A Study on Trajectory
February 4th 2009
◦ Building a data warehouse for Rio de Janeiro Traffic Dpt
◦ Prototype a trajectory datawarehouse
◦ Explore DW potentialities
◦ How to integrate GPS data into a TrDW?
◦ Which kind of information could be extracted?
◦ Discover the issues
◦ How the results could be presented?
Rio The Janeiro: a Metropolis
HDI (2000) 0.842 – high
Number of cars is mostly doubled during
the last year!
Which problems will be considered?
Congestions: is a condition on any network as use
increases and is characterized by slower speeds,
longer trip times, and increased queuing
Emissions of CO2: How much CO2 is produced by
vehicles? Calculated on average production index
of 200 gr/Km
From Velocity to Traffic Density
How to use that information?
◦ We can extract the same information while
looking at vehicles’ average speed
-> ∞ 140
Why a TrDW for Rio?
We would like to run queries like
◦ How the traffic congestions are evolving during
the week? (Spatial)
◦ Q2: Which are the most polluted streets?
◦ Q3: Which streets are the most congested?
How could Trajectories be helpful?
Trajectory is the unit of work for our
traffic management application
we partially use the trajectory model
developed (i.e. Stops-Moves)
◦ Stops have been already calculated and are
represented by an attribute for each trajectory
◦ Trajectory segmentation is constrainted by
road network segmentation
◦ Street segmentation
◦ Street names
The Star Schema
Fact table entry:
A trajectory instance
Oracle OLAP SQL interface
How to access MOLAP using SQL?
First Query: Spatial
Which is the correlation between pollution
caused by high speed and congestions?
Second Query: Spatio-Temporal
How Congestions are evolving during week?
Third Query: Numeric
Which streets have globally the worst
Traffic Index Street
For the Overall Rio
AVN AMARO CAVALCANTE
27,886 ACESSO A PTE PRES COSTA E SILVA
ACESSO AVN GOVERN CARLOS LACERDA
ACESSO DO VTO DE MANGUINHOS
Remarks using Oracle OLAP
◦ Good Expressive Power for Aggregations
◦ Multi-dimensional representation
◦ SQL interface from MOLAP to Relational
◦ Too many Catalog tables!
◦ No robust bulk loading methods: Fatal Errors!
◦ Slow queries also with simple mapping to Relational
◦ To query a Cube with streets and Time dimension, it is
required 3-4 Mins.
◦ Limitations of supported types:
◦ Only TEXT, Number, Date
◦ No Complex Objects
The design process is dangerous!
◦ Lack of Error Handling
SQL interface leads to wider uses e.g. GIS
Future work: use OLAP DML to enhance