  The area of Traffic Management (TM) is characterized by uncertainty,
complexity, and imprecision. The complexity of software systems in the TM
domain which contributes to a more challenging Requirements Engineering (RE)
job mainly stems from the diversity of stakeholders and complexity of
requirements elicitation in this domain. This work brings an interactive
solution for exploring functional and non-functional requirements of
software-reliant systems in the area of traffic management. We prototyped the
RETTA tool which leverages the wisdom of the crowd and combines it with machine
learning approaches such as Natural Language Processing and Naive Bayes to help
with the requirements elicitation and classification task in the TM domain.
This bridges the gap among stakeholders from both areas of software development
and transportation engineering. The RETTA prototype is mainly designed for
requirements engineers and software developers in the area of TM and can be
used on Android-based devices.
