Using outdoor public WiFi and GPS integrated method for position updating of knowledge-based logistics system in dense high rise urban environments

Nowadays, logistics and supply chain industires are facing high competition on providing customers with efficient delivery service and quick response to customers' requests. With such demands, different Knowledge-based Logistics Systems (KLS) have been proposed and developed to assist decision making in real time. An important information in devising real-time decision making algorithms is the fleet's positional information, and Global Satellite Navigation Systems (GNSS), such as the U.S. Global Positioning System (GPS) has been widely used in KLS for this purpose. However, in dense high rise environments GPS may not be able to determine positions due to insufficient satellite measurement data. Moreover, poor receiver-satellite geometry and signal multipath effects would lead to large positional error, which in turn leads to incorrect interpretation of the fleet's position in the road network database, and incorrect determination of optimal solution for the KLS. In this paper, the use of integrated outdoor public WiFi and GPS positioning method is proposed to improve the availability and accuracy of positional information for KLS. Field test results show that vehicle positions along road sections surrounded by tall buildings can be correctly identified with outdoor public WiFi networks without additional set up and maintenance costs. This approach can also be used to calculate the real-time traffic flow in an area, to be incorporated in a KLS.