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This paper advocates a new paradigm of transportation systems for future smart cities, namely, public vehicles (PVs), that provides dynamic ridesharing trips at requests. Passengers will enjoy more convenient and flexible transportation services with much less expense. In the PV system, both the number of vehicles and required parking spaces will be significantly reduced. There will be less traffic...
Public vehicle (PV) systems will be efficient traffic-management platforms in future smart cities, where PVs provide ridesharing trips with balanced QoS (quality of service). PV systems differ from traditional ridesharing due to that the paths and scheduling tasks are calculated by a server according to passengers' requests, and all PVs corporate with each other to achieve higher transportation efficiency...
In recent years, use of mobile robot acting as a data mule for collecting data in the wireless sensor network has become an important issue. This data collection problem of generating a path as short as possible for a data mule to gather all data from all of sensor nodes is known as a NP-hard problem named Traveling Salesman Problem with Neighborhoods (TSPN). We proposed a clustering-based genetic...
The problem of planning a path for minimizing the distance the mobile robot has to traverse to accomplish the task of gathering the data stored in a spatially distributed wireless sensor network is a kind of Traveling Salesman Problem with Neighborhoods (TSPN). We proposed a one-hop data-gathering scheme using clustering-based genetic algorithm (CBGA) that performs well: following the planned route,...
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