Skip to main content
Erschienen in:

04.09.2021

Lane-Level Vehicle Counting Based on V2X and Centimeter-level Positioning at Urban Intersections

verfasst von: Jianchun Jiang, Yi Yang, Yuhuan Li, Rong Wang, Suhua Zeng

Erschienen in: International Journal of Intelligent Transportation Systems Research | Ausgabe 1/2022

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Accurate vehicles counting for all-weather in cities are an important part of traffic management in the application of Intelligent Transportation Systems (ITS). Vehicle counting is currently collected with computer vision and sensor network methods. However, these methods require expensive hardware to achieve real-time and anti-interference capability, and do not provide lane-level vehicle information for ITS traffic management. This paper presents a lane-level vehicle counting system that is based on V2X communications and centimeter-level positioning technologies. This system can be used to traffic survey of ITS at a range of urban intersections. For realizing lane-level counting, a lane determination method is designed with on-board units (OBUs) in this paper. The lane is identified by matching the vehicle positioning information with road information from the roadside unit (RSU). The RSU collects the vehicle counting information from OBUs in different instances. The counting information includes the vehicle location data, the vehicle status data, and the vehicle number of each lane in the range of intersections. Verification and analysis were performed by a hardware-in-the-loop simulation platform. The results showed an average vehicle counting accuracy rate (99.60%). The system enabled the collection of real-time statistics with low-power consumption and low latency, providing accurate data to ITS.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

ATZelectronics worldwide

ATZlectronics worldwide is up-to-speed on new trends and developments in automotive electronics on a scientific level with a high depth of information. 

Order your 30-days-trial for free and without any commitment.

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Weitere Produktempfehlungen anzeigen
Literatur
1.
Zurück zum Zitat Bao, X., Li, H., Xu, D., Jia, L., Ran, B., Rong, J.: Traffic vehicle counting in jam flow conditions using low-cost and energy-efficient wireless magnetic sensors. Sensors (Basel). 16(11), (2016) Bao, X., Li, H., Xu, D., Jia, L., Ran, B., Rong, J.: Traffic vehicle counting in jam flow conditions using low-cost and energy-efficient wireless magnetic sensors. Sensors (Basel). 16(11), (2016)
2.
Zurück zum Zitat Zu, X., et al.: Vehicle counting and moving direction identification based on small-aperture microphone array. Sensors (Basel). 17(5), (2017) Zu, X., et al.: Vehicle counting and moving direction identification based on small-aperture microphone array. Sensors (Basel). 17(5), (2017)
3.
Zurück zum Zitat Chen, Z et al.: Roadside Sensor Based Vehicle Counting Incomplex Traffic Environment. 2019 IEEE Globecom Workshops (GC Wkshps) IEEE, (2020) Chen, Z et al.: Roadside Sensor Based Vehicle Counting Incomplex Traffic Environment. 2019 IEEE Globecom Workshops (GC Wkshps) IEEE, (2020)
4.
Zurück zum Zitat Park, M.-W., In Kim, J., Lee, Y.-J., Park, J., Suh, W.: Vision-based surveillance system for monitoring traffic conditions. Multimed. Tools. Appl. 76(23), 25343–25367 (2017)CrossRef Park, M.-W., In Kim, J., Lee, Y.-J., Park, J., Suh, W.: Vision-based surveillance system for monitoring traffic conditions. Multimed. Tools. Appl. 76(23), 25343–25367 (2017)CrossRef
5.
Zurück zum Zitat Velazquez-Pupo, R., et al.: Vehicle detection with occlusion handling, tracking, and OC-SVM classification: a high performance vision-based system. Sensors (Basel). 18(2), (2018) Velazquez-Pupo, R., et al.: Vehicle detection with occlusion handling, tracking, and OC-SVM classification: a high performance vision-based system. Sensors (Basel). 18(2), (2018)
6.
Zurück zum Zitat Barcellos, P., Bouvié, C., Escouto, F.L., Scharcanski, J.: A novel video based system for detecting and counting vehicles at user-defined virtual loops. Expert Syst. Appl. 42(4), 1845–1856 (2015)CrossRef Barcellos, P., Bouvié, C., Escouto, F.L., Scharcanski, J.: A novel video based system for detecting and counting vehicles at user-defined virtual loops. Expert Syst. Appl. 42(4), 1845–1856 (2015)CrossRef
7.
Zurück zum Zitat Kuang, H., Yang, K.-F., Chen, L., Li, Y.-J., Chan, L.L.H., Yan, H.: Bayes saliency-based object proposal generator for nighttime traffic images. IEEE Trans. Intell. Transp. Syst. 19(3), 814–825 (2018)CrossRef Kuang, H., Yang, K.-F., Chen, L., Li, Y.-J., Chan, L.L.H., Yan, H.: Bayes saliency-based object proposal generator for nighttime traffic images. IEEE Trans. Intell. Transp. Syst. 19(3), 814–825 (2018)CrossRef
8.
Zurück zum Zitat Guo, J.-M., Hsia, C.-H., Wong, K., Wu, J.-Y., Wu, Y.-T., Wang, N.-J.: Nighttime vehicle lamp detection and tracking with adaptive mask training. IEEE Trans. Veh. Technol. 65(6), 4023–4032 (2016)CrossRef Guo, J.-M., Hsia, C.-H., Wong, K., Wu, J.-Y., Wu, Y.-T., Wang, N.-J.: Nighttime vehicle lamp detection and tracking with adaptive mask training. IEEE Trans. Veh. Technol. 65(6), 4023–4032 (2016)CrossRef
9.
Zurück zum Zitat Yang, H., Qu, S.: Real-time vehicle detection and counting in complex traffic scenes using background subtraction model with low-rank decomposition. IET Intell. Transp. Syst. (2017) Yang, H., Qu, S.: Real-time vehicle detection and counting in complex traffic scenes using background subtraction model with low-rank decomposition. IET Intell. Transp. Syst. (2017)
12.
Zurück zum Zitat Engel, J.I., Martin, J., Barco, R.: A low-complexity vision-based system for real-time traffic monitoring. IEEE Trans. Intell. Transp. Syst. 18(5), 1279–1288 (2017)CrossRef Engel, J.I., Martin, J., Barco, R.: A low-complexity vision-based system for real-time traffic monitoring. IEEE Trans. Intell. Transp. Syst. 18(5), 1279–1288 (2017)CrossRef
13.
Zurück zum Zitat Rajput, H., Som, T., Kar, S.: "An automated vehicle license plate recognition system," (in English). Comp, Article. 48(8), 56–61 (2015) Rajput, H., Som, T., Kar, S.: "An automated vehicle license plate recognition system," (in English). Comp, Article. 48(8), 56–61 (2015)
15.
Zurück zum Zitat Di, B., Song, L., Li, Y., Li, G.Y.: Non-orthogonal multiple access for high-reliable and low-latency V2X communications in 5G systems. IEEE J. Sel. Areas Commun. 35(10), 2383–2397 (2017)CrossRef Di, B., Song, L., Li, Y., Li, G.Y.: Non-orthogonal multiple access for high-reliable and low-latency V2X communications in 5G systems. IEEE J. Sel. Areas Commun. 35(10), 2383–2397 (2017)CrossRef
16.
18.
Zurück zum Zitat He, X., Zhang, X., Tang, L., Liu, W.: Instantaneous real-time kinematic decimeter-level positioning with BeiDou triple-frequency signals over medium baselines. Sensors (Basel). 16(1), (2015) He, X., Zhang, X., Tang, L., Liu, W.: Instantaneous real-time kinematic decimeter-level positioning with BeiDou triple-frequency signals over medium baselines. Sensors (Basel). 16(1), (2015)
19.
Zurück zum Zitat Li, X., Zhang, X., Ren, X., Fritsche, M., Wickert, J., Schuh, H.: Precise positioning with current multi-constellation Global Navigation Satellite Systems: GPS, GLONASS, Galileo, and BeiDou. Sci. Rep. 5, 8328 (2015)CrossRef Li, X., Zhang, X., Ren, X., Fritsche, M., Wickert, J., Schuh, H.: Precise positioning with current multi-constellation Global Navigation Satellite Systems: GPS, GLONASS, Galileo, and BeiDou. Sci. Rep. 5, 8328 (2015)CrossRef
20.
Zurück zum Zitat Chen, W., Hu, K., Li, E.: Low-cost land vehicle attitude determination using single-epoch GPS data, MEMS-based inclinometer measurements. Acta Geod. Geophys. 52(1), 111–129 (2017)CrossRef Chen, W., Hu, K., Li, E.: Low-cost land vehicle attitude determination using single-epoch GPS data, MEMS-based inclinometer measurements. Acta Geod. Geophys. 52(1), 111–129 (2017)CrossRef
21.
Zurück zum Zitat Poolsin, C., Sa-Ngiam, N., Sutthisangiam, N.: Development of Centimeter Level Positioning Mobile Based Application. 2021 23rd International Conference on Advanced Communication Technology (ICACT), pp. 63-67 (2021) 10.23919/ ICACT51234.2021.9370509 Poolsin, C., Sa-Ngiam, N., Sutthisangiam, N.: Development of Centimeter Level Positioning Mobile Based Application. 2021 23rd International Conference on Advanced Communication Technology (ICACT), pp. 63-67 (2021) 10.23919/ ICACT51234.2021.9370509
22.
Zurück zum Zitat Kong, H., Chen, W., Fu, S., Zheng, H., Du, L., Mao, Y.: OBU Design and Test Analysis with Centimeter-Level Positioning for LTE-V2X. 2019 5th International Conference on Transportation Information and Safety (ICTIS), pp. 383-387 (2019) 10.1109/ICTIS.2019.8883715 Kong, H., Chen, W., Fu, S., Zheng, H., Du, L., Mao, Y.: OBU Design and Test Analysis with Centimeter-Level Positioning for LTE-V2X. 2019 5th International Conference on Transportation Information and Safety (ICTIS), pp. 383-387 (2019) 10.1109/ICTIS.2019.8883715
23.
Zurück zum Zitat Bila, C., Sivrikaya, F., Khan, M.A., Albayrak, S.: Vehicles of the future: a survey of research on safety issues. IEEE Trans. Intell. Transp. Syst. 18(5), 1046–1065 (2017)CrossRef Bila, C., Sivrikaya, F., Khan, M.A., Albayrak, S.: Vehicles of the future: a survey of research on safety issues. IEEE Trans. Intell. Transp. Syst. 18(5), 1046–1065 (2017)CrossRef
25.
Zurück zum Zitat Gaikwad, V., Lokhande, S.: Lane departure identification for advanced driver assistance. IEEE Trans. Intell. Transp. Syst. 1–9 (2014) Gaikwad, V., Lokhande, S.: Lane departure identification for advanced driver assistance. IEEE Trans. Intell. Transp. Syst. 1–9 (2014)
26.
Zurück zum Zitat Knoop, V.L., de Bakker, P.F., Tiberius, C.C.J.M., van Arem, B.: Lane determination with GPS precise point positioning. IEEE Trans. Intell. Transp. Syst. 18(9), 2503–2513 (2017)CrossRef Knoop, V.L., de Bakker, P.F., Tiberius, C.C.J.M., van Arem, B.: Lane determination with GPS precise point positioning. IEEE Trans. Intell. Transp. Syst. 18(9), 2503–2513 (2017)CrossRef
27.
Zurück zum Zitat Gwon, G.-P., Hur, W.-S., Kim, S.-W., Seo, S.-W.: Generation of a precise and efficient lane-level road map for intelligent vehicle systems. IEEE Trans. Veh. Technol. 66(6), 4517–4533 (2017)CrossRef Gwon, G.-P., Hur, W.-S., Kim, S.-W., Seo, S.-W.: Generation of a precise and efficient lane-level road map for intelligent vehicle systems. IEEE Trans. Veh. Technol. 66(6), 4517–4533 (2017)CrossRef
28.
Zurück zum Zitat Dashtinezhad, S., Nadeem, T., Dorohonceanu, B., Borcea, C., Kang, P., Iftode, L.: TrafficView: a driver assistant device for traffic monitoring based on car-to-car communication. In 59th IEEE Veh. Technol. Conf. (VTC), vol. 5, pp. 2946-2950 (2004) Dashtinezhad, S., Nadeem, T., Dorohonceanu, B., Borcea, C., Kang, P., Iftode, L.: TrafficView: a driver assistant device for traffic monitoring based on car-to-car communication. In 59th IEEE Veh. Technol. Conf. (VTC), vol. 5, pp. 2946-2950 (2004)
29.
Zurück zum Zitat Bauza, R., Gozalvez, J.: Traffic congestion detection in large-scale scenarios using vehicle-to-vehicle communications. J. Netw. Comput. Appl. 36(5), 1295–1307 (2013)CrossRef Bauza, R., Gozalvez, J.: Traffic congestion detection in large-scale scenarios using vehicle-to-vehicle communications. J. Netw. Comput. Appl. 36(5), 1295–1307 (2013)CrossRef
30.
Zurück zum Zitat Sanguesa, J.A., et al.: Sensing traffic density combining V2V and V2I wireless communications. Sensors (Basel). 15(12), 31794–31810 (2015)CrossRef Sanguesa, J.A., et al.: Sensing traffic density combining V2V and V2I wireless communications. Sensors (Basel). 15(12), 31794–31810 (2015)CrossRef
31.
Zurück zum Zitat Cardenas-Benitez, N., Aquino-Santos, R., Magana-Espinoza, P., Aguilar-Velazco, J., Edwards-Block, A., Medina Cass, A.: Traffic congestion detection system through connected vehicles and big data. Sensors (Basel). 16(5), (2016) Cardenas-Benitez, N., Aquino-Santos, R., Magana-Espinoza, P., Aguilar-Velazco, J., Edwards-Block, A., Medina Cass, A.: Traffic congestion detection system through connected vehicles and big data. Sensors (Basel). 16(5), (2016)
32.
Zurück zum Zitat Florin, R., Olariu, S.: Towards real-time density estimation using vehicle-to-vehicle communications. Transp. Res. B Methodol. 138, 435–456 (2020)CrossRef Florin, R., Olariu, S.: Towards real-time density estimation using vehicle-to-vehicle communications. Transp. Res. B Methodol. 138, 435–456 (2020)CrossRef
34.
Zurück zum Zitat Chopde, N.R., Nichat, M.K.: Landmark based shortest path detection by using A* and Haversine formula. Int. J. Innov. Res. Comput. Commun. Eng. 1(2), 298–302 (2013) Chopde, N.R., Nichat, M.K.: Landmark based shortest path detection by using A* and Haversine formula. Int. J. Innov. Res. Comput. Commun. Eng. 1(2), 298–302 (2013)
35.
Zurück zum Zitat Roess, R.P., Prassas, E.S., McShane, W.R.: Traffic engineering, 4th edn. Prentice Hall (2011) Roess, R.P., Prassas, E.S., McShane, W.R.: Traffic engineering, 4th edn. Prentice Hall (2011)
Metadaten
Titel
Lane-Level Vehicle Counting Based on V2X and Centimeter-level Positioning at Urban Intersections
verfasst von
Jianchun Jiang
Yi Yang
Yuhuan Li
Rong Wang
Suhua Zeng
Publikationsdatum
04.09.2021
Verlag
Springer US
Erschienen in
International Journal of Intelligent Transportation Systems Research / Ausgabe 1/2022
Print ISSN: 1348-8503
Elektronische ISSN: 1868-8659
DOI
https://doi.org/10.1007/s13177-021-00271-4

    Marktübersichten

    Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen.