State Transportation Agency Decision-Making for System Performance: Practitioner’s Playbook (2023) / Chapter Skim
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Pages 53-61
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53 "Plays 1–4" utilize the analytic framework to inform an understanding of the interrelated and interconnected trends and issues that are pressuring the transportation system and improve the ability to integrate that information into the approaches an agency takes to improve system performance. That information is applied at the front end of the system-management process.
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54 State Transportation Agency Decision-Making for System Performance: Practitioner's Playbook Figure 46. The analytic framework can be applied to linking emerging data and analytic capacity to system performance measures.
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Play 5: Emerging Data and Analytic Capacity 55 so their service life can be better predicted (Alhasan et al., forthcoming) The Regional Integrated Transportation Information System (RITIS)
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56 State Transportation Agency Decision-Making for System Performance: Practitioner's Playbook of how different populations were utilizing the network. This awareness enabled the development of mobility optimization and prioritization measures better aligned with and responsive to traveler profiles and transportation mode usage distribution.
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Play 5: Emerging Data and Analytic Capacity 57 time) of the system they operate.
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58 State Transportation Agency Decision-Making for System Performance: Practitioner's Playbook Pilot Three: Resiliency Pilot Three addressed the system objective of resiliency by developing optimization strategies for vehicle-to-infrastructure (V2I) implementation.
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Play 5: Emerging Data and Analytic Capacity 59 Lessons Learned The work conducted for the pilots revealed several key lessons for transportation agencies exploring the use of emerging data sources and analytic capacity. The Value of a Unified Dataset The pilots utilized a unified dataset comprised of existing and emerging data sources that had been prepared for the Atlanta Metro Area.
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60 State Transportation Agency Decision-Making for System Performance: Practitioner's Playbook Data Preparation Regardless of how well data collection is conducted, there are challenges to using cross-functional datasets. A common experience is that this can lead to significant effort in data cataloging, data verification, and data ingestion.
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Play 5: Emerging Data and Analytic Capacity 61 The data source monitoring profile must suit the desired analytics and conform to any constraints in the analytic tool being used. Revisions to topology or coverage should be considered to optimally address any change in the data source monitoring profile parameters -- such as target functions, spatial or temporal requirements, or operational procedures -- or if network constraint patterns emerge and an agency initiates a course(s)
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