Optimizing Road Networks for Automated Vehicles with Dedicated Links, Dedicated Lanes, and Mixed-Traffic Subnetworks
This study focuses on network configurations to accommodate automated vehicles (AVs) on road networks during the transition period to full automation. The literature suggests that dedicated infrastructure for AVs and enhanced infrastructure for mixed traffic (i.e., AVs on the same lanes with convent...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/8853583 |
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| _version_ | 1832550812854779904 |
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| author | Bahman Madadi Rob Van Nes Maaike Snelder Bart Van Arem |
| author_facet | Bahman Madadi Rob Van Nes Maaike Snelder Bart Van Arem |
| author_sort | Bahman Madadi |
| collection | DOAJ |
| description | This study focuses on network configurations to accommodate automated vehicles (AVs) on road networks during the transition period to full automation. The literature suggests that dedicated infrastructure for AVs and enhanced infrastructure for mixed traffic (i.e., AVs on the same lanes with conventional vehicles) are the main alternatives so far. We utilize both alternatives and propose a unified mathematical framework for optimizing road networks for AVs by simultaneous deployment of AV-ready subnetworks for mixed traffic, dedicated AV links, and dedicated AV lanes. We model the problem as a bilevel network design problem where the upper level represents road infrastructure adjustment decisions to deploy these concepts and the lower level includes a network equilibrium model representing the flows as a result of the travelers’ response to new network topologies. An efficient heuristic solution method is introduced to solve the formulated problem and find coherent network topologies. Applicability of the model on real road networks is demonstrated using a large-scale case study of the Amsterdam metropolitan region. Our results indicate that for low AV market penetration rates (MPRs), AV-ready subnetworks, which accommodate AVs in mixed traffic, are the most efficient configuration. However, after 30% MPR, dedicated AV lanes prove to be more beneficial. Additionally, road types can dictate the viable deployment plan for certain parts of road networks. These insights can be used to guide planners in developing their strategies regarding road network infrastructure during the transition period to full automation. |
| format | Article |
| id | doaj-art-0d983e537e244d0eb49d5aadadbf7f99 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-0d983e537e244d0eb49d5aadadbf7f992025-02-03T06:05:44ZengWileyJournal of Advanced Transportation0197-67292042-31952021-01-01202110.1155/2021/88535838853583Optimizing Road Networks for Automated Vehicles with Dedicated Links, Dedicated Lanes, and Mixed-Traffic SubnetworksBahman Madadi0Rob Van Nes1Maaike Snelder2Bart Van Arem3Delft University of Technology, Civil Engineering Faculty, Transport & Planning Department, 2628 CN Delft, NetherlandsDelft University of Technology, Civil Engineering Faculty, Transport & Planning Department, 2628 CN Delft, NetherlandsDelft University of Technology, Civil Engineering Faculty, Transport & Planning Department, 2628 CN Delft, NetherlandsDelft University of Technology, Civil Engineering Faculty, Transport & Planning Department, 2628 CN Delft, NetherlandsThis study focuses on network configurations to accommodate automated vehicles (AVs) on road networks during the transition period to full automation. The literature suggests that dedicated infrastructure for AVs and enhanced infrastructure for mixed traffic (i.e., AVs on the same lanes with conventional vehicles) are the main alternatives so far. We utilize both alternatives and propose a unified mathematical framework for optimizing road networks for AVs by simultaneous deployment of AV-ready subnetworks for mixed traffic, dedicated AV links, and dedicated AV lanes. We model the problem as a bilevel network design problem where the upper level represents road infrastructure adjustment decisions to deploy these concepts and the lower level includes a network equilibrium model representing the flows as a result of the travelers’ response to new network topologies. An efficient heuristic solution method is introduced to solve the formulated problem and find coherent network topologies. Applicability of the model on real road networks is demonstrated using a large-scale case study of the Amsterdam metropolitan region. Our results indicate that for low AV market penetration rates (MPRs), AV-ready subnetworks, which accommodate AVs in mixed traffic, are the most efficient configuration. However, after 30% MPR, dedicated AV lanes prove to be more beneficial. Additionally, road types can dictate the viable deployment plan for certain parts of road networks. These insights can be used to guide planners in developing their strategies regarding road network infrastructure during the transition period to full automation.http://dx.doi.org/10.1155/2021/8853583 |
| spellingShingle | Bahman Madadi Rob Van Nes Maaike Snelder Bart Van Arem Optimizing Road Networks for Automated Vehicles with Dedicated Links, Dedicated Lanes, and Mixed-Traffic Subnetworks Journal of Advanced Transportation |
| title | Optimizing Road Networks for Automated Vehicles with Dedicated Links, Dedicated Lanes, and Mixed-Traffic Subnetworks |
| title_full | Optimizing Road Networks for Automated Vehicles with Dedicated Links, Dedicated Lanes, and Mixed-Traffic Subnetworks |
| title_fullStr | Optimizing Road Networks for Automated Vehicles with Dedicated Links, Dedicated Lanes, and Mixed-Traffic Subnetworks |
| title_full_unstemmed | Optimizing Road Networks for Automated Vehicles with Dedicated Links, Dedicated Lanes, and Mixed-Traffic Subnetworks |
| title_short | Optimizing Road Networks for Automated Vehicles with Dedicated Links, Dedicated Lanes, and Mixed-Traffic Subnetworks |
| title_sort | optimizing road networks for automated vehicles with dedicated links dedicated lanes and mixed traffic subnetworks |
| url | http://dx.doi.org/10.1155/2021/8853583 |
| work_keys_str_mv | AT bahmanmadadi optimizingroadnetworksforautomatedvehicleswithdedicatedlinksdedicatedlanesandmixedtrafficsubnetworks AT robvannes optimizingroadnetworksforautomatedvehicleswithdedicatedlinksdedicatedlanesandmixedtrafficsubnetworks AT maaikesnelder optimizingroadnetworksforautomatedvehicleswithdedicatedlinksdedicatedlanesandmixedtrafficsubnetworks AT bartvanarem optimizingroadnetworksforautomatedvehicleswithdedicatedlinksdedicatedlanesandmixedtrafficsubnetworks |