Spatio-temporal Networks: Modeling, Storing, and Querying Temporally-Detailed Roadmaps - Space-Time Integration in Geography and GIScience - page 75

6.2 Illustrative Application Domains

In the present discussion, modeling is not the same as predicting in this context.
Incidents that happen without any warning and against all forecasts are part of
the unpredictable future . Random road accidents and consequent changes in traffic
patterns fall under this category. In the absence of such events, changes in the
network largely follow known patterns. In such predictable future scenarios, we
assume that the changes in network parameters and topology are known in advance.
This allows for the development of clear and concise representations for modeling.

6.2.1 Transportation Network Routing

Transportation networks are the kernel framework of many advanced transportation
systems such as the Advanced Traveler Information System and Intelligent Trans-
portation Systems. These transportation networks are spatio-temporal in nature and
require significant database support to handle the storage of their large amounts
of multi-dimensional data. Many important applications based on transportation
networks, including travelers' trip planning, consumer business logistics, and
evacuation planning are built upon spatio-temporal networks. A transportation
network displays non-stationary characteristics when route preferences change with
time, possibly due to non-uniform congestion levels at different parts of the network
or a time-dependent availability of certain road segments or faster services in a
public transport system.
With the increasing use of sensor networks to monitor traffic data on spatial
networks and the subsequent availability of time-varying traffic data, it becomes
important to incorporate this data into the models and algorithms related to
transportation networks. As an example, Fig. 6.1 shows a layout of traffic sensors
in the Twin Cities of Minneapolis-St Paul and the congestion measurements at two
different times of a day.

6.2.2 Emergency Traffic Management

A key step in emergency management is the evacuation of a population from areas
affected by disasters to safe locations. One significant challenge in this step comes
from the time-dependence of the transportation network. Travel times on the road
segments and the available capacities of the roads are both time-dependent. The
dynamic nature of the networks raises some interesting questions (as given in
Tab le 6.1 ) and the model for the transportation networks should provide support
for such queries.