Constructing Route Choice Mobile Application Using the Real-Time Traffic Information | ||||
| Port-Said Engineering Research Journal | ||||
| Article 5, Volume 26, Issue 3, September 2022, Page 46-55 PDF (1.56 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/pserj.2022.141421.1187 | ||||
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| Authors | ||||
Ahmed Abd-elazeem1; mohamed Serag sadek2; marwa elsayed elbany   3
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| 1transportation planning and traffic engineering,civil engineering dep., faculty of engineering, Suez Canal university, Ismailia, Egypt | ||||
| 2Professor of Transportation and Traffic Eng.,Faculty of Engineering,Giza high institute of engineering,Cairo | ||||
| 3CIVIL ENGINEERING, FACULTY OF ENGINEERING, PORT SAID UNIVERSITY, EGYPT | ||||
| Abstract | ||||
| Traffic congestion is one of the most serious concerns in the transportation networks. It is a multidimensional problem with many challenges which makes it difficult to solve in the short term because it needs a predictable route choice behavior and decisions. Providing travelers with real-time traffic data during their trips is the most significant option for avoiding congestion and reducing their waste of time and the associated waste of money. Novel technologies such as mobile route choice applications are required to facilitate travelers’ route choice decisions and faceless traffic congestion. Port Said city has an important location on Suez Canal that makes the importance of its transit activities to/from Port Fouad city. This paper presents a route choice mobile application for people traveling from Port-Said to Port-Fouad. It depends on predicting the real travel time between the two cities with addition to queuing time. Intelligent traffic system techniques and the Google Application Programming Interface (API) maps have been used to collect travel data. The application travel time estimations have been corroborated using actual values. The results show that the model is performing well and give an acceptable prediction of the average percentage error around 7% which is lower than the average percentage error of Google Maps travel time estimates by about 23%. This indicates the recommended effective outcome of the introduced mobile application in addition to facilitate the provision of route data for the traveler at any time. | ||||
| Keywords | ||||
| real-time traffic data; assignment; API; route choice mobile application | ||||
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