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The autonomous vehicles emergence is a significant step forward in the development of safe and dependable intelligent transportation systems. In vehicular automation, digital connectivity has been one of the most critical specifications. In this paper, we focus on the autonomous train, which is one of the most rapidly growing applications of autono...
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Driven by the ever-increasing requirements of autonomous vehicles, such as traffic monitoring and driving assistant, deep learning-based object detection (DL-OD) has been increasingly attractive in intelligent transportation systems. However, it is difficult for the existing DL-OD schemes to realize the responsible, cost-saving, and energy-efficien...
Citations
... The architecture of the CBTC system is primarily comprised of three primary components and two secondary components. These include the VOBC, the ATS system, and the Zone Controller, as well as balises and Global Positioning System (GPS) [25]. Balises are positioned along the track to provide location information, while GPS provides additional location data that can be used to supplement the balise information to estimate with more precision the train's position. ...
... Adopting this advanced detection method in ADAS systems can enhance the safety of new types of automated trams and automated rapid trams (ART). Zamouche et al. [17] focused on autonomous train-related technologies and addressed safety issues through Enhanced Train Centered Communication-Based Train Control (ETc-CBTC). A novel safety checking method based on process algebra was employed to track and correct train behaviors in real time, ensuring operational safety. ...
As an important part of modern transportation, smart rail system need to handle a large number of delay-sensitive and task-intensive tasks in a high-speed mobile state. However, high-speed mobility challenges the traditional information processing modes a lot, such as service interruptions and information congestion. In order to solve these problems, we proposed a service migration strategy based on intelligent agent group cooperative prediction combined with edge computing service migration technology. The aim is to reduce system latency and overhead and ensure service continuity. Firstly, we constructed a cloud-edge-end collaborative scheduling network architecture model for distributed smart rail system is constructed, integrating mobility management and business orchestration to provide effective support for intelligent decision-making. Then we proposed an intelligent grouping collaborative migration strategy by consolidating resources for similar or identical tasks and employing a group negotiation mechanism, where the migration process is divided into four steps: detection, interaction, coordination and execution. Finally, a deep reinforcement learning algorithm is utilized to train multi-agent models for group collaborative prediction in edge migration strategies. The strategy dynamically adjusts task migration between edge nodes and the cloud based on real-time system status and task requirements to optimize its performance. Experimental results show that the proposed architecture and algorithm can effectively reduce total task delay and system overhead. Instead it can guarantee migration rate for task-intensive requirements, and effectively improve the reliability, effectiveness, and safety of smart rail system services. The present study lays a foundation for the future researches on applications of smart rail system.
... Railway control systems in operation were addressed in [30,31]. The dependencies of railway infrastructure capacity were described in [17], with testing being conducted via a computer-based simulation model, which provided results for further research on the issue. ...
The issues that determine the capacity of railway infrastructure are topical in situations that are reaching operating limits. According to the objectives of the European transport policy, it is assumed that up to 30% of road freight over 300 km should shift to other modes such as rail or waterborne transport by 2030. The transport system should become more competitive and efficient in the use of resources. This places high demands on the railway infrastructure, which is mainly operated in a mixed transport mode, with both passengers and freight. It is necessary to increase the capacity of these lines as a priority. The intent of this paper is to propose procedures that will simply and accurately determine the quantification of benefits for increasing the throughput performance of the line. For the initial estimates and assessments of investment measures, it is advantageous to use analytical methods to determine the throughput performance. The methodological approach for determining the throughput performance in the anticipated timetable and case study were approximated on the example of the rail freight corridor marked “Amber” that passes through Slovakia. Analytical procedures have been proposed according to the methodology used on the railways of Slovakia, and the quality issues were assessed using a new approach for determining the optimal and critical throughput performance. The mentioned procedures are advantageous for assessing infrastructural measures from the point of view of a railway infrastructure manager.
... At each speed change, we also assume that we record the instantaneous speed of the vehicle. In this paper, we use the Conditional Basic Process Algebra (CBP A * 0,1 ) [17] [18]. Process algebras are a mathematical formalism for the description and study of complex systems by algebraic means. ...
... We evaluate how well the proposed approach satisfies the most stringent requirement of the safety-related applications in terms of delays through the response time. We evaluate the bandwidth demanded by vehicular communication in the [48] is a framework that allows treating variables and conditions while specifying systems. Supposing that a is an action that belongs to a finite set of actions and P 1 ; P 2 two processes belong to a set of processes. ...
Connected Vehicles (CVs) are the key enabling technology for Intelligent Transportation Systems (ITSs) that offer great opportunities for improving traffic safety and efficiency. They provide several innovative safety-related applications such as traffic management and monitoring, which involve the transmission of messages from all vehicles on the road. Basic Safety Messages (BSMs) constitute an essential type of control message. However, several critical issues affect the BSM messages’ reliability. In this paper, a model-based approach for detecting discordant BSMs is proposed, which allows to avoid the vehicle disturbance. This approach consists of detecting incoherence in communication metric values, where the detection is formulated as an anomaly detection problem that is solved using the Gaussian distribution. The detection process allows the vehicles to cross their prediction to achieve more precision in deciding whether to accept or reject a message from a vehicle. The efficiency of our model for detecting an anomaly has been evaluated through simulations using our generated dataset. The obtained results indicate that the proposed model provides high performance in terms of detection rate. Moreover, we evaluate and validate the proposed approach through formal evaluation, where it demonstrates promising performances, as compare it with a concurrent approach through simulations considering important metrics.
... Train to infrastructure communication unit in charge of requiring resource with Resources Management Unit; Train to train communication unit provides the function of proceeding trains' identification and data exchanging, and respond to its following train's request. More details about how the system structure and data acquisition of T2T and T2G communication is implemented can be found in our previous publication [15]; the hardware structure of train-centric communication unit and availability evaluation are introduced in [16], [17]; the availability and performance analysis of T2T data communication system is discussed in [18], [19]. Readers who have an interest in communication systems can give more information in our aforementioned previous publications. ...
... The control problem of trains can be described as (16)(17). ...
Driverless train control systems are becoming popular in the world. Notably, this technology has already been applied for several years. However, these kinds of Automatic Train Operation systems are still under the framework that network elements and movement authority are generated from the ground control center. Hence, the aforementioned rail systems are "automated" but not "autonomous", and the architecture utilization and train tracking interval are limited. With the development of advanced sensors and control algorithms, the train intends to be equipped with a decision-making capability. In order to further improve train movement coordination and efficiency, an Autonomous Train Control System (ATCS) is proposed. This paper provides three main contributions: Firstly, the system structure is described, and the information following in ATCS is discussed with general operation scenarios. Secondly, data isolation is broken under ATCS, and data prediction and edge-based information fusion are applied to process the real dynamic data and estimate the train's speed and position. Thirdly, with the assistant of data fusion, model predictive and data-based control methodologies are discussed.
