Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Taxi waiting queues or passenger waiting queues usually reflect the imbalance beten taxi supply and demand, which consequently decrease a city’s trac system productivity and commuters’ satisfaction. ,  present a queue detection and analysis system to conduct analytics on both taxi and passenger queues. The system utilizes the event-driven taxi traces and the taxi state transition knowledge to detect queue locations at a coordinate level and subsequently identify 4 di↵erent types of queue context (e.g., only passengers queuing or only taxis queuing). More specifically, it adopts the novel and easy-to-implement algorithms to selectively extract taxi pickup events and their critical features. The extracted taxi pickup locations are then used to detect queue locations, and the extracted critical features are used to infer queue context. The extensive empirical evaluations, which run on daily 12.4 million taxi trace records from nearly 15000 taxis in Singapore, demonstrate the high accuracy and stability of the queue analytics results. Finally,  discuss the real world deployment issues and the gained insights from the queue analysis results.
['Yu Lu', 'Shili Xiang', 'Wei Wu']
I am writing a research paper on a idea Taxi Queue, Passenger Queue or No Queue? A Queue Detection and Analysis System using Taxi State Transition
[{"from": "human", "value": "I am writing a research paper on a idea Taxi Queue, Passenger Queue or No Queue? A Queue Detection and Analysis System using Taxi State Transition"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Taxi waiting queues or passenger waiting queues usually reflect the imbalance beten taxi supply and demand, which consequently decrease a city\u2019s trac system productivity and commuters\u2019 satisfaction. ,  present a queue detection and analysis system to conduct analytics on both taxi and passenger queues. The system utilizes the event-driven taxi traces and the taxi state transition knowledge to detect queue locations at a coordinate level and subsequently identify 4 di\u21b5erent types of queue context (e.g., only passengers queuing or only taxis queuing). More specifically, it adopts the novel and easy-to-implement algorithms to selectively extract taxi pickup events and their critical features. The extracted taxi pickup locations are then used to detect queue locations, and the extracted critical features are used to infer queue context. The extensive empirical evaluations, which run on daily 12.4 million taxi trace records from nearly 15000 taxis in Singapore, demonstrate the high accuracy and stability of the queue analytics results. Finally,  discuss the real world deployment issues and the gained insights from the queue analysis results."}]