A Smart Real-time Ride-share for Riyadh City

Abstract

Traffic jam is a growing problem especially in big cities like Riyadh. Wherever, streets are congested with cars and the need of cost-effective system is increasing in order to reduce the traffic jam impact. At the same time, each car's capacity can take up to four persons but this capacity is generally underexploited. If we can take advantage of the free space in each car, this will lead us to its best use with an optimal equation for achieving: fewer cars in the streets with more number of passengers. In this context, our mobile application "Where are you ?" is proposed as a solution that can help solving traffic jam problem. "Where are you ? " is a real-time application, which connects for free people living in the same city and having the same travel needs. Users rideshare their cars, based on the GPS position of the requester, the system searches the nearest and available car on the way of the requester. The system provides feedback and favorite driver's features, so that will help to recommend the best available driver. Our system is developed for android phones. It is considered as a social media since it provides communications between individuals or groups. Our application is based on trusted users. Users are authorized to register as part of a university or a company group or validated by their administrator. A "female only option" is also provided by the system. Our application is environmentally friendly because it provides carpooling service, which reduces carbon emissions, traffic jam, and the need for parking spaces.

Estimating the Potential of Ride Sharing in Urban Areas: the Milan Metropolitan Area Case Study

“…-Riyadh [14], where GPS data are used to match rides and drives through a free app, with the aim to reduce traffic jams; -Beijing [15], where the main focus is on environmental performances, and both a "state of the art" Ride Sharing and an evolution in terms of less vehicles and adoption of Electric vehicles is studied; -Paris region [16], where also long-term effects of RS (such as rebound effect due to relocation of part of the population in outer areas) are considered; -Dublin [17], where a model is built with the same software as used for this work (COPERT) and the impact is considered in terms of reductions in emissions and the vehicle kilometres travelled; -a comparison between Barcelona and Hanover ( [18]), where two pilot tests were held in order to evaluate mostly behavioural factors such as the intention of use RS for commuting and leisure trips and the most important design factors to attract users. For Italy, some studies show example of modelling algorithms applied to simulated realities and tested with focus groups [19] and of optimization of ride sharing services through the use of mobile-phone data [20].…”