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Pickup and drop-off (PUDO) facilities have long been important to support passenger transportation and goods delivery. Typical examples of passenger PUDO facilities are expected:
at inter-mobility stations or terminals where passengers switch between different transportation modes,
outside the stadiums where large-scale sports events or concerts are hosted, and
at schools where students are dropped off in the morning and picked up in the afternoon.
Meanwhile, the last mile of the freight delivery system has gauged unprecedented and continuing attention since the booming of e-commerce and time-sensitive delivery services, leading to frequent pickups and drop-offs of small shipments close to their end consumers. The pickup and drop-off of passengers, as well as the loading and unloading of goods, are frequently observed at the designated spaces on the curb or in the parking lots. The recent increase in the adoption of the above-mentioned transportation services and the anticipated continuation of this trend with the introduction of self-driving vehicles imply that PUDO facilities will become more widespread and substantial.
However, have you ever observed those processes of pickups and dropoffs closely? Take ride-hailing services for example. The transportation facility was not constructed to meet this increasing demand for pickup and dropoff services. In a busy urban context, congestion can be observed everywhere in conjunction with those services. From the perspective of road management, every single stopped vehicle can delay the entire lane. There is limited curb space or curb length, so is it capable of handling all pickup and drop services?
For example, Portland International Airport has launched a pilot project starting in May 2019, to test out a new process of late-binding. In this process, riders join a queue and receive a code from the ride-hailing apps instead of knowing their driver immediately. When a rider becomes the first in line, he or she rides a car and shows the driver the code for trip information. When high demand quickly accumulates within a compact area, road congestion is aggravated. The above late-binding process was proposed to resolve the excessive delay as riders and drivers struggle to identify each other in a highly congested area. However, as the following picture (click the dropdown button to see it) from Portland suggests, this process alone may not be sufficient to address the congestion.
Thus, my research aims at the design and throughput capacity evaluation of PUDO facilities. Efficient computational tools are developed to provide insights into the design of facility layouts and operational policies. Different methods are introduced for different types of PUDO facilities, namely,
(1) the passenger PUDO facilities with a uniform spot size,
(2) the passenger PUDO facilities with regular and handicapped parking spots (as an example for multiple spot sizes), and
(3) a delivery bay (with flexible spot sizes).
My doctoral dissertation presents mathematical and computational models that optimize the long-term performance metrics for various types of passenger and freight transportation facilities. In summary, my work:
(i) evaluates the throughput capacity of PUDO facility layouts and operational policies making provisions for long-term demand shifts and uncertainty,
(ii) formulates this design problem as Markov decision processes (MDPs), verifies any modeling assumptions, and characterizes the optimal design decisions,
(iii) conjectures practical, interpretable, and implementable approximate policies or near-optimal solutions, and
(iv) develops microscopic discrete-event simulation frameworks with realistic vehicle trajectories for validation.
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