  Auto manufacturers and research groups are working on autonomous driving for
long period and achieved significant progress. Autonomous vehicles (AV) are
expected to transform road traffic reduction from current conditions, avoiding
accidents and congestion. As the implementation of an autonomous vehicle
ecosystem includes complex automotive technology, ethics, passenger behaviour,
traffic management policies and liability etc., the maturity of AV solutions
are still evolving. The proposed model to improve AV user experience, uses a
hybrid AV Network of multiple connected autonomous vehicles which communicate
with each other in an environment shared by human driven vehicles. The proposed
Optimal AV Network (OAVN) solution provides better coordination and
optimization of autonomous vehicles, improved Transportation efficiency,
improved passenger comfort and safety, real-time dynamic adaption of traffic &
road conditions along with improved in-cabin assistance with inputs from
various sensors. The true optimal solution for this problem, is to devise an
automated guidance system for vehicles in an AV network, to reach destinations
in best possible routes along with passenger comfort and safety. A custom
informed search model is proposed along with other heuristic goals for better
user experience. The results are analysed and compared to evaluate the
effectiveness of the solution and identify gaps and future enhancements.
