Transition probability matrix generation:[[BR]]
1. convert timestamp to serial number and then sort[[BR]]
2. divide area into grids[[BR]]
3. loop: for each taxiid, find current grid & next grid, fill into grid matrix (row is current grid #, column is next grid #)[[BR]]
4. get probability matrix by normalizing grid matrix 

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Update generation:[[BR]]
1. divide updates into three different speed groups[[BR]]
2. in each speed group, set timestamp(poisson distribution) for each update[[BR]]
3. pick GUID (and its corresponding source AS) for each update randomly[[BR]]
4. compute destination AS[[BR]]

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table TAXIDATA has all data loaded, table TAXI1 loads only the first data file[[BR]]

table contents are below[[BR]]
CREATE TABLE TAXIDATA[[BR]]
([[BR]]   
ID NUMBER(10) CONSTRAINT TAXIDATA_ID NOT NULL, [[BR]]
TAXIID NUMBER(7), [[BR]]
LONGITUDE NUMBER(9,6),[[BR]] 
LATITUDE NUMBER(8,6), [[BR]]
SPEED NUMBER(3), [[BR]]
ANGLE NUMBER(3), [[BR]]
DATETIME TIMESTAMP(6),[[BR]] 
STATUS NUMBER(1), [[BR]]
EXTENDSTATUS NUMBER(1),[[BR]] 
REVISED NUMBER(1), [[BR]]
PRIMARY KEY(ID) )[[BR]]
TABLESPACE USERS;[[BR]]
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[[Image(location(10K_100grids).jpg)]][[BR]]
The picture shows 10k entries chosen from the first data file. The covered area is longitude from 121.2 to 121.8 and latitude from 31 to 31.5. The area is divided into 10*10 grids, which is 100 grids in total.[[BR]]