A REAL-TIME TRAFFIC SIGNAL CONTROL SYSTEM: ARCHITECTURE, ALGORITHMS, AND ANALYSIS

By Pitu B. Mirchandani, L. Head. 2001

735 citations recorded by the source corpus.

Subfields: Building and Construction, Control and Systems Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/2513eff8be757864a4346bb3dfc9061c816caa39

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

In Control and Systems Engineering

In Transportation

Citations in the corpus

Traffic Signal Control with Connected Vehicles (2013, methodology): “PAMSCOD is based on RHODES, a point detection-based rolling horizon traffic control algorithm first published in 2001 [70].”
The Max-Pressure Controller for Arbitrary Networks of Signalized Intersections (2013, methodology): “Previous designs of traffic-responsive controllers (Robertson and Bretherton 1991; Mirchandani and Head 2001; Heydecker 2004; Aboudolas et al. 2009b; Cai et al. 2009) require (or make) an estimate of the arrivals over a finite or infinite horizon and select the control that minimizes queues or…”
Store-and-forward based methods for the signal control problem in large-scale congested urban road networks (2009, methodology): “Other elaborated model-based traffic-responsive strategies such as PRODYN (Farges et al., 1983) and RHODES (Mirchandani and Head, 1998; Mirchandani and Wang, 2005) employ dynamic programming while OPAC (Gartner, 1983) employs exhaustive enumeration.”
Urban traffic signal control with connected and automated vehicles: A survey (2019, methodology): “Although the idea of platoon-based traffic signal control has been proposed for several decades (Mirchandani and Head, 2001), it became realistic only after V2X technique was introduced (He et al., 2012; Liang et al., 2018; Lioris et al., 2017; Xie et al., 2012).”
Analysis of fixed-time control☆ (2014, background): “The movement of vehicles is often modeled as a queuing network as, for example, in Papageorgiou et al. (2003); Mirchandani and Head (2001).”
A robust optimization approach for dynamic traffic signal control with emission considerations (2012, methodology): “According to the power demand-based emission model proposed by Post et al. (1984), the overall instantaneous total power demand Z (in kilowatt) for a vehicle with mass m in (kilogram) is given by Z = (0.04 v + 0.5× 10−3v2 + 10.8× 10−6v3) + m 1000 v 3.6 ( a 3.6 + 9.81 sin θ ) (3.8) where the above…”
Traffic signal timing via deep reinforcement learning (2016, neutral): “Rt = ∞ ∑ i=t γ i−tri = rt + γRt+1, (1) where γ ∈ [0,1] are the discount factor.”
Cooperative Intersection Management: A Survey (2016, background): “The introduction of traffic lights has helped to improve the traffic condition at intersections, and systems such as the Sydney Coordinated Adaptive Traffic (SCAT) system [3], SCOOT [4], as well as RHODES [5] have tried to improve the efficiency by adapting the traffic signals based on”