There are economies of scale in the construction of regional wastewater treatment systems. Effluent dischargers have the option of participating in a regional system or constructing separate smaller systems. In order to encourage participation in a regional system so that the economies are realized, the cost allocation method employed must offer economic incentives. The cost allocation problem is viewed in game theoretic terms, and the Shapley value (a game theory solution) is suggested as an allocation method. The method is applied to the Meramec River Basin in Missouri where eight dischargers are identified. The problems of application are discussed and the reactions of the eight dischargers are cited. INTRODUCTION Comprehensive regional wastewater treatment systems can provide economic and environmental benefits to wastewater dischargers, since it may be less expensive to construct and operate a single large treatment facility than to have numerous smaller facilities for the various discharges. Environmental benefits can arise from the increased reliability possible in larger, better funded systems, and the opportunity to move effluents to those discharge points where they will result in minimal adverse impacts.While regional wastewater treatment systems can be shown to offer significant advantages, such systems are often difficult to implement. The first step in the development of such a system is to determine the location and equipment configuration that yields a least cost solution. Oncea regional system is found to be economically efficient, it must then be "sold" to each discharger and a single regional authority must be formed. Such regional authorities require state and local legislative approval. In some cases, a regional system can be formed as an extension of some previously existent adjacent sanitary agency, or alternatively some existing regional governance can be given increased authority. The formation of such authorities is at,political process often tied to other regional issues, The Areawide Wastewater Treatment Program implemented by EPA under Section 208 of the 1972 Amendments to the Federal Water Pollution Control Act is one atteml•t to deal with these situations.Along with the potential cost savings of regional wastewater treatment systems comes the problem of their distribution: how should economic benefits (cost savings) be distributed among all members of a regional system? If one or more dischargers do not receive what they consider to be their 'fair' share of the benefits (i.e., they are overcharged), they may be encouraged to withdraw from the regional system and treat their effluents in a smaller facility. Thus the least cost solution is not attained and a suboptimum solution results that can be altered to the advantage of all dischargers. This paper is addressed to the problem of implementing a cost allocation method that will provide incentives for least

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Predictive Energy Management (PrEM) research is at the forefront of modern transportation's energy consumption reduction efforts. The development of PrEM optimization algorithms has been tailored to selfish vehicle operation and implemented in the form of vehicle dynamics and/or adaptive powertrain control functions. With the progress in vehicle automation, this paper focuses on extending PrEM into the realm of a System of Systems (SoS). The proposed approach uses the shared information among Connected and Automated Vehicles (CAV) and the infrastructure to synthesize a reduced energy speed trajectory at the cohort level within urban environments. Neuroevolution is employed to incorporate a generalized optimum controller, robust to the emergent behaviors typical of multi-agents SoS. The authors demonstrated the use of heuristics and systems engineering processes in abstracting and integrating the resulting neural network within the control architecture, which enables novel added-value features such as green wave pass/fail classification and e-Horizon velocity prediction. The resulting controller is faster than real-time and was validated with a multi-agent simulation environment and on a real-world closed-loop track at the American Center for Mobility (ACM). The GM Bolt and Volt CAV mixed cohort testing at ACM demonstrated energy reductions from 7% to 22% depending on scenarios.