Fuzzy Power Heronian function based CoCoSo method for the advantage prioritization of autonomous vehicles in real-time traffic management

One of the key solutions to resolving the traffic congestion problem is the traffic management systems, aiming to increase the efficiency of the road networks so that the traffic flow condition on the road segment is improved. Integration of the advancements in communication and autonomous vehicle technologies might increase the benefits of the existing real-time traffic management systems. Hence, in this study, the advantages of six different real-time traffic management methods, which are dynamic speed limits, lane control systems, variable message signs, ramp metering, traffic diversion, and integrating autonomous vehicles into other traffic management systems, with four main criteria, namely economic, public and political, environmental, and traffic safety, and 13 sub-criteria using fuzzy multi-criteria decision making (MCDM) are prioritized. For this purpose, we propose novel extensions of the combined compromise solution (CoCoSo) methodology, including the logarithmic method and the Power Heronian function. The validation of the results is presented to verify the flexibility of the proposed methodology. Finally, these results of the effect of parameters p and q on decision outcome show that the ranking results were not influenced.