Intelligent Roadway Information System
Real time vehicle data is used for several purposes:
- Traffic maps
- Travel times
- Ramp metering
- Tolling rate calculation
- Parking area availability
- Variable speed advisories
Different techonlogies, such as inductive loops, magnetometers, radar and video are available for detecting vehicles. Collectively, these systems are called detectors.
Every 30 seconds, the most recent collected data from all online detectors is
written to files. An XML file called
det_sample.xml.gz and a JSON file
station_sample are generated.
Detectors can collect several different types of data:
- Count: The number of vehicles in a period of time
- Duration: Interval of time a vehicle occupied a detector (ms)
- Occupancy: Percentage of time period detector was occupied
- Speed: Vehicle speed (mph)
- Headway: Interval of time between the start of consecutive vehicles (ms)
- Length: Physical length of vehicle (ft)
Some data can be derived from collected data:
- Flow: Rate of vehicles travelling past a detector (vehicles per hour)
- Density: The number of vehicles per mile in a segment of road (one lane)
- Speed: If not collected, can be derived from flow divided by density
Flow is calculated by multiplying vehicle count by the number of time periods in an hour. For example, a count of 10 vehicles in 30 seconds equals a flow rate of 1200, because there are 120 periods of 30 seconds in an hour.
Density can be derived by dividing flow (vehicles per hour) by speed (miles per hour). For detectors which cannot collect speed data, density can be estimated using just occupancy and field length (see below).
To create a detector, first select the r_node at the proper location. Then
select the Detectors tab for that
r_node. Enter the detector Name
and press the Create button.
After selecting a detector in the
r_node detector table, its properties, such
as lane type and lane # can be changed. Lanes are numbered from
right-to-left, starting with the right lane as 1. A label will be created
from this information, including abbreviations of the roads associated with
Field length (ft) is the detection “field” of an average vehicle. It is used to derive density from occupancy, for detectors which cannot measure speed directly.
If a detector is no longer used, it can be marked abandoned.
|Auxiliary||Mainline auxiliary (ends within a mile)|
|CD Lane||Collector / Distributor|
|Merge||Freeway on-ramp (counts all merging traffic)|
|Queue||Ramp metering queue|
|Bypass||Ramp meter bypass|
|Passage||Ramp meter passage|
|Velocity||Mainine speed loop|
|Green||Ramp meter displayed green count|
|Wrong Way||Exit-ramp wrong way detector|
|HOV||High occupancy vehicles only|
|HOT||High occupancy or tolling only|
|Parking||Parking space presence detector|
To move a detector to another
r_node, select the target
r_node and enter the
detector Name. The current label for that detector will appear on the
right. To move it to the current
r_node, press the Transfer button.
|SmartSensor 125 HD||5 sec to 1 hour||Count, Occupancy, Speed|
|SmartSensor 125 vlog||N/A||vlog|
|SmartSensor 105||5 sec to 1 hour||Count, Occupancy, Speed|
|RTMS G4||5 sec to 1 hour||Count, Occupancy, Speed|
|RTMS G4 vlog||N/A||vlog|
|MnDOT-170||30 sec||Count, Occupancy|
|DXM||N/A (presence)||Magnetic Field|
|NTCIP||0-255 sec||Count, Occupancy|
For protocols which allow the binning intereval to be adjusted, it will be set to the poll period of the comm link.
Traffic data is continuously checked for five common failure conditions. When
one of these first occurs and every hour that it persists, an event is logged in
detector_event database table. The
detector_auto_fail_view can be used
to check recent events.
detector_auto_fail_enable system attribute is
true, the auto
fail flag for each detector will be set and cleared automatically whenever
these conditions change.
This failure condition occurs if no vehicles are counted for a duration determined by the lane type. It clears immediately when a vehicle is counted.
|Mainline, CD Lane, Velocity||4 hours|
|Exit, Wrong Way, HOV||8 hours|
|Queue, Passage, Merge||12 hours|
|Bypass, Green, Omnibus, HOT, Reversible, Shoulder||72 hours|
If a detector reports an unreasonably high count of 38 vehicles or more in a 30 second period, this condition will be triggered. It will be cleared if 24 hours pass with all counts below that threshold.
This condition occurs if the detector reports 100% occupancy for a duration determined by lane type. It is also sustained if the occupancy drops to zero with no intervening values. The condition will be cleared after 24 hours of good occupancy data.
|Mainline, Auxiliary, CD Lane, Reversible, Velocity, HOV, HOT, Shoulder||2 minutes|
|Merge, Queue, Exit, Bypass, Passage, Omnibus, Green, Wrong Way||30 minutes|
If occupancy is greater than zero and does not change for 24 hours, this condition will be triggered. It will clear immediately if the occupancy changes.
A spike timer is kept for each detector. For every 25% change in occupancy between two consecutive data values, 30 seconds are added to the timer. If its value ever exceeds 60 seconds, the condidtion is triggered. After every poll, 30 seconds are removed from the timer. The condition will be cleared after 24 hours of no spikes.
If a detector has a fault which is not handled automatically, it can be force failed. This flag is only set manually, so it must be cleared once the failure is corrected.
When a detector is failed (auto fail or force fail), its data will not be used for travel time, ramp metering, etc. In that case, fake detection can be used — this field can contain one or more other detector names, separated by spaces. The average density or speed of those detectors (which are not also failed) will be used instead.
The IRIS client user interface includes a traffic map layer which is created automatically from the road topology. By default, this layer uses traffic density to determine the color of each segment. Other themes are available for speed and flow. The Legend menu at the top of the map can be used to view the thresholds used for each color in a theme.
Every 30 seconds, the client will make an HTTP request for the current
XML file. The URL to locate that file is declared as a property in the
/etc/iris/iris-client.properties file (on the IRIS server). The property is
tdxml.detector.url, and it should point to the
det_sample.xml.gz XML file,
as made available by
nginx on the IRIS server.
The appearance of the traffic map layer changes depending on the current zoom level. If the zoom level is below 10, the layer will not be visible. At zoom levels 10 through 13, the layer will display segments as aggregate of all detectors in each mainline station. At zoom level 14 or above, each mainline detector will be displayed as a separate segment.
The maximum distance between adjacent stations to draw segments on the map is
specified by the
map_segment_max_meters system attribute. It is also the
maximum downstream distance for associating station data with a segment.
Traffic Data Archiving
Traffic data are stored in
/var/lib/iris/traffic, in a directory with the
district name. Within that directory a new subdirectory is created for each
year, with a 4-digit name (e.g.
As data is collected, a new subdirectory is created every day — the name is
12 and day-of-month
At 10 PM, all traffic data from the previous day is moved into a single ZIP file
with the 8-digit base name and a
.vlog format is a comma-separated text log. Each vehicle event is
recorded as a single line of values, ending with a newline
|1||Duration||How long vehicle occupied detector (ms)|
|2||Headway||Time since previous vehicle (ms)|
|4||Speed||Vehicle speed (mph)|
|5||Length||Vehicle length (ft)|
Duration is the time a vehicle occupied the detector area, between 1 and
60000 ms. An invalid or missing value is represented by a
Headway is the difference in arrival time from the previous vehicle to the
current one. It is a positive integer between 1 and 3600000 ms (1 hour). An
invalid or missing value is represented by a
Time is when the vehicle left the detection area. Normally, this field is left blank, but it is included when the headway is invalid or missing, or for the first event after the beginning of each hour. Changes due to daylight saving time are not recorded.
Speed is the measured vehicle speed. It is a positive integer value from 5 to 120 mph. An invalid or missing value is left empty.
Length is the measured vehicle length. It is a positive integer value from 1 to 255 ft. An invalid or missing value is left empty.
All trailing commas at the end of a line are removed. This means that an event with only duration and headway would only contain the two values, separated by one comma.
A gap in sampling data due to communication errors is represented by
(U+002A) on a line by itself.
.vlog data for 11 vehicles:
IRIS can collect these types of binned traffic data:
|Vehicle Count||Count of vehicles detected||v||8 bits|
|Occupancy||30-second scan count (0 to 1800)||c||16 bits|
|Speed||Average speed (mph) of detected vehicles||s||8 bits|
A binned data file consists of some number of periods of equal duration. The first period begins (and the last period ends) at midnight. The binning interval determines the number of periods collected per day — a shorter interval results in more periods. If the interval is longer than 30 seconds, the values are allocated evenly into 30-second bins for storage.
|Period||Binning Interval||Values||Stored Bins|
|5||5 seconds||17280||5 seconds|
|6||6 seconds||14400||6 seconds|
|10||10 seconds||8640||10 seconds|
|15||15 seconds||5760||15 seconds|
|20||20 seconds||4320||20 seconds|
|30||30 seconds||2880||30 seconds|
For each detector, a binned data file is created for each data type. The
base file name is the detector name. The file extension is the code and
period (in seconds). For example, 60-second vehicle counts collected from
detector 100 would be stored in a file called
100.v60, containing 2880 bins.
Each data value is either an 8- or 16-bit signed integer, depending on the data type. 16-bit value are in high-byte first order. A negative value (-1) indicates missing data. Any data outside the valid ranges should be considered missing.