Highway Improvement Project Rankings due to Uncertain Model Inputs: Application of Traditional Transportation and Land Use Models

Duthie, Jennifer; Voruganti, Avinash; Kockelman, Kara M.; Waller, S. Travis

doi:10.1061/(asce)up.1943-5444.0000026

Cited by 9 publications

(4 citation statements)

References 26 publications

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“…Major transportation projects are costly investments, which are aimed at improving the existing conditions. When multiple projects are in consideration, one must carefully prioritise the appropriate project, keeping in mind the budget constraints and the long-term project impacts [75]. The ultimate purpose of estimating OD matrices (and transportation planning models in general) for any network is to evaluate different transportation scenarios or/and infrastructure design projects [3,76].…”

Section: Validation Using the Project Selection Methodsmentioning

confidence: 99%

Rapidex: A Novel Tool to Estimate Origin–Destination Trips Using Pervasive Traffic Data

et al. 2021

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A traffic assignment model is a critical tool for developing future transport systems, road policies, and evaluating future network upgrades. However, the development of the network and demand data is often highly intensive, which limits the number of cases where some form of the models are available on a global basis. These problems include licensing restrictions, bureaucracy, privacy, data availability, data quality, costs, transparency, and transferability. This paper introduces Rapidex, a novel origin–destination (OD) demand estimation and visualisation tool. Firstly, Rapidex enables the user to download and visualise road networks for any city using a capacity-based modification of OpenStreetMap. Secondly, the tool creates traffic analysis zones and centroids, as per the user-specified inputs. Next, it enables the fetching of travel time data from pervasive traffic data providers, such as TomTom and Google. With Rapidex, we tailor the genetic-algorithm (GA)-based metaheuristic approach to derive the OD demand pattern. The tool produces critical outputs such as link volumes, link travel times, OD travel times, average trip length and duration, and congestion level, which can also be used for validation. Finally, Rapidex enables the user to perform scenario evaluation, where changes to the network and/or demand data can be made and the subsequent impacts on performance metrics can be identified. In this article, we demonstrate the applicability of Rapidex on the network of Sydney, which has 15,646 directional links, 8708 nodes, and 178 zones. Further, the model was validated using the Household Travel Survey data of Sydney using the aggregated metrics and a novel project selection method. We observed that 88% of the time, the “estimated” and “observed” OD matrices identified the same project (i.e., the rapid process estimated the more intensive traditional approach in 88% of cases). This tool would help practitioners in rapid decision making for strategic long-term planning. Further, the tool would provide an opportunity for developing countries to better manage traffic congestion, as cities in these countries are prone to severe congestion and rapid urbanisation while often lacking the traditional models entirely.

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Section: Validation Using the Project Selection Methodsmentioning

confidence: 99%

Rapidex: A Novel Tool to Estimate Origin–Destination Trips Using Pervasive Traffic Data

et al. 2021

Self Cite

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“…While little research has examined the impact of considering uncertainty in the road network design problem, this is not the first. Duthie et al (2010) assigned probability distributions to baseline employment and household regional control totals, and pairs of road improvements to find the one that worked best in terms of future traffic on average. Lam and Tam (1998) used Monte Carlo simulation methods to study the impact of uncertainty in traffic and revenue forecasts for road investment projects.…”

Section: Introductionmentioning

confidence: 99%

Comparing Delay Minimization and Emissions Minimization in the Network Design Problem

Ferguson¹,

Duthie

Waller

2012

Computer aided Civil Eng

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Traditionally, transportation road networks are designed for minimal congestion. Unfortunately, such approaches do not guarantee minimal vehicle emissions. To fill this apparent gap in network design research, an emissions network design problem and solution method is proposed in this article for the purposes of comparing to the traditional network design results. Three air pollutants are considered on two road networks. The model is formulated as a bi‐level optimization problem and a solution is approximated using a genetic algorithm. The influence of demand uncertainty is also incorporated into the model. Designing for minimal congestion tends to increase emissions of criteria air pollutants. However, not adding capacity to a road network also increases emissions of pollutants. Therefore, an optimization problem and solution method, such as the emissions network design problem and solution method presented here, is useful for identifying capacity additions that reduce vehicle emissions. It is also useful for understanding the tradeoffs between designing a network for minimal congestion versus minimal vehicle emissions.

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“…Wegener (2013) Franklin et al, 2002;Duthie et al, 2010). It is likely that sensitivity tests using scenarios increase both the scientific value of the modeling process and the understanding of the modeling process by the end user/ practitioner.…”

Section: How Reliable Are Luti Models? Obstacles In Terms Of Calibratmentioning

confidence: 99%

Making land use – Transport models operational tools for planning: From a top-down to an end-user approach

Saujot¹,

Lapparent²,

Arnaud³

et al. 2016

Transport Policy

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Land Use and Transport Integrated models (LUTIs) are promising approaches for urban planning. There is large literature describing their technical architectures or using them in various scientific contexts. Yet little attention has been paid to expectations of practitioners (planners) and to the operational use of such models. The gap between lab application and operational use for planning practice is still to be filled. We shed light on what would make them definitely accepted and more used by planners to evaluate a range of urban and transport policies. In addition to literature review and our own experience dealing with urban planning agencies, we have interviewed different types of end users in France to identify their motivations and barriers to use LUTI models. The results show demand for a far more bottom-up oriented approach: the models should consider objectives and general needs of end users to live up to their expectations. Only a closer collaboration between modelers and end users, and more efforts to integrate modeling into urban planning, will make LUTIs considered as relevant approaches. Key words: Land Use and Transport Integrated models; Planning support system, Planning practice Highlights: A gap between theory and practice has to be filled for LUTI modeling. This effort to make LUTI operational tools is more critical than technical improvements. Academics should build up on more bottom-up approaches, based on end-users expectations and resources. Calibration and validation procedures should be harmonized, improved and adapted to specific LUTI use.1

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Highway Improvement Project Rankings due to Uncertain Model Inputs: Application of Traditional Transportation and Land Use Models

Cited by 9 publications

References 26 publications

Rapidex: A Novel Tool to Estimate Origin–Destination Trips Using Pervasive Traffic Data

Rapidex: A Novel Tool to Estimate Origin–Destination Trips Using Pervasive Traffic Data

Comparing Delay Minimization and Emissions Minimization in the Network Design Problem

Making land use – Transport models operational tools for planning: From a top-down to an end-user approach

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