Traffic control process of expressway by fuzzy logic
Fuzzy Sets and Systems - Fuzzy Control
A PSO-aided neuro-fuzzy classifier employing linguistic hedge concepts
Expert Systems with Applications: An International Journal
Fuzzy risk analysis based on fuzzy numbers with different shapes and different deviations
Expert Systems with Applications: An International Journal
A neuro-fuzzy based forecasting approach for rush order control applications
Expert Systems with Applications: An International Journal
Design of a two-stage fuzzy classification model
Expert Systems with Applications: An International Journal
Generating fuzzy rules from training instances for fuzzy classification systems
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Fuzzy classification systems based on fuzzy information gain measures
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A fuzzy guided multi-objective evolutionary algorithm model for solving transportation problem
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Forecasting stock market short-term trends using a neuro-fuzzy based methodology
Expert Systems with Applications: An International Journal
Fuzzy Sets and Systems
The simulation of MRT transfer system based on bus holding strategies with platform constraints
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Distributed architecture for real-time coordination of bus holding in transit networks
IEEE Transactions on Intelligent Transportation Systems
Hi-index | 12.05 |
In this research, we aim to design real-time fuzzy bus holding system (FBHS) for the mass rapid transit (MRT) transfer system with real-time information for a terminal station with in a metropolitan area. We employ fuzzy logic to develop a model for the MRT-bus system to achieve the following goals pertaining to bus holding strategies used: to reduce the bus waiting time, to reduce the passenger waiting time, and to reduce passenger traveling time. In order to enhance the performance of the MRT-bus transfer system, we develop several fuzzy rules in the transfer models that are different functions of the travel time taken by buses during different time periods, such as rush hours and off-peak hours. Real-time traffic information acquired by the intelligent transportation systems through global positioning systems is used as input data for the FBHS. A performance index function is derived and served as the performance measure to compare our system with real data. The experimental results show that the FBHS significantly reduces the overall passenger waiting time and improves the performance of the MRT-bus transfer system.