News | PSR Researcher Maged Dessouky Examines Cost-Sharing Mechanisms to Encourage Ridesharing

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One phenomena of the modern era is the increasing connectivity of individuals to their surroundings—as well as to each other. Noteworthy leaps in navigation technology, such as a growing number of people with GPS in their pocket via their mobile phones, have allowed dynamic industries like ridesharing to emerge.


With increased connectivity, ridesharing has become more real-time, flexible, and user-based as individuals are increasingly able to adapt their routes and coordinate with each other instantaneously. This still emergent industry reduces unused vehicle space and could prove beneficial for the transportation sector, which seeks creative solutions to reduce congestion, vehicle delay, and vehicle miles traveled. The important part is making these developing technologies accessible and attractive to commuters in a way that is also beneficial in terms of social and environmental impact.


In a PSR-funded study, Maged Dessouky, the Dean’s Professor and Chair of the Daniel J. Epstein Department of Industrial and Systems Engineering at the University of Southern California, seeks to increase incentives toward ridesharing by determining a just cost and discovering a method of cost-allocation that benefits both drivers and passengers. The report, “Cost-Sharing Mechanisms for Ridesharing,” was co-authored by USC Assistant Professor Phebe Vayanos and USC Doctoral Research Assistant Shichun Hu. They stress the importance of a fair cost-sharing mechanism for all participants involved in order for constructive ride-share to endure. The creation of a sustainable ride-sharing population has promising implications for the environment and for regions that struggle with congestion and vehicle delay. 

The researchers are not interested in the model of ridesharing that for-profit companies such as Uber and Lyft offer. The well-known model of Uber and Lyft employs individuals who are driving specifically to earn money, which may generate more traffic congestion as drivers spend additional idling time on the streets seeking more trips. In their design, the researchers put forth a model where a driver adds passengers to their own pre-existing routine commutes. That way, drivers have their existing costs—such as fuel and vehicle depreciation—covered by passengers who are willing to pay a just fare for the service. Optimally, the driver does minimal extra driving, and the total cost of the trip is split fairly among all riders, who end up spending less than they would if they each drove individually.

Upon reviewing the literature, the researchers found extensive research on route optimization- origin and destination coupling, matching drivers and passengers heading in the same direction, and reducing total vehicle miles traveled. However, they saw a significant need for information on cost-allocation. Consequently, their study strives to determine what a reasonable cost would be for all participants involved and design a model that benefits drivers and passengers alike. The research factors in the value of time, added miles traveled, picking up passengers, and cost of fuel. Costs must then be allocated in a way that benefits the driver and all passengers in order to make ridesharing feasible for all. The researchers emphasize the importance of analyzing cost-allocation and determining a fair price because without each person benefiting from the system, there is no natural incentive towards this form of rideshare.

Their research demonstrates that with effective cost-sharing and successful matching of passengers, there is potential for a sustainable ride-share population to form over time. Widespread employment of ridesharing would mitigate congestion issues by employing unused vehicle space and optimizing routes. Although not a complete solution, this format of rideshare could certainly alleviate present and future congestion issues in urban areas by offering a decentralized, real-time, dynamic form of transportation. Once a reliable cost-allocation model is in place, the authors expect a gravitation towards this mutually beneficial style of ridesharing.