Traffic is for storing the annual pavement condition survey results and their locations, such as AADT (Annual Average Daily Traffic), Truck Percentage, ESAL (Equivalent Single Axle Load), etc. Out of the box, the table is named PMS_TRAFFIC, and the corresponding window is located under Pavement Analyst > Asset Inventory > Traffic > Traffic Data menu.
PMS_TRAFFIC is also a strictly Location-referenced data table i.e., the data is identified strictly by a location in the LRS network (route with "from" and "to" point boundaries). It is very similar to the pavement condition table and also has an EFF_YEAR column to identify the data year of the record.
Out of the box, PMS_TRAFFIC table has these 8 columns:
COLUMN_NAME | DATA_TYPE | DATA_LENGTH | NULLABLE | COMMENTS |
---|---|---|---|---|
LOC_IDENT | NUMBER | (22,0) | N | Location # used in SETUP_LOC_IDENT table to store the record’s location in the LRS. This is a system column. |
EFF_YEAR | NUMBER | (22,0) | Y | Data year. |
AADT | NUMBER | (22,0) | Y | AADT – Annual Average Daily Traffic |
PCT_TRUCK | NUMBER | (22,2) | Y | Truck percentage in AADT |
ESAL | NUMBER | (22,2) | Y | Equivalent Single Axle Load |
DATE_UPDATE | DATE | 7 | Y | Last update date of the record |
USER_UPDATE | VARCHAR2 | 400 | Y | Last update user of the record |
COMMENT_STR | VARCHAR2 | 4000 | Y | Comment of the record |
Table and Window Configuration
Similar to pavement condition data, the configuration of this dataset starts by expanding the PMS_TRAFFIC table structure to include customer-specific traffic data element and then add those columns to the window.
Follow the instruction detailed in “Create and Import Lookup Values” and “Add Columns to a Table” Chapter in “AgileAssets System Foundation Configuration Guide” and add them into the PMS_ROADWAY_INVENTORY table.
After all the columns have been added to the table, follow the instruction detailed in “Add Columns to a Data Window” section in “AgileAssets System Foundation Configuration Guide” to add those columns to the window.
At this point, the system will have an empty PMS_TRAFFIC table and the window will display an empty dataset.
Import Data
The next step is to create an Import Configuration and load the data into the table. Follow the instruction detailed in “Load Data into Tables” chapter in “AgileAssets System Foundation Configuration Guide” to create the import on traffic table.
Out of the box, a standard import using csv file has been configured that matches the PMS_TRAFFIC configuration. It uses a csv file with the following specification:
Column Header | Data Type | Description |
---|---|---|
EFF_YEAR | Number | Effective year of the traffic data |
ROUTE_NAME | String | Route Identifier in the LRS network |
LANE_DIR | Number | 1 for Ascending (Cardinal or Primary) direction. 2 for Descending (Non-cardinal or Reverse or Non-Primary) direction. 0 for both directions. |
LANE_ID | Number | 0 for all lanes. Otherwise the specific lane number (1,2,3, etc.) |
OFFSET_FROM | Number | Start Measure of the location |
OFFSET_TO | Number | Start Measure of the location |
AADT | Number | AADT |
PCT_TRUCK | Number | Truck percentage |
ESAL | Number | Equivalent Single Axle Load |
If there is client-specific configuration to PMS_TRAFFIC to track additional traffic data element, the template can be expanded to include those fields. In addition, the following objects needs to be updated to reflect those changes to ensure all the steps in the import are running correctly:
- PMS_TRAFFIC table and window
- Import configuration into the PMS_TRAFFIC table
The guideline for updating or creating additional import configuration is similar to pavement condition data. Most of the time, when you update the traffic data, you will only import (or replace) the data with a specific year (or latest year), and leave the historical data untouched. This can be achieved by specifying a “Replace Where Clause” in the import Configuration, for example:
EFF_YEAR=2019
After running the import, the system will have a populated PMS_TRAFFIC table and the window will display the corresponding data.