Passenger Flow Forecast Algorithm for Urban Rail Transit
نویسندگان
چکیده
To exactly forecast the urban rail transit passenger flow, a multi-level model combining neural network and Kalman filter was proposed. Firstly, ELAN neural network model was introduced to implement a preliminary forecast of the passenger flow. Then the Kalman filter was used to correct the preliminary forecast results, so as to further improve the accuracy. Finally, in order to validate the proposed model, the passenger flow in Shanghai subway transport hub was observed and simulated. Experimental results showed that the proposed multi-level model reduced error by about 0.8% and had better actual effect compared with any single algorithm.
منابع مشابه
Demand-oriented timetable design for urban rail transit under stochastic demand
In the context of public transportation system, improving the service quality and robustness through minimizing the average passengers waiting time is a real challenge. This study provides robust stochastic programming models for train timetabling problem in urban rail transit systems. The objective is minimization of the weighted summation of the expected cost of passenger waiting time, its va...
متن کاملDynamic Schedule-Based Assignment Model for Urban Rail Transit Network with Capacity Constraints
There is a great need for estimation of passenger flow temporal and spatial distribution in urban rail transit network. The literature review indicates that passenger flow assignment models considering capacity constraints with overload delay factor for in-vehicle crowding are limited in schedule-based network. This paper proposes a stochastic user equilibrium model for solving the assignment p...
متن کاملWavelet Neural Network-based Short-Term Passenger Flow Forecasting on Urban Rail Transit
Accurate forecasting of short-term passenger flow has been one of the most important issues in urban rail transit planning and operation. Considering the shortcomings of traditional forecasting methods, and in order to improve forecasting accuracy of passenger flow, this paper presents a wavelet neural network (WNN) for short-term passenger flow forecasting. One real urban rail transit station ...
متن کاملFundamental Diagram of Rail Transit and Its Application to Dynamic Assignment
Urban rail transit often operates with high service frequencies to serve heavy passenger demand during rush hours. Such operations can be delayed by train congestion, passenger congestion, and the interaction of the two. Delays are problematic for many transit systems, as they become amplified by this interactive feedback. However, there are no tractable models to describe transit systems with ...
متن کاملThe modeling of attraction characteristics regarding passenger flow in urban rail transit network based on field theory
Aimed at the complicated problems of attraction characteristics regarding passenger flow in urban rail transit network, the concept of the gravity field of passenger flow is proposed in this paper. We establish the computation methods of field strength and potential energy to reveal the potential attraction relationship among stations from the perspective of the collection and distribution of p...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013