung, and D. H. Choi, “Multi-Scale Detector for Accurate Vehicle Detection in Traffic Surveillance Data,” IEEE Access, vol. 7, pp. 78311–78319, 2019, doi: 10.1109/ACCESS.2019.2922479.

[52] S. W. Kim, W. Liu, M. H. Ang, E. Frazzoli, and D. Rus, “The Impact of Cooperative Perception on Decision Making and Planning of Autonomous Vehicles,” IEEE Intell. Transp. Syst. Mag., vol. 7, no. 3, pp. 39–50, 2015, doi: 10.1109/MITS.2015.2409883.

[53] T. Kumar and D. S. Kushwaha, “An intelligent surveillance system based on IoT for internal security of a nation,” Int. J. Inf. Secur. Priv., vol. 13, no. 3, pp. 1–30, 2019, doi: 10.4018/IJISP.201907010101.

[54] M. D. Lee and D. E. Us, “United States Patent Number?:,” no. 19, pp. 1–3, 2010.

[55] X. Li, J. Niu, S. Kumari, F. Wu, and K. K. R. Choo, “A robust biometrics based three-factor authentication scheme for Global Mobility Networks in smart city,” Futur. Gener. Comput. Syst., vol. 83, pp. 607–618, 2018, doi: 10.1016/j.future.2017.04.012.

[56] M. Likhachev and D. Ferguson, “Planning long dynamically-feasible maneuvers for autonomous vehicles,” Robot. Sci. Syst., vol. 4, pp. 214–221, 2009, doi: 10.15607/rss.2008.iv.028.

[57] M. Lu et al., “Cooperative and connected intelligent transport systems for sustainable European road transport Citation for published version (APA): Cooperative and Connected Intelligent Transport Systems for Sustainable European Road Transport,” no. 2018, 2018, [Online]. Available: www.tue.nl/taverne.

[58] Z. Lv, X. Li, W. Wang, B. Zhang, J. Hu, and S. Feng, “Government affairs service platform for smart city,” Futur. Gener. Comput. Syst., vol. 81, pp. 443–451, 2018, doi: 10.1016/j.future.2017.08.047.

[59] S. Lyu et al., “UA-DETRAC 2018: Report of AVSS2018 IWT4S Challenge on Advanced Traffic Monitoring,” Proc. AVSS 2018 - 2018 15th IEEE Int. Conf. Adv. Video Signal-Based Surveill., pp. 1–7, 2019, doi: 10.1109/AVSS.2018.8639089.

[60] V. C. Maha Vishnu, M. Rajalakshmi, and R. Nedunchezhian, “Intelligent traffic video surveillance and accident detection system with dynamic traffic signal control,” Cluster Comput., vol. 21, no. 1, pp. 135–147, 2018, doi: 10.1007/s10586-017-0974-5.

[61] V. Mayya and A. Nayak, Summarization for Detecting Traffic Rules Violators Using R-CNN. Springer Singapore, 2018.

[62] V. A. Memos, K. E. Psannis, Y. Ishibashi, B. G. Kim, and B. B. Gupta, “An Efficient Algorithm for Media-based Surveillance System (EAMSuS) in IoT Smart City Framework,” Futur. Gener. Comput. Syst., vol. 83, no. 2018, pp. 619–628, 2018, doi: 10.1016/j.future.2017.04.039.

[63] A. Mhalla, T. Chateau, S. Gazzah, and N. E. Ben Amara, “An Embedded Computer-Vision System for Multi-Object Detection in Traffic Surveillance,” IEEE Trans. Intell. Transp. Syst., vol. 20, no. 11, pp. 4006–4018, 2019, doi: 10.1109/TITS.2018.2876614.

[64] J. S. B. Mitchell, D. W. Payton, and D. M. Keirsey, “Planning and reasoning for autonomous vehicle control,” Int. J. Intell. Syst., vol. 2, no. 2, pp. 129–198, 1987, doi: 10.1002/int.4550020204.

[65] Muhammad Syarif Hartawan, Arman Syah Putra, and Ayub Muktiono, “Smart City Concept for Integrated Citizen Information Smart Card or ICISC in DKI Jakarta,” Int. J. Sci. Technol. Manag., vol. 1, no. 4, pp. 364–370, 2020, doi: 10.46729/ijstm.v1i4.76.

[66] A. Murtaza, S. J. Hussain Pirzada, L. Jianwei, and T. Xu, “Air traffic surveillance using IP-Based space information network,” 2019 28th Wirel. Opt. Commun. Conf. WOCC 2019 - Proc., no. May, 2019, doi: 10.1109/WOCC.2019.8770697.

[67] V. Murugan, V. R. Vijaykumar, and A. Nidhila, “A deep learning RcNn approach for vehicle recognition in traffic surveillance system,” Proc. 2019 IEEE Int. Conf. Commun. Signal Process. ICCSP 2019, pp. 157–160, 2019, doi: 10.1109/ICCSP.2019.8698018.

[68] P. G. V. Naranjo, Z. Pooranian, M. Shojafar, M. Conti, and R. Buyya, “FOCAN: A Fog-supported smart city network architecture for management of applications in the Internet of Everything environments,” J. Parallel Distrib. Comput., vol. 132, pp. 274–283, 2019, doi: 10.1016/j.jpdc.2018.07.003.

[69] K. Nellore and G. P. Hancke, “A survey on urban traffic management system using wireless sensor networks,” Sensors (Switzerland), vol. 16, no. 2, 2016, doi: 10.3390/s16020157.

[70] B. Nemade, “Automatic Traffic Surveillance Using Video Tracking,” Procedia Comput. Sci., vol. 79, pp. 402–409, 2016, doi: 10.1016/j.procs.2016.03.052.

[71] K. Nguyen et al., “Vehicle Re-identification with Learned Representation and Spatial Verification and Abnormality Detection with Multi-Adaptive Vehicle Detectors for Traffic Video Analysis,” Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. Work., pp. 363–372, 2019.

[72] S. Parekh, N. Dhami, S. Patel, and J. Undavia, “Traffic signal automation through iot by sensing and detecting traffic intensity through ir sensors,” Smart Innov. Syst. Technol., vol. 106, pp. 53–65, 2019, doi: 10.1007/978-981-13-1742-2_6.

[73] D. Parker, J. T. Reason, A. S. R. Manstead, and S. G. Stradling, “Driving errors, driving violations and accident involvement,” Ergonomics, vol. 38, no. 5, pp. 1036–1048, 1995, doi: 10.1080/00140139508925170.

[74] S. D. Pendleton et al., “Perception, planning, control, and coordination for autonomous vehicles,” Machines, vol. 5, no. 1, pp. 1–54, 2017, doi: 10.3390/machines5010006.

[75] R. B. Pendor and P. P. Tasgaonkar, “An IoT framework for intelligent vehicle monitoring system,” Int. Conf. Commun. Signal Process. ICCSP 2016, pp. 1694–1696, 2016, doi: 10.1109/ICCSP.2016.7754454.

[76] S. Pohlmann and U. Traenkle, “Orientation in road traffic. Age-related differences using an in-vehicle navigation system and a conventional map,” Accid. Anal. Prev., vol. 26, no. 6, pp. 689–702, 1994, doi: 10.1016/0001-4575(94)90048-5.

[77] P. Polack, F. Altche, B. DAndrea-Novel, and A. De La Fortelle, “The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles?,” IEEE Intell. Veh. Symp. Proc., no. Iv, pp. 812–818, 2017, doi: 10.1109/IVS.2017.7995816.

[78] A. Pongpunwattana and R. Rysdyk, “Real-time planning for multiple autonomous vehicles in dynamic uncertain environments,” J. Aerosp. Comput. Inf. Commun., vol. 1, no. DEC., pp. 580–604, 2004, doi: 10.2514/1.12919.

[79] A. S. Putra and F. R. Radita, “Paradigma Belajar Mengaji Secara Online Pada Masa Pandemic Coronavirus Disease 2019 ( Covid-19 ),” Mataazir J. Adm. dan Manaj. Pendidik., vol. 1, no. 1, pp. 49–61, 2020.

[80] H. Lisnawati and A. Sinaga, “Data mining with associated methods to predict consumer purchasing patterns,” Int. J. Mod. Educ. Comput. Sci., vol. 12, no. 5, pp. 16–28, 2020, doi: 10.5815/ijmecs.2020.05.02.

[81] M. Mitra and A. Chowdhury, “A modernized voting system using fuzzy logic and blockchain technology,” Int. J. Mod. Educ. Comput. Sci., vol. 12, no. 3, pp. 17–25, 2020, doi: 10.5815/ijmecs.2020.03.03.

[82] S. Sathasivam, S. A. Alzaeemi, and M. Velavan, “Mean-field theory in hopfield neural network for doing 2 satisfiability logic programming,” Int. J. Mod. Educ. Comput. Sci., vol. 12, no. 4, pp. 27–39, 2020, doi: 10.5815/ijmecs.2020.04.03.

[83] Y. Sulema, E. E. Kerre, and O. Shkurat, “Vector image retrieval methods based on fuzzy patterns,” Int. J. Mod. Educ. Comput. Sci., vol. 12, no. 3, pp. 8–16, 2020, doi: 10.5815/ijmecs.2020.03.02.

[84] A. O. Eboka and A. A. Ojugo, “Mitigating technical challenges via redesigning campus network for greater efficiency, scalability and robustness: A logical view,” Int. J. Mod. Educ. Comput. Sci., vol. 12, no. 6, pp. 29–45, 2020, doi: 10.5815/ijmecs.2020.06.03.

[85] I. Ramadhan, A. Kurniawan, and A. S. Putra, “Penentuan Pola Penindakan Pelanggaran Lalu Lintas di DKI Jakarta Menggunakan Metode Analytic Network Process ( ANP ),” vol. 5, no. 1, pp. 51–57.

[86] W. Schwarting, J. Alonso-Mora, and D. Rus, “Planning and Decision-Making for Autonomous Vehicles,” Annu. Rev. Control. Robot. Auton. Syst., vol. 1, no. 1, pp. 187–210, 2018, doi: 10.1146/annurev-control-060117-105157.

[87] M. Scotch and B. Parmanto, “SOVAT: Spatial OLAP visualization and analysis tool,” Proc. Annu. Hawaii Int. Conf. Syst. Sci., vol. 00, no. C, p. 142, 2005, doi: 10.1109/hicss.2005.550.

[88] B. Singh and A. Gupta, “Recent trends in intelligent transportation systems: a review,” J. Transp. Lit., vol. 9, no. 2, pp. 30–34, 2015, doi: 10.1590/2238-1031.jtl.v9n2a6.

[89] T. Taleshian and S. Minagar, “Motion planning for an autonomous underwater vehicle,” Conf. Proc. 2015 2nd Int. Conf. Knowledge-Based Eng. Innov. KBEI 2015, pp. 285–290, 2016, doi: 10.1109/KBEI.2015.7436061.

[90] D. N. N. Tran, L. H. Pham, H. M. Tran, and S. V. U. Ha, “Probabilistic model and neural network for scene classification in traffic surveillance system,” Adv. Intell. Syst. Comput., vol. 672, no. June, pp. 685–695, 2018, doi: 10.1007/978-981-10-7512-4_68.

[91] V. Tsakanikas and T. Dagiuklas, “Video surveillance systems-current status and future trends,” Comput. Electr. Eng., vol. 70, pp. 736–753, 2018, doi: 10.1016/j.compeleceng.2017.11.011.

[92] V. Tsakanikas and T. Dagiuklas, “Video surveillance systems-current status and future trends,” Comput. Electr. Eng., vol. 70, pp. 736–753, 2018, doi: 10.1016/j.compeleceng.2017.11.011.

[93] P. Wang, L. Li, Y. Jin, and G. Wang, “Detection of unwanted traffic congestion based on existing surveillance system using in freeway via a CNN-architecture trafficnet,” Proc. 13th IEEE Conf. Ind. Electron. Appl. ICIEA 2018, no. 51505037, pp. 1134–1139, 2018, doi: 10.1109/ICIEA.2018.8397881.