The Assessor Mag Summer 2024 Web - Flipbook - Page 31
1. WHAT IS PACE-AI AND WHAT
DATA DOES IT REQUIRE?
PACE-AI is a forensics support system
that aims to reduce pedestrian collision
design space in seconds using only
a few inputs (vehicle pro昀椀le, damage
coordinates, and pedestrian height
and weight) and no advanced forensic
calculation skills. It is not a replacement
for forensic reconstruction analysis, but
a step towards narrowing the design
space instantaneously by providing
realistic accident characteristics to
assist effective accident reconstruction.
It can be used by the roadside.
2. How is PACE-AI developed?
PACE-AI is trained using over 3000
Madymo pedestrian computed
collisions. Madymo is a multibody
solver, which was chosen thanks to
its capability, evidenced in research
publications, to predict accurately
pedestrian kinematics. PACE-AI, via
a patented search and convergence
algorithm, extracts from vehicle pro昀椀le
and damage, as well as pedestrian
anthropometry, plausible vehicle
impact speed, pedestrian crossing
speed, crossing direction and gait, in
this in seconds.
3. What is the scienti昀椀c
underpinning PACE-AI?
Publication available upon request:
Shrinivas, V, Bastien, C, Davies,
H, Daneshkhah, A, Hardwicke,
J & Neal-Sturgess, CE 2024,
'Integrating Machine Learning in
Pedestrian Forensics: A Comprehensive
Tool for Analysing Pedestrian
Collisions', SAE Technical Papers,
24SS-01_0328, (In-Press).
4. How can PACE-AI help me with
forensic investigation?
Suppose you are investigating a
pedestrian collision, which could
be a hit-and-run case. Evidence on
the road, necessary to perform any
accident forensic analysis and accident
reconstruction, can be sparse and take
a long time to collect, i.e., the point of
collision may not be evident, and the
weather conditions not favourable to
collect this relevant data. You would
like to calculate, in seconds, by the
side of the road, what happened
at the time of the collision. That is
where PACE-AI comes in. PACE-AI is
a simple web-based application that
can calculate, from the bumper and
windscreen damage and the estimated
height and weight of the victim, the
most plausible set of circumstances
at the time of impact. PACE-AI will
help you narrow the range of possible
scenarios and have a more realistic
idea of what happened. This way,
you can determine the driver’s level
of responsibility, and take preventive
actions, if necessary, while you wait
for a more detailed and conclusive
collision reconstruction report. The
computation results from PACE-AI can
also be provided later to the forensic
investigation team, making the 昀椀nal
reconstruction quicker, hence saving
investigator resource, time and cost.
5. Is PACE-AI validated?
Yes, it is validated using the pedestrian
collisions available from the Road
Accident In-Depth Studies (RAIDS)
database. PACE-AI's performance was
within an error margin of 5 km/h.
www.iaea-online.org/news/the-assessor | SUMMER 2024 | THE ASSESSORS JOURNAL
6. What happens to the data
entered into PACE-AI? Is
PACE-AI GDPR compliant?
The server, located in the UK,
processes the collision data. Upon
completion, the collision parameter
information is sent back to the
PACE-AI user, no data having been
stored. PACE-AI is GDPR compliant
7. What languages are available
within PACE interface?
English, French, German and Spanish
(other languages upon request).
8. PACE licensing?
A PACE-AI licence runs as a webbased application, which can process
individual cases one at a time or
multiple cases at the same time. Please
contact the authors for pricing.
9. Who to contact:
Dr Christophe Bastien,
Associate Professor
E: christophe.bastien@coventry.ac.uk
T: +44 (0)7974 984055.
Editor’s note: for a copy of the
peer-reviewed scienti昀椀c paper
explaining the underpinning of
the science behind the technology
discussed in this article, please
contact: editor@theiaea.org.
Simcenter Madymo, software for
simulating human safety in transport
and road users, is part of Siemens
PLM Software.
31