References
- Ahmed, M. M., Franke, R., Ksaibati, K., & Shinstine, D. S. (2018). Effects of truck traffic on crash injury severity on rural highways in Wyoming using Bayesian binary logit models. Accident Analysis and Prevention, 117, 106–113. doi:10.1016/j.aap.2018.04.011
- Barriere, J. F., Farges, J. L., & Henry, J. J. (1986). Decentralization vs hierarchy in optimal traffic control. In IFAC Control in Transportation Systems. Vienna, Austria.
- Bell, M. (1992). Future directions in traffic signal control. Transportation Research Part A: Policy and Practice, 26, 303–313. doi:10.1016/0965-8564(92)90018-3
- Chilukuri, B., Perrin, J., & Martin, P. T. (2004). SCOOT and incidents: Performance evaluation in simulated environment. Transportation Research Record, 1867, 224–232.
- Day, C., Ernst, J., Brennan, T., Chou, C.-S., Hainen, A., Remias, S., & Bullock, D. (2012). Performance measures for adaptive signal control: Case study of system-in-the-loop simulation. Transportation Research Record: Journal of the Transportation Research Board, 2311, 1–15. doi:10.3141/2311-01
- Federal Highway Administration. (2012). Model Systems Engineering Documents for Adaptive Signal Control Technology (ASCT) Systems, (August).
- Fontaine, M. D. (2012). Evaluating travel time data quality form a private sector data provider: A case study of I-66 in Northern Virginia.” In North American Traffic Monitoring Exhibition and Conf., Dallas.
- Gartner, N. H., Pooran, F. J., & Andrews, C. M. (2002). Optimized policies for adaptive control strategy in real-time traffic adaptive control systems: Implementation and field testing. Transportation Research Record: Journal of Transportation Research Board, 1811, 148–156. doi:10.3141/1811-18
- Haghani, A., Hamedi, M., & Parvan, K. (2013). I-95 Corridor Coalition Vehicle Probe Project: Validation of INRIX Data Monthly Report, (June).
- Hu, J., Fontaine, M. D., Park, B. B. (2015). Field evaluations of an adaptive traffic signal — using private-sector probe data. Journal of Transportation Engineering, 142(1), 1–9. doi:10.1061/(ASCE)TE.1943-5436.0000806.
- Infra, I. T. (2016). Split cycle offset optimization technique. Retrieved from http://www.scoot-utc.com/DetailedHowSCOOTWorks.php?menu=Technical
- Kamrani, M., Ramin, A., & Khattak, A. J. (2018). Extracting useful information from connected vehicle data: An empirical study of driving volatility measures and crash frequency at intersections. Transportation Research Record, Journal of Transportation Research Board, 2672, 290–301. doi:10.1177/0361198118773869
- Kergaye, C., Stevanovic, A., & Martin, P. (2010). Comparative evaluation of adaptive traffic control system assessments through field and microsimulation. Journal of Intelligent Transportation Systems, 14(2), 109–124. doi:10.1080/15472451003719764
- Kergaye, C., Stevanovic, A., & Martin, P. T. (2009). Comparison of before-after versus off-on adaptive traffic control evaluations. Transportation Research Record: Journal of the Transportation Research Board, 2128(1), 192–201. doi:10.3141/2128-20
- Khattak, A. J., & Wali, B. (2017). Analysis of volatility in driving regimes extracted from basic safety messages transmitted between connected vehicles. Transportation Research Part C, 84, 48–73. doi:10.1016/j.trc.2017.08.004
- Khattak, Z. H. (2016). Evaluating the Operational & Safety Aspects of Adaptive Traffic Control Systems in Pennsylvania (University of Pittsburgh Thesis).
- Khattak, Z. H., Fontaine, M. D., & Boateng, R. A. (2018). Evaluating the impact of adaptive signal control technology on driver stress and behavior using real world experimental data. Transportation Research Part F, 58. doi:10.1016/j.trf.2018.06.006.
- Khattak, Z. H., Fontaine, M. D., Smith, B. L., & Ma, J. (2019). Crash severity effects of adaptive signal control technology: An empirical assessment with insights from Pennsylvania and Virginia. Accident Analysis and Prevention, 154, 151–162. doi:10.1016/j.aap.2019.01.008
- Khattak, Z. H., Magalotti, M. J., & Fontaine, M. D. (2018). Estimating safety effects of adaptive signal control technology using the empirical Bayes method. Journal of Safety Research, 64, 121–128. doi:10.1016/j.jsr.2017.12.016
- Khattak, Z. H., Park, H., Hong, S., Boateng, R., & Smith, B. L. (2018). Investigating cybersecurity issues in active traffic management systems. Transportation Research Record, Journal of Transportation Research Board, 2672, 79–90. doi:10.1177/0361198118787636
- Kim, C. O., Park, Y., & Baek, J.-G. (2005). Optimal signal control using adaptive dynamic programming. International Conference on Computational Science & Its Applications. Singapore.
- Mirchandani, P., & Head, L. (2001). A real-time traffic signal control system - architecture, algorithms, and analysis. Transportation Research Part C: Emerging Technologies, 9(6), 415–432. doi:10.1016/S0968-090X(00)00047-4
- Newell, G. (1998). The rolling horizon scheme of traffic signal control. Transportation Research Part A: Policy and Practice, 32, 39–44. doi:10.1016/S0965-8564(97)00017-7
- NSW (2018). Sydney coordinated adaptive traffic signal. Retrieved from http://www.scats.com.au/how-scats-works.html
- Porche, I., & Lafortune, S. (1999). Adaptive look-ahead optimization of traffic signals. ITS Journal-Intelligent Transportation Systems Journal, 4(3-4), 209–254. doi:10.1080/10248079908903749
- Robertson, D. I., & Bretherton, R. (1974). Optimum control of an intersection for any known sequence of vehicle arrivals. IFAC/IFIP/IFORS Symposium on Traffic Control and Transportation Systems. Monte Carlo, Monaco.
- Robotics Institute, C. M. U. (2013). Scalable Urban Traffic Control. Retrieved from http://www.surtrac.net/
- Sen, S., & Head, K. (1997). Controlled optimization of phases at an intersection. Transportation Science, 31(1), 5–17. doi:10.1287/trsc.31.1.5
- Shelby, S. (2004). Single-intersection evaluation of real-time adaptive traffic signal control algorithms. Transportation Research Record: Journal of the Transportation Research Board, 1867(1), 183–192. doi:10.3141/1867-21
- Slavin, C., Feng, W., Figliozzi, M., & Koonce, P. (2013). A Statistical Study of the Impacts of SCATS Adaptive Traffic Signal Control on Traffic and Transit Performance. 92nd Annual Meeting of the Transportation Research Board, 53.
- Smith, S., Barlow, G., Xie, X.-F., & Rubinstein, Z. B. (2013). SURTRAC: Scalable Urban Traffic Control. Transportation Research Board Annual Meeting, 15. Retrieved from https://www.ri.cmu.edu/publication_view.html?pub_id=7408
- Smith, S. F., Barlow, G. J., Xie, X.-F., & Rubinstein, Z. B. (2013). Smart urban signal networks: initial application of the SURTRAC adaptive traffic signal control system. Icaps, 434–442.
- Sussman, J. S. (2008). Perspectives on Intelligent Transportation Systems (ITS). New York: Springer Science & Business Media. Retrieved from https://books.google.com/books?id=t6mJGZocOnIC&pgis=1
- Swarco. (2016). Urban Traffic Optimization by Integration Automation. Retrieved from https://www.swarco.com/en/Products-Services/Traffic-Management/Urban-Traffic-Management/Urban-Traffic-Systems/UTOPIA
- Tian, Z., Ohene, F., & Hu, P. (2011). Arterial performance evaluation on an adaptive traffic signal control system. In 6th International Symposium on Highway Capacity and Quality of Service (Vol. 16). Retrieved from http://trid.trb.org/view.aspx?id=1136429
- Wang, X., Khattak, A. J., Liu, J., Masghati-Amoli, G., & Son, S. (2015). What is the level of volatility in instantaneous driving decisions? Transportation Research Part C, 58, 413–427. doi:10.1016/j.trc.2014.12.014
- Xie, X.-F., Smith, S. F., Lu, L., & Barlow, G. J. (2012). Schedule-driven intersection control. Transportation Research Part C, 24, 168–189. doi:10.1016/j.trc.2012.03.004