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.

While the situation where all vehicles for overtaking trajectory generation with real time operation on the road are fully autonomous remains a long term capability but often lack safety guarantees. While these goal, it is likely that most initial CAVs introduced will methods have not been applied to incoming lane overtaking, need to operate side by side with human driven vehicles our previous work [10] explored the use of a mixed-integer (HDVs) resulting in a mixed traffic situation. This results model predictive control (MI-MPC) strategy for bidirectional in many additional challenges brought about by the lack overtaking for a single autonomous agent. of cooperation and unpredictability of human drivers [1]. The use of communication among CAVs in order to Overtaking on the incoming lane is a scenario where these improve the overall efficiency and safety of many complex issues play a significant role due to the increased possibility traffic conditions such as highway merging [11] and traffic of head on collisions.