Smartphone technology enables dynamic ride-sharing systems that bring together people with similar itineraries and time schedules to share rides on short-notice. This paper considers the problem of matching drivers and riders in this dynamic setting. We develop optimization-based approaches that aim at minimizing the total system-wide vehicle miles and individual travel costs. To assess the merits of our methods we present a simulation study based on 2008 travel demand data from metropolitan Atlanta. The simulation results indicate that the use of sophisticated optimization methods instead of simple greedy matching rules may substantially improve the performance of ride-sharing systems. Furthermore, even with relatively low participation rates, it appears that sustainable populations of dynamic ride-sharing participants may be possible even in relatively sprawling urban areas with many employment centers.

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Erasmus Research Institute of Management
hdl.handle.net/1765/20456
ERIM Report Series Research in Management
ERIM report series research in management Erasmus Research Institute of Management
Erasmus Research Institute of Management

Agatz, N., Erera, A., Savelsbergh, M., & Wang, X. (2010). The Value of Optimization in Dynamic Ride-Sharing: a Simulation Study in Metro Atlanta (No. ERS-2010-034-LIS). ERIM report series research in management Erasmus Research Institute of Management. Retrieved from http://hdl.handle.net/1765/20456