Empirical Study on the Key Drivers Affecting Durations for Right-of-Way Acquisition on Highway Projects

Sohn, Taehong; Azambuja, Marcelo; O’Connor, James T.; O’Brien, William J.

doi:10.1061/(asce)me.1943-5479.0000264

Cited by 6 publications

(11 citation statements)

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“…It is also found that widening projects generally take relatively longer durations compared to other project types. The type of work impacts the ROW acquisition durations because the type of parcels to acquire would depend on it (Sohn et al, 2014). In a previous study conducted by Persad et al (1995), widening project was found to be a complex project type that requires one of the most engineering man hours in the preconstruction phase.…”

Section: Discussionmentioning

confidence: 99%

“…(1) disputes on compensation and pricing; (2) title curative problems; (3) third-party delays; (4) parcel characteristics, and owner-initiated and improvement delays; (5) environmental sensitivity and expert witness delays; (6) legal activity causing delays; (7) utility delays; (8) design change or revision delays; and (9) terrain features dispute causing delays. Sohn et al (2014) conducted a workshop with ROW practitioners to identify key factors that could affect the ROW acquisition durations and could be utilized in estimating the durations for future projects. The factors found were: (1) project type, (2) district annual ROW budget, (3) available funds to the project, (4) funding limitation, (5) level of political pressure, (6) need for relocation assistance, (7) availability of replacement housing facilities and (8) likelihood of title curative action.…”

Section: Literature Reviewmentioning

confidence: 99%

“…(1) Number of Parcels: Sohn et al (2014) and Aleithawe et al (2012) found how the number of parcels is a significant factor in estimating the acquisition timeline from examining historical project details.…”

Section: Data Descriptionmentioning

confidence: 99%

“…The type of work (e.g. widening, bridge and intersection improvement) is an important feature with potential to determine the acquisition timeline (Sohn et al, 2014) because the type of parcel to acquire would differ. The geographic locations, such as urban and rural, are another feature to consider because different locations create different challenges in completing the acquisition process (Jeong et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…The type of work (e.g. widening, bridge and intersection improvement) is an important feature with potential to determine the acquisition timeline (Sohn et al. , 2014) because the type of parcel to acquire would differ.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Forecasting Right-of-Way (ROW) acquisition timeline of transportation projects

Zeng,

Chung,

Ashuri

2023

BEPAM

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PurposeCompleting Right-of-Way (ROW) acquisition process on schedule is critical to avoid delays and cost overruns on transportation projects. However, transportation agencies face challenges in accurately forecasting ROW acquisition timelines in the early stage of projects due to complex nature of acquisition process and limited design information. There is a need of improving accuracy of estimating ROW acquisition duration during the early phase of project development and quantitatively identifying risk factors affecting the duration.Design/methodology/approachThe quantitative research methodology used to develop the forecasting model includes an ensemble algorithm based on decision tree and adaptive boosting techniques. A dataset of Georgia Department of Transportation projects held from 2010 to 2019 is utilized to demonstrate building the forecasting model. Furthermore, sensitivity analysis is performed to identify critical drivers of ROW acquisition durations.FindingsThe forecasting model developed in this research achieves a high accuracy to predict ROW durations by explaining 74% of the variance in ROW acquisition durations using project features, which is outperforming single regression tree, multiple linear regression and support vector machine. Moreover, number of parcels, average cost estimation per parcel, length of projects, number of condemnations, number of relocations and type of work are found to be influential factors as drivers of ROW acquisition duration.Originality/value This research contributes to the state of knowledge in estimating ROW acquisition timeline through (1) developing a novel machine learning model to accurately estimate ROW acquisition timelines, and (2) identifying drivers (i.e. risk factors) of ROW acquisition durations. The findings of this research will provide transportation agencies with insights on how to improve practices in scheduling ROW acquisition process.

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Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%