Explore Connected and Cooperative Mobility
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Explore Connected and Cooperative Mobility
Blind Spot Detection (BSD)
Emergency Vehicle Warning (EVW)
Flexible Infrastructure (FI)
Green Light Optimal Speed Advisory (GLOSA)
Green Priority (GP)
In-Vehicle Signage (IVS)
Motorcycle Approaching Indication (MAI)
Road Hazard Warning (RHW)
Road Works Working (RWW)
Signal Violation Warning (SVW)
Warning System for Pedestrian (WSP)
BSD in Bilbao
Bilbao became in 2020 the first city in the world with more than 300,000 inhabitants to limit the speed limit to 30 km/h on all its streets. Therefore, in the last years mobility of other means of transport such as bicycles has been boosted. Cyclists can drive around the whole city but, in some segments, they would share the path with other road users.
Thus, BSD service will warn the cyclist about the possible collision risk with other vehicles at the surroundings when they are approaching to complex intersection at the city.
Sample Data Description
For the evaluation of the BSD service deployment in Bilbao there are four relevant files logged. The PID of the user automatically records all these log files.
- CAM: contains information about the position and speed of the cyclist.
- DENM: contains the information of the DENM message (encoded in ASN1) that the PID receives
- denmaction: contains the status of the HMI and thus record the information that was presented to the cyclist at each moment.
- denmevent: contain the basic information for each event (e.g., timestamp, log_stationid, eventcausecode etc.)
The frequency of these data (expect from DENM) is approximately 1Hz. The following fields are particularly relevant for the BSD service:
|Hmipriority||Indicates if the collision risk is imminent because a vehicle is very near the cyclist (WARNING), or if the message is just informative due to the complexity of the intersection (RELEVANT)|
|Warningdistance||Indicates the distance to the event location|
|Warningsound||Indicates if the application generates vibration and sound patterns for the warning|
|Eventcausecode||This field is set to 97 (collision risk) for the BSD service|
Indicates the priority of the warning:
· 0 (unavailable) is set for the low priority warning
· 4 (VRU) is set for high priority warning
At the denmevent file the evaluator could check the cause codes to confirm which kind of event/service is recorded. The CAM logging is mainly used to derive the vehicle position, speed, and acceleration for the entire duration of the event at a frequency of approximately 1Hz. For a more in-depth description of the logging format and the data fields in each log type please visit Open Common Log Data Format.
The sample data set provided consist of a BSD event logged in Bilbao the XX/XX/XXXX. This dataset includes a treatment data event which is logged when the service is fully functional.
Both CAM and DENM files will contain the original C-ITS message, which need to be decoded to access the whole information. In a deep analysis of this decoded message, we could find for example the field stationType = 2 of the Cam messages, which will confirm that the vehicle that generated this data is a cyclist.
Analysing denmaction and denmevent files we could see that the cyclist will receive a low-priority warning (denmevent codes: 97, 0) when s/he is more than 50 meters away from the collision point. And a high-priority warning (denmevent codes: 97, 4) which includes vibration and sound, when s/he is next to the collision point (<50m).
You can download the log data here.
The example data set provided here consists of all BSD events logged in Bilbao. The data set includes both baseline and treatment events. ‘Baseline’ indicates that the service was not active (no information was presented to the driver) and is used as a point of reference, whereas ‘treatment’ events are logged when the service is fully functional. Separating events by baseline/treatment is possible by analyzing the content of the denmaction log files and, more specifically, by checking for the existence of rows where eventmodelid==6 (indicating that certain information was displayed on the screen). The BSD app deployed in Bilbao randomly switches between baseline/treatment with pre-defined probabilities (percentage of baseline events is 50%). Therefore, the example data set provided here consists of roughly 50 treatment events and 50 baseline events.
To simplify the provision and processing of data, all denmaction logs are grouped into one iviaction.csv file, all denmevent logs into one ivievent.csv file and all CAM logs into one CAM.csv file. Individual events can be identified through unique combinations of the (log_stationid, eventid) fields. As defined in the log format specification, each event should begin with eventmodelid=5 and eventactionid=1 and end with eventmodelid=5 and eventactionid=3. In case there are multiple instances of these combination for one event, the first (5,1) and (5,3) are used to define the start and end of the event.
There are several indicators to evaluate the performance of BSD service. The most important ones are related to the speed and acceleration profiles of the cyclist. In the following table, some of these indicators are explained.
|Short name||Long name||Description||Expected effect|
|numberofstops||Number of stops||How many times does the cyclist stop during the event (intersection approach and passage)||decrease|
|meanspeed||Mean speed||The mean speed of the cyclist during the event||decrease|
|speedvariance||Speed variance||Standard deviation of the speed of one cyclist during the event||decrease|
|maxdeceleration||Maximum deceleration||The maximum deceleration (braking intensity) of the cyclist during the event||increase|
|maxacceleration||Maximum acceleration||The maximum acceleration of the cyclist during the event||decrease|
The evaluation results data set provided here also contains a table with the above-mentioned indicators calculated for each event to exemplify the indicator extraction procedure. The overall impact of BSD could be calculated by grouping events by baseline/treatment and comparing the indicator averages over both groups. The following table gives an overview of the main indicators as extracted from the sample data. Due to some errors in the recording of the speed values in the app, the speed values are abnormally low and therefore the indicator values provided here are just for exemplification purposes and do not reflect the real values.
You can download the evaluation data here.