An Integrated Pipeline Architecture for Modeling Urban Land Use, Travel Demand, and Traffic Assignment

Waddell, Paul G.; Boeing, Geoff; Gardner, M. W.; Porter, Emily

doi:10.48550/arxiv.1802.09335

Cited by 2 publications

(6 citation statements)

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“…The objective of this study is to perform a regionalscale microsimulation of vehicular traffic of the Bay Area, incorporating individual trips on a typical workday morning. The microsimulator builds on the initial implementation by [2], [22]. In this section, the network generation, demand creation, routing, and simulation architectures are described in detail.…”

Section: Componentsmentioning

confidence: 99%

“…The network contains all roads in the Bay Area, from large primary roads to tertiary streets. The OSM network currently considers points representing curves or bends in edges to be nodes, which is not topologically accurate for network analysis [22], [23]. Hence, the network topology is simplified by retaining only those nodes at intersections and dead-ends.…”

Section: A Street Networkmentioning

confidence: 99%

“…After mapping nodes to their TAZs, each origin and destination is randomly assigned to one of the TAZ nodes. This process differs from [22], where each origin or destination is assigned to the centroid of the respective TAZ. Given that microsimulation models individual vehicle behavior, adding diversity of nodes to the simulation, rather than using the same node for every trip that contains the same origin or destination TAZ, is expected to mimic travel patterns more realistically.…”

Section: B Demandmentioning

confidence: 99%

“…where v is the current acceleration of the vehicle, a is the maximum possible acceleration of the vehicle, v is the current speed of the vehicle, v o is the speed limit of the edge, δ is TABLE I: IDM parameter ranges, derived from [26] the acceleration exponent, s is the gap between the vehicle and the leading vehicle, s 0 is the minimum spacing allowed between vehicles when they are at a standstill, T is the desired time headway, and b is the braking deceleration of the vehicle [2], [22]. The exact position of each vehicle at the current timestep is computed using this calculated acceleration value v.…”

Section: Microsimulationmentioning

confidence: 99%

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Microsimulation Analysis for Network Traffic Assignment (MANTA) at Metropolitan-Scale for Agile Transportation Planning

Yedavalli¹,

Kumar²,

Waddell³

2020

Preprint

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Abrupt changes in the environment, such as increasingly frequent and intense weather events due to climate change or the extreme disruption caused by the coronavirus pandemic, have triggered massive and precipitous changes in human mobility. The ability to quickly predict traffic patterns in different scenarios has become more urgent to support short-term operations and long-term transportation planning, emergency management, and resource allocation. Urban traffic exhibits a high spatial correlation in which links adjacent to a congested link are likely to become congested due to spillback effects. The spillback behavior requires modeling the entire metropolitan area to recognize all of the upstream and downstream effects from intentional or unintentional perturbations to the network. However, there is a well-known trade-off between increasing the level of detail of a model and decreasing computational performance. To achieve traffic microsimulation levels of detail, current implementations often compromise by simulating small spatial scales, such as intersections or corridors that ignore larger network dependencies. These simulators also either require access to expensive high performance computing systems or have computation times on the order of days or weeks that discourage productive research and real-time planning. This paper addresses these performance shortcomings by introducing a new platform, MANTA (Microsimulation Analysis for Network Traffic Assignment), for traffic microsimulation at the metropolitan-scale. MANTA employs a highly parallelized GPU implementation that is fast enough to run simulations on large-scale demand and networks within a few minutes. We test our platform to simulate the entire Bay Area metropolitan region over the course of the morning using half-second time steps. The runtime for the nine-county Bay Area simulation is just over four minutes, not including routing and initialization. This computational performance significantly improves the state of the art in large-scale traffic microsimulation, and offers new capacity for analyzing the detailed travel patterns and travel choices of individuals for infrastructure planning and emergency management.

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Section: Componentsmentioning

confidence: 99%

Section: A Street Networkmentioning

confidence: 99%

Section: B Demandmentioning

confidence: 99%

Section: Microsimulationmentioning

confidence: 99%

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Microsimulation Analysis for Network Traffic Assignment (MANTA) at Metropolitan-Scale for Agile Transportation Planning

Yedavalli¹,

Kumar²,

Waddell³

2020

Preprint

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“…Moreover, PS2 integrates three venues of modeling: macroeconomics ABM [9], land-use change [12] and transport and urban planning [13]. In fact, we have no knowledge of any other model that (a) is open source, (b) uses intraurban official data for a number of metropolitan regions, (c) applies explicit spatial rules for three different markets, (d) includes a tax system at the municipal level (e) is based on firms and households decision-modeling, and (f) whose policy experiment is implemented from endogenous demand and offer processes.…”

Section: Introductionmentioning

confidence: 99%

PolicySpace2: modeling markets and endogenous public policies

Furtado¹

2021

Preprint

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Policymakers decide on alternative policies facing restricted budgets and uncertain, ever-changing future. Designing housing policies is further difficult giving the heterogeneous characteristics of properties themselves and the intricacy of housing markets and the spatial context of cities. We propose PolicySpace2 (PS2) as an adapted and extended version of the open source PolicySpace agent-based model. PS2 is a computer simulation that relies on empirically detailed spatial data to model real estate, along with labor, credit and goods and services markets. Interaction among workers, firms, a bank, households and municipalities follow the literature benchmarks to integrate economic, spatial and transport literature. PS2 is applied to a comparison among three competing municipal housing policies aimed at alleviating poverty: (a) property acquisition and distribution, (b) rental vouchers and (c) monetary aid. Within the model context, the monetary aid, that is, a smaller amounts of help for a larger number of households, makes the economy perform better in terms of production, consumption, reduction of inequality and maintenance of financial duties. PS2 as such is also a framework that may be further adapted to a number of related research questions.

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An Integrated Pipeline Architecture for Modeling Urban Land Use, Travel Demand, and Traffic Assignment

Cited by 2 publications

References 0 publications

Microsimulation Analysis for Network Traffic Assignment (MANTA) at Metropolitan-Scale for Agile Transportation Planning

Microsimulation Analysis for Network Traffic Assignment (MANTA) at Metropolitan-Scale for Agile Transportation Planning

PolicySpace2: modeling markets and endogenous public policies

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