Development of Virtual Automated Transit System (VATS) Software for Use in Simulation and Feasibility Analysis of BRT

2003 ◽  
Author(s):  
Joseph H. Solomon ◽  
Pedro Gonzalez-Mohino ◽  
Farid Amirouche
Keyword(s):  
Flow Simulation ◽  
Simulation Software ◽  
Bus Rapid Transit ◽  
Longitudinal Control ◽  
Transit System ◽  
Passenger Flow ◽  
Simulation Engine ◽  
Automation Systems ◽  
Efficient Route ◽  
Highway Automation

The steps involved in creating automated BRT (Bus Rapid Transit) simulation software with Matlab and Simulink are explained, incorporating CVHAS (Cooperative Vehicle-Highway) Automation systems) technologies. Methods of concise and efficient route definition, realistic passenger flow simulation, engine dynamics, lateral/longitudinal control and overall program structure are suggested.

scholarly journals Performance of the Priority Control Strategies for Bus Rapid Transit: Comparative Study from Scenario Microsimulation Using VISSIM

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Min Yang ◽  
Wei Wang ◽  
Bo Wang ◽  
Jing Han
Keyword(s):  
Control Strategies ◽  
Speed Control ◽  
Service Level ◽  
Simulation Software ◽  
Bus Rapid Transit ◽  
Base Case ◽  
Rapid Transit ◽  
Transit System ◽  
Flexible Control ◽  
Transit Speed

Bus rapid transit (BRT) has a great potential to improve the service level of transit system and has been implemented in many Chinese cities. However, the priority it can provide to buses has not been explored fully. Therefore, this study mainly investigated two advanced control strategies (signal priority using advanced detection and transit speed control). Signal priority using advanced detection is a strategy which detects one cycle ahead of buses’ arrival in order to adapt a more flexible control algorithm to provide signal priority for buses. Another is transit speed control, which provides priority at intersections for buses by controlling the speed of them and predicting their arrival at certain intersection. These two advanced strategies were modeled and evaluated using simulation software VISSIM and presented better performance than other three scenarios (base case, exclusive bus lane, and conventional transit signal priority). Only the eastbound direction would be researched as its traffic flow and bus volume are much larger than those of the other direction. Data used in this model was collected in Yingtan City. It is also shown that both the operation of BRT and the efficiency of private traffic can be much improved by applying the two strategies proposed above.

Life cycle emissions from a Bus Rapid Transit system and comparison with other modes of passenger transportation

2016 ◽  
Vol 6 (3) ◽  
pp. 123-134 ◽  
Author(s):  
Yohen Cuéllar ◽  
Rodrigo Buitrago Tello ◽  
Luis Carlos Belalcazar Ceronn
Keyword(s):  
Life Cycle ◽  
Bus Rapid Transit ◽  
Rapid Transit ◽  
Transit System ◽  
Passenger Transportation

scholarly journals Bus Rapid Transit System Introduction in Johor Bahru: A Simulation-Based Assessment

2021 ◽  
Vol 13 (8) ◽  
pp. 4437
Author(s):  
Sitti Asmah Hassan ◽  
Intan Nurfauzirah Shafiqah Hamzani ◽  
Abd. Ramzi Sabli ◽  
Nur Sabahiah Abdul Sukor
Keyword(s):  
Public Transport ◽  
Traffic Congestion ◽  
Economic Benefits ◽  
Bus Rapid Transit ◽  
Urban Mobility ◽  
Rapid Transit ◽  
Bus Priority ◽  
Time Saving ◽  
Transit System ◽  
Mobility Solution

Bus rapid transit (BRT) is one of the strategies to promote improvements in urban mobility. In this study, BRT scenarios, which integrate exclusive bus lanes and bus priority signal control in mixed traffic scenarios, were modelled using a VISSIM microsimulation. Three scenarios of BRT were modelled to represent 16:84, 38:62 and 54:46 modal splits between public transport and private vehicles. It was found that Scenario 4 (the 54:46 scenario) offers better benefits in terms of delay time saving and economic benefits. In general, it was found that the BRT system enhances the functioning of the transport system and provides people with faster and better mobility facilities, resulting in attractive social and economic benefits, especially on a higher modal split of public transport. It is regarded as one strategy to alleviate traffic congestion and reduce dependency on private vehicles. The finding of this study provides an insight on the effective concept of the BRT system, which may promote the dissemination of an urban mobility solution in the city. The results can help policymakers and local authorities in the management of a transport network in order to ensure reliable and sustainable transport.

Computer Simulation of an Engine Environmental Control System

2013 ◽  
Vol 850-851 ◽  
pp. 355-358
Author(s):  
Dong Du
Keyword(s):  
Control System ◽  
Distribution System ◽  
Environmental Control ◽  
Cooling System ◽  
Flow Simulation ◽  
Aircraft Engine ◽  
Simulation Software ◽  
Temperature Decrease ◽  
Environmental System ◽  
Passenger Aircraft

This paper describes the use of Fluid Flow Simulation Software to model a passenger aircraft engine environmental control system. The analysis simulates the cooling pack and the engine distribution system in a single model.The engine environmental system is very important for engine working efficiently. Using AMEsim software to simulate the cooling system can make it easily and clearly. The influence of the heat component and the fan operating is studied also. Through the analysis of the cooling system, we know that with the help of fan, the system can get additional air in the radiator and make the temperature decrease consequently.

scholarly journals Three Revised Kalman Filtering Models for Short-Term Rail Transit Passenger Flow Prediction

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Pengpeng Jiao ◽  
Ruimin Li ◽  
Tuo Sun ◽  
Zenghao Hou ◽  
Amir Ibrahim
Keyword(s):  
Real Time ◽  
Nonparametric Regression ◽  
Kalman Filtering ◽  
Rail Transit ◽  
Correction Coefficient ◽  
Short Term ◽  
Transit System ◽  
Filtering Method ◽  
Passenger Flow ◽  
Model Based

Short-term prediction of passenger flow is very important for the operation and management of a rail transit system. Based on the traditional Kalman filtering method, this paper puts forward three revised models for real-time passenger flow forecasting. First, the paper introduces the historical prediction error into the measurement equation and formulates a revised Kalman filtering model based on error correction coefficient (KF-ECC). Second, this paper employs the deviation between real-time passenger flow and corresponding historical data as state variable and presents a revised Kalman filtering model based on Historical Deviation (KF-HD). Third, the paper integrates nonparametric regression forecast into the traditional Kalman filtering method using a Bayesian combined technique and puts forward a revised Kalman filtering model based on Bayesian combination and nonparametric regression (KF-BCNR). A case study is implemented using statistical passenger flow data of rail transit line 13 in Beijing during a one-month period. The reported prediction results show that KF-ECC improves the applicability to historical trend, KF-HD achieves excellent accuracy and stability, and KF-BCNR yields the best performances. Comparisons among different periods further indicate that results during peak periods outperform those during nonpeak periods. All three revised models are accurate and stable enough for on-line predictions, especially during the peak periods.

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