  This work describes the use of on-board vehicle data from cars with advanced
driver assistance features as a trip summary, with the goal of helping drivers
contextualize their driving habits in terms of sustainability. The approach is
similar to recent advancements in fitness tracking apps, which leverage
smartwatches and other wearable devices to characterize activities during a
workout or as part of daily fitness monitoring. Instead of adding new vehicle
sensors, the data used for this work is from on-board driving data, namely,
signals decoded from the vehicle's Controller Area Network (CAN) bus. With the
deepening research of automatic driving technologies, Autonomous Vehicles (AVs)
have gradually entered the consumer field, and more users are benefiting from
the convenience and safety assistance provided by driving assistance and
autonomous driving. However, various technical obstacles persist due to the
complex environment, the non-communication of technologies, and users' trust.
We propose indicators for evaluating the key characteristics of each drive, to
facilitate drivers' familiarity with advanced driver assistance systems and to
allow them to consider how different driving styles affect sustainability
metrics. Further extensions will allow users to add feedback as part of the
driving summary, laying a data foundation for future controller iterations
based on real driving data and the attitude of drivers towards it.
