- -

Detecting Vehicles' Relative Position on Two-Lane Highways Through a Smartphone-Based Video Overtaking Aid Application

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

  • Estadisticas de Uso

Detecting Vehicles' Relative Position on Two-Lane Highways Through a Smartphone-Based Video Overtaking Aid Application

Show full item record

Patra, S.; Van Hamme, D.; Veelaert, P.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Manzoni, P.; Zamora, W. (2020). Detecting Vehicles' Relative Position on Two-Lane Highways Through a Smartphone-Based Video Overtaking Aid Application. Mobile Networks and Applications. 25(3):1084-1094. https://doi.org/10.1007/s11036-020-01526-2

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/176479

Files in this item

Item Metadata

Title: Detecting Vehicles' Relative Position on Two-Lane Highways Through a Smartphone-Based Video Overtaking Aid Application
Author: Patra, Subhadeep Van Hamme, David Veelaert, Peter Tavares De Araujo Cesariny Calafate, Carlos Miguel Cano, Juan-Carlos Manzoni, Pietro Zamora, Willian
UPV Unit: Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Issued date:
Abstract:
[EN] In this paper we present a smartphone-based real-time video overtaking architecture for vehicular networks. The developed application aims to prevent head-on collisions that might occur due to attempts to overtake ...[+]
Subjects: VANET , ITS , Image processing , Plate recognition , Smartphone application , Android
Copyrigths: Reserva de todos los derechos
Source:
Mobile Networks and Applications. (issn: 1383-469X )
DOI: 10.1007/s11036-020-01526-2
Publisher:
Springer-Verlag
Publisher version: https://doi.org/10.1007/s11036-020-01526-2
Project ID:
info:eu-repo/grantAgreement/AEI//RTI2018-096384-B-I00-AR//SOLUCIONES PARA UNA GESTION EFICIENTE DEL TRAFICO VEHICULAR BASADAS EN SISTEMAS Y SERVICIOS EN RED/
Thanks:
This work was partially funding by the "Ministerio de Ciencia, Innovacion y Universidades, Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2018", Spain, under ...[+]
Type: Artículo

References

AbdulQawy A, Elkhouly R, Sallam E (2018) Approaching rutted road-segment alert using smartphone. In: 2018 13th International Conference on Computer Engineering and Systems (ICCES), pp 341–346

National Highway Traffic Safety Administration, et al. (2008) National motor vehicle crash causation survey: Report to congress. National Highway Traffic Safety Administration Technical Report DOT HS 811:059

Akritas MG, Murphy SA, Lavalley MP (1995) The Theil-Sen estimator with doubly censored data and applications to astronomy. J Am Stat Assoc 90(429):170–177 [+]
AbdulQawy A, Elkhouly R, Sallam E (2018) Approaching rutted road-segment alert using smartphone. In: 2018 13th International Conference on Computer Engineering and Systems (ICCES), pp 341–346

National Highway Traffic Safety Administration, et al. (2008) National motor vehicle crash causation survey: Report to congress. National Highway Traffic Safety Administration Technical Report DOT HS 811:059

Akritas MG, Murphy SA, Lavalley MP (1995) The Theil-Sen estimator with doubly censored data and applications to astronomy. J Am Stat Assoc 90(429):170–177

Bastani Zadeh R, Ghatee M, Eftekhari HR (2018) Three-phases smartphone-based warning system to protect vulnerable road users under fuzzy conditions. IEEE Trans Intell Transp Syst 19(7):2086–2098

Bhandari R, Raman B, Padmanabhan V (2019) Fullstop: A camera-assisted system for characterizing unsafe bus stopping. IEEE Trans. Mob. Comput: 1–1

Clarke DD, Ward P, Jones J (1998) Overtaking accidents. Transport Research Laboratory

El-Wakeel AS, Li J, Noureldin A, Hassanein HS, Zorba N (2018) Towards a practical crowdsensing system for road surface conditions monitoring. IEEE Internet of Things Journal 5(6):4672–4685

Galarza EE, Egas FD, Silva FM, Velasco PM, Galarza ED (2018) Real time driver drowsiness detection based on driver’s face image behavior using a system of human computer interaction implemented in a smartphone. In: Rocha Á, Guarda T (eds) Proceedings of the International Conference on Information Technology & Systems (ICITS 2018). Springer International Publishing, Cham, pp 563–572

Groeger J, Clegg B (1994) Why isn’t driver training contributing more to road safety?. In: Behavioural Research in Road Safety IV. Proceedings of a seminar held 6-7 September 1993, Brunel University.(TRL published article PA 3035/94)

Hadiwardoyo SA, Patra S, Calafate CT, Cano JC, Manzoni P (2018) An intelligent transportation system application for smartphones based on vehicle position advertising and route sharing in vehicular ad-hoc networks. J Comput Sci Technol 33(2): 249–262

Kataoka K, Gangwar S, Mudda KY, Mandal S (2018) A smartphone-based probe data platform for road management and safety in developing countries. In: 2018 IEEE international conference on data mining workshops (ICDMW), pp 612–615

Ma Y, Zhang Z, Chen S, Yu Y, Tang K (2019) A comparative study of aggressive driving behavior recognition algorithms based on vehicle motion data. IEEE Access 7:8028–8038

Mantouka EG, Barmpounakis EN, Vlahogianni EI (2019) Identifying driving safety profiles from smartphone data using unsupervised learning. Saf Sci 119:84–90

Patra S, Calafate CT, Cano JC, Veelaert P, Philips W (2017) Integration of vehicular network and smartphones to provide real-time visual assistance during overtaking. International Journal of Distributed Sensor Networks 13(12):1550147717748114

Patra S, Zamora W, Calafate CT, Cano JC, Manzoni P, Veelaert P (2019) Using the smartphone camera as a sensor for safety applications. In: Proceedings of the 5th EAI International Conference on Smart Objects and Technologies for Social Good, GoodTechs ’19. ACM, New York, pp 84–89

Phillips RF (2002) Least absolute deviations estimation via the EM algorithm. Stat Comput 12(3):281–285

Rousseeuw PJ, Van Driessen K (2006) Computing LTS regression for large data sets. Data Mining and Knowledge Discovery 12(1):29–45

Shikishima A, Nakamura K, Wada T (2018) Detection of texting while walking by using smartphone’s posture and acceleration information for safety of pedestrians. In: 2018 16th International Conference on Intelligent Transportation Systems Telecommunications (ITST), pp 1–6

Siegel AF (1982) Robust regression using repeated medians. Biometrika 69(1):242–244

Tanaka S, Takami K (2018) Detection of cyclists’ violation of stop sign rules using smartphone sensors. In: TENCON 2018 - 2018 IEEE Region 10 Conference, pp 1387–1392

Tornell SM, Patra S, Calafate CT, Cano JC, Manzoni P (2015) GRCBox: extending smartphone connectivity in vehicular networks. International Journal of Distributed Sensor Networks 11(3):478,064

Wallace GK (1991) The JPEG still picture compression standard. Commun ACM 34(4):30–44

Warren I, Meads A, Wang C, Whittaker R Awan I, Younas M, Ünal P, Aleksy M (eds) (2019) Monitoring driver behaviour with backpocketdriver. Springer International Publishing, Cham

Xie J, Hilal AR, Kulic D (2018) Driver distraction recognition based on smartphone sensor data. In: 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp 801–806

Xu X, Yu J, Chen Y, Zhu Y, Kong L, Li M (2019) Breathlistener: Fine-grained breathing monitoring in driving environments utilizing acoustic signals. In: Proceedings of the 17th annual international conference on mobile systems, applications, and services, MobiSys ’19. ACM, New York, pp 54–66

Xu X, Yu J, Chen Y, Zhu Y, Qian S, Li M (2018) Leveraging audio signals for early recognition of inattentive driving with smartphones. IEEE Trans Mob Comput 17(7):1553–1567

[-]

recommendations

 

This item appears in the following Collection(s)

Show full item record