Applications of real-time speed control in rail-bound public transportation systems

2013 ◽  
Vol 7 (3) ◽  
pp. 305-314 ◽  
Author(s):  
Thomas Albrecht ◽  
Christian Gassel ◽  
Anne Binder
Keyword(s):  
Real Time ◽  
Public Transportation ◽  
Speed Control ◽  
Transportation Systems ◽  
Public Transportation Systems

scholarly journals A Comprehensive Comparative Analysis of the Basic Theory of the Short Term Bus Passenger Flow Prediction

Symmetry ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 369 ◽  
Author(s):  
Huawei Zhai ◽  
Licheng Cui ◽  
Yu Nie ◽  
Xiaowei Xu ◽  
Weishi Zhang
Keyword(s):  
Real Time ◽  
Public Transportation ◽  
Transportation Systems ◽  
Training Data ◽  
Time Data ◽  
Short Term ◽  
Passenger Flow ◽  
Modeling Process ◽  
Automatic Passenger Counters ◽  
Public Transportation Systems

In order to meet the real-time public travel demands, the bus operators need to adjust the timetables in time. Therefore, it is necessary to predict the variations of the short-term passenger flow. Under the help of the advanced public transportation systems, a large amount of real-time data about passenger flow is collected from the automatic passenger counters, automatic fare collection systems, etc. Using these data, different kinds of methods are proposed to predict future variations of the short-term bus passenger flow. Based on the properties and background knowledge, these methods are classified into three categories: linear, nonlinear and combined methods. Their performances are evaluated in detail in the major aspects of the prediction accuracy, the complexity of training data structure and modeling process. For comparison, some long-term prediction methods are also analyzed simply. At last, it points that, with the help of automatic technology, a large amount of data about passenger flow will be collected, and using the big data technology to speed up the data preprocessing and modeling process may be one of the directions worthy of study in the future.

scholarly journals The UbiBus Project: Using Context and Ubiquitous Computing to build Advanced Public Transportation Systems to Support Bus Passengers

2012 ◽  
Author(s):  
Vaninha Vieira ◽  
Ana Carolina Salgado ◽  
Patricia Tedesco ◽  
Valeria Times ◽  
Carlos Ferraz ◽  
...  
Keyword(s):  
Ubiquitous Computing ◽  
Real Time ◽  
Public Transportation ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Time Factors ◽  
Transportation Systems ◽  
Urban Mobility ◽  
Public Transportation Systems ◽  
Real Time Information

Urban mobility is a problem that affects all cities. Providing real time information that can assist citizens on planning their trips by choosing times and itineraries more appropriate to their needs are essential on smart cities. Our project, named UbiBus, investigates how Computational Context and Ubiquitous Computing can be applied to Intelligent Transportation Systems to aid bus passengers mobility on cities, since dynamic real-time factors can affect transportation means. This paper describes the overall ideas concerning the UbiBus Project and presents some of the applications under development with their preliminary results.

scholarly journals Virus Transmission Risk in Urban Rail Systems: Microscopic Simulation-Based Analysis of Spatio-Temporal Characteristics

2021 ◽  
pp. 036119812110101
Author(s):  
Jiali Zhou ◽  
Haris N. Koutsopoulos
Keyword(s):  
Public Transportation ◽  
Virus Transmission ◽  
Flow Characteristics ◽  
Transportation Systems ◽  
Transmission Risk ◽  
Microscopic Simulation ◽  
Spatial And Temporal Patterns ◽  
Subway System ◽  
Public Transportation Systems ◽  
The Impact

The transmission risk of airborne diseases in public transportation systems is a concern. This paper proposes a modified Wells-Riley model for risk analysis in public transportation systems to capture the passenger flow characteristics, including spatial and temporal patterns, in the number of boarding and alighting passengers, and in number of infectors. The model is used to assess overall risk as a function of origin–destination flows, actual operations, and factors such as mask-wearing and ventilation. The model is integrated with a microscopic simulation model of subway operations (SimMETRO). Using actual data from a subway system, a case study explores the impact of different factors on transmission risk, including mask-wearing, ventilation rates, infectiousness levels of disease, and carrier rates. In general, mask-wearing and ventilation are effective under various demand levels, infectiousness levels, and carrier rates. Mask-wearing is more effective in mitigating risks. Impacts from operations and service frequency are also evaluated, emphasizing the importance of maintaining reliable, frequent operations in lowering transmission risks. Risk spatial patterns are also explored, highlighting locations of higher risk.

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