Name
Abstract | ||
|---|---|---|
Large cities face growing mobility problems, due to the major traffic jams that result from high numbers of vehicles on the roads. In response, city and national governments have invested in alternative means of urban passenger transit, such as subways, trains, as well as Bus Rapid Transit (BRT). This article aims to analyze the BRT system, by attempting to calculate the probability of reaching a destination at a specific time, thereby providing a tool that can be employed to improve the system and increase passenger confidence in it. To this end, a Continuous Time Markov Chain (CTMC) model is proposed to represent the bus stations and compute the probability metric for arrival at the destination within the specified time frame. The model allows a mathematical function to calculate the probabilities for the corresponding architecture. Two case studies were conducted in order to verify the model and illustrate its potential value in the planning of BRT systems. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/SMC.2015.227 | 2015 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2015): BIG DATA ANALYTICS FOR HUMAN-CENTRIC SYSTEMS |
Keywords | Field | DocType |
Bus Rapid Transit (BRT), CTMC, Probability | Architecture,Markov process,Function (mathematics),Time frame,Continuous-time Markov chain,Computer science,Control theory,Simulation,Operations research,Bus rapid transit,Probabilistic logic,Train | Conference |
ISSN | Citations | PageRank |
1062-922X | 0 | 0.34 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Renata Dantas | 1 | 0 | 0.34 |
| Jamilson Dantas | 2 | 61 | 12.24 |
| Paulo Romero Martins Maciel | 3 | 363 | 59.24 |
| Renata Dantas | 4 | 0 | 0.34 |
| Gabriel Alves | 5 | 1 | 2.41 |