BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//modelica.simtek.cc//amfc2026//speaker//D3ZWRV
BEGIN:VTIMEZONE
TZID:CST
BEGIN:STANDARD
DTSTART:20000101T000000
RRULE:FREQ=YEARLY;BYMONTH=1
TZNAME:CST
TZOFFSETFROM:+0800
TZOFFSETTO:+0800
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
UID:pretalx-amfc2026-LQJB7C@modelica.simtek.cc
DTSTART;TZID=CST:20260921T092000
DTEND;TZID=CST:20260921T095000
DESCRIPTION:The report focuses on AI safety and R&D toolchains for intellig
 ent vehicles. Drawing on the team’s extensive research in the system saf
 ety of connected and autonomous vehicles (CAVs) and autonomous driving con
 trol\, it analyzes failure risks in AI perception and decision-making algo
 rithms\, as well as functional safety and data security challenges. It fur
 ther elaborates on a comprehensive safety protection framework tailored fo
 r full-scenario autonomous driving. Addressing key industry pain points\, 
 the report introduces an end-to-end R&D toolchain for intelligent driving\
 , covering simulation testing and electronic control development platforms
 \, while demonstrating their practical applications in algorithm verificat
 ion and safety assessment. Finally\, by integrating theoretical insights w
 ith engineering practice\, it explores iterative pathways for advancing AI
  safety technologies and outlines future directions for domestically devel
 oped tools\, offering actionable strategies to drive technological upgrade
 s and real-world deployment across the industry.
DTSTAMP:20261004T070711Z
LOCATION:Main hall (R1016)
SUMMARY:AI Safety and Development Tools for Autonomous Driving - Shichun Ya
 ng
URL:https://modelica.simtek.cc/amfc2026/talk/LQJB7C/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-amfc2026-QHWTVG@modelica.simtek.cc
DTSTART;TZID=CST:20260921T120500
DTEND;TZID=CST:20260921T123000
DESCRIPTION:A 22-DOF vehicle dynamics model is developed in Modelica and im
 plemented in MWorks Sysplorer 2025a.The generalized coordinates comprise s
 ix sprung-body motions\, twelve translational motions of the four unsprung
  masses\, and four wheel-spin motions. The physical plant is formulated as
  a coupled differential-algebraic equation system: the body\, suspension\,
  unsprung mass\, wheel\, tire\, and road components are connected through 
 custom acausal physical connectors\, whereas steering and wheel-torque com
 mands are retained only as external causal boundaries. The model is assess
 ed using acceleration\, braking\, and steering-step datasets from MWorks\,
  a 22-DOF Simulink model\, and road tests. The threesource comparison demo
 nstrates consistent overall dynamic trends and close agreement in key perf
 ormance indicators\, particularly in braking-distance prediction and stead
 y steering response\, thereby validating the effectiveness of the proposed
  acausal 22-DOF modeling framework.
DTSTAMP:20261004T070711Z
LOCATION:(Electric) Mobility & Buildings (R2003)
SUMMARY:22-DOF Full-Coupled Vehicle Dynamics Modeling and Control Based on 
 Modelica - Yufan Guo\, Zehua Wu\, Bingtao Ren\, Shichun Yang
URL:https://modelica.simtek.cc/amfc2026/talk/QHWTVG/
END:VEVENT
END:VCALENDAR