Redirigiendo al acceso original de articulo en 24 segundos...
ARTÍCULO
TITULO

Model of Passenger Counting System Data Treatment

Olga Lebedeva    
Alexander Mikhailov    

Resumen

In recent decades, the technologies for automated monitoring passenger throughput have been developing at a rapid pace. One of the most popular types of equipment is presented by various detectors counting incoming/outgoing passengers allowing for assessing a rolling stock fill in real time. The archive data can be used to determine the passenger throughput and scope of work made. Therewith the input/output data allows calculating inter-stopping O-D matrix which, in its turn, allows assessing such characteristics as the average trip distance, turnaround of one passenger seat, etc. The analysis of measurement accuracy to estimate the passenger throughput on bus routes as well the data given by domestic and foreign producing companies showed that the maximum error (i.e., the difference between the aggregate number of incoming and outgoing passengers) could reach ± 15%. Therefore, to assess the inter-stopping O-D matrix the procedure resistant to spikes should be used. The paper addresses the methods that can be used to assess inter-stopping O-D matrix allowing for the increase of quality of processing the data supplied by I/O detectors.

 Artículos similares

       
 
Ivan Catipovic, Marta Pedi?ic-Buca and Jo?ko Parunov    
An innovative tourist submarine was studied by scale-model tests in a towing tank to determine its steering capabilities and detect motion instabilities during usual manoeuvres and emergency rising. Motion instabilities are caused by the combination of t... ver más

 
Liang Wang, Yangli Li, Shudan Deng and Juan Zhao    
The research focuses on the air-conditioning system in a public area of a subway station. To address this, an optimization model based on the grid time segmentation method was constructed, specifically a GM (1,1) model. We explored the influence of the h... ver más
Revista: Buildings

 
Xianlei Fu, Maozhi Wu, Sasthikapreeya Ponnarasu and Limao Zhang    
This research introduces a hybrid deep learning approach to perform real-time forecasting of passenger traffic flow for the metro railway system (MRS). By integrating long short-term memory (LSTM) and the graph convolutional network (GCN), a hybrid deep ... ver más
Revista: Buildings

 
Min Yue and Shuhong Ma    
A crucial component of multimodal transportation networks and long-distance travel chains is the forecasting of transfer passenger flow between integrated hubs in urban agglomerations, particularly during periods of high passenger flow or unusual weather... ver más
Revista: Applied Sciences

 
Lingxiang Wei, Dongjun Guo, Zhilong Chen, Jincheng Yang and Tianliu Feng    
Rational use of urban underground space (UUS) and public transportation transfer underground can solve urban traffic problems. Accurate short-term prediction of passenger flow can ensure the efficient, safe, and comfortable operation of subway stations. ... ver más