dc.contributor.author | Ahmed, Zarraf | |
dc.contributor.author | Khan, Injamamul Moin | |
dc.contributor.author | Das, Shaibal | |
dc.contributor.author | Kamal, Sonia | |
dc.date.accessioned | 2018-08-10T17:50:43Z | |
dc.date.available | 2018-08-10T17:50:43Z | |
dc.date.issued | 2018-08-10 | |
dc.identifier.uri | http://dspace.uiu.ac.bd/handle/52243/384 | |
dc.description.abstract | Traffic jam is a common situation in the capital cities and big towns especially in rising
countries such as Bangladesh. In this condition, people are missing their valuable time of
their busy platform by getting stacked in weighty traffic. Moreover, any faithful traffic
blocking avoidance or prediction tool for providing real time traffic jam data and path
selection is not available in Bangladesh. Shortest path traffic data is a challenging
assignment that can be used for traffic predicting and improving traffic flow. In this paper,
we offered an intelligent system using special types of cost function, which will fix optimal
paths of lowest travel budget with duration and distance considering both shortest path and
historical traffic data which was offer different time of structures in 24 hours. We have
compared all possible paths along with the shortest path to fix the optimal path. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | United International University | en_US |
dc.subject | Traffic jam | en_US |
dc.subject | Shortest path | en_US |
dc.subject | historical traffic data | en_US |
dc.subject | Prediction of Traffic Flow | en_US |
dc.title | Shortest Path Algorithm Based On Historical Traffic Data | en_US |
dc.type | Thesis | en_US |