Lessons Learned from Field Operational Test of Integrated Network Management in Amsterdam

Author:

Hoogendoorn S. P.1,Van Kooten J.2,Adams R.3

Affiliation:

1. Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, Netherlands

2. ARANE Adviseurs in Verkeer en Vervoer, 2805 TD Gouda, Netherlands

3. Praktijkproef Amsterdam, Toekanweg 7, 2035 LC Haarlem, Netherlands

Abstract

The Amsterdam Practical Trial (APT) is a multiyear program initiated by the Dutch Ministry of Transport and the Environment and is carried out in close cooperation by Rijkswaterstaat, the City of Amsterdam, the Province of North Holland, and the Amsterdam Metropolitan Region. The APT aims to integrate innovative roadside and in-car developments networkwide. After the proof of concept was finished in 2009, two parallel tracks started in the Amsterdam region: the roadside track (aiming at an innovative, automated working system with ramp metering and traffic lights) and the in-car track (aiming at individualized travel and traffic information in the car for commuter traffic and for large-event traffic). This paper aims specifically at the innovative APT roadside system. Development of this system began in 2012, with the system becoming operational in April 2014. After all technical and functional tests were completed, the system parameters were tuned and finalized the implementation phase. Starting April 14, 11 weeks were taken to collect the data for the ex post assessment. In doing so, the authors have used an alternating assessment design, implemented by switching the system on and off every week so that a fair comparison could be made. From the collected data, it could be concluded that while the system caused additional delays on the urban network and ramps, the throughput on the freeway arterial was improved. Detailed analysis of the data showed the system performed as expected and which improvements can be made to further increase its effectiveness. These optimizations are discussed, as are the expected effects of implementing them in the system. How they are operationalized in Phase 2 of this innovative project will also be discussed.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Novel Framework Combining MPC and Deep Reinforcement Learning With Application to Freeway Traffic Control;IEEE Transactions on Intelligent Transportation Systems;2024-07

2. Percolation-based dynamic perimeter control for mitigating congestion propagation in urban road networks;Transportation Research Part C: Emerging Technologies;2022-12

3. Introduction;Systems & Control: Foundations & Applications;2022

4. Percolation-Based Dynamic Perimeter Control for Urban Road Networks;SSRN Electronic Journal;2022

5. Freeway traffic control: A survey;Automatica;2021-08

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