Scipediacontent: Scipediacontent moved page Draft Content 269746128 to AbdelAziz et al 2019a

2021-02-01T23:19:40Z

Scipediacontent moved page Draft Content 269746128 to AbdelAziz et al 2019a

Scipediacontent: Created page with " == Abstract == Developing countries suffer from traffic congestion, poorly planned road/rail networks, and lack of access to public transportation facilities. This context r..."

2021-02-01T23:19:35Z

Created page with " == Abstract == Developing countries suffer from traffic congestion, poorly planned road/rail networks, and lack of access to public transportation facilities. This context r..."

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== Abstract ==

Developing countries suffer from traffic congestion, poorly planned road/rail networks, and lack of access to public transportation facilities. This context results in an increase in fuel consumption, pollution level, monetary losses, massive delays, and less productivity. On the other hand, it has a negative impact on the commuters feelings and moods. Availability of real-time transit information - by providing public transportation vehicles locations using GPS devices - helps in estimating a passenger's waiting time and addressing the above issues. However, such solution is expensive for developing countries. This paper aims at designing and implementing a crowd-sourced mobile phones-based solution to estimate the expected waiting time of a passenger in public transit systems, the prediction of the remaining time to get on/off a vehicle, and to construct a real time public transit schedule. Trans-Sense has been evaluated using real data collected for over 800 hours, on a daily basis, by different Android phones, and using different light rail transit lines at different time spans. The results show that Trans-Sense can achieve an average recall and precision of 95.35% and 90.1%, respectively, in discriminating lightrail stations. Moreover, the empirical distributions governing the different time delays affecting a passenger's total trip time enable predicting the right time of arrival of a passenger to her destination with an accuracy of 91.81%.In addition, the system estimates the stations dimensions with an accuracy of 95.71%.

Comment: 8 pages, 11 figures,

== Original document ==

The different versions of the original document can be found in:

* [http://arxiv.org/abs/1906.07575 http://arxiv.org/abs/1906.07575]

* [http://arxiv.org/pdf/1906.07575 http://arxiv.org/pdf/1906.07575]

* [http://xplorestaging.ieee.org/ielx7/8822235/8824788/08824808.pdf?arnumber=8824808 http://xplorestaging.ieee.org/ielx7/8822235/8824788/08824808.pdf?arnumber=8824808],
: [http://dx.doi.org/10.1109/sahcn.2019.8824808 http://dx.doi.org/10.1109/sahcn.2019.8824808]

* [https://dblp.uni-trier.de/db/journals/corr/corr1906.html#abs-1906-07575 https://dblp.uni-trier.de/db/journals/corr/corr1906.html#abs-1906-07575],
: [https://academic.microsoft.com/#/detail/2971728825 https://academic.microsoft.com/#/detail/2971728825]

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AbdelAziz et al 2019a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 269746128 to AbdelAziz et al 2019a

Scipediacontent: Created page with " == Abstract == Developing countries suffer from traffic congestion, poorly planned road/rail networks, and lack of access to public transportation facilities. This context r..."