Decentralized Motion Coordination Method Design using CO-FIELD Approach of SWARM AI metaheuristics for Improving the Reliability of Bus Transit System
| dc.contributor.advisor | Alemu, Getachew(PhD) | |
| dc.contributor.author | Mitiku, Sisay | |
| dc.date.accessioned | 2018-06-29T06:27:04Z | |
| dc.date.accessioned | 2023-11-04T15:14:33Z | |
| dc.date.available | 2018-06-29T06:27:04Z | |
| dc.date.available | 2023-11-04T15:14:33Z | |
| dc.date.issued | 2014-11 | |
| dc.description.abstract | Bus transit system plays a major role in combating both air pollution and road congestion and is one of the most important modes of transportation. In spite all this however, it is not considered to be reliable mode of transportation by its customers. The complex nature of the transportation system in general and bus transit operation in particular makes it difficult for the application of traditional mathematical model. In this thesis, the problem of regulating and monitoring the reliability of a bus transit system using a SWARM artificial intelligence solution is addressed. The increasing availability of near-real time data from intelligent bus transit system makes the applicability of such solution more attractive. As the bus transit system is distributed and stochastically dynamic because of uncertain inter-stop trip time and uneven passenger distribution, the application of interaction based and emergent self-organized solution such as swarm ai solution is highly recommended. The problem is formulated as a distributed motion coordination problem. A gradient field (co-field) coordination model of swarm artificial intelligence which is inspired by the nature of naturally found fields such as electro statistic and electromagnetic fields is used to solve the proposed model. Multi-agent simulation model is used both to model the bus transit system and to iteratively design the SWARM artificial intelligence metaheuristics. The simulation is implemented with NetLogo integrated development environment so that the desired emergent phenomena is designed and evaluated. Line 31 of Ambessa Awtobis organization, Addis Ababa, Ethiopia, is taken as a case study to improve the reliability of the developed multi-agent simulation. Different simulation experiment is carried out and different measure of effectiveness of the system is collected. The result from the multi-agent simulation experiment shows that the proposed method is adaptive to wider passenger density scenarios. From the result, we can conclude that decentralized metaheuristics of control methods without any sort of formal mathematical model can be a viable solution for improving the bus transit system reliability problem. More over this method also helps to solve the problem of how effectively to utilize the increasingly available huge near-time data from intelligent transit system. Our recommendation is that a research on design support system of swarm Artificial intelligence solution, such as reducing a programming overhead for rapid prototyping of emergent phenomena is worth doing in the future. Key words: Bus transit reliability problem, Bus holding, Computational field, Multi-agent simulation, Case study | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/123456789/4810 | |
| dc.language.iso | en | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Bus Transit Reliability Problem | en_US |
| dc.subject | Bus Holding | en_US |
| dc.subject | Computational Field | en_US |
| dc.subject | Multi-Agent Simulation | en_US |
| dc.subject | Case Study | en_US |
| dc.title | Decentralized Motion Coordination Method Design using CO-FIELD Approach of SWARM AI metaheuristics for Improving the Reliability of Bus Transit System | en_US |
| dc.type | Thesis | en_US |