Isikhathi sezimoto ezizimele siyeza, ekhoneni engingakusho. Asingabazi ukuthi ukufika kwesimo esizimele kuzosiza kakhulu ekusweleni kwezingozi, kanye nasekutholakaleni okulungile nokoketshezi emigwaqeni, kuzenze zisebenze kakhulu futhi zisebenze, futhi okubaluleke kakhulu, zisongela isikhathi ku indlela yokusebenza. Kepha ngenkathi konke lokho kuqhubeka, i-MIT ifinyelele esiphethweni esibalulekile mayelana nokugcwala kwezimoto nokuxinana kwezimoto emigwaqeni yethu. Ngakho-ke, ake sithole ukuthi i-MIT icabangani nge-carpooling nokuthi lokhu kuthinta kanjani impilo yethu yansuku zonke.
Izinsizakalo ezinjenge-Uber noma iLyft sezithandwa kakhulu, futhi zinenzuzo kuzo zonke izindawo, kokubili mayelana nokungcola kanye nasezigabeni ezibhekise esiminyaneni sezimoto emigwaqeni. Kungakho iMIT izinikele ekuhlaziyeni ukuthi ukuhlanganyela kwezimoto kuyithonya kanjani ithrafikhi emadolobheni amakhulu, futhi ngosizo lukaProfesa Daniela Rus bafinyelele eziphethweni ezithakazelisa kakhulu.
Kulokhu basebenzise iNew York City njengengulube yeginea. Leli dolobha linamatekisi angekho ngaphansi kuka-14.000, nawo afaka isandla ekungcoleni nasekuminyana. Ngokuya ngama-algorithms, Ama-95% wesidingo samatekisi angagculiseka ngezimoto ezingama-2.000 XNUMX ezinomthamo wabantu abayishumi. Kepha into ebaluleke kakhulu ukuthi u-98% walesi sidingo ungagculiseka futhi ngezimoto ezingama-3.000 zabagibeli ezine zohlobo lwe-Uber neLyft, okungukuthi, babelana ngemoto phakathi kwabantu ongabazi.
Lolu cwaningo aluhlosile ukonakalisa umsebenzi wabashayeli bamatekisi, kodwa ukuqonda kangcono isimilo sabantu nezimoto ukusetshenziselwa umuntu ngamunye. Ukufika esiphethweni sokugcina ukuthi uma bonke abasebenzisi babelana ngezimoto zabo, ithrafikhi eNew York ibizoncishiswa kuze kufike kuma-75%.