Search Results

Routing quality always dominates the top 20% of in vehicle- navigation customer complaints. In vehicle navigation routing engines do not customize results based on customer behavior. For example, some users prefer the quickest route while some prefer direct routes. This is because in vehicle navigation systems are traditionally embedded systems. Toyota announced that new model vehicles in JP, CN, US will be connected with routing function switching from the embedded device to the cloud in which there are plenty of probe data uploaded from the vehicles. Probe data makes it possible to analyze user preferences and customize routing profile for users. This paper describes a method to analyze the user preferences from the probe data uploaded to the cloud. The method includes data collection, the analysis model of route scoring and user profiling. Furthermore, the evaluation of the model will be introduced at the end of the paper.

A hybrid navigation system [1] that performs route calculations and highly flexible natural speech location searches in the cloud using dynamic databases that combine probe data collected from the vehicle and external data, and transmits to on-board devices has been developed. The system automatically switches to the on-board device when the vehicle is out of mobile network communication range or when faster processing is required for tasks such as re-routing. The transition between the on-board devices and the cloud provide a seamless user experience adapted to use conditions and other factors. In addition, representing the route downloaded from the cloud by the on-board device requires synchronizing the map with the cloud, and a map caching function has been used to reduce the volume of data that needs to be synchronized. The cloud-based route calculation is based not only on average travel time, but on dispersion as well.