A case study on traffic congestion control system using data mining and machine learning applications

Author:

Asif S.,Kartheeban K.

Publisher

AIP Publishing

Reference129 articles.

1. Reed, T.; Kidd, J. Global Traffic Scorecard; INRIX Research: Altrincham, UK, 2019.

2. “Traffic congestion and reliability: Trends and advanced strategies for congestion mitigation,” https://ops.fhwa.dot.gov/congestionreport/executivesummary.htm, 2017, [Online; accessed 19-Aug-2017].

3. http://timesofindia.indiatimes.com/articleshow/63918040.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst, India News [Online; accessed April 26, 2018].

4. Systematic, C. Traffic Congestion and Reliability: Trends and Advanced Strategies for Congestion Mitigation; Cambridge Systematic Inc.: Cambridge, MA, USA, 2005.

5. FHWA. Operations–Reducing Recurring Congestion. Available online: https://ops.fhwa.dot.gov/program_areas/reduce-recur-cong.htm (accessed on 10 December 2019).

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