The integration of Global Navigation Satellite System(GNSS)technology into railway train control systems is a crucial step toward achieving the vision of a digital railway.Traditional train control systems undergo ext...The integration of Global Navigation Satellite System(GNSS)technology into railway train control systems is a crucial step toward achieving the vision of a digital railway.Traditional train control systems undergo extensive in-house tests and prolonged field tests for certification and approval before operational deployment,leading to high costs,delays,and operational disruptions.This paper introduces a GNSS-based train control localization framework which eliminates the need for on-site testing by leveraging train movement dynamics and 3D environment modeling to create a zero on-site testing platform.The proposed framework simulates train movement and the surrounding 3D environment using collected railway line location data and environmental attributes to generate realistic multipath signals and obscuration effects.This approach enables comprehensive laboratory-based case studies for train localization,reducing the huge amount test of needed for physical field trials.The framework is established in house,using the data collected at the Test Base of China Academy of Railway Sciences(Circular Railway).Results from the open area and cutting environment tests demonstrate high localization accuracy repeatability within the simulated environment,validating the feasibility and effectiveness of zero on-site testing for GNSS-based train control systems.This research highlights the potential of GNSS simulation platforms in enhancing cost efficiency,operational safety,and accuracy for future digital railways.展开更多
In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the disco...In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the discontinuation of local railway lines and introduce replacement buses to secure the transportation methods of the local people especially in rural areas. Based on the above background, targeting local railway lines that may be discontinued in the near future, appropriate bus stops when provided with potential bus stops were selected, the present study proposed a method that introduces routes for railway replacement buses adopting ant colony optimization (ACO). The improved ACO was designed and developed based on the requirements set concerning the route length, number of turns, road width, accessibility of railway lines and zones without bus stops as well as the constraint conditions concerning the route length, number of turns and zones without bus stops. Original road network data were generated and processed adopting a geographic information systems (GIS), and these are used to search for the optimal route for railway replacement buses adopting the improved ACO concerning the 8 zones on the target railway line (JR Kakogawa line). By comparing the improved ACO with Dijkstra’s algorithm, its relevance was verified and areas needing further improvements were revealed.展开更多
基金supported by the National Natural Science Foundation of China(62027809,U2268206,T2222015,U2468202).
文摘The integration of Global Navigation Satellite System(GNSS)technology into railway train control systems is a crucial step toward achieving the vision of a digital railway.Traditional train control systems undergo extensive in-house tests and prolonged field tests for certification and approval before operational deployment,leading to high costs,delays,and operational disruptions.This paper introduces a GNSS-based train control localization framework which eliminates the need for on-site testing by leveraging train movement dynamics and 3D environment modeling to create a zero on-site testing platform.The proposed framework simulates train movement and the surrounding 3D environment using collected railway line location data and environmental attributes to generate realistic multipath signals and obscuration effects.This approach enables comprehensive laboratory-based case studies for train localization,reducing the huge amount test of needed for physical field trials.The framework is established in house,using the data collected at the Test Base of China Academy of Railway Sciences(Circular Railway).Results from the open area and cutting environment tests demonstrate high localization accuracy repeatability within the simulated environment,validating the feasibility and effectiveness of zero on-site testing for GNSS-based train control systems.This research highlights the potential of GNSS simulation platforms in enhancing cost efficiency,operational safety,and accuracy for future digital railways.
文摘In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the discontinuation of local railway lines and introduce replacement buses to secure the transportation methods of the local people especially in rural areas. Based on the above background, targeting local railway lines that may be discontinued in the near future, appropriate bus stops when provided with potential bus stops were selected, the present study proposed a method that introduces routes for railway replacement buses adopting ant colony optimization (ACO). The improved ACO was designed and developed based on the requirements set concerning the route length, number of turns, road width, accessibility of railway lines and zones without bus stops as well as the constraint conditions concerning the route length, number of turns and zones without bus stops. Original road network data were generated and processed adopting a geographic information systems (GIS), and these are used to search for the optimal route for railway replacement buses adopting the improved ACO concerning the 8 zones on the target railway line (JR Kakogawa line). By comparing the improved ACO with Dijkstra’s algorithm, its relevance was verified and areas needing further improvements were revealed.
