  Better fuel efficiency leads to better financial security as well as a
cleaner environment. We propose a novel approach for improving fuel efficiency
in unstructured and unregulated traffic environments. Existing intelligent
transportation solutions for improving fuel efficiency, however, apply only to
traffic intersections with sparse traffic or traffic where drivers obey the
regulations, or both. We propose GameOpt+, a novel hybrid approach for
cooperative intersection control in dynamic, multi-lane, unsignalized
intersections. GameOpt+ is a hybrid solution that combines an auction mechanism
and an optimization-based trajectory planner. It generates a priority entrance
sequence for each agent and computes velocity controls in real-time, taking
less than 10 milliseconds even in high-density traffic with over 10,000
vehicles per hour. Compared to fully optimization-based methods, it operates
100 times faster while ensuring fairness, safety, and efficiency. Tested on the
SUMO simulator, our algorithm improves throughput by at least 25%, reduces the
time to reach the goal by at least 70%, and decreases fuel consumption by 50%
compared to auction-based and signaled approaches using traffic lights and stop
signs. GameOpt+ is also unaffected by unbalanced traffic inflows, whereas some
of the other baselines encountered a decrease in performance in unbalanced
traffic inflow environments.
