Advanced automation and information systems are shaping the future of transportation. They improve safety and energy efficiency of personal transport by enabling advanced approaches such as ecodriving control systems. Such systems are partly already in place and reduce the environmental footprint of vehicles, but they have several downsides. They are usually not aware of pollutant emissions, only applicable in specific driving situations such as highway or straight roads, and can therefore not consider the passengers? comfort, which is linked to lateral acceleration. This thesis contributes to field of ecodriving control by developing approaches that are able to address this downsides. The presented methods are able to deal with curvy roads, combining road grade and curvature look ahead to keep the driving comfortable, while also considering pollutant emissions within a unified ecodriving control problem. The formulation and solution of emission aware ecodriving as an optimal control problem is presented. The solution approaches range from dynamic programming based offline methods to nonlinear optimization based online approaches. Their feasibility and potential is shown by means of simulation case studies based on real world test cases, a validated vehicle model, and measured road topologies. Hence, it is shown that emission aware ecodriving is a viable option and that developers of future ecodriving systems should expand their focus from solely energy efficiency towards additional targets.