[
Asudegi, M. and Haghani, A. (2013). Optimal number and location of node-based sensors for collection of travel time data in networks, Transportation Research Record: Journal of the Transportation Research Board 2338(1): 35–43.10.3141/2338-05
]Search in Google Scholar
[
Chang, B.-J., Hwang, R.-H., Tsai, Y.-L., Yu, B.-H. and Liang, Y.-H. (2019). Cooperative adaptive driving for platooning autonomous self driving based on edge computing, International Journal of Applied Mathematics and Computer Science 29(2): 213–225, DOI: 10.2478/amcs-2019-0016.10.2478/amcs-2019-0016
]Search in Google Scholar
[
Chen, A., Chootinan, P. and Pravinvongvuth, S. (2004). Multiobjective model for locating automatic vehicle identification readers, Transportation Research Record: Journal of the Transportation Research Board 1886(1): 49–58.10.3141/1886-07
]Search in Google Scholar
[
Gentili, M. and Mirchandani, P.B. (2018). Review of optimal sensor location models for travel time estimation, Transportation Research C: Emerging Technologies 90: 74–96.10.1016/j.trc.2018.01.021
]Search in Google Scholar
[
Haghani, A., Hamedi, M., Sadabadi, K., Young, S. and Tarnoff, P. (2010). Data collection of freeway travel time ground truth with Bluetooth sensors, Transportation Research Record: Journal of the Transportation Research Board 2160(1): 60–68.10.3141/2160-07
]Search in Google Scholar
[
Li, X. and Ouyang, Y. (2012). Reliable traffic sensor deployment under probabilistic disruptions and generalized surveillance effectiveness measures, Operations Research 60(5): 1183–1198.10.1287/opre.1120.1082
]Search in Google Scholar
[
Mazaré, P., Tossavainen, O. and Bayen, A. (2012). Trade-offs between inductive loops and GPS probe vehicles for travel time estimation: Mobile century case study, Transportation Research Board 91st Annual Meeting, Washington DC, USA, Paper no. 2746.
]Search in Google Scholar
[
Patan, M. and Kowalów, D. (2018). Distributed scheduling of measurements in a sensor network for parameter estimation of spatio-temporal systems, International Journal of Applied Mathematics and Computer Science 28(1): 39–54, DOI: 10.2478/amcs-2018-0003.10.2478/amcs-2018-0003
]Search in Google Scholar
[
Sánchez-Cambronero, S., Jiménez, P., Rivas, A. and Gallego, I. (2017). Plate scanning tools to obtain travel times in traffic networks, Journal of Intelligent Transportation Systems 21(5): 390–408.10.1080/15472450.2017.1298037
]Search in Google Scholar
[
Sherali, H.D., Desai, J. and Rakha, H. (2006). A discrete optimization approach for locating automatic vehicle identification readers for the provision of roadway travel times, Transportation Research B: Methodological 40(10): 857–871.10.1016/j.trb.2005.11.003
]Search in Google Scholar
[
Soriguera, F., Thorson, L. and Robusté, F. (2007). Travel time measurement using toll infrastructure, Transportation Research Record: Journal of the Transportation Research Board 2027(1): 99–107.10.3141/2027-13
]Search in Google Scholar
[
Sun, W., Shen, L., Shao, H. and Liu, P. (2021). Dynamic location models of mobile sensors for travel time estimation on a freeway, International Journal of Applied Mathematics and Computer Science 31(2): 271–287, DOI: 10.34768/amcs-2021-0019.
]Search in Google Scholar
[
Wardorp, J. (1952). Some theoretical aspects of road traffic research, ICE Proceedings Engineering Divisions 1(5): 767–768.10.1680/ipeds.1952.11362
]Search in Google Scholar
[
Zhu, N., Liu, Y., Ma, S. and He, Z. (2014). Mobile traffic sensor routing in dynamic transportation systems, IEEE Transactions on Intelligent Transportation Systems 15(5): 2273–2285.10.1109/TITS.2014.2314732
]Search in Google Scholar
[
Zhu, N., Ma, S. and Zheng, L. (2017). Travel time estimation oriented freeway sensor placement problem considering sensor failure, Journal of Intelligent Transportation Systems 21(1): 26–40.10.1080/15472450.2016.1194206
]Search in Google Scholar