Article
A Practical Approach for High Precision
Reconstruction of a Motorcycle Trajectory
Using a Low-Cost Multi-Sensor System
Sarra Smaiah
1,2,
*, Rabah Sadoun
1,2
, Abdelhafid Elouardi
1
, Bruno Larnaudie
1
, Samir Bouaziz
1
,
Abderahmane Boubezoul
1,3
ID
, Bastien Vincke
1
and Stéphane Espié
1,3
1
SATIE Laboratory, University Paris Sud, 91405 Orsay, France; rabah.sadoun@g.enp.edu.dz (R.S.);
abdelhafid.elouardi@u-psud.fr (A.E.); Bruno.larnaudie@u-psud.fr (B.L.); samir.bouaziz@u-psud.fr (S.B.);
abderrahmane.boubezoul@ifsttar.fr (A.B.); bastien.vincke@u-psud.fr (B.V.); stephane.espie@ifsttar.fr (S.E.)
2
Signal and Communication Laboratory, National Polytechnic School, 16200 El-Harrach, Algiers, Algeria
3
IFSTTAR, Champs-sur-Marne, F-77447 Marne la Vallée, France
* Correspondence: sarra.smaiah@u-psud.fr; Tel.: +33-78-388-3572
Received: 4 June 2018; Accepted: 9 July 2018; Published: 14 July 2018
Abstract:
Motorcycle drivers are considered among the most vulnerable road users, as attested by
the number of crashes increasing every year. The significant part of the fatalities relates to “single
vehicle” loss of control in bends. During this investigation, a system based on an instrumented
multi-sensor platform and an algorithmic study was developed to accurately reconstruct motorcycle
trajectories achieved when negotiating bends. This system is used by the French Gendarmerie in
order to objectively evaluate and to examine the way riders take their bends in order to better train
riders to adopt a safe trajectory and to improve road safety. Data required for the reconstruction
are acquired using a motorcycle that has been fully instrumented (in VIROLO++ Project) with
several redundant sensors (reference sensors and low-cost sensors) which measure the rider actions
(roll, steering) and the motorcycle behavior (position, velocity, acceleration, odometry, heading, and
attitude). The proposed solution allowed the reconstruction of motorcycle trajectories in bends with
a high accuracy (equal to that of fixed point positioning). The developed algorithm will be used
by the French Gendarmerie in order to objectively evaluate and examine the way riders negotiate
bends. It will also be used for initial training and retraining in order to better train riders to learn and
estimate a safe trajectory and to increase the safety, efficiency and comfort of motorcycle riders.
Keywords:
trajectory reconstruction; low-cost sensors; embedded systems; powered two wheels
(PTW); safe trajectory; data fusion
1. Introduction
Motorcycle drivers are considered the most vulnerable road users. In France, such riders account
for more than 20% of all road fatalities (compared with 15% in Europe as a whole) and 43% of road
injuries (ONISR, 2014). For the same distance traveled, the risk to be killed in a fatal crash is 35 times
higher for a motorcyclist than for an automobilist [
1
]. More than 50% of individual motorcycle crashes
are due to loss of control in bends (including crossroads and intersections) because of the complexity
of motorcycle dynamics and the intrinsic instability of such vehicles. In 2012, in France, more than a
third of all the powered two wheels (PTW) fatalities occurred in bends (248 killed).
Counter-measures are needed to improve road safety and decrease the risk of crashes in bends.
In order to do so, it is necessary to better train riders to learn, estimate, and adopt a safe trajectory [
2
,
3
].
Motorcycle trajectory reconstruction represents a fairly important tool for an objective evaluation of
bend taking practices and the characterization of the achieved trajectories compared to a safe trajectory.
Sensors 2018, 18, 2282; doi:10.3390/s18072282 www.mdpi.com/journal/sensors
