IVS (speed limit) in Barcelona

Regular speed limit in Barcelona city is 50km/h. However, there are streets and special areas in which that limit is lower, i.e. 20km/h and 30km/h. The In-Vehicle Signage service informs the user of such cases.

Sample Data Description

For the evaluation of the IVS (speed limit) service deployment in Barcelona, the relevant log items are the iviaction, ivievent and CAM log files. All of these log files are automatically recorded by the PID of the user. The ivievent logs contain the basic information for each event (e.g. timestamp, log_stationid, iviidentificationnumber etc.). The iviaction logs contain the status of the HMI and thus record the information that was presented to the driver at each moment in time with a frequency of approximately 1Hz. The following fields are particularly relevant for the IVS (speed limit) data:

• Speedlimit (between 10 km/h and 130 km/h with the majority of events occurring in 50 km/h and 80 km/h zones)
• servicecategorycode (=12), pictogramcategorycode (=557) and text (hex-encoded, = ‘56656c6f6369646164206dc3a178696d61’) to filter IVS (speed limit) events from other events using IVI messages
• Warningdistance: indicating the distance to the event location

The CAM logging is mainly used to derive the vehicle position, speed and acceleration for the entire duration of the event, also 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 example data set provided here consists of all IVS (speed limit) events logged in Barcelona between 01/02/2021 and 01/04/2021. 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 tlmaction 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 App by IDIADA deployed in Barcelona randomly switches between baseline/treatment with pre-defined probabilities (percentage of baseline events is 25%). Therefore, the example data set provided here consists of roughly 2,200 treatment events and 1,800 baseline events.

To simplify the provision and processing of data, all iviaction logs are grouped into one iviaction.csv file, all ivievent 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.

You can download the log data here.

Evaluation Results

Several indicators can be used to evaluate the impact of IVS (speed limit) on the traffic flow, mainly in terms of safety. The following table briefly describes some of the main indicators. IVS (speed limit) is expected to decrease the mean speed and the frequency of speed violations, since drivers should be more aware of the speed limit. Furthermore, the speed variance should also decrease, both within each event and between all vehicle passages.

The evaluation results data set provided here also contains a table with the above-mentioned indicators calculated for each event. The overall impact of IVS (speed limit) can then 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. The results based on the sample data indicate that, when using the service, the mean speed and the speed variance (standard deviation of speed during the event) increase. At the same time, the frequency and duration of speed violation decreases, which has positive implications on the traffic safety.

To better understand and evaluate these indicators, the mean values are not enough. The probability density functions (PDF) of the indicators for baseline and treatment should also be considered. The following figure illustrates this concept for two of the indicators. Although there is a clear difference in the mean values between baseline and treatment, the relatively widely dispersed distributions and high standard deviation values suggest that the impact of the service is still uncertain.

In order to have more robust and meaningful evaluation results, a larger data sample and a more in-depth analysis of the data (e.g. filtering events by certain criteria, taking into consideration peak/off-peak traffic conditions, checking for incomplete events or errors in the log data etc.) is required. For further details on this please consult <add link to D6.4 (when it will be published)>.

You can download the evaluation data here.