xivDesign, Optimization and Simulation of Tradable Mobility Credits
BackgroundRoad traffic and congestion is a critical problem affecting urban mobility worldwide, and its severity continues to increase, causing significant costs at the individual, environmental, economic, and societal level (Schrank et al., 2015; Eurostat andEU Commission, 2018). Continuing this trend, by 2030 greenhouse gas emissions from the transport sector may account for 40% of Denmark's emissions (Dansk Industri, 2019). According to United Nations Department of Economic and Social Affairs ( 2019), the proportion of the world's population residing in urban areas is expected to increase from 55% to 68% by 2050, which will contribute more to the congestion problem.Efforts to alleviate road congestion have been explored from both supply and demand perspectives. On the supply side, the standard response to congestion is to increase road capacity, which is often constrained by finance, space, and environment, and most importantly, known sometimes to be counterproductive (Johnston et al., 1995). On the demand side, reducing demand generation through city planning and urban design can greatly mitigate future congestion while having limited impacts on shortterm changes. Thus, viable transportation system management (Kuhn et al., 2017), including traffic man agement through intelligent transportation systems (e.g., automation and electrification, signal control) and demand management (e.g., congestion pricing), has received signifi cant attention.