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Vehicle Detection and Traffic Estimation with Sensors Technologies for Intelligent Transportation Systems

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Abstract

The paper reviews the vehicle detection methods using the intrusive and non-intrusive sensors. The objective of literature review is to summarize the sensors and technologies used in vehicle detection and traffic estimation. Integrating these sensors will give vital information by communicating with the monitoring station related to the presence of the vehicle on the road. Sensors and communicating technologies have a widespread application in intelligent transportation systems. The modern devices and technologies are discussed that determine the vehicle count, classification, location, speed, traffic volume, density, traffic estimation. Sensors fusion can further integrate information from different sources and provides more accuracy.

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References

  1. Akyildiz, I., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. ELSEVIER Journal on Computer Networks, 38(4), 393–422.

    Google Scholar 

  2. Alessandretti, G., Broggi, A., & Cerri, P. (2007). Vehicle and guard rail detection using radar and vision data fusion. IEEE Transactions on Intelligent Transportation Systems, 8(1), 95–105.

    Google Scholar 

  3. Alexander, A., Taylor, R., Vairavanathan, V., Fu, Y., Hossain, E., & Noghanian, S. (2008). Solar-powered ZigBee-based wireless motion surveillance: A prototype development and experimental results. Journal of Wireless Communications and Mobile Computing, 8, 1255–1276.

    Google Scholar 

  4. Almomani I., Alkhalil N., Ahmad E. & Jodeh R. (2011). Ubiquitous GPS vehicle tracking and management system. In IEEE conference on applied electrical engineering and computing technologies, 6–8 Dec. 2011, Amman, Jordan

  5. Aloquili, O., Elbanna, A., & Al-Azizi, A. (2009). Automatic vehicle location tracking system based on GIS environment. The IET Software, 3(4), 255–263.

    Google Scholar 

  6. Anandhalli, A., & Baligar, V. (2018). A novel approach in real-time vehicle detection and tracking using Raspberry Pi. ELSEVIER Alexandria Engineering Journal, 57, 1597–1607.

    Google Scholar 

  7. Bernas, M., Płaczek, B., Korski, W., Loska, P., Smyła, J., & Szymała, P. (2018). A survey and comparison of low-cost sensing technologies for road traffic monitoring. Sensors Journal, 18(10), 3243. https://doi.org/10.3390/s18103243.

    Article  Google Scholar 

  8. Burnos, P., Gajda, J., Piwowar, P., Sroka, R., Stencel, M., & Zeglen, T. (2007). Measurements of road traffic parameters using inductive loops and piezoelectric sensors. Metrology and Measurement Systems Journal, 14(2), 187–203.

    Google Scholar 

  9. Cao, L., Wang, C., & Li, J. (2016). Vehicle detection from highway satellite images via transfer learning. ELSEVIER Journal on Information Sciences, 366, 177–187.

    MathSciNet  Google Scholar 

  10. Chavez-Garcia, R., & Aycard, O. (2016). Multiple sensor fusion and classification for moving object detection and tracking. IEEE Transactions on Intelligent Transportation Systems, 17(2), 525–534.

    Google Scholar 

  11. Chen W., Chen L., Chen Z., & Tu,S. (2006). WITS: A wireless sensor network for intelligent transportation system. In: Proceedings of the first international multi-symposiums on computer and computational sciences, 20–24 June 2006, Hanzhou, Zhejiang, China.

  12. Chen Y., Cheng L., Chen C. & Ma, J. (2009). ‘Wireless sensor network for data sensing in intelligent transportation system. In: VTC spring 2009: IEEE 69th vehicular technology conference, 26–29 April 2009, Barcelona, Spain.

  13. Cheng, G., & Han, J. (2016). A survey on object detection in optical remote sensing images. ISPRS Journal of Photogrammetry and Remote Sensing, 117, 11–28.

    Google Scholar 

  14. Derekenaris, G., Garofalakis, J., Makris, C., Prentzas, J., Sioutas, S., & Tsakalidis, A. (2001). Integrating GIS, GPS and GSM technologies for the effective management of ambulances. Journal of Computers, Environment, and Urban Systems, 25(3), 267–278.

    Google Scholar 

  15. Elloumi. M., Dhaou, R., Escrig, B., Idoudi. H. & Saidane. L. (2018). Monitoring road traffic with a UAV-based system. In: IEEE wireless communications and networking conference (WCNC 2018) (pp. 1–6) 15–18 April 2018, Barcelona, Spain.

  16. Fang J., Meng H., Zhang H., & Wang, X. (2007). A low-cost vehicle detection and classification system based on unmodulated continuous-wave radar. In Proceedings of the 2007 IEEE intelligent transportation systems conference Seattle, 30 Sept.-3 Oct. 2007, Seattle, WA, USA.

  17. Fernández-Ares, A., Mora, A., Odeh, S., García-Sánchez, P., & Arenas, M. (2017). Wireless monitoring and tracking system for vehicles: A study case in an urban scenario. ELSEVIER Journal of Simulation Modelling Practice and Theory, 73, 22–42.

    Google Scholar 

  18. Government of India, Ministry of Road Transport & Highways, 12th five year plan. (2012–17). Report of the Working Group on Central Roads Sector.

  19. Guerrero-Ibáñez, J., Zeadally, S., & Contreras-Castillo, J. (2018). Sensor technologies for intelligent transportation systems. Sensors Journal, 18(4), 1212. https://doi.org/10.3390/s18041212.

    Article  Google Scholar 

  20. Hanan, M., Mustapha, A., Hussain, A. & Basri, H. (2012). Intelligent bus monitoring and management system. In Proceedings of the world congress on engineering and computer science, 24–26 October 2012, San Francisco, USA.

  21. Hatem, B., & Habib, H. (2009). Bus management system using RFID in WSN. In European and mediterranean conference on information systems, April 12–3 2009, Abu Dhabi, UAE.

  22. Hostettler, R., & Djuric, P. (2015). Vehicle tracking based on fusion of magnetometer and accelerometer sensor measurements with particle filtering. IEEE Transactions on Vehicular Technology, 64(11), 4917–4928.

    Google Scholar 

  23. Jensen, J., & Cowen, D. (1999). Remote sensing of urban/suburban infrastructure and socio-economic attributes. Journal of Photogrammetric Engineering and Remote Sensing, 65(5), 611–622.

    Google Scholar 

  24. Jeon, S., Kwon, E., & Jung, I. (2014). Traffic measurement on multiple drive lanes with wireless ultrasonic sensors. Sensors Journal, 14(12), 22891–22906. https://doi.org/10.3390/s141222891.

    Article  Google Scholar 

  25. Ji, Y., & Sprou, G. (2009). FreeMobility: Dynamic location computing using GIS. Wiley Journal on Wireless Communications and Mobile Computing, 13, 998–1013.

    Google Scholar 

  26. Jo, Y., & Jung, I. (2014). Analysis of vehicle detection with WSN-based ultrasonic sensor. Sensors Journal, 14(8), 14050–14069.

    Google Scholar 

  27. Jo, Y., Choi, J., & Jung, I. (2014). Traffic information acquisition system with ultrasonic sensors in wireless sensor networks. Hindawi Publishing Corporation International Journal of Distributed Sensor Networks, 2014, 9610.

    Google Scholar 

  28. Khakpour, S., Pazzi, R., & Khatib, K. (2017). Using clustering for target tracking in vehicular ad hoc networks. ELSEVIER Journal of Vehicular Communications, 9, 83–96.

    Google Scholar 

  29. Kim, S., Kim, H., Yoo, W., & Huh, K. (2016). Sensor fusion algorithm design in detecting vehicles using laser scanner and stereo vision. IEEE Transactions on Intelligent Transportation Systems, 17(4), 1072–1084.

    Google Scholar 

  30. Kumar, K., Parida, M., & Katiyar, V. (2013). ‘Short term traffic flow prediction for a non-urban highway using artificial neural network’, 2nd Conference of Transportation Research Group of India. Procedia - Social and Behavioural Sciences, Agra, India, 104, 755–764.

    Google Scholar 

  31. Kumar, T., & Kushwaha, D. (2016). An efficient approach for detection and speed estimation of moving vehicles. In Twelfth international multi-conference on information processing-2016 (IMCIP-2016), procedia computer science, vol. 89, pp. 726–731.

  32. Lee, W., Tseng, S., & Shieh, W. (2010). Collaborative real-time traffic information generation and sharing framework for the intelligent transportation system. ELSEVIER Journal of Information Sciences, 180(2010), 62–70.

    Google Scholar 

  33. Lewandowski, M., Placzek, B., Bernas, M., & Szymala, P. (2018). Road traffic monitoring system based on mobile devices and BLUETOOTH low energy beacons. Wiley Hindawi Journal of Wireless Communications and Mobile Computing. https://doi.org/10.1155/2018/3251598.

    Article  Google Scholar 

  34. Li, D., Wong, K., Hu, Y., & Sayeed, A. (2002). Detection, classification, and tracking of targets. IEEE Signal Processing Magazine, 19(2), 17–29.

    Google Scholar 

  35. Liu, J., Han, J., Lv, H., & Li, B. (2015). An ultrasonic sensor system based on a two-dimensional state method for highway vehicle violation detection applications. Sensors Journal, 15, 9000–9021.

    Google Scholar 

  36. Luo, Z., Habibi, S., & Mohrenschildt, M. (2016). LiDAR based real-time multiple vehicle detection and tracking. International Journal of Computer and Information Engineering, 10(6), 1125–1132.

    Google Scholar 

  37. Ma, W., Xing, D., McKee, A., Bajwa, R., Flores, C., Fuller, B., et al. (2014). A wireless accelerometer-based automatic vehicle classification prototype system. IEEE Transactions on Intelligent Transportation Systems, 15(1), 104–111.

    Google Scholar 

  38. Mao, X., Tang, S., Wang, J., & Li, X. (2013). iLight: Device-free passive tracking using wireless sensor networks. IEEE Sensors Journal, 13(10), 3785–3792.

    Google Scholar 

  39. Mintsis, G., Basbas, S., Papaioannou, P., Taxiltaris, C., & Tziavos, I. (2004). Applications of GPS technology in the land transportation system. ELSEVIER European Journal of Operational Research, 152, 399–409.

    MATH  Google Scholar 

  40. Mohan, P., Padmanabhan, V., & Ramjee, R.(2008). Nericell: Rich monitoring of road and traffic conditions using mobile smartphones. In SenSys 08, November 5–7,2008, Raleigh, North Carolina, USA.

  41. Mustapha, H. M., Hussain, A., & Basri, H. (2009). ‘UKM campus bus identification a monitoring using RFID and GIS. In Proceedings of IEEE conference on research and development, 16–18 Nov 2009, Serdang, Malaysia.

  42. Nafar, F., & Shamsi, H. (2018). Design and implementation of an RFID-GSM based vehicle identification system on highways. IEEE Sensors Journal, 18(17), 7281–7293.

    Google Scholar 

  43. Nellore, K., & Hancke, G. (2016). A survey on urban traffic management system using wireless sensor networks. Sensors Journal. https://doi.org/10.3390/s16020157.

    Article  Google Scholar 

  44. Nguyen, D., Dow, C., & Hwang, S. (2018). An efficient traffic congestion monitoring system on the internet of vehicles. Hindawi Wireless Communications and Mobile Computing, 2018, 9136813.

    Google Scholar 

  45. Ni, L., Zhang, D., & Souryal, M. (2011). RFID -based localization and tracking technologies. Journal of IEEE Wireless Communications, 18(2), 45–51.

    Google Scholar 

  46. Ning, Y., Zhong-qin, W., Malekian, R., Ru-chuan, W., & Abdullah, A. H. (2013). Design of accurate vehicle location system using RFID. Elektronika Ir Elektrotechnika Journal, 19, 8.

    Google Scholar 

  47. Odat, E., Shamma, J., & Claudel, C. (2018). Vehicle classification and speed estimation using combined passive infrared/ultrasonic sensors. IEEE Transactions on Intelligent Transportation Systems, 19(5), 1593–1606.

    Google Scholar 

  48. Ozbay, S., & Ercelebi, E. (2005). Automatic vehicle identification by plate recognition. World Academy of Science, Engineering and Technology, 1(9), 1418–1421.

    Google Scholar 

  49. Pendor, R., & Tasgaonkar, P. (2016). An IoT framework for intelligent vehicle monitoring system. In International conference on communication and signal processing, April 6–8, 2016, Melmaruvathur, India, pp. 1694–1696.

  50. Planas, E., Pastor, E., Presutto, F., & Tixier, J. (2008). Results of the MITRA project: Monitoring and intervention for the transportation of dangerous goods. ELSEVIER Journal of Hazardous Materials, 152, 516–526.

    Google Scholar 

  51. Premebida, C., Ludwig, O., & Nunes, U. (2009). LIDAR and vision-based pedestrian detection system. Wiley Journal of Field Robotics, 26(9), 696–711.

    Google Scholar 

  52. Prinsloo, J., & Malekian, R. (2016). Accurate vehicle location system using RFID, and Internet of Things approach. Sensors Journal, 16(6), 825. https://doi.org/10.3390/s16060825.

    Article  Google Scholar 

  53. Pritee, K., & Garg, R. (2017). ‘Identification of optimum shortest path using multipath dijkstra’s algorithm approach. International Journal of Advanced Remote Sensing and GIS 2017, 6(1), 2442–2448.

    Google Scholar 

  54. Razakarivony, S., & Jurie, F. (2016). Vehicle detection in aerial imagery: A small target detection benchmark. ELSEVIER Journal of Visual Communication and Image Representation, 34, 187–203.

    Google Scholar 

  55. Reinartz, P., Lachaise, M., Schmeer, E., Krauss, T., & Runge, H. (2006). Traffic monitoring with serial images from airborne cameras. ISPRS Journal of Photogrammetry and Remote Sensing, 61, 149–158.

    Google Scholar 

  56. Rivas, J., Wunderlich, R., & Heinen, S. (2017). Road vibrations as a source to detect the presence and speed of vehicles. IEEE Sensors Journal, 17(2), 377–385.

    Google Scholar 

  57. Schoepflin, T., & Dailey, D. (2003). Dynamic camera calibration of roadside traffic management cameras for vehicle speed estimation. IEEE Transactions on Intelligent Transportation Systems, 4(2), 90–98.

    Google Scholar 

  58. SeokJu, L., Girma, T., & Jaerock, K. (2014). Design and implementation of vehicle tracking system using GPS/GSM/GPRS technology and smartphone application. In IEEE world forum on internet of things, 6–8 March 2014, Seoul, Korea.

  59. Sharma, B., Katiyar, V., Gupta, A., & Singh, A. (2014). The automated vehicle detection of highway traffic images by differential morphological profile. Journal of Transportation Technologies, 4, 150–156.

    Google Scholar 

  60. Sharp, C., Schaffert, S., Woo, A., Sastry, N., Karlof, C., Sastry, S., & Culler, D. (2005). Design and implementation of a sensor network system for vehicle tracking and autonomous interception. robotics.eecs.berkeley.edu.

  61. Sifuentes, E., Casas, O., & Pallas-Areny, R. (2011). Wireless magnetic sensor node for vehicle detection with optical wake-up. IEEE Sensors Journal, 11(8), 1669–1676.

    Google Scholar 

  62. Soni, U. (2019).Integration of traffic data from social media and physical sensors for near real-time road traffic analysis. M.Sc Thesis, Faculty of Geo-Information Science and Earth Observation of the University of Twente, March 2019.

  63. Suresh, K., Mahesh, G., & Rajagopalan, A. (2007). Superresolution of license plates in real traffic video. IEEE Transactions On Intelligent Transportation Systems, 8(2), 321–331.

    Google Scholar 

  64. Taghvaeeyan, S., & Rajamani, R. (2014). Portable roadside sensors for vehicle counting, classification, and speed measurement. IEEE Transactions on Intelligent Transportation Systems, 15(1), 73–83.

    Google Scholar 

  65. Tan, R., Xing, G., Wang, J., & Cheung, H.(2008). Collaborative target detection in wireless sensor networks with reactive mobility. In 16th international workshop on quality of service, 2–4 June 2008, Enschede, Netherlands.

  66. Tubaishat, M., Zhuang, P., & Shang, Q. (2009). Wireless sensor networks in intelligent transportation systems. Wiley Journal of Wireless Communications and Mobile Computing, 9, 287–302.

    Google Scholar 

  67. Vancin, S., & Erdem, E. (2017). Implementation of the vehicle recognition systems using wireless magnetic sensors. Sadhana Journal, 42(6), 841–854.

    Google Scholar 

  68. Velisavljevic, V., Cano, E., Dyo, V., & Allen, B. (2016). Wireless magnetic sensor network for road traffic monitoring and vehicle classification. Journal of Transport and Telecommunication, 17(4), 274–288.

    Google Scholar 

  69. Wen, W. (2010). An intelligent traffic management expert system with RFID technology. ELSEVIER International Journal of Expert Systems with Applications, 37, 3024–3035.

    Google Scholar 

  70. Wenjie, C., Liqiang, G., Zhilei, C., Zhanglong, C., & Shiliang, T. (2005). An intelligent guiding and controlling system for transportation network based on wireless sensor network technology. In Proceedings of fifth international conference on computer and information technology, 21–23 Sept. 2005, Shanghai, China.

  71. Xiang, X., Zhai, M., Lv, N., & Saddik, A. (2018). Vehicle counting based on vehicle detection and tracking from aerial videos. Sensors Journal, 18(8), 5. https://doi.org/10.3390/s18082560.

    Article  Google Scholar 

  72. Xiong, Z., Song, Z., Scalera, A., Ferrera, E., Sottile, F., Brizzi, P., et al. (2013). Hybrid WSN and RFID indoor positioning and tracking system. EURASIP Journal on Embedded Systems. https://doi.org/10.1186/1687-3963-2013-6.

    Article  Google Scholar 

  73. Zarza, H., Yousefi, S., & Benslimane, A. (2016). RIALS: RSU/INS-aided localization system for GPS-challenged road segments. Wiley Journal on Wireless Communications and Mobile Computing, 2016, 1290–1305.

    Google Scholar 

  74. Zhang, C., Pan, X., Li, H., Gardiner, A., Sargent, I., Hare, J., et al. (2018). A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification. ISPRS Journal of Photogrammetry and Remote Sensing, 140, 133–144.

    Google Scholar 

  75. Zhang, E., Jiang, W., Kuang, Y., & Umer, M. (2011).’Active RFID positioning of vehicles in road traffic. In The 11th international symposium on communications & information technologies (ISCIT 2011), October 12–14, 2011, Zhejiang University, Hangzhou, China.

  76. Zhang, G., Avery, R., & Wang, Y. (2007). Video-based vehicle detection and classification system for real-time traffic data collection using uncalibrated video cameras. Journal of the Transportation Research Board, 1993, 138–147.

    Google Scholar 

  77. Zhang, W., Sun, X., Wang, N., & Fu, K. (2015). A generic discriminative part-based model for geospatial object detection in optical remote sensing images. ISPRS Journal of Photogrammetry and Remote Sensing, 99, 30–44.

    Google Scholar 

  78. Zhou, J., Gao, D., & Zhang, D. (2007). Moving vehicle detection for automatic traffic monitoring. IEEE Transactions On Vehicular Technology, 56(1), 51–59.

    Google Scholar 

  79. Zhu, H., & Yu, F. (2016). A cross-correlation technique for vehicle detections in wireless magnetic sensor network. IEEE Sensors Journal, 16(11), 4484–4494.

    MathSciNet  Google Scholar 

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  1. Civil Engineering Department, Indian Institute of Technology, Roorkee, Roorkee, India

    Pankaj P. Tasgaonkar, Rahul Dev Garg & Pradeep Kumar Garg

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Tasgaonkar, P.P., Garg, R.D. & Garg, P.K. Vehicle Detection and Traffic Estimation with Sensors Technologies for Intelligent Transportation Systems. Sens Imaging 21, 29 (2020). https://doi.org/10.1007/s11220-020-00295-2

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