Abstract / Description of output
Automatically generated routing instructions are provided by Satnav and Internet based mapping services in order to assist us in getting to unfamiliar places. Instructions from these devices are based around least cost algorithms, described on a street- by- street basis. Taking no account of what we might already know, the instructions are long, difficult to remember and require effort to interpret. If we could opportunistically route the person via known areas, the recognition process would be easier, the instructions could be fewer, and the users would find greater comfort in travelling through spaces familiar to them. In this paper we model a user’s heterogeneous familiarity of the city such that it modifies a cost surface, resulting in directions that route the user via familiar spaces. A familiarity index was created based on historical GPS based trajectories. Participant route choice was found to be closer to outputs from the model than simple shortest path.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of GISRUK Conference, Leeds |
| Publication status | Published - 2015 |
Keywords / Materials (for Non-textual outputs)
- smart cities
- trajectory analysis
- pedestrian modelling