Using Event Data Recorder to Detect Road Infrastructure Failures from a Safety Point of View.

Using Event Data Recorder to Detect Road Infrastructure Failures from a Safety Point of View.


Vincent Ledoux, CEREMA, Peggy Subirats, CEREMA, Thierry Serre, IFSTTAR


This paper aims at presenting some results of a French research project in which studies were carried out to assess how Event Data Recorders can help local authorities to detect road infrastructures defects related to safety issues


Accident data are useful to define road safety policies and particularly to identify where the road infrastructure should be improved. But the international trend of reduction of accidents amount this last decade induced a lack of reliable data : there are less accidents and their location is more diffuse. Thus, local authorities can face difficulties to set priorities in their intervention policy on their road network.
This issue is particularly strong on the secondary road networks. In France, for instance, the great majority of the road fatalities occurs on this network. Nevertheless, due to its length and traffic volume, the rate of road fatalities per kilometre is four times lower than on the main road network. In addition, the number of road fatalities on this network was reduced by 40% within ten years.
Consequently, local road authorities face increasing difficulties to identify risky road locations using only crash data.
In light of this, the French government (DSCR) decided to support the SVRAI project (Saving Lives through Road Incident Analysis Feedback) to complete accidentology with incidentology data. One of the project’s objectives is to investigate if data collected by the device can be used by local road authorities to detect safety failures or defaults in road infrastructure.
This project rely on the use of an Event Data Recorder called EMMA (Embedded data logger for accident mechanisms) specifically designed by IFSTTAR-LMA. The device detects some driving situations considered as risky, during which the vehicle reaches high dynamics demands in longitudinal, lateral or combined directions.
EMMA acquires different signals (longitudinal and transversal accelerations, GPS location and speed,…) from internal and eventually external sensors.
The data are analyzed, using real-time processing performed by an embedded software, to detect potential situations of interest (events). The processing is based on the following principles: when acceleration and jerk signals exceed simultaneously some thresholds, an event is triggered. The data acquired 30 seconds before and 15 seconds after the trigger are stored in the device. The file containing the whole data set is automatically sent to a secured server using GSM network. The event is then examined by an operator and if considered of interest, the event is classified as incident and stored as such in the global database.
In addition all the itineraries travelled by the equipped vehicle are also recorded from GPS and stored at a rate of 1 position/minute. This allow to know which roads were circulated and determine the exposure.
50 EMMA were implemented on public vehicles fleets, in three regions. The data collection started in August 2012 and lasted one year.
First, the paper will present a general overview of the project and some global results.
Then, focus will be given on the results obtained in a French Department, where 24 instrumented vehicles were in use.
Inputs will be given regarding to the proportions and types of roads that were circulated by those vehicles, and regarding to detected incidents.
The proportion of incidents occurrence in which road infrastructure could be totally or partially incriminated, will be given. The methodology implemented for this analysis will be described.
By a better knowledge on the network and by spotting priority road locations where infrastructure should be improved, insight will be given into the potential of incident analysis regarding to local road safety policies.


Association for European Transport