Path prediction using the historic path taken by person
I think we've covered this question before but I can't find my response... A lot of work has been done in this area. I don't know of any packages, but the basic idea is to discretize the search space. One way is to just to use the cellular grid, which makes sense if you have that information. Another is to first extract the "locations" from the location trace; i.e., places the users revisits and spends significant time in. Then you can apply well-known techniques such as HMMs to estimate the next discrete location from the recent past. Most of the papers I read on this subject are about a decade old, so they came out before the deep learning flurry. If they were revisiting the subject I'm sure I'd see papers using recurrent neural networks.

Here are some papers for inspiration:


Learning and Inferring Transportation Routines
A personal route prediction system based on trajectory data mining
A Comparison of First- and Second-Order HMMs in the Task of Predicting the Next Locations of Mobile Individuals
Using GPS to Learn Significant Locations and Predict Movement Across Multiple Users