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    Tytuł:
    Quantitative safety analysis of train control system based on statistical model checking
    Autorzy:
    Lin, Junting
    Min, Xiaoqin
    Powiązania:
    https://bibliotekanauki.pl/articles/2124711.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    train control systems
    statistical model checking
    safety analysis
    hybrid automata
    UPPAAL-SMC
    system sterowania pociągiem
    analiza bezpieczeństwa
    automaty hybrydowe
    Opis:
    With the rapid development of communication technology, the Train-centric Communication-based Train Control (TcCBTC) system adopting the train-train communication mode to reduce the transmission link of control information, will become the direction of urban rail transit field development. At present, TcCBTC system is in the stage of key technology research and prototype development. Uncertain behavior in the process of system operation may lead to operation accidents. Therefore, before the system is put into use, it must undergo strict testing and security verification to ensure the safe and efficient operation of the system. In the paper, the formal modeling and quantitative analysis of train tracking operation under moving block are carried out. Firstly, the structure of TcCBTC system and the train tracking interval control strategy under moving block conditions are analyzed. The subsystem involved in train tracking and the uncertain factors in system operation are determined. Then, based on the Stochastic Hybrid Automata (SHA), a network of SHA model of train dynamics model, communication components and on-board controller in the process of train tracking is established, which can formally describe the uncertain environment in the process of system operation. UPPAAL-SMC is used to simulate the change curve of train position and speed during tracking, it is verified that the model meets the safety requirements in static environment. Finally, taking Statistical Model Checking (SMC) as the basis of safety analysis, the probability of train collision in uncertain environment is calculated. The results show that after accurately modeling the train tracking operation control mechanism through network of SHA, the SMC method can accurately calculate the probability of train rearend collision, which proves that the method has strong feasibility and effectiveness. Formal modeling and analysis of safety-critical system is very important, which enables designers to grasp the hidden dangers of the system in the design stage and safety evaluation stage of train control system, and further provides theoretical reference for the subsequent TcCBTC system design and development, practical application and related specification improvement.
    Źródło:
    Archives of Transport; 2022, 61, 1; 7--19
    0866-9546
    2300-8830
    Pojawia się w:
    Archives of Transport
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bicycle free-flow speed estimation based on GPS data – comparison of bike sharing system and Strava data
    Autorzy:
    Pazdan, Sylwia
    Kiec, Mariusz
    Powiązania:
    https://bibliotekanauki.pl/articles/27322534.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    bike sharing system
    bicycle traffic
    bicycle speed
    safety analysis
    Strava
    GPS data
    system rowerów publicznych
    ruch rowerowy
    natężenie ruchu rowerowego
    analiza bezpieczeństwa
    dane GPS
    Opis:
    The increasing number of cyclists in cities around the world results in a greater focus on bicycle traffic. Next to traffic volume, the main characteristic of traffic used in road safety analysis, infrastructure planning, design, etc. is its speed. Bicycle speed is strongly affected by the type of bicycle facility, motor vehicle traffic parameters (volume, speed, share of heavy vehicles), trip motivation, weather conditions, etc., and therefore it is difficult to estimate. Traditionally, bicycle speed is determined directly using speed radar or indirectly, as a quotient of measurement base length and travel time calculated using a stopwatch or video technique. There are also researches where bicycle speed was esti mated based on GPS sources, mainly mobile apps. However, depending on the GPS source and the group of cyclists, bicycle speed gained from GPS data can be different from the speed of regular cyclists (due to different levels of experience or types of bicycle). In the paper, the relationships between bicycle speed obtained from empirical measurements and two different GPS sources, which were bike sharing system (Wavelo) and Strava app, were analysed. In total 18 research sites were selected different in terms of bicycle facility (bicycle path, shared pedestrian/bicycle path, contra flow lane) and element of road network (road segment, bicycle crossing with or without traffic signals). Two tailed test for two means was conducted to analyses the statistical significance of differences in bicycle speed estimated based on GPS data and empirical measurements using video technique. It showed that Wavelo and Strava speeds are by 17.4% lower are by 23.1% higher than the speeds of regular cyclists respectively. Two linear regression models describing relationships between bicycle speeds from empirical measurements and GPS data were developed. The results show that the variance of bicycle speed is almost 80% described by the variance of Wavelo speed and 60% described by the variance of Strava speed, which suggests that bicycle free-flow speed can be estimated based on GPS data either from bike share system or dedicated app.
    Źródło:
    Archives of Transport; 2023, 68, 4; 77--90
    0866-9546
    2300-8830
    Pojawia się w:
    Archives of Transport
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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