This paper explores the potential environmental benefits of ride-sharing in New York City by finding a balance between supply and demand; for the supply side considering factors such as distance and emissions while taking into account demand-side factors like waiting time and deviation from ride time (DRT). A heuristic algorithm called ADARTW (Advanced Dial-A-Ride problems with Time Windows) is used for a time-constrained version of the Dial-A-Ride problem. The algorithm creates a "pick-up window" for each request and assigns customers to vehicles by finding feasible customer insertions into the work schedules of vehicles. Furthermore, a cost function is employed to optimize the insertion process to select the best customer insertion within the algorithm. This cost function takes into consideration several key factors. Then employs a nonlinear objective function to guide the insertion process and estimate the potential reduction in the number of vehicles required for transportation. The study reveals that ride-sharing could reduce the number of vehicles by 52% and greenhouse gas emissions by 35% in NYC.
Environmental benefits of taxi ride-sharing in New York City / Afsari, Marzieh; Ippolito, Nicola; BRESCIANI MIRISTICE, LORY MICHELLE; Gentile, Guido. - In: TRANSPORTATION RESEARCH PROCEDIA. - ISSN 2352-1465. - 78:(2024), pp. 345-352. [10.1016/j.trpro.2024.02.044]
Environmental benefits of taxi ride-sharing in New York City
Marzieh Afsari;Nicola Ippolito;Lory Michelle Bresciani Miristice;Guido Gentile
2024
Abstract
This paper explores the potential environmental benefits of ride-sharing in New York City by finding a balance between supply and demand; for the supply side considering factors such as distance and emissions while taking into account demand-side factors like waiting time and deviation from ride time (DRT). A heuristic algorithm called ADARTW (Advanced Dial-A-Ride problems with Time Windows) is used for a time-constrained version of the Dial-A-Ride problem. The algorithm creates a "pick-up window" for each request and assigns customers to vehicles by finding feasible customer insertions into the work schedules of vehicles. Furthermore, a cost function is employed to optimize the insertion process to select the best customer insertion within the algorithm. This cost function takes into consideration several key factors. Then employs a nonlinear objective function to guide the insertion process and estimate the potential reduction in the number of vehicles required for transportation. The study reveals that ride-sharing could reduce the number of vehicles by 52% and greenhouse gas emissions by 35% in NYC.File | Dimensione | Formato | |
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Afsari_Environmental-benefits-of-taxi_2024.pdf
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