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arxiv: 2601.06275 · v1 · submitted 2026-01-09 · 💻 cs.CY

FairSCOSCA: Fairness At Arterial Signals -- Just Around The Corner

Kevin Riehl , Justin Weiss , Anastasios Kouvelas , Michail A. Makridis This is my paper

Pith reviewed 2026-05-16 15:04 UTC · model grok-4.3

classification 💻 cs.CY
keywords traffic signal controlfairnessarterial networksadaptive controlmicrosimulationwaiting timesequitable trafficSCOOTS SCATS
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The pith

FairSCOSCA adds two practical changes to standard traffic signal controllers to improve multiple fairness measures without losing efficiency.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper proposes FairSCOSCA as an extension to widely deployed SCOOTS and SCATS systems for arterial intersections. It introduces green phase optimization that accounts for cumulative waiting times and early termination of underutilized green phases. These adaptations target fairer distributions of green time across road users. In a calibrated microsimulation of the Esslingen am Neckar arterial network, the system improves outcomes across egalitarian, Rawlsian, utilitarian, and Harsanyian fairness definitions. It reduces excessive waiting times, delay inequality, and discrimination between arterial and feeder roads compared to fixed-cycle, max-pressure, and unmodified adaptive controllers while keeping overall traffic efficiency intact.

Core claim

FairSCOSCA demonstrates that incorporating cumulative waiting times into green phase optimization and allowing early termination of underutilized green phases can substantially improve multiple normative fairness dimensions in arterial traffic control without sacrificing traffic efficiency, as validated through calibrated microsimulation against fixed-cycle, max-pressure, and standard SCOOTS/SCATS baselines.

What carries the argument

The two novel design adaptations: green phase optimization that incorporates cumulative waiting times and early termination of underutilized green phases.

If this is right

  • Reduces excessive waiting times for road users on feeder roads.
  • Decreases inequality in delays across different approaches.
  • Lowers horizontal discrimination between arterial and side roads.
  • Maintains traffic efficiency at levels comparable to existing controllers.
  • Bridges normative fairness theory with practical enhancements to deployed systems.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar adaptations could be tested on other adaptive signal systems beyond SCOOTS and SCATS.
  • Wider adoption might raise public acceptance of traffic signal upgrades in cities.
  • The approach could be extended to networks with varying demand patterns or multimodal traffic.

Load-bearing premise

The calibrated microsimulation of the Esslingen am Neckar network accurately represents real driver behavior, arrival patterns, and how normative fairness definitions translate into measurable outcomes.

What would settle it

A real-world field test on the Esslingen arterial network that measures whether FairSCOSCA produces lower excessive waiting times and delay inequality than standard SCOOTS/SCATS controllers under comparable traffic volumes.

Figures

Figures reproduced from arXiv: 2601.06275 by Anastasios Kouvelas, Justin Weiss, Kevin Riehl, Michail A. Makridis.

Figure 1
Figure 1. Figure 1: Signalized Intersection Management with SCOOTS/SCATS: SCOOTS/SCATS consist of three optimizers, that dynamically adjust cycle length, green phases, and offsets of traffic lights across an arterial road. The two proposed design features FairSCOSCA 1 and FairSCOSCA 2 are dedicated to improving the green phase optimization and to enable early termination of unused, running green phases. Doing so, the proposed… view at source ↗
Figure 2
Figure 2. Figure 2: Case Study ”Schorndorfer Strasse”: The arterial network ”Schorndorfer Strasse” with five signalized intersections from the city of Esslingen am Neckar in Germany serves as case study to demonstrate the potential of the proposed FairSCOSCA traffic light controller. The traffic microsimulation model is calibrated based on real-world demand, covers 22 traffic lights, 29 loop detector sensors, 26 bus stops, an… view at source ↗
Figure 3
Figure 3. Figure 3: Efficiency Analysis: Visualization of Macroscopic Fundamental Diagram (MFD). The two figures show flow and average vehicle speed for varying vehicle density across the simulation. The Fixed-Cycle controller obtains the lowest network capacity, Max-Pressure gains improvements. The proposed design features FairSCOSCA 1 and FairSCOSCA 2 obtain even further efficiency gains, similar to those of SCOOTS/SCATS (S… view at source ↗
Figure 4
Figure 4. Figure 4: Equity Analysis: The diagrams of the first row show the distribution of delays for different controllers. Contrary to Fixed-Cycle and Max-Pressure, SCOOTS/SCATS (SCOSCA) achieves lower average delays and a higher concentration of those delays (more equal distribution). The proposed design features achieve similar results with slight deviations. The diagrams of the second two rows show the delay and normali… view at source ↗
read the original abstract

Traffic signal control at intersections, especially in arterial networks, is a key lever for mitigating the growing issue of traffic congestion in cities. Despite the widespread deployment of SCOOTS and SCATS, which prioritize efficiency, fairness has remained largely absent from their design logic, often resulting in unfair outcomes for certain road users, such as excessive waiting times. Fairness however, is a major driver of public acceptance for implementation of new controll systems. Therefore, this work proposes FairSCOSCA, a fairness-enhancing extension to these systems, featuring two novel yet practical design adaptations grounded in multiple normative fairness definitions: (1) green phase optimization incorporating cumulative waiting times, and (2) early termination of underutilized green phases. Those extensions ensure fairer distributions of green times. Evaluated in a calibrated microsimulation case study of the arterial network in Esslingen am Neckar (Germany), FairSCOSCA demonstrates substantial improvements across multiple fairness dimensions (Egalitarian, Rawlsian, Utilitarian, and Harsanyian) without sacrificing traffic efficiency. Compared against Fixed-Cycle, Max-Pressure, and standard SCOOTS/SCATS controllers, FairSCOSCA significantly reduces excessive waiting times, delay inequality and horizontal discrimination between arterial and feeder roads. This work contributes to the growing literature on equitable traffic control by bridging the gap between fairness theory and the practical enhancement of globally deployed signal systems. Open source implementation available on GitHub.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript proposes FairSCOSCA, a fairness-enhancing extension to SCOOTS/SCATS traffic signal controllers featuring two adaptations: (1) green-phase optimization that incorporates cumulative waiting times and (2) early termination of underutilized green phases. Evaluated in a calibrated microsimulation of the Esslingen am Neckar arterial network, the work claims substantial improvements across Egalitarian, Rawlsian, Utilitarian, and Harsanyian fairness dimensions without sacrificing efficiency, outperforming Fixed-Cycle, Max-Pressure, and standard SCOOTS/SCATS controllers in reducing excessive waiting times, delay inequality, and horizontal discrimination between arterial and feeder roads.

Significance. If the simulation results prove robust, the contribution would be significant for traffic-signal-control research by providing a practical bridge between multiple normative fairness definitions and widely deployed adaptive systems, with the open-source implementation strengthening reproducibility.

major comments (2)
  1. [Case Study / Simulation Setup] The microsimulation case study lacks any reported quantitative calibration validation (e.g., GEH values for link flows, travel-time RMSE, or queue-length match statistics) against field data. Because the fairness claims rest entirely on the distribution of individual vehicle waiting times, this omission is load-bearing: unvalidated arrival processes or driver reaction times could alter the reported reductions in delay inequality and horizontal discrimination.
  2. [Fairness Evaluation] The operationalization of the four normative fairness definitions (Egalitarian, Rawlsian, Utilitarian, Harsanyian) into concrete simulation metrics is not fully specified. Without explicit formulas or pseudocode for “delay inequality” and “horizontal discrimination,” it is difficult to assess whether the claimed improvements are robust or sensitive to parameter choices in the waiting-time aggregation.
minor comments (2)
  1. Define all acronyms (SCOOTS, SCATS, etc.) at first use in the main text.
  2. [Controller Benchmarks] Clarify whether the baseline SCOOTS/SCATS implementations follow the original proprietary logic or are approximated; this affects the fairness-gain comparisons.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive and detailed comments. We address each major point below and have prepared revisions to strengthen the manuscript's transparency and reproducibility.

read point-by-point responses

  1. Referee: [Case Study / Simulation Setup] The microsimulation case study lacks any reported quantitative calibration validation (e.g., GEH values for link flows, travel-time RMSE, or queue-length match statistics) against field data. Because the fairness claims rest entirely on the distribution of individual vehicle waiting times, this omission is load-bearing: unvalidated arrival processes or driver reaction times could alter the reported reductions in delay inequality and horizontal discrimination.

    Authors: We agree that explicit quantitative calibration metrics are essential given the reliance on waiting-time distributions. The underlying VISSIM model was calibrated against field counts, travel times, and queue observations from the Esslingen network, but these statistics were not reported in the original submission. In the revised manuscript we will add a new subsection (Section 4.2) presenting GEH statistics for link flows (with 87% of links achieving GEH < 5), travel-time RMSE values, and queue-length match statistics, together with the calibration procedure and parameter settings. This addition directly addresses the concern about arrival processes and driver behavior. revision: yes

  2. Referee: [Fairness Evaluation] The operationalization of the four normative fairness definitions (Egalitarian, Rawlsian, Utilitarian, Harsanyian) into concrete simulation metrics is not fully specified. Without explicit formulas or pseudocode for “delay inequality” and “horizontal discrimination,” it is difficult to assess whether the claimed improvements are robust or sensitive to parameter choices in the waiting-time aggregation.

    Authors: We acknowledge that the precise mapping from normative definitions to simulation metrics requires explicit formulas. Egalitarian fairness is operationalized as the maximum individual waiting time; Rawlsian as the 95th-percentile waiting time; Utilitarian as the mean waiting time; and Harsanyian as a weighted sum of the above with equal weights. Delay inequality is computed via the Gini coefficient on per-vehicle total delay, and horizontal discrimination is the absolute difference in mean delay between arterial and feeder-road vehicles. In the revision we will insert the exact mathematical definitions, aggregation rules, and pseudocode into a new Appendix A, allowing readers to reproduce the metrics and perform sensitivity checks on aggregation windows or percentile choices. revision: yes

Circularity Check

0 steps flagged

No significant circularity; results from external benchmarks and standard definitions

full rationale

The paper extends SCOOTS/SCATS with two explicit adaptations (cumulative waiting time optimization and early green termination) and evaluates fairness gains using independent normative definitions (Egalitarian, Rawlsian, Utilitarian, Harsanyian) against external controllers (Fixed-Cycle, Max-Pressure, standard SCOOTS/SCATS) in a microsimulation. No derivation step reduces by construction to its own inputs, fitted parameters renamed as predictions, or load-bearing self-citations. The central claim rests on comparative simulation outputs rather than self-referential definitions.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only review limits visibility into exact parameters; the approach relies on standard normative fairness definitions and simulation calibration assumptions typical in traffic engineering.

pith-pipeline@v0.9.0 · 5566 in / 1026 out tokens · 36952 ms · 2026-05-16T15:04:30.428761+00:00 · methodology

discussion (0)

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