Neon Snow in NYC
Ride-sharing services can provide not only a very personalized mobility experience but also ensure efficiency and sustainability via large-scale ride pooling. Large-scale ride-sharing requires mathematical models and algorithms that can match large groups of riders to a fleet of shared vehicles in real time, a task not fully addressed by current solutions. We present a highly scalable anytime optimal algorithm and experimentally validate its performance using New York City taxi data and a shared vehicle fleet with passenger capacities of up to ten. Our results show that 2,000 vehicles (15% of the taxi fleet) of capacity 10 or 3,000 of capacity 4 can serve 98% of the demand within a mean waiting time of 2.8 min and mean trip delay of 3.5 min.
good luck out there tonight chummers
apparently this was combat search and rescue training (one guess as to who this would be for given the location)Seeing multiple reports of a USAF C-130 and several Black Hawk helicopters circling low (3,000 feet) over Manhattan.
No, that is not normal pic.twitter.com/DaFByrAX3O— Jason Rabinowitz (@AirlineFlyer)December 13, 2016
when u miss ur train in queens but have a 9am meeting in midtown
kreuzaderny