DEVELOPMENT OF AN ADVANCED TRAVELER INFORMATION SYSTEM USING CROWDSOURCED DATA WITH APPLICATION ON SAMPLE CORRIDORS IN CAIRO

Abstract

Traffic demand is continuously growing resulting in the traffic congestions, delays, pollution etc. On the other hand, the capacity of the road network expansion does not match the traffic demand increasing due to lack or resources, space, etc.… Thus, the term managing the traffic is strongly emerging as the traffic demand could be managed in order to achieve the best use of the existing road network capacity. This process becomes vital for any community in order to reduce the bad effects resulting from the traffic congestion. Intelligent Transportation Systems (ITS) is the technology currently and foreseen to be used to managing the traffic. ITS depends on best use the available resources for managing traffic and decrease congestion. For instance, mobile GPS is one of the technologies that is embedded in mobiles and becomes popular and increasingly used as an element of ITS. This thesis provides a crowdsourced application that periodically provides road users with the time-dependent shortest path based on travel time prediction on network links. The application predict the travel time on the road network by combining the real-time data collected from road users with data stored in the database. In addition, the application continuously updates the database in a way to improve the travel-time prediction provided to road users. Noting that the travel time collected from road users via GPS. The travel time database considers different scenarios related to demand patterns variation through the year and the occurrence of incidents. The results shows decrease the travel time of the users that request shortest paths and as the number of users that request shortest path increase the overall travel time of the system decreases. Besides, that it sensible for the changes in the behavior of the network due to incident which lead to changing the users suggested paths in order to avoid incident or congestion locations.