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Ing. Martin Zajíček

2026, 2026 Smart City Symposium Prague (SCSP), IEEE eXplore), p. 1-7), ISBN 979-8-3315-8260-9, ISSN 2831-5618

Autonomous public transport is becoming an integral component of the Smart City paradigm and, concurrently, a key element of critical urban infrastructure. Besides operational benefits, increasing automation, connectivity, and digitalization introduce updated requirements for security, reliability, and resilience against cyberattacks and unintended system behaviors. This article presents a methodological and technological framework for deploying autonomous public transport management in urban environments, with a special emphasis on rail-based modes and their safe integration into a city’s critical infrastructure. The proposed approach combines dynamic HD maps, a digital twin of the urban environment, and cooperative intelligent transport systems (C-ITS) to achieve precise localization, enhanced situational awareness, and real-time data exchange among vehicles, infrastructure, and dispatch centers. Vehicle and infrastructure sensors feed a unified data platform that supports monitoring, diagnostics, and operational control. The architecture prioritizes secure data transmission, network segmentation, access control, and cyber-threat mitigation to ensure business continuity and high service availability.

Proceedings paper from a prestigious conference

2026, 2026 Smart City Symposium Prague (SCSP), IEEE eXplore), ISBN 979-8-3315-8260-9, ISSN 2831-5618

This paper reviews current approaches to cybersecurity risk analysis in critical transport infrastructure, with particular focus on their applicability to complex cyber-physical environments such as tunnel control systems. Modern transport infrastructures are characterised by strong interdependencies between digital control technologies and physical operational processes, which increase cybersecurity risks and the potential for cascading failures. The review shows that existing methodologies are based on standards-driven and governance-oriented frameworks. While these approaches provide structured procedures for risk identification and regulatory compliance, they remain largely qualitative, static, and limited in their ability to represent uncertainty, system interdependencies, and dynamic cyber-physical interactions. To address these limitations, the paper discusses the potential of probabilistic modelling approaches capable of supporting decision-making under uncertainty. Probabilistic graphical models offer mechanisms for modelling complex dependencies, integrating expert knowledge with available data, and improving analytical support for cybersecurity risk management. The findings highlight the need to complement compliance-oriented methodologies with probabilistic and decision-oriented approaches to enhance cybersecurity resilience in critical transport infrastructure.

Proceedings paper from a prestigious conference (Scopus)

2026, 2026 Smart City Symposium Prague (SCSP), IEEE eXplore), ISBN 979-8-3315-8260-9, ISSN 2831-5618

Urban traffic management increasingly relies on accurate, timely and robust traffic detection to support safe, efficient and sustainable mobility in complex urban environments. While a wide range of traffic detection technologies is currently available, many limitations persist due to fragmented data utilization, limited interoperability and sensor-centric system architectures. This paper provides a structured review of commonly used urban traffic detection technologies and analyses their technical and system-level limitations. Based on this analysis, a data-centric reference architecture is proposed, which decouples traffic detection capabilities from individual sensing technologies and enables the integration of heterogeneous infrastructure-based sensors, mobile data and C-ITS sources through harmonization and AI-based multi-source fusion. Rather than presenting a concrete system implementation, the proposed architecture serves as a conceptual framework supporting resilient, scalable and future-ready traffic detection. Its relevance is illustrated using representative use cases focusing on vulnerable road user detection, predictive traffic management and incident handling. The paper argues that use case-driven, data-centric architectural design represents a key enabler for next-generation urban traffic management in smart city environments.

Proceedings paper from a prestigious conference

2025

Lokalizace AV je založena na kombinaci absolutní lokalizace (satelitní navigace – není dostupná všude, rušení, odrazy, stromy atd.) a relativní lokalizace založené na určení vzdálenosti od objektů (přesná poloha je zaznamenána v HD mapách). Poloha objektů určená ze senzorů pomocí HD map je důležitým bezpečnostním požadavkem pro provoz AV. Bude zkoumána odolnost systému a budou zavedena možná opatření k jejímu zvýšení.

Research report in Czech

2025

Na základě identifikovaných rizik budou vyvinuty a popsány bezpečnostní modely, které budou následně otestovány ve formě funkčních vzorků a popsány ve výsledné studii jako vodítko pro implementaci bezpečnostních prvků pro sběr, zpracování a distribuci dat/informací pro potřeby autonomní mobility.

Research report in Czech

2024, Applied Sciences, 14 (20), ISSN 2076-3417

In the field of Cooperative Intelligent Transport Systems (C-ITSs), the traditional approach to testing often emphasizes technological parameters, leaving the validation of message content insufficiently addressed. Since the content of these messages is crucial for the correct functioning of C-ITS, this article demonstrates the potential for automated evaluation of C-ITS message content against relevant standards. It leverages our novel tools, Karlos and C-ITS SIM, to facilitate this process. Through detailed laboratory testing and data analysis, the study showcases the effectiveness of these automated solutions in enhancing the accuracy and reliability of message content validation.

Article in a journal indexed in SCI Expanded

2024, 2024 Smart City Symposium Prague - IEEE PROCEEDINGS, New York, IEEE Press), ISBN 979-8-3503-6096-7, ISSN 2831-5618

In the era of Industry 4.0 and the rise of smart cities, the integration of industrial and telematics systems has become increasingly prevalent, revolutionizing the way we manage and optimize processes. These systems, which encompass everything from manufacturing plants to transportation networks, rely heavily on interconnected devices and data exchange to enhance efficiency and functionality. However, this interconnectedness also brings about a heightened level of vulnerability to cyber threats, emphasizing the critical importance of robust cybersecurity measures. This article specifically delves into a case study of a selected Denial of Service (DoS) cyber attack on industrial networks, highlighting the critical need for such cybersecurity solutions. Current software was utilized to simulate an attack. The results are provided using the software that was created specifically for this type of task, demonstrating the practical application and effectiveness of these cybersecurity measures in real-world scenarios.

Proceedings paper from a prestigious conference

2024

Tato souhrnná zpráva analyzuje kybernetické hrozby a zranitelnosti tunelových systémů jako součásti kritické dopravní infrastruktury. Popisuje architekturu tunelových systémů, metodologii analýzy rizik a hodnotí klíčová aktiva z hlediska důvěrnosti, integrity a dostupnosti. Zaměřuje se na aktuální kybernetické hrozby, zranitelnosti a možnosti jejich zneužití, přičemž navrhuje mitigace a ochranná opatření. Dokument je určen pro odborníky na kybernetickou bezpečnost a správce tunelových systémů, aby zvýšil jejich odolnost vůči kybernetickým útokům.

Research report in Czech