Artificial Intelligence Enabled Road Vehicle-Train Collision Risk Assessment Framework for Unmanned Railway Level Crossings

Singhal, Vivek; Jain, Shailendra Pratap; Anand, Divya; Singh, Aman; Verma, Sahil; Kavita, .; Rodrigues, Joel J. P. C.; Jhanjhi, N. Z.; Ghosh, Uttam; Jo, Ohyun; Iwendi, Celestine

doi:10.1109/access.2020.3002416

Cited by 75 publications

(21 citation statements)

References 23 publications

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“…A novel predictive control framework for realtime data is presented in Singhal et al (2020), however, the proposed model neglects forecasting errors. Extending the work in Singhal et al (2020), using a non-cooperative nash game, active players reduce electricity costs by reshaping the respective load profiles (Zhang et al, 2011). Non-active users are also benefited by the proposed scheme due to reduced peak load.…”

Section: Optimization Techniques For Future Networked Gridmentioning

confidence: 99%

Utilization of ICT and AI techniques in harnessing residential energy consumption for an energy-aware smart city: A review

al.¹

2021

Int. j. adv. appl. sci.

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Fusion of Information and Communication Technologies (ICT) in traditional grid infrastructure makes it possible to share certain messages and information within the system that leads to optimized use of energy. Furthermore, using Computational Intelligence (CI) in the said domain opens new horizons to preserve electricity as well as the price of consumed electricity effectively. Hence, Energy Management Systems (EMSs) play a vital role in energy economics, consumption efficiency, resourcefulness, grid stability, reliability, and scalability of power systems. The residential sector has its high impact on global energy consumption. Curtailing and shifting load of the residential sector can result in solving major global problems and challenges. Moreover, the residential sector is more flexible in reshaping power consumption patterns. Using Demand Side Management (DSM), end users can manipulate their power consumption patterns such that electricity bills, as well as Peak to Average Ratio (PAR), are reduced. Therefore, it can be stated that Home Energy Management Systems (HEMSs) is an important part of ground-breaking smart grid technology. This article gives an extensive review of DSM, HEMS methodologies, techniques, and formulation of optimization problems. Concluding the existing work in energy management solutions, challenges and issues, and future research directions are also presented.

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Section: Optimization Techniques For Future Networked Gridmentioning

confidence: 99%

Utilization of ICT and AI techniques in harnessing residential energy consumption for an energy-aware smart city: A review

al.¹

2021

Int. j. adv. appl. sci.

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“…Therefore, the automatic level crossing control scheme should provide optimal level crossing control from the point of view of the train location. Paper [26] presents a study of the vehicle-train collision risk assessment using artificial intelligence, which may lead to the development of a road vehicle-train collision avoidance system on unmanned railroad crossings. Article [18] analyzed the impact of aggressive driving behavior on driver-injury severity at US railroad crossings by considering an extensive set of variables.…”

Section: Literature Reviewmentioning

confidence: 99%

Relation between pre-warning time and actual train velocity in automatic level crossing signalling systems at level crossings

Łukasik¹

2021

Diagnostyka

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At level crossings equipped with automatic level crossing signalling devices (which are category B and C crossings in Poland), warning time depends on several factors including the length of what is referred to as the level crossing's danger zone for road vehicles, and the train velocity. These systems are designed by taking into consideration the maximum train velocity applicable to the given railway line, which is why a train running with a velocity that is lower than the maximum one, e.g. a freight train, produces pre-warning time excess. The pre-warning time excess affects the redundant prolongation of the time when the level crossing is closed for road vehicles. What has been proposed in the article is to reduce the pre-warning time excess by making the pre-warning time depended on the actual train velocity. It describes a structural concept of a solution which should first be implemented in automatic level crossing signalling systems. Owing to adequate assumptions, the concept of the pre-warning time excess reduction exerts no negative effect on safety at level crossings.

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“…An AI-based study was also conducted that focuses on risk assessment of road vehicle and train collisions. This may lead to the development of a system to avoid collisions between vehicles and fibers at railway crossings with no human control [20]. AI can help improve safety and efficiency in data-driven intelligent transport systems and new Internet of Vehicle (IoV) services.…”

Section: Artificial Intelligence In Digital Transport Systemmentioning

confidence: 99%

Artificial Intelligence Application in Different Scenarios of the Networked Society 5.0 Environment

Peraković¹,

Periša²,

Cvitić³

et al. 2021

Zbornik Radova Trideset Devetog Simpozijuma O Novim Tehnologijama U Poštanskom I Telekomunikacionom Saobraćaju – Postel 2021

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A technologically based society geared towards every human being represents a Society 5.0 environment whose goal is to upgrade society to improve daily human life. It can be achieved through the significant application of information and communication networks, technologies, services, and user equipment. Industry 4.0 is the basis for developing the Society 5.0 environment in which the harmonious coexistence of people and machines comes to the fore. Artificial intelligence is one of the critical technologies for the further growth and development of the Society 5.0 environment, whose ability is to convert collected networked stakeholder's data into values. The authors in this paper systematically review the literature to investigate the application of artificial intelligence technology within the Society 5.0 environment. This paper aims to present the possibilities and scenarios of using artificial intelligence in different areas of the Society 5.0 environment, such as the digital transport system, healthcare, and manufacturing.

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Artificial Intelligence Enabled Road Vehicle-Train Collision Risk Assessment Framework for Unmanned Railway Level Crossings

Cited by 75 publications

References 23 publications

Utilization of ICT and AI techniques in harnessing residential energy consumption for an energy-aware smart city: A review

Utilization of ICT and AI techniques in harnessing residential energy consumption for an energy-aware smart city: A review

Relation between pre-warning time and actual train velocity in automatic level crossing signalling systems at level crossings

Artificial Intelligence Application in Different Scenarios of the Networked Society 5.0 Environment

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