An AI‐based approach for transit route system planning and design

M. Hadi Baaj*, Hani S. Mahmassani

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

208 Scopus citations


We present an AI‐based solution approach to the transit network design problem (TNDP). Past approaches fall into three categories: optimization formulations of idealized situations, heuristic approaches, or practical guidelines and ad hoc procedures reflecting the professional judgement and practical experience of transit planners. We discuss the sources of complexity of the TNDP as well as the shortcomings of the previous approaches. This discussion motivates the need for AI search techniques that implement the existing designer's knowledge and expertise to achieve better solutions efficiently. Then we propose a hybrid solution approach that incorporates the knowledge and expertise of transit network planners and implements efficient search techniques using AI tools, algorithmic procedures developed by others, and modules for tools implemented in conventional languages. The three major components of the solution approach are presented, namely, the lisp‐implemented route generation design algorithm (RGA), the analysis procedure TRUST (Transit Route Analyst), and the route improvement algorithm (RIA). An example illustration is included.

Original languageEnglish (US)
Pages (from-to)187-209
Number of pages23
JournalJournal of Advanced Transportation
Issue number2
StatePublished - 1991

ASJC Scopus subject areas

  • Automotive Engineering
  • Economics and Econometrics
  • Mechanical Engineering
  • Computer Science Applications
  • Strategy and Management


Dive into the research topics of 'An AI‐based approach for transit route system planning and design'. Together they form a unique fingerprint.

Cite this