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french institute of science and technology for transport ... - Ifsttar

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Research orientation 2_Transport system quality, safety <strong>and</strong> optimization<br />

Communication in<br />

a mobile environment<br />

Progress towards interoperability<br />

Enormous implications <strong>of</strong> road safety.<br />

The ANR PLATA project (Programmable Telematics<br />

On-board Multist<strong>and</strong>ard Radio Plat<strong>for</strong>m) sets out to implement<br />

a new multist<strong>and</strong>ard radio telematics plat<strong>for</strong>m <strong>for</strong> the<br />

automobile sector based on emerging s<strong>of</strong>tware radio technologies.<br />

The flexibility <strong>of</strong> this <strong>technology</strong> makes it possible to use<br />

different communications st<strong>and</strong>ards <strong>for</strong> vehicle/vehicle <strong>and</strong><br />

vehicle/infrastructure communications. The ultimate goal is<br />

to provide Europe-wide interoperability between communication<br />

systems.<br />

In 2011, a PLATA project demonstrator was developed. At the<br />

same time, a large number <strong>of</strong> simulations were per<strong>for</strong>med,<br />

making it possible to evaluate the scaling-up process <strong>and</strong> the<br />

behaviour <strong>of</strong> the system with an increase in the number <strong>of</strong><br />

equipped vehicles. The framework that has been put in place<br />

allows us to carry out realistic simulations <strong>of</strong> vehicle movement.<br />

For this purpose; a simulator - SUMO (Simulation <strong>of</strong> Urban<br />

Mobility) - was interconnected with the trajectory management<br />

functionalities in the OPNET network simulator. The result was<br />

that the trajectory <strong>and</strong> behaviour <strong>of</strong> each individual vehicle<br />

could be identified. The next stage will be to simulate communications<br />

with the OPNET s<strong>of</strong>tware program. During trials<br />

we have simulated the movement <strong>of</strong> several hundred vehicles<br />

with the communications between them.<br />

@ CONTACT<br />

christophe.gransart@ifsttar.fr<br />

55<br />

Simulations on the Satory test track <strong>and</strong> on the<br />

edge <strong>of</strong> the campus <strong>of</strong> Lille 1 University.<br />

Energy <strong>and</strong> planning railway timetables<br />

A new timetabling criterion<br />

The ESTAS research unit is specialized in rail-related<br />

themes <strong>and</strong> its expertise is widely recognized among its<br />

partners (SNCF, RFF) as a result <strong>of</strong> several projects (the<br />

national CIGIFRET project <strong>and</strong> the European ON-TIME<br />

project). In 2009, it began to take energy into account<br />

in its work on traffic management.<br />

with a set <strong>of</strong> distinct possible solutions <strong>and</strong> can then construct<br />

timetables that simultaneously meet passenger dem<strong>and</strong> <strong>and</strong><br />

take account <strong>of</strong> energy consumption.<br />

@ CONTACT<br />

remy.chevrier@ifsttar.fr<br />

The research into optimizing timetable planning which<br />

has got under way since this decision there<strong>for</strong>e now includes<br />

energy as a criterion. Planning <strong>of</strong> this type depends, in particular,<br />

on train movement times allowing <strong>for</strong> disruptions <strong>and</strong><br />

drifting, i.e. when the train moves under its own inertia with its<br />

motor turned <strong>of</strong>f which leads to substantial savings. In 2011,<br />

ESTAS proposed a method that generated a variety <strong>of</strong> driving<br />

strategies using a number <strong>of</strong> speed pr<strong>of</strong>iles based on a trade-<strong>of</strong>f<br />

between journey times <strong>and</strong> energy consumption.<br />

The method involves the multi-goal optimization <strong>of</strong> train movement<br />

<strong>and</strong> is based on evolutionary algorithms <strong>for</strong> the competitive<br />

optimization <strong>of</strong> energy consumption <strong>and</strong> journey times.<br />

For a given optimization task the decision-maker is presented<br />

Speed (m/s)<br />

90<br />

80<br />

70<br />

60<br />

50<br />

40<br />

30<br />

20<br />

10<br />

0<br />

0<br />

20 000<br />

40 000<br />

Benchmark<br />

Alternative solution<br />

60 000<br />

Position (m)<br />

80 000<br />

100 000<br />

120 000<br />

140 000<br />

Example <strong>of</strong> TGV speed pr<strong>of</strong>iles <strong>for</strong> a 135 km journey: the red plot shows<br />

the minimized journey time <strong>and</strong> the green plot shows an alternative strategy<br />

which saves energy while slightly increasing the journey time.<br />

ANNUAL REPORT 2011 ifsttar.fr

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