The transportation sector represents a major part in the current and future US economy, with more than 10% of the United States’ GDP directly related to transportation activity. The significant congestion and projected demand increases with limited infrastructure investment make necessary the development of significant improvement on transportation systems. Transportation planners must therefore find ways to improve transportation conditions in a cost-efficient manner. Significant advances have been made in the procurement and provision of real-time information that would be required for the effective control of a transportation system. Yet, this information is mostly used in a centralized transit system design and operation. These efforts have had limited success to date addressing congestion in most American cities, which have a dispersed demand due to a lack of single high-density business and residential centers. Congestion in the US continues to rise, stressing vital infrastructure, causing delayed shipments, late employees, and countless other problems. Although these new mobility options such as ride-sharing are not the complete answer to congestion nationwide, their ability to augment existing public infrastructure, such as mass transit, could help to solve many congestion related problems in urban areas like Los Angeles.
However, one of the drawbacks of ridesharing is the extra inconvenience to the drivers and passengers of excessive detours to pick up new riders. This can be alleviated by having passengers walk to a common area from their origin for pick up or dropped off that is close to their origin/destination. This idea is already being adopted by e-hailing companies where for example it is a feature in UberPool. This research will adopt this feature to the ridesharing routing problem where the driver is not a professional driver but also has their own unique origin and destination. The research team refers to this problem as the “The Ridesharing Routing Problem with Flexible Pickup and Dropoff Points.” In this problem the pickup and drop-off points as well as the routes need to be determined. The research team will develop an optimization-based solution procedure to solve this problem based on iteratively solving the routing and pick up and drop off points.