Kevin Riehl


Last Name

Riehl

First Name

Kevin

ORCID

0000-0003-4620-8379

Organisational unit

08686 - Gruppe Strassenverkehrstechnik

Filters

2024 - 202627
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Publications 1 - 10 of 27
  • Priority pass
    Item type: Conference Paper
    Riehl, Kevin; Kouvelas, Anastasios; Makridis, Michail (2024)
    Signalized intersection management is typically designed with a focus on transportation efficiency metrics such as throughput, queue length and average delay time, to the neglect of vehicle-specific urgencies. This conceptual work proposes a Priority Pass for urban networks as a feasible, economic instrument to expedite entitled vehicles at auction-controlled signalized intersections using movement-phase bidders. The interplay of transportation and economic efficiency at intersections with varying saturation, symmetry, and entitlement is analyzed. The value of the concept is robustly demonstrated for a wide range of scenarios. The Priority Pass creates significant benefits for entitled vehicles without causing arbitrary delays for not-entitled vehicles or de trop worsening transportation efficiency. What’s more, no significant conflict between transportation and economic efficiency was found in the given setup.
  • Decentralized highway decongestion with variable speed limit control
    Item type: Conference Poster
    Riehl, Kevin; Pusino, Davide (2025)
  • Decentralized variable speed limit Bellman control
    Item type: Conference Paper
    Riehl, Kevin; Pusino, Davide; Kouvelas, Anastasios; et al. (2025)
    Variable Speed Limit control can help avoid traffic jams before congestion forms. Vehicles upstream are required to decelerate at times in order to stop emerging congestion from propagating. This work proposes a fully decentralized, model-free, and infrastructure-free approach to Variable Speed Limit control, that employs connected vehicles as communication infrastructure, and as moving sensors and actuators. Dedicated Short Range Communication, consensus, and gossip algorithms, and a Bellman controller are components of this approach. The proposed method achieves significant improvements in traffic states, with up to 15% higher speeds, 5% lower density, and 8% higher flows. Significant improvements can be achieved at a compliance rate of at least 25% of all vehicles. Moreover, the approach is robust to gaps between platoons and recovers from periods of disconnection. The proposed method achieves traffic improvements similar to previous, centralized approaches, without the necessity of any infrastructure or model knowledge.
  • Towards fair roads
    Item type: Working Paper
    Riehl, Kevin; Kouvelas, Anastasios; Makridis, Michail (2024)
    arXiv
    Traffic engineering aims to control infrastructure and population behavior to achieve optimal usage of road networks. Fairness is fundamental to stimulate cooperation in large populations, and plays an important role in traffic engineering, as it increases the well-being of users, improves driving safety by rule-adherence, and overcomes public resistance at legislative implementation. Despite the importance of fairness, only a few works have translated fairness into the transportation domain, with a focus on transportation planning rather than traffic engineering. This work highlights the importance of fairness when solving conflicts of large populations for scare, public good, road-network resources with traffic engineering, and establishes a connection to the modern fairness theories. Moreover, this work presents a fairness framework that serves when designing traffic engineering solutions, when convincing in public debates with a useful, argumentative tool-set to confront equity considerations, and enables systematic research and design of control systems.
  • Resource Allocation with Karma Mechanisms
    Item type: Journal Article
    Riehl, Kevin; Kouvelas, Anastasios; Makridis, Michail (2024)
    Economies
    Monetary markets serve as established resource allocation mechanisms, typically achieving efficient solutions with limited information. However, they are susceptible to market failures, particularly under the presence of public goods, externalities, or inequality of economic power. Moreover, in many resource allocating contexts, money faces social, ethical, and legal constraints. Consequently, research increasingly explores artificial currencies and non-monetary markets, with Karma emerging as a notable concept. Karma, a non-tradeable, resource-inherent currency for prosumer resources, operates on the principles of contribution and consumption of specific resources. It embodies fairness, near incentive compatibility, Pareto-efficiency, robustness to population heterogeneity, and can incentivize a reduction in resource scarcity. The literature on Karma is scattered across disciplines, varies in scope, and lacks of conceptual clarity and coherence. Thus, this study undertakes a comprehensive review of the Karma mechanism, systematically comparing its resource allocation applications and elucidating overlooked mechanism design elements. Through a systematic mapping study, this review situates Karma within its literature context, offers a structured design parameter framework, and develops a road-map for future research directions.
  • Fair money
    Item type: Working Paper
    Riehl, Kevin; Kouvelas, Anastasios; Makridis, Michail (2024)
    arXiv
    City road infrastructure is a public good, and over-consumption by self-interested, rational individuals leads to traffic jams. Congestion pricing is effective in reducing demand to sustainable levels, but also controversial, as it introduces equity issues and systematically discriminates lower-income groups. Karma is a non-monetary, fair, and efficient resource allocation mechanism, that employs an artificial currency different from money, that incentivizes cooperation amongst selfish individuals, and achieves a balance between giving and taking. Where money does not do its job, Karma achieves socially more desirable resource allocations by being aligned with consumers' needs rather than their financial power. This work highlights the value proposition of Karma, gives guidance on important Karma mechanism design elements, and equips the reader with a useful software framework to model Karma economies and predict consumers' behaviour. A case study demonstrates the potential of this feasible alternative to money, without the burden of additional fees.
  • Decentralized variable speed limit Bellman control
    Item type: Other Conference Item
    Riehl, Kevin; Pusino, Davide; Kouvelas, Anastasios; et al. (2025)
  • Fair road pricing with Karma economies
    Item type: Conference Poster
    Riehl, Kevin; Kouvelas, Anastasios; Makridis, Michail (2025)
  • Quantitative Fairness - A Framework For The Design Of Equitable Cybernetic Societies
    Item type: Working Paper
    Riehl, Kevin; Makridis, Michail; Kouvelas, Anastasios (2024)
    arXiv
    Advancements in computer science, artificial intelligence, and control systems of the recent have catalyzed the emergence of cybernetic societies, where algorithms play a significant role in decision-making processes affecting the daily life of humans in almost every aspect. Algorithmic decision-making expands into almost every industry, government processes critical infrastructure, and shapes the life-reality of people and the very fabric of social interactions and communication. Besides the great potentials to improve efficiency and reduce corruption, missspecified cybernetic systems harbor the threat to create societal inequities, systematic discrimination, and dystopic, totalitarian societies. Fairness is a crucial component in the design of cybernetic systems, to promote cooperation between selfish individuals, to achieve better outcomes at the system level, to confront public resistance, to gain trust and acceptance for rules and institutions, to perforate self-reinforcing cycles of poverty through social mobility, to incentivize motivation, contribution and satisfaction of people through inclusion, to increase social-cohesion in groups, and ultimately to improve life quality. Quantitative descriptions of fairness are crucial to reflect equity into algorithms, but only few works in the fairness literature offer such measures; the existing quantitative measures in the literature are either too application-specific, suffer from undesirable characteristics, or are not ideology-agnostic. Therefore, this work proposes a quantitative, transactional, distributive fairness framework, which enables systematic design of socially feasible decision-making systems. Moreover, it emphasizes the importance of fairness and transparency when designing algorithms for equitable, cybernetic societies.
  • Oriented object detection for aerial vehicle trajectory extraction
    Item type: Conference Paper
    Riehl, Kevin; El-Baklish, Shaimaa K.; Kouvelas, Anastasios; et al. (2025)
    Vehicle trajectories offer valuable insights for a wide range of road transportation applications and research fields. A growing branch of literature explores vehicle trajectory extraction from aerial videos, where object detection using neural networks is an important component. Horizontal bounding box object detection struggles to differentiate well between rotated vehicles, especially when dealing with complex backgrounds or densely packed vehicles. In this work, we demonstrate how oriented object detection and the use of angular, directional information can be used to significantly improve the quality of extracted trajectories. The benchmark of 18 object detection models on a real world video dataset shows, that oriented object detection achieves 0.20m (15%) better internal, and 0.75m (20%) better platoon consistency; REDET and S2A from the openmmlab family count amongst the best performing detection models. Additionally, the analysis of synthetic trajectories with different levels of noise and coverage highlights, that improvements with angular information can be achieved when positional noise is high, coverage is low. At the presence of very noisy angular information however, these improvements diminish.
Publications 1 - 10 of 27