1372297 - Spatial Multi-Objective Optimization of Transportation-Related Sustainability Objectives in Smart Cities

A smart city seeks to leverage data from information, communication, and sensor technologies (ICSTs) for achieving transportation sustainability objectives related to enhancing mobility, accessibility, safety, and equity. However, city decision-makers usually consider these objectives in isolation, ignoring their interrelationships. Consequently, solutions that the decision-makers deploy to achieve these objectives, however well-intended, typically do not generate mutually optimal benefits across these objectives. Additionally, the decision-makers typically focus on achieving community-level (i.e., system-level) sustainability objectives which may not achieve sustainability at the zone level resulting in inequities across zones within the city. To address these problems, this study develops a mathematical model by taking a spatial multi-objective approach to optimize the sustainability objectives simultaneously by considering the complex interrelationships between them in a smart city environment. In the spatial multi-objective optimization model, we seek to maximize community-level mobility, accessibility, and safety while equitable zone-level sustainability is achieved through spatial optimization across each sustainability objective by minimizing the gaps between the corresponding objective values for each zone pair across all zones. Thereby, our model overcomes the limitations of addressing only community-level sustainability objectives that cannot seamlessly handle zone-level equity issues. The solution obtained from the optimization model is in terms of the traffic flow pattern and mode split, transportation access needs for different zones, transportation supply gaps of mobility service providers, and safety enhancement needs. The City of Peachtree Corners (PTC), GA, a smart city serving as a living lab in this study, is used as an example to implement the developed spatial multi-objective optimization model. The data collected from ICSTs at PTC is used to assess the current state of the city in terms of the aforementioned sustainability objectives and they are benchmarked against the optimal values of these objectives obtained through the proposed model. The proposed model has the potential to guide city decision-makers while deploying different solution mechanisms to holistically move their city closer to the desired transportation-related sustainability objectives.