Predicting the probability of getting the seat in the bus
M. Suchithra
, Likhitha R , Nousheen Taj
Passenger count, Bus, boarding, alighting, deboarding, cognitive-agents, Behavior-Observation-Belief-model;
The most frequently available means of transportation in present day is Bus which is highly cost efficient and convenient means to travel nearby places. Moreover, by using the buses will help to control the traffic growth and increase in private vehicles which in turn helps to encourage common public mode of transportation and greatly reduces congestion by achieving a change of commute mode. During the peak hours buses gets overcrowded due to the less availability of the required number of buses. During any urgency, passengers do not prefer to wait for the bus and instead they choose the other private means of transportation which in turn leads to increased traffic and pollution. Instead, if the user gets to know the probability of getting seat at any station before the destination then this would help the passengers to take the better decision. Today with the development of smart phones and android made very easy to provide the all the features to the common man by application. In this case Cognitive Agents (CAs) can be found helpful as they can think and act accordingly as a human brain. In this paper using CAs with Behavior-Observation-Belief (BOB) model and android application the tracking of count and suggesting is done.
"Predicting the probability of getting the seat in the bus ", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.5, Issue 5, page no.372 - 375, May-2020, Available :https://ijsdr.org/papers/IJSDR2005058.pdf
Volume 5
Issue 5,
May-2020
Pages : 372 - 375
Paper Reg. ID: IJSDR_191794
Published Paper Id: IJSDR2005058
Downloads: 000347302
Research Area: Engineering
Country: Ananthapur, Andhra Pradesh, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
