Max-pressure (MP) signal timing is an actuated decentralized signal control policy. Rigorous mathematical studies have proven the stability properties and established the benefits of different MP policies. However, theoretical studies make assumptions about traffic properties that may not represent reality and whose effects are not explored much in the literature under realistic traffic conditions. This study focuses on examining how different variations of MP perform in realistic scenarios and on finding the most practical policy among those for implementation in real roads. Microsimulation models of seven intersections from two corridors, County Road (CR) 30 and CR 109 from Hennepin County, Minnesota were created. Real-life demand and current signal timing data provided by Hennepin County were used to make the simulations as close to reality as possible. In this paper, we compare the performance of current actuated-coordinated signal control with an acyclic MP and two variations of cyclic MP policies. We present the performance of different control policies as delay, throughput, worst lane delay, and number of phase changes. We also present how different parameters affect the performance of the MP policies. We found that better performance can be achieved with a cyclic MP policy by allowing phase skipping when no vehicles are waiting. Our findings also suggest that most of the claimed performance benefits can still be achieved in real-life traffic conditions even with the simplified assumptions made in the theoretical models. In most cases, MP control policies outperformed current signal control.
|Original language||English (US)|
|Title of host publication||Transportation Research Record|
|Publisher||Sage Publications Ltd|
|Number of pages||19|
|State||Published - Jun 2022|
|Name||Transportation Research Record|
Bibliographical noteFunding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: We gratefully acknowledge the support of the National Science Foundation, award no. 1935514 and the Minnesota Department of Transportation.
© National Academy of Sciences: Transportation Research Board 2022.
- Planning and analysis
- Simulation modeling
- Traffic signal
- Traffic signal systems
- Transportation network modeling