Abstract
Technological evolution impacts several industries, including automotive. The combination of software with advancements in sensory capabilities results in new Advanced Driver Assistance System (ADAS). The pervasiveness of smartphones and their sensory capabilities makes them an solid platform for the development of ADAS. Our work is motivated by concerns on the reliability of data acquired from such devices for developing ADAS. We performed a number of controlled experiments to understand which factors impact the collection of accelerometer data with smartphones. We conclude that the quality of data acquired is not significantly affected by using different smartphones, car mounts, rates of sampling, or vehicles for the purpose of developing ADAS. Our results indicate that smartphone sensors can be used to develop ADAS.
Research sponsored by the Portugal Incentive System for Research and Technological Development. Project in co-promotion no. 002797/2015 (INNOVCAR 2015–2018).
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Notes
- 1.
Due to space constraints, only first run’s table is shown. For all tables, see [11].
References
Douangphachanh, V., Oneyama, H.: A study on the use of smartphones under realistic settings to estimate road roughness condition. Proc. Eastern Asia Soc. Transp. Stud. 9(2007), 14 (2013)
Du, Y., Liu, C., Wu, D., Jiang, S.: Measurement of IRI by using Z-axis accelerometers and GPS. Math. Probl. Eng. (2014)
Eriksson, J., Girod, L., Hull, B., Newton, R., Madden, S., Balakrishnan, H.: The pothole patrol: using a mobile sensor network for road surface monitoring. In: Proceedings of the 6th International Conference on Mobile Systems, Applications, and Services (2008)
Fazeen, M., Gozick, B., Dantu, R., Bhukhiya, M., González, M.C.: Safe driving using mobile phones. IEEE Trans. Intell. Transp. Syst. 13(3), 1462–1468 (2012)
Han, H., et al.: SenSpeed: sensing driving conditions to estimate vehicle speed in urban environments. In: IEEE Conference on Computer Communications, vol. 15, pp. 727–735 (2014)
Lindgren, A., Chen, F.: State of the art analysis: an overview of advanced driver assistance systems (ADAS) and possible human factors issues. Hum. Factors Econ. Aspects Saf. 38–50 (2006)
Mohan, P., Padmanabhan, V.N., Ramjee, R.: Nericell: rich monitoring of road and traffic conditions using mobile smartphones. In: Proceedings of the 6th ACM Conference on Embedded Networked Sensor Systems, p. 323 (2008)
Piras, M., Lingua, A., Dabove, P., Aicardi, I.: Indoor navigation using smartphone technology: a future challenge or an actual possibility? In: IEEE Position, Location and Navigation Symposium, pp. 1343–1352 (2014)
Ratanamahatana, C.A., Keogh, E.: Exact indexing of dynamic time warping. Knowl. Inf. Syst. 7(3), 358–386 (2004). https://doi.org/10.1007/s10115-004-0154-9
Salvador, S., Chan, P.: FastDTW: toward accurate dynamic time warping in linear time and space. Intell. Data Anal. 11, 561–580 (2007)
Santos, N.M.: A feasibility study on the use of smartphone sensors for development of advanced driver assistance systems. M.Sc. thesis, University of Minho, Portugal (2017)
Seraj, F., van der Zwaag, B.J., Dilo, A., Luarasi, T., Havinga, P.: RoADS: a road pavement monitoring system for anomaly detection using smart phones. In: Atzmueller, M., Chin, A., Janssen, F., Schweizer, I., Trattner, C. (eds.) Big Data Analytics in the Social and Ubiquitous Context. LNCS (LNAI), vol. 9546, pp. 128–146. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-29009-6_7
Tai, Y., Chan, C., Hsu, J.Y.: Automatic road anomaly detection using smart mobile device. In: 15th Conference on Artificial Intelligence and Applications (2010)
Texas Instruments: Advanced Driver Assistance (ADAS) Solutions Guide. Technical report, Texas Instruments (2015)
Yi, C., Chuang, Y., Nian, C.: Toward crowdsourcing-based road pavement monitoring by mobile sensing technologies. IEEE Trans. Intell. Transp. Syst. 16(4), 1905–1917 (2015)
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Santos, N.M., Ferreira, A.L., Fernandes, J.M. (2020). On the Use of Smartphone Sensors for Developing Advanced Driver Assistance Systems. In: Santos, H., Pereira, G., Budde, M., Lopes, S., Nikolic, P. (eds) Science and Technologies for Smart Cities. SmartCity 360 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 323. Springer, Cham. https://doi.org/10.1007/978-3-030-51005-3_11
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