The Long Road Ahead International Workshop on Autonomous, Connected, and Smart Transportation

Self-driving vehicles will bring capillary and irreversible transformations into the worlds of transportation, logistics and urban design. However, it is now clear that the development of this AI-based technology constitutes a long-term, complex challenge: despite some impressive technological achievements and the boastful announcements often made by makers and entrepreneurs, autonomous vehicles are not roaming our roads yet and it is still unclear when they will eventually be mature enough to operate in ‘full’ or ‘semi’ autonomous mode. What is still needed to make this innovation real? What are the obstacles faced by developers and makers, and do the underlying problems have a communal root? We will tackle these questions with the help of authoritative experts from academia, private sector, and public administration. The workshop aims to identify and investigate with an integrative and interdisciplinary approach the fundamental challenges faced by the sector.

Scope and thematic sessions 

The program includes keynotes, roundtable discussions, and presentations with experts of: machine learning, computer vision, data; logistics and transportation science; human factors & ergonomics; cognitive science and human performance; public policy and regulation of emerging technologies; ethics, philosophy, and sociology of AI. The workshop will feature thematic sessions dedicated to: (I) technological and implementational problems (developing instruments and solutions); (II) foundational and methodological problems (conceiving appropriate frameworks, standards, and models); (III) ethico-legal and normative problems (what individuals and societies want, what regulatory authorities should do).

Call for abstracts (deadline 10 May 2023, for information and submission

Suitable abstracts (300-500 word for 20 min presentations) include, but are not limited to, the following topics:

  • Sensors, machine vision, and scene understanding.
  • Limited and biased data.
  • Real-time traffic negotiation and coordination among vehicles.
  • Smart infrastructures and systems interoperability.
  • Value alignment and sensitive design.
  • Ethical decision and societal acceptance
  • Knowledge representation and the frame problem.
  • Interpreting and producing human-like behaviours.
  • Trust marks and safety assessment.
  • Transitioning from full-autonomy to meaningful human control.
  • Risk perception and public policy.


The LORA research series is convened by: Max Cappuccio (SEIT, coordinator), Stephen Coleman (HASS), Essam Debie (SEIT), Helen Dickinson (School of Business), Vinayax Dixit (rCITI), Milad Ghasrikhouzani (SEIT), Oleksandra Molloy (SEIT), Maurice Pagnucco (UNSW Kensington), Michael Regan (rCITI), Eduardo Benitez Sandoval (UNSW Paddington).