This dataset provides an indicator of train occupancy for individual train services from November 2018 to February 2019. The occupancy status is provided at each train station per train service per day. Occupancy <65% train capacity : MANY_SEATS_AVAILABLE Occupancy >= 65% train capacity : FEW_SEATS_AVAILABLE Occupancy >= 105% train capacity : STANDING_ROOM_ONLY This dataset is used at Transport for NSW for planning purposes. To note: • Train services between Midnight and 1.30 am are not in the dataset • There are services with no occupancy status, as the train service type (train capacity) was not available

This dataset shows the customer occupancy as determined by loadweigh for each stop on each Long Island Rail Road revenue trip made by M7 and M9 trains.

이 데이터는 한국철도공사의 기관사용 내비게이션 시스템에서 수집된 일별 열차 운행 통계 정보를 제공하는 운행 이력 데이터입니다. 데이터는 2025년 8월 12일부터 8월 27일까지 약 2주간의 일별 통계를 포함합니다. 이 데이터는 일별 열차 운행 편수 및 패턴 분석, 열차 등급별·노선별 운행 빈도 및 추이 파악, 기관사용 내비게이션 시스템 활용 현황 모니터링, 열차 운행 계획 대비 실제 운행 실적 검증, 철도 운영 효율성 및 서비스 수준 평가, 열차 다이어그램 최적화 및 배차 계획 개선 연구에 필수적인 운행 통계 데이터로 활용됩니다.

The dataset provides the number of patrons that boarded and alighted a particular train service per business date. Estimated passenger counts includes all persons aged 5 and over, excluding drivers and station staff. Data users should interpret the data cautiously, as the model provides estimates only, and its algorithms rely on a series of assumptions that are listed in the Data Quality section below. In particular, greatest caution is needed in relying on estimated train loadings at busier stations where there are greater transfers between train services, such as at the City Loop station and other transfer hubs. Methodologies for the estimation of patronage are subject to continuing improvements as new technology and techniques are available, and this data may be refined and updated over time. Data Quality 1) Passenger counts is derived from a model which includes source data of manual survey counts, myki ticketing data, myki barrier data and manual conductor counts. The purpose of the patronage survey is to determine the transaction rate, which is the percentage of passengers who ‘touch-on’ when they travel. Ticketing transactions are boosted according to the transaction rate to provide an estimate of total patronage. 2) As of January 2021, metropolitan train patronage uses barrier count data, where available, in place of survey observations to determine the transaction rate. 3) Metropolitan train patronage totals are derived from a count of station entries, plus a 5% ‘transfer uplift’ to account for trips following a transfer within a station. Those reported figures will not reconcile with the totals shown here due to the differing methods and application of rounding. 4) Patronage data for regional train is provided by V/Line and is based on conductor or driver counts for each regional train and coach service. 5) Business Date is used instead of the actual date for all fields. The Day of Week and Day Type will follow the Business Date and not the calendar day. 6) Due to the granular nature of the data, the fields of ‘Passenger Boardings’, ‘Passenger Alightings’, ‘Passenger Arrival Load’, and ‘Passenger Departure Load’ have been aggregated into Bin sizes to protect passenger privacy. 7) For Direction, ‘U’ (up) denotes services travelling towards Flinders Street Station and ‘D’ (Down) denotes services travelling away from Flinders Street Station. 8) Line and Group is not differentiated for V/Line services and will have identical cells for V/Line services. 9) For time intervals, 0 is defined as 00:00 (minutes:seconds) to 29:59 and 30 is defined as 30:00 to 59:59 10) Non-timetabled services that ran within the paper ticket section of the train system are not included. This affects passenger counts for V/Line services at non-Myki stations. 11) Services lacking a patronage data source are recorded as having zero counts. It should be noted that in actuality, the passenger counts are unknown and are unlikely to be zero. 12) It is difficult to infer and validate the correct service a patron transferred to in locations where there are multiple transfer options, so the data’s accuracy around these services is reduced. 13) The model is not capacity-constrained, leading to some few services with unrealistically high service load. Such services should be assumed to be very crowded, but these reported loads should not be treated as fact. 14) Where atypical events occurred (e.g. disruptions), the accuracy of the data is significantly reduced. 15) Some trips between Southern Cross and Flinders Street contain ‘dummy’ in their train number field. Due to model limitations, the exact service caught by these passengers is not known, although there is reasonable confidence that these passengers travelled between Southern Cross and Flinders Street at approximately the time shown.