Snapcab: Urban Scale Context-Aware Smart Transport Using Adaptive Context Tries

Traffic gridlock has become a very familiar scene in cities due to the inefficiencies of existing transport systems. Context-aware dispatch has the potential to solve such congestion problems. Thus, this paper addresses the problem of realising large scale real-time taxi dispatch with service guarantees on road networks. Such a system requires the dynamic matching of travel requests made by passengers with appropriate taxis. Crucially this must occur while also ensuring the satisfaction of all waiting or travel times constraints. Results gained from simulations show that a novel approach, based on Adaptive Context Tries (ACT), provides fast response times, bounded complexity and thus scalability.