## 3 Communication Technologies for Improved Energy Efficiency and Safety in Railways
### State of the Art in Communication Systems in Railways
The introduction of nonlinear train dynamics and motion resistances due to track gradient and curvature, as well as the locomotive power limitations and safety constraints at junctions into the rail traffic model based on high-bandwidth communication for the precise position and speed of the trains, may lead to significant reductions in headways, thus improving the railway system's capacity and throughput [123]. Most of the above efforts are either aimed at developing intra-vehicle communications over the limited-range wireless sensor networks of on-board trains [113; 114; 117] or massive V2V or V2I communication networks [115; 116; 118; 120], which utilise a substantial portion of the communication bandwidth to carry a wide range of both service-related and user data. However, from a practical standpoint, it is particularly worthwhile to investigate the possibility of narrow-band (NB) communications within the IoT paradigm for railways, wherein limited amounts of highly structured service data could be exchanged during low-volume V2I communications. These structured data could then be used to improve the transportation safety and energy efficiency while also preserving the communication system bandwidth for other tasks [34]. Since autonomous (or driverless) trains are driven remotely with the aid of a central computer control system augmented with advanced wireless communication technologies (such as 5G and IoT), advanced sensor suites (e.g., cameras, LIDAR), and artificial intelligence-based algorithms [124], the main goal is to obtain at least the same level of transportation safety as in the case when a human driver is present in the driver's cabin [125]. In that respect, human-machine cooperative action based on expert know-how and information sharing [126] has been identified as one of the key aspects of automated railway transportation safety and reliability [127], which are also necessary for the wider acceptance of autonomous trains [128]. Recent research in expert systems and artificial intelligence for railways, including applications for maintenance, traffic planning and management, safety, and security, and autonomous driving was extensively reviewed in reference [129]. In the above examples of the utilisations of Industry 4.0 technologies in automated traffic and autonomous transport, equally important operational aspects for safe operation are the reliability and cybersecurity of the wireless communication systems in railways [130] due to their inherent vulnerabilities compared to fixed lines (such as signal loss and interference) [131]. This applies both to V2X communications [30] and the utilisation of wireless sensor networks to enhance traffic safety and facilitate automated and autonomous transport [23]. Different solutions can be used to ensure secure data exchange, such as the implementation of secure data link architecture, and decentralised and pairwise secure key exchange between communication nodes [23]. Suitable metrics are developed to establish the maturity of different cybersecurity models [132] and gauge their resilience to cyber-attacks [133], wherein risk management techniques play important roles in cyber-attack mitigation and communication link recovery [131]. Naturally, these advanced transportation features are subject to strict regulatory oversight, wherein balance between traffic safety and the need for innovative solutions needs to be maintained [25].