Abstract

The unsustainable way of burying utilities has resulted in difficulties in regular maintenance, which is one of the main reasons for the poor state of these utilities. Accessing these utilities through open-cut excavation leads to detrimental socioeconomic and environmental impacts, which can be quantified as social costs incurred during the asset's lifecycle. To reduce social costs, synchronized interventions of collocated assets (e.g., water and sewer pipes and pavements) can minimize excavations in a specific street segment over time for preventive maintenance. Few studies have prioritized street segments based on the socioeconomic impacts of intervention activities, such as street closures. Additionally, synchronized interventions are not a long-term solution as they do not eliminate the need for future excavations.
A more sustainable solution is the Multi-Purpose Utility Tunnels (MUTs), as they integrate all underground utilities in one accessible tunnel. MUTs eliminate the need for future excavations and their associated costs, as well as the resulting socioeconomic impacts. Meanwhile, both the synchronized interventions and the MUT are not generally practiced. Although several MUTs have been implemented in different parts of the world, their locations have either been politically influenced or selected to preserve heritage sites. In some cases, MUTs are built to take advantage of some opportunities, such as a newly developed area. Nevertheless, choosing the street segments for MUTs is affected by several criteria with different spatial characteristics. Combining these characteristics and managing their trade-offs determine the ranking of alternative MUT locations. Therefore, a systematic approach for MUT location selection that is based on the spatial characteristics of the criteria, as well as the lifecycle costs of each alternative is needed. Furthermore, the social cost of maintaining, repairing, or replacing utility assets during synchronized interventions or MUT implementation can be reduced by predicting the closure of street segments based on the need for intervention determined by asset conditions.
The main goal of this research is to develop a framework for MUT location selection considering social costs. To achieve this goal, the specific objectives are: (1) Establishing the relationships between intervention activities and their socioeconomic impacts; (2) Classifying the conditions of different spatially collocated underground municipal assets (i.e., pavements, water and sewer pipes) within a segment; (3) Determining street closures based on the synchronized or unsynchronized interventions at the segment level; (4) Developing a multi-criteria decision-making model (MCDM) for MUT location selection; and (5) Optimizing the location selection of MUTs considering agency and social lifecycle costs.
The main contributions developed in the context of this thesis are: (1) Developing a geospatial visual analytics model that supports the understanding of the socioeconomic impacts of unsynchronized intervention practices; (2) Developing an ML method for systematic condition classification of different spatially collocated underground municipal assets (i.e., pavements, water and sewer pipes) within a segment. To the best of our knowledge, there is no existing research about determining street closures based on the combined conditions of spatially collocated municipal infrastructure assets at the segment level; (3) Applying a heuristic approach for determining street closures based on the synchronized or unsynchronized interventions at the segment level induced by combining the interventions of individual assets within each segment; (4) Defining a comprehensive MCDM model that identifies and quantifies the criteria that influence the MUT location selection using subjective and objective methods; (5) Defining a multi-objective optimization model that was able to identify the potential MUT locations and a multi-year plan for MUT implementation that offers lifecycle savings; (6) Developing a systematic method for comparing the results of the MUT optimization with those of the synchronized interventions. This comparison is based on the agency and social LCCs, and the network deterioration generated by the MUTs and synchronized method of utility interventions at the network and segment levels; and (7) Developing three regression models for capturing the social cost of both alternatives at the network and segment levels.