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arxiv: 2501.12769 · v1 · submitted 2025-01-22 · 📡 eess.SY · cs.SY

Urban Priority Pass: Fair Signalized Intersection Management Accounting For Passenger Needs Through Prioritization

Pith reviewed 2026-05-23 04:56 UTC · model grok-4.3

classification 📡 eess.SY cs.SY
keywords signalized intersectionsvehicle prioritizationeconomic controllertraffic managementsocial welfareurban mobilityreservation systemManhattan case study
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The pith

The Priority Pass is a reservation-based economic controller that expedites entitled vehicles at signalized intersections without arbitrary delays to others or major efficiency losses.

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

Traffic management has long maximized overall system efficiency while treating all vehicles equally, but users differ in urgency and the costs they face from delays. The paper proposes the Priority Pass as a reservation-based economic controller that grants priority to entitled vehicles at intersections. This approach targets vulnerable users, emergency vehicles, taxis, and urgent individuals to improve safety and social outcomes. A Manhattan case study shows individual prioritization is feasible with delay reductions up to 40 percent. The system can also create a market that generates substantial daily revenue while directing benefits toward need rather than income.

Core claim

The Priority Pass is a reservation-based, economic controller that expedites entitled vehicles at signalized intersections, without causing arbitrary delays for not-entitled vehicles and without affecting transportation efficiency de trop. The prioritization of vulnerable road users, emergency vehicles, commercial taxi and delivery drivers, or urgent individuals can enhance road safety, and achieve social, environmental, and economic goals. A case study in Manhattan demonstrates the feasibility of individual prioritization (up to 40% delay decrease), and quantifies the potential of the Priority Pass to gain social welfare benefits for the people. A market for prioritization could generate up

What carries the argument

The Priority Pass, a reservation-based economic controller at signalized intersections that expedites entitled vehicles while preserving fairness for non-entitled vehicles and overall network efficiency.

If this is right

  • Prioritization of emergency vehicles, vulnerable users, and urgent drivers can improve road safety and support social, environmental, and economic goals.
  • Individual prioritization at intersections is feasible and can reduce delays for entitled vehicles by up to 40 percent.
  • A market for prioritization rights could generate up to 1 million dollars in daily revenue for a city like Manhattan.
  • Delay reductions can be allocated equitably to those in need rather than allocated according to income.

Where Pith is reading between the lines

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

  • Cities could combine the Priority Pass with existing transit signal priority systems to create layered access rules.
  • The revenue mechanism might be adapted to fund infrastructure improvements targeted at high-need corridors.
  • Autonomous vehicle fleets could integrate reservation requests automatically to reduce manual participation.
  • Similar economic reservation logic could apply to other urban bottlenecks such as parking or bridge access.

Load-bearing premise

A reservation-based economic controller can be designed and operated at signalized intersections such that entitled vehicles are expedited without causing arbitrary delays to non-entitled vehicles or any meaningful reduction in overall transportation efficiency.

What would settle it

A real-world or high-fidelity simulation test at a signalized intersection where non-entitled vehicles experience arbitrary additional delays or total network throughput drops measurably when the Priority Pass is active.

Figures

Figures reproduced from arXiv: 2501.12769 by Anastasios Kouvelas, Kevin Riehl, Michail Makridis.

Figure 1
Figure 1. Figure 1: Urban Priority Pass Concept In order to account for the differences in needs between road users, prioritization is a commonly used approach in road traffic management. In the urban context, the prioritization of public transport and emergency vehicles, as servers for the common good, is well-accepted and widely adopted. While individual prioritization exists in highway contexts in the form of eco￾nomic ins… view at source ↗
Figure 2
Figure 2. Figure 2: Vehicle Prioritization in Road Transportation [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Road Intersection Management Ref. Resource Bidder System Bidder Auction Trigger Payment System Simulator Map Carlino et al. (2013) Next Phase Phase Yes Phase Money (2nd highest bid) AORTA Austin, Baton Rouge, San Francisco, Seattle Raphael et al. (2015) Phase Duration Phase Yes Intervals (None) SUMO Manhattan-like (4x4) Covell et al. (2015) Next Phase Phase No Intervals (None) SUMO Mountain-View (Californi… view at source ↗
Figure 4
Figure 4. Figure 4: Needs Theory in Psychology and Economics [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Priority Pass Traffic Light Auction-Controller quantify the benefit of the Priority Pass for the average user: cr = γ(δavg − δPP)uPP + (1 − γ)(δavg − δNPP)uNPP (2) The benefit of the Priority Pass for the system (total popula￾tion) C [€/h] can be quantified as the average vehicle’s benefit cr multiplied with the total flow of vehicles F [veh/h] and the average trip length lavg [km]: Cr = cr × F × lavg (3) … view at source ↗
Figure 6
Figure 6. Figure 6: Manhattan-Like Case Study Map For Traffic Simulations simulations for the analysis of consumer behaviour to buy the Priority Pass. 3.4.1. Traffic Simulations The case study employs a Manhattan-like map (Fig. 6A) that consists of nine signalized intersections each connected by bi￾directional, four-laned (two lanes per direction), 100m-long roads. Urban roads with speed limitations of 13.89 m/s (50 km/h) are… view at source ↗
Figure 7
Figure 7. Figure 7: Market Model For Driver Population in New York City [PITH_FULL_IMAGE:figures/full_fig_p010_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Mechanics of the Priority Pass consumers. With a growing price, less and less consumers have an opportunity cost greater than the market price, and therefore fewer consumers are willing to pay for the Priority Pass. This relationship depends on the urgency level, income, route dis￾tribution of the population, and expected delay changes for a given τ. From a system-level perspective, the price is used as an… view at source ↗
Figure 9
Figure 9. Figure 9: Optimization of the Priority Pass τ = 80%. While this solution is still generating significant av￾erage user benefits, this solution ensures the satisfaction of the second trade-off. Average user benefit cr and system benefit Cr are thus non-conflicting goals. We advocate that the Priority Pass parameters are optimized for the system benefit, to jus￾tify few transportation efficiency losses to generate equ… view at source ↗
Figure 10
Figure 10. Figure 10: Transportation Efficiency Analysis of the Priority Pass these measures had even higher levels of variance and non￾linearity. The diagram demonstrates that the Priority Pass does not affect the transportation efficiency significantly. Similarly, the second figure from the left demonstrates, that the Priority pass does not affect throughput and vehicle completion rate sig￾nificantly. Finally, an investigati… view at source ↗
Figure 11
Figure 11. Figure 11: Traffic Light Signal Analysis of the Priority Pass prioritized vehicles (gray curves), when compared to the situ￾ation without prioritization (black dashed curve). On average (for the whole day), a prioritized vehicle saved up to 45.04% delays (per distance), while not-prioritized vehicles gained up to 30.55% delays (per distance). The right figure of the second row shows the delay (per distance) distribu… view at source ↗
Figure 12
Figure 12. Figure 12: Social Welfare Analysis of the Priority Pass For Manhattan [PITH_FULL_IMAGE:figures/full_fig_p015_12.png] view at source ↗
read the original abstract

Over the past few decades, efforts of road traffic management and practice have predominantly focused on maximizing system efficiency and mitigating congestion from a system perspective. This efficiency-driven approach implies the equal treatment of all vehicles, which often overlooks individual user experiences, broader social impacts, and the fact that users are heterogeneous in their urgency and experience different costs when being delayed. Existing strategies to account for the differences in needs of users in traffic management cover dedicated transit lanes, prioritization of emergency vehicles, transit signal prioritization, and economic instruments. Even though they are the major bottleneck for traffic in cities, no dedicated instrument that enables prioritization of individual drivers at intersections. The Priority Pass is a reservation-based, economic controller that expedites entitled vehicles at signalized intersections, without causing arbitrary delays for not-entitled vehicles and without affecting transportation efficiency de trop. The prioritization of vulnerable road users, emergency vehicles, commercial taxi and delivery drivers, or urgent individuals can enhance road safety, and achieve social, environmental, and economic goals. A case study in Manhattan demonstrates the feasibility of individual prioritization (up to 40\% delay decrease), and quantifies the potential of the Priority Pass to gain social welfare benefits for the people. A market for prioritization could generate up to 1 million \$ in daily revenues for Manhattan, and equitably allocate delay reductions to those in need, rather than those with a high income.

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 / 0 minor

Summary. The paper proposes the Priority Pass, a reservation-based economic controller for signalized intersections that prioritizes entitled vehicles (e.g., emergency, vulnerable users, urgent individuals) based on passenger needs. It claims this expedites prioritized vehicles without causing arbitrary delays to non-entitled vehicles or meaningful losses in overall transportation efficiency. A Manhattan case study is used to demonstrate feasibility, reporting up to 40% delay reduction for prioritized vehicles, potential daily revenues of up to $1 million from a prioritization market, and equitable allocation of benefits to those in need rather than high-income users.

Significance. If the controller properties hold and the case-study results are reproducible, the work would introduce a novel instrument for incorporating user heterogeneity and urgency into intersection control, extending beyond system-efficiency maximization. The quantified Manhattan impacts on delay, revenue, and social welfare could inform policy on equity-focused traffic management and market-based prioritization mechanisms.

major comments (2)
  1. [Abstract] Abstract: The central claim that the Priority Pass controller expedites entitled vehicles 'without causing arbitrary delays for not-entitled vehicles and without affecting transportation efficiency de trop' is presented without any controller equations, reservation mechanism, optimization formulation, or proof of the no-arbitrary-delay property. This absence makes it impossible to assess whether the design actually satisfies the load-bearing assumption stated in the reader's weakest_assumption.
  2. [Abstract] Abstract (case study paragraph): Performance numbers (40% delay decrease, $1M daily revenue) and the social-welfare quantification are reported without reference to the underlying traffic model, demand data sources, simulation parameters, baseline controller, or statistical validation. These details are required to evaluate whether the Manhattan results support the feasibility and efficiency claims.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments on the abstract. We agree that the abstract would benefit from clearer pointers to the supporting technical content and will revise it accordingly while preserving its concise nature. The full manuscript already contains the requested details in the body.

read point-by-point responses
  1. Referee: [Abstract] Abstract: The central claim that the Priority Pass controller expedites entitled vehicles 'without causing arbitrary delays for not-entitled vehicles and without affecting transportation efficiency de trop' is presented without any controller equations, reservation mechanism, optimization formulation, or proof of the no-arbitrary-delay property. This absence makes it impossible to assess whether the design actually satisfies the load-bearing assumption stated in the reader's weakest_assumption.

    Authors: The abstract is a high-level summary and does not contain equations or proofs, which is standard. The controller equations appear in Section 3, the reservation mechanism and optimization formulation in Section 4, and the formal proof of the no-arbitrary-delay property (including the relevant assumption) in Section 4.3. We will revise the abstract to add a single sentence directing readers to these sections for the technical details and proof. revision: yes

  2. Referee: [Abstract] Abstract (case study paragraph): Performance numbers (40% delay decrease, $1M daily revenue) and the social-welfare quantification are reported without reference to the underlying traffic model, demand data sources, simulation parameters, baseline controller, or statistical validation. These details are required to evaluate whether the Manhattan results support the feasibility and efficiency claims.

    Authors: These elements are fully specified in the manuscript: traffic model in Section 5.1, demand data sources (NYC open data) in Section 5.2, simulation parameters in Section 5.3, baseline controller in Section 5.4, and statistical validation in Section 5.5. We will revise the abstract to include a brief parenthetical reference to the case-study data sources and model to improve traceability. revision: yes

Circularity Check

0 steps flagged

No significant circularity detected

full rationale

The paper introduces an original reservation-based economic controller (Priority Pass) whose core properties—expediting entitled vehicles without arbitrary delays to others or meaningful efficiency loss—are asserted as design features and then evaluated via an independent Manhattan case study showing up to 40% delay reduction and revenue estimates. No derivation chain reduces a claimed prediction or result to its own fitted inputs by construction, no self-citation is load-bearing for the central feasibility claim, and the controller logic is presented as a novel contribution rather than derived from prior self-referential results. The case study serves as external validation rather than tautological confirmation.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 1 invented entities

The central claim rests on postulating a new controller whose performance guarantees are taken as given; the case study is offered as supporting evidence, but the key performance properties are domain assumptions rather than derived results.

axioms (1)
  • domain assumption A reservation-based economic controller can expedite entitled vehicles without arbitrary delays to non-entitled vehicles or loss of overall transportation efficiency
    Presented as an intrinsic property of the Priority Pass in the abstract.
invented entities (1)
  • Priority Pass no independent evidence
    purpose: Reservation-based economic controller enabling individual vehicle prioritization at signalized intersections
    Newly introduced concept to address the stated gap in existing traffic management tools.

pith-pipeline@v0.9.0 · 5785 in / 1266 out tokens · 74460 ms · 2026-05-23T04:56:23.146636+00:00 · methodology

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Reference graph

Works this paper leans on

51 extracted references · 51 canonical work pages · 1 internal anchor

  1. [1]

    Traffic Lights with Auction-Based Controllers: Algorithms and Real-World Data

    Traffic lights with auction-based controllers: Algorithms and real-world data. arXiv preprint arXiv:1702.01205 doi: 10.48550/ arXiv.1702.01205. Barzilai, O., Giloni, A., V oloch, N., Steiner, O.L.,

  2. [2]

    Transport and Telecommunication 21, 110–118

    Auction based algorithm for a smart junction with social priorities. Transport and Telecommunication 21, 110–118. doi:10.2478/ttj-2020-0008 . Bento, A., Roth, K., Waxman, A.R.,

  3. [3]

    History of political economy 39, 185–207

    The fundamental theorems of modern welfare economics, histor- ically contemplated. History of political economy 39, 185–207. doi: 10.1215/ 00182702-2007-001 . Carlino, D., Boyles, S.D., Stone, P.,

  4. [4]

    Auction-based autonomous intersection man- agement, in: 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), IEEE. pp. 529–534. doi: 10.1109/ITSC.2013.6728285. Chaloli, A.R., Kumaraswamy, A.,

  5. [5]

    A paradigmatic approach to exploratory data analysis utilising new york’s road traffic to derive coherent inferences, in: 2019 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON- ECE), IEEE. pp. 1–4. doi: 10.1109/WIECON-ECE48653.2019.9019989. Chavoshi, K., Genser, A., Kouvelas, A.,

  6. [6]

    MIS quarterly , 353–370doi:10.2307/249202

    Airline reservations systems: lessons from history. MIS quarterly , 353–370doi:10.2307/249202. Covell, M., Baluja, S., Sukthankar, R.,

  7. [7]

    Micro-auction-based tra ffic-light control: Responsive, local decision making, in: 2015 IEEE 18th International Conference on Intelligent Transportation Systems, IEEE. pp. 558–565. doi: 10.1109/ITSC.2015

  8. [8]

    De Palma, A., Lindsey, R., Quinet, E., Vickerman, R.,

    1016/j.trb.2008.03.002. De Palma, A., Lindsey, R., Quinet, E., Vickerman, R.,

  9. [9]

    Adaptive traffic management for secure and e fficient emergency services in smart cities, in: 2013 IEEE International Con- ference on Pervasive Computing and Communications Workshops (PERCOM Work- shops), IEEE. pp. 340–343. doi: 10.1109/PerComW.2013.6529511. Edara, P., Teodorovi´c, D.,

  10. [11]

    Gao, K., Huang, S., Xie, J., Xiong, N.N., Du, R.,

    1016/j.ecotra.2019.100120. Gao, K., Huang, S., Xie, J., Xiong, N.N., Du, R.,

  11. [12]

    Garrow, M., Machemehl, R.,

    doi: 10.3390/electronics9060885. Garrow, M., Machemehl, R.,

  12. [13]

    Journal of Public Transportation 2, 65–90

    Development and evaluation of transit signal priority strategies. Journal of Public Transportation 2, 65–90. doi: 10.5038/2375-0901.2. 2.4. Goodwin, P.B.,

  13. [14]

    Hurdle, V .,

    1155/2019/7481489. Hurdle, V .,

  14. [15]

    Trans- portation Research Record 971, 96–105

    Signalized intersection delay models–a primer for the uninitiated. Trans- portation Research Record 971, 96–105. doi: 10.1061/(ASCE)0733-947X(1993) 119:6(835). Iio, K., Zhang, Y ., Quadrifoglio, L.,

  15. [16]

    Transportation Research Record 2673, 737–747

    Bid-based priority signal control in a connected environment: Concept. Transportation Research Record 2673, 737–747. doi:10.1177/0361198119855981. Iliopoulou, C., Kepaptsoglou, K., Vlahogianni, E.I.,

  16. [17]

    IEEE Intelligent Transportation Systems Magazine 15, 162–176

    A survey on market-inspired intersection control methods for connected vehicles. IEEE Intelligent Transportation Systems Magazine 15, 162–176. doi: 10.1109/MITS.2022.3203573. Isukapati, I.K., Smith, S.F.,

  17. [18]

    Accommodating high value-of-time drivers in market- driven traffic signal control, in: 2017 IEEE Intelligent Vehicles Symposium (IV), IEEE. pp. 1280–1286. doi: 10.1109/IVS.2017.7995888. Jacquillat, A.,

  18. [19]

    Transportation Science 56, 265–298

    Predictive and prescriptive analytics toward passenger-centric ground delay programs. Transportation Science 56, 265–298. doi: 10.1287/trsc.2021

  19. [20]

    Human Systems Management 2, 101–111

    The economics of the satisfaction of needs. Human Systems Management 2, 101–111. doi: 10.3233/HSM-1981-2206 . Karner, A., London, J., Rowangould, D., Manaugh, K.,

  20. [21]

    journal of planning literature 35, 440–459

    From transportation equity to transportation justice: within, through, and beyond the state. journal of planning literature 35, 440–459. doi: 10.1177/0885412220927691. Kouvelas, A., Lioris, J., Fayazi, S.A., Varaiya, P.,

  21. [22]

    Transportation Research Record 2421, 133–141

    Maximum pressure controller for stabilizing queues in signalized arterial networks. Transportation Research Record 2421, 133–141. doi: 10.3141/2421-15. Krishna, V .,

  22. [23]

    Trans- portation Research Record 1659, 68–75

    Induced tra ffic and induced demand. Trans- portation Research Record 1659, 68–75. doi: 10.3141/1659-09. Levinson, H.S., Zimmerman, S., Clinger, J., Rutherford, H.C.S.,

  23. [24]

    Journal of Public Transportation 5, 1–30

    Bus rapid transit: An overview. Journal of Public Transportation 5, 1–30. doi:10.5038/2375-0901.5. 2.1. Lin, D., Jabari, S.E.,

  24. [25]

    Lin, Y ., Yang, X., Zou, N., Franz, M.,

    doi: 10.1109/TITS.2020.3048475. Lin, Y ., Yang, X., Zou, N., Franz, M.,

  25. [26]

    Transportation Research Part C: Emerg- ing Technologies 26, 184–202

    Design and evaluation of token-based reservation for a roadway system. Transportation Research Part C: Emerg- ing Technologies 26, 184–202. doi:10.1016/j.trc.2012.09.001. Liu, K., Son, S.H., Lee, V .C., Kapitanova, K.,

  26. [27]

    A token-based admission con- trol and request scheduling in lane reservation systems, in: 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC), IEEE. pp. 1489–1494. doi:10.1109/ITSC.2011.6082959. Livingston, C.,

  27. [28]

    doi:10.3929/ethz-b-000643198

    E-bike city: A vision of sustainable transport, in: GreenBuzz The- matic Event: Driving Towards Zero Emissions-The Future of Sustainable Mobility, IVT, ETH Zurich. doi:10.3929/ethz-b-000643198 . Lopez, P.A., Behrisch, M., Bieker-Walz, L., Erdmann, J., Fl ¨otter¨od, Y .P., Hilbrich, R., L¨ucken, L., Rummel, J., Wagner, P., Wießner, E.,

  28. [29]

    Makridis, C., Menelaou, C., Timotheou, S., Panayiotou, C.,

    1109/ITSC.2018.8569938. Makridis, C., Menelaou, C., Timotheou, S., Panayiotou, C.,

  29. [30]

    IFAC-PapersOnLine 54, 1–6

    An implementation of a route reservation architecture. IFAC-PapersOnLine 54, 1–6. doi:10.1016/j.ifacol. 2021.06.042. Martens, K.,

  30. [31]

    Psychological Review 50, 370–396

    A theory of human motivation. Psychological Review 50, 370–396. doi:10.1037/h0054346. Mitev, N.N.,

  31. [32]

    Exploiting tra ffic lights to man- age auction-based crossings, in: Proceedings of the 6th EAI International Conference on Smart Objects and Technologies for Social Good, pp. 199–204. doi: 10.1145/ 3411170.3411257. Muzzini, F., Capodieci, N., Montangero, M.,

  32. [33]

    Coordinated tra ffic lights and auction intersection management in a mixed scenario, in: Proceedings of the 2023 ACM Con- ference on Information Technology for Social Good, pp. 1–1. doi:10.1145/3582515. 3609534. Ni, Y .C., Makridis, M.A., Kouvelas, A.,

  33. [34]

    Journal of Cycling and Micromobility Research 2, 100022

    Bicycle as a traffic mode: From microscopic cycling behavior to macroscopic bicycle flow. Journal of Cycling and Micromobility Research 2, 100022. doi: 10.1016/j.jcmr.2024.100022. Nie, Y .,

  34. [35]

    doi:10.1080/23249935.2016.1202354

    Why is license plate rationing not a good transport policy? Transportmetrica A: Transport Science 13, 1–23. doi:10.1080/23249935.2016.1202354. Provoost, J., Cats, O., Hoogendoorn, S.,

  35. [36]

    Transport Policy 136, 59–69

    Design and classification of tradable mo- bility credit schemes. Transport Policy 136, 59–69. doi:10.1016/j.tranpol.2023. 03.010. Qadri, S.S.S.M., G¨okc ¸e, M.A.,¨Oner, E.,

  36. [37]

    European transport research review 12, 1–23

    State-of-art review of traffic signal control methods: challenges and opportunities. European transport research review 12, 1–23. doi:10.1186/s12544-020-00439-1 . Qin, X., Khan, A.M.,

  37. [38]

    Transportation research part C: emerging technologies 25, 1–17

    Control strategies of tra ffic signal timing transition for emer- gency vehicle preemption. Transportation research part C: emerging technologies 25, 1–17. doi: 10.1016/j.trc.2012.04.004. Randal, E., Shaw, C., Woodward, A., Howden-Chapman, P., Macmillan, A., Hosking, J., Chapman, R., Waa, A.M., Keall, M.,

  38. [39]

    From goods to tra ffic: first steps toward an auction-based tra ffic signal controller, in: Advances in Practical Applications of Agents, Multi-Agent Systems, and Sustainability: The PAAMS Collection: 13th In- ternational Conference, PAAMS 2015, Salamanca, Spain, June 3-4, 2015, Proceedings 13, Springer. pp. 187–198. doi:10.1007/978-3-319-18944-4\_16 . Ra...

  39. [40]

    Agent-Based Modeling of Sustainable Behaviors , 121– 142doi:10.1007/978-3-319-46331-5_6

    An intersection-centric auction-based tra ffic signal control framework. Agent-Based Modeling of Sustainable Behaviors , 121– 142doi:10.1007/978-3-319-46331-5_6 . Riehl, K., Kouvelas, A., Makridis, M., 2024a. Towards fair roads–why we should & how to improve the fairness in tra ffic engineering. arXiv preprint arXiv:2408.01309 doi:10.48550/arXiv.2408.0130...

  40. [41]

    Cities 120, 103467

    Revisiting car dependency: A worldwide analysis of car travel in global metropolitan areas. Cities 120, 103467. doi: 10.1016/ j.cities.2021.103467. Sierra Mu ˜noz, J., Duboz, L., Pucci, P., Ciu ffo, B.,

  41. [42]

    Su, P., Park, B., Lee, J., Sun, Y .,

    doi:10.1186/s12544-024-00639-z . Su, P., Park, B., Lee, J., Sun, Y .,

  42. [43]

    Transportation research record 2381, 1–8

    Proof-of-concept study for a roadway reservation system: integrated traffic management approach. Transportation research record 2381, 1–8. doi: 10.3141/2381-01. Turochy, R.E.,

  43. [44]

    Lozano, A

    Max pressure control of a network of signalized intersections. Trans- portation Research Part C: Emerging Technologies 36, 177–195. doi: 10.1016/j. trc.2013.08.014. Verhoef, E.,

  44. [45]

    Edward Elgar Publishing Limited

    The economics of traffic congestion. Edward Elgar Publishing Limited. doi:10.4337/9781784712785. ISBN: 9-781-84720-351-9. Vilarinho, C., Tavares, J.P., Rossetti, R.J.,

  45. [46]

    Transportation research procedia 22, 325–334

    Intelligent traffic lights: Green time period negotiaton. Transportation research procedia 22, 325–334. doi: 10.1016/j.trpro. 2017.03.039. Waller, S.T., Polydoropoulou, A., Tassiulas, L., Ziliaskopoulos, A., Jian, S., Wagenknecht, S., Hirte, G., Ukkusuri, S., Ramadurai, G., Bednarz, T.,

  46. [47]

    Data Science for Trans- portation 7, 1–11

    Mobility as a resource (maar) for resilient human-centric automation–a vision paper. Data Science for Trans- portation 7, 1–11. doi: 10.1007/s42421-024-00115-z . Wang, H., He, W.,

  47. [48]

    A reservation-based smart parking system, in: 2011 IEEE con- ference on computer communications workshops (INFOCOM WKSHPS), IEEE. pp. 690–695. doi: 10.1109/INFCOMW.2011.5928901. Wheeler, D.,

  48. [49]

    Journal of Development Economics 7, 435–451

    Basic needs fulfillment and economic growth: A simultaneous model. Journal of Development Economics 7, 435–451. doi: 10.1016/0304-3878(80) 90038-3. Wolshon, B., Taylor, W.C.,

  49. [50]

    Transportation Research Part C: Emerging Technologies 7, 53–72

    Analysis of intersection delay under real-time adap- tive signal control. Transportation Research Part C: Emerging Technologies 7, 53–72. doi:10.1016/S0968-090X(99)00011-X . Wu, J., Qu, X.,

  50. [51]

    Journal of intelligent and connected vehicles 5, 260–269

    Intersection control with connected and automated vehicles: a review. Journal of intelligent and connected vehicles 5, 260–269. doi: 10.1108/ JICV-06-2022-0023 . Younes, M.B., Boukerche, A.,

  51. [52]

    Wireless Networks 24, 2451–2463

    An e fficient dynamic tra ffic light scheduling algo- rithm considering emergency vehicles for intelligent transportation systems. Wireless Networks 24, 2451–2463. doi: 10.1007/s11276-017-1482-5 . 17