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Distinguished Lecture: Safe, Trustworthy Autonomous Mobility: A Human-Centered Symbiotic Systems Perspective

This in-person event is an opportunity to network and interact with an expert whose talk promises a rare blend of decades‑long technical insight, real‑world research examples, and a forward-looking vision for how humans, AI, and infrastructure can actually make autonomy safer, scalable, and trustworthy.

Autonomous mobility is largely approached as a vehicle-centric problem. Persistent challenges in safety,

scalability, and public trust suggest a deeper issue: “intelligence” is often considered in isolation rather than as

distributed. This presentation argues that truly safe and trustworthy autonomy will emerge only through

symbiotic computational systems, where perception, decision-making, and control are distributed across

humans, machines, and infrastructure.

 

The presentation starts with an overview of the four decades-long progress in autonomous driving and related

advancements in driver assistance technologies. It is followed by a discussion of the central thesis: that many

failures in autonomous mobility stem not from algorithms alone, but from how system boundaries are defined—

what is sensed, where intelligence resides, and how responsibility is shared. Framing autonomy as a systems-

level problem, the talk draws on principles of distributed and embodied cognition to unify perspectives from

robotics, artificial intelligence, human–computer interaction, and transportation engineering.

 

Concrete examples from multidisciplinary research by the CVRR and LISA teams at UC San Diego, conducted

on real vehicles in real-world driving environments and validated through both quantitative benchmarks and

qualitative studies in collaboration with industry partners, illustrate how shared autonomy can tightly couple

human state (e.g., intent, attention, readiness) with environmental context to enable safer and more adaptive

human–AI interaction. The lecture also discusses how advances in foundation models, self-supervised learning,

and active learning can improve generalization and robustness in safety-critical settings.

 

The talk concludes with key open challenges, including multimodal foundation models for traffic ecosystems,

human–AI co-adaptation, and continual learning under domain shift, important problems to realize scalable,

trustworthy autonomous mobility.

Date and Time

Date: 29 Apr 2026Time: 05:00 PM PDT to 06:30 PM PDT

Location

  • This event has virtual attendance info. Please visit the event page to attend virtually.
  • Dr. Martin Luther King, Jr. Library (SJSU)
  • 150 E San Fernando St San Jose, California 95112
  • San Jose, California
  • United States
  • Room Number: MLK Room 225
  • Click here for Map

Hosts

Registration

  • Starts 24 April 2026 12:00 AM PDT
  • Ends 29 April 2026 05:00 PM PDT
  • No Admission Charge

Speakers

Professor Mohan Trivedi

 

Topic:

Safe, Trustworthy Human-Centered Autonomous Mobility: A Human-Centered Symbiotic Systems Perspective

Dr. Vishnu S Pendyala of San Jose State University

 

Topic:

Moderator



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Attachments:
Santa Clara Valley Section Chapter, C16 : https://r6.ieee.org/scv-cs/
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