First order multi-lane traffic flow model – an incentive based macroscopic model to represent lane change dynamics
| Autor: | Victor L. Knoop, Hari Hara Sharan Nagalur Subraveti, Bart van Arem |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Mathematical optimization
Computer science incentives Macroscopic traffic flow model ComputerApplications_COMPUTERSINOTHERSYSTEMS Transportation Regression analysis ComputerSystemsOrganization_PROCESSORARCHITECTURES cell transmission model Reduction (complexity) Incentive Order (exchange) Modeling and Simulation Lane-level Linear regression macroscopic traffic flow model State (computer science) lane flow distribution Software Cell Transmission Model |
| Zdroj: | Transportmetrica B: Transport Dynamics, 7(1) |
| ISSN: | 2168-0566 |
| Popis: | Unbalanced lane usage on motorways might lead to the reduction in capacityof the motorway. Lane-level traffic management present new opportunitiesto balance the lane-flow distribution and help reduce congestion.In order to come up with efficient traffic management strategies on alane-level, there is a need for accurate lane-specific traffic state estimationmodels. This paper presents a first-order lane-level traffic flow model. Theproposed model differs from the existing models in the following areas: (i)incentive-based motivation for lane changes and consideration of downstreamconditions (ii) transfer of lateral flows among cells. The model istested against real-world data. It is observed that the model is able to capturethe lane-level dynamics in terms of the lane flow distribution. Themodel results are compared to a linear regression model and results showthat the developed model performs better than the regression model onthe test sections. |
| Databáze: | OpenAIRE |
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