The SCHEDULE feed is an extract of train schedules from Network Rail's ITPS (Integrated Train Planning System).Association records are contained within the SCHEDULE data feed, and provide information about the possible associations between train schedules. These can list the service that forms a given schedule and / or the service that a given schedule goes on to form.This table includes the associations between unique id pairs of trains, with attributes for start and end dates of the association, the type of association and the location of where the association applies through TIPLOC (Timing Point Location) id.

The SCHEDULE feed is an extract of train schedules from Network Rail's ITPS (Integrated Train Planning System).Tiploc records are contained within the SCHEDULE data feed, and provide information about the possible timing point locations in train schedules.This table includes location data with the attributes for the following associated codes and descriptions:TIPLOC - Timing Point LocationsNLC - National Location CodeSTANOX - Station NumberCRS - Computer Reservation System code. Now 3-Alpha Code.description - The short name of the location. Not populated for every location.tps_description - The name of the location

The Rolling O&D survey (RODS) is a rolling programme to capture information about journeys on the LUL network. Warning: It is important to note that these data are reconciled to November counts and represent the number of people travelling on a typical (or average) weekday. Therefore, year-on-year RODS fluctuations do not necessarily reflect whole-year annual demand changes. Furthermore, these data are adjusted to remove the effect of any abnormal circumstances that may effect demand such as industrial action or long-term closures.The RODS dataset comprises information about: -Boarders and alighters by station, line, and time of day -Line loading by section, line, and time of day -Station flows by station and time of day -Origin-destination matrix by station, zone, and time of day -Route choice by origin-destination pair -Journeys involving interchange by zone, and number of interchanges -National Rail and DLR journeys to and from each LU station by zone and time of day -Total entries and exits by borough and time of day -Access and egress mode by entry/exit station, zone, and time of day -Age, gender, and mobility category split by entry/exit station, zone, and time of day -Average journey time by entry/exit station, zone, and time of day -Distance travelled by entry/exit station by zone, line, journey purpose, time of day, and ticket type -Journey frequency by entry/exit station, zone, journey purpose, time of day, and ticket type -Journey purpose by entry/exit station by zone, time of day, and ticket type -Ticket type by entry/exit station, zone, and time of dayPlease note that you will need to register (for free) as a data feed user on the TfL website to be able to access this information.Find out more about the feeds available from Transport for London here

This is a GTFS feed with data for The Fort Bus, Manila Metro Rail Transit Corporation, Philippine National Railways and 3 additional operators with the Onestop ID of "f-wdw-manila". There are 3 versions of this feed.

Caltrain heavy rail network created from the Caltrain General Transit Feed Specification (GTFS) data

Drone Rail Inspection Market Outlook

According to our latest research, the global drone rail inspection market size reached USD 1.38 billion in 2024, driven by the increasing adoption of drone technology for railway infrastructure monitoring and maintenance. The market is exhibiting a robust growth trajectory, registering a CAGR of 16.2% from 2025 to 2033. Based on this growth rate, the market is projected to achieve a value of USD 4.09 billion by 2033. The expansion is primarily fueled by the growing demand for efficient, cost-effective, and safe rail inspection solutions, as well as advancements in drone hardware and software capabilities. The surge in railway network expansions and the need for predictive maintenance are further propelling market growth, as per our latest research findings.

One of the most significant growth factors for the drone rail inspection market is the increasing emphasis on safety and operational efficiency within the global railway sector. Traditional rail inspection methods are not only labor-intensive but also expose workers to hazardous conditions and often require partial or complete rail line closures, disrupting services. Drones, equipped with advanced imaging and sensor technologies, enable real-time, high-resolution monitoring of tracks, bridges, tunnels, and overhead lines without interrupting rail operations. This capability substantially reduces inspection time and costs, while simultaneously improving the accuracy of defect detection and reducing human error. As railway operators and infrastructure maintenance companies worldwide seek to minimize downtime and enhance safety standards, the adoption of drone-based inspection systems is expected to surge, further driving market growth.

The rapid technological advancements in drone hardware and software represent another key growth driver for the drone rail inspection market. Recent innovations have led to the development of drones with extended flight times, enhanced payload capacities, and sophisticated sensors such as LiDAR, thermal imaging, and AI-powered analytics. These advancements enable comprehensive data collection and analysis, allowing for early detection of structural anomalies and predictive maintenance. Moreover, the integration of cloud-based platforms and artificial intelligence facilitates efficient data processing and actionable insights, empowering railway operators to make informed decisions swiftly. The continuous evolution of drone technology is not only expanding the range of inspection applications but also making drone solutions more accessible and affordable for a broader range of end-users, including government agencies and smaller maintenance firms.

Regulatory support and increasing investments in railway modernization projects are also playing a crucial role in shaping the drone rail inspection market. Governments across major economies are prioritizing the upgrade and expansion of rail infrastructure to support economic growth and urbanization. In tandem, regulatory bodies are establishing clear guidelines for the commercial use of drones, streamlining approval processes and ensuring safety and privacy compliance. These favorable regulatory frameworks are encouraging both public and private stakeholders to invest in drone-based inspection technologies. Furthermore, the rising awareness of the environmental benefits of drone inspections—such as reduced carbon emissions compared to traditional inspection vehicles—aligns with global sustainability goals, adding another layer of momentum to market expansion.

The integration of Drone-Based Railway Security is becoming increasingly vital as railway operators seek to enhance the safety and security of their networks. By utilizing drones equipped with advanced surveillance capabilities, operators can monitor vast stretches of railway infrastructure for potential security threats, such as unauthorized access or vandalism. These drones can be deployed rapidly in response to security alerts, providing real-time video feeds and data to security personnel, thereby enhancing situational awareness and response times. The ability to conduct regular aerial patrols without disrupting rail operations adds a significant layer of security, complementing existing ground-based measures. As security concerns continue to grow, the adoption of drone-based solutions is expected to play a crucial role in safeguarding rai

This map communicates the upcoming disruptions that will impact the transport network in the West Midlands Combined Authority conurbation.This map identifies the planned road and rail closures during the works with predicted timescales and severity of disruption.Planned roadworks on the West Midlands Strategic Road Network collected through open data RSS feed from Highways England.Highways England Area9 Roadspace Bookings received from Highways England contractor updates daily and aggregated to a weekly update digitised to OpenStreetMap basemapPlanned railway closures received as spreadsheet via Network Rail.Birmingham highways works foreward programme digitised using FME to map to Ordnance Survey Highways with Unique Street Reference Numbers (USRN) as identifier.Birmingham highways forward programme clashes created by running intersect tool between promoters on Birmingham highways works dataset.West Midlands Events captured as part of the Events Management collaboration project. Event data collated from Police and local authorities and stored in smartsheets. Spatial data created manually from venue location.