Smart City-Wide Package Distribution Using Crowdsourced Public Transportation Systems

The demand for package delivery services is extremely huge every day, because of the rapid development on online retailers. This leads to huge traffic congestion, resource consumption, and environmental pollution (e.g., carbon emission). However, the urban public transport system offers a large amount of under-utilized capacity outside the peak hours. In this paper, we present the city-wide package distribution problem using crowdsourced public transportation systems (CPTSs). That is, packages are delivered by carefully utilizing the considerable amount of idle capacity of the CPTS. Specifically, given a number of packages and the timetable of available CPTS trips, we optimize the package delivering scheme by determining the four identified states of any package at any time slot (waiting, riding, rewaiting, and being unloaded). The delivering scheme can be modeled as an instance of the multicommodity flow problem, and formulated by the integer linear programming techniques. We then propose an efficient heuristic solution for this NP-hard problem. Finally, this paper is validated via comprehensive emulations with a real bus transportation network.