Data-driven travel demand modelling and agent-based traffic simulation in Amsterdam urban area
The goal of this project is the development of a large-scale agent-based traffic simulation system for Amsterdam urban area, validated on sensor data and adjusted for decision support in critical situations and for policy making in sustainable city development, emission control and electric car rese...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Language: | English |
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2018
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| Online Access: | https://hdl.handle.net/10356/89726 http://hdl.handle.net/10220/47118 |
| _version_ | 1811678008162910208 |
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| author | Melnikov, V. R. Krzhizhanovskaya, V. V. Lees, Michael Harold Boukhanovsky, A. V. |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Melnikov, V. R. Krzhizhanovskaya, V. V. Lees, Michael Harold Boukhanovsky, A. V. |
| author_sort | Melnikov, V. R. |
| collection | NTU |
| description | The goal of this project is the development of a large-scale agent-based traffic simulation system for Amsterdam urban area, validated on sensor data and adjusted for decision support in critical situations and for policy making in sustainable city development, emission control and electric car research. In this paper we briefly describe the agent-based simulation workflow and give the details of our data- driven approach for (1) modeling the road network of Amsterdam metropolitan area extended by major national roads, (2) recreating the car owners population distribution from municipality demographic data, (3) modeling the agent activity based on travel survey, and (4) modeling the inflow and outflow boundary conditions based on the traffic sensor data. The models are implemented in scientific Python and MATSim agent-based freeware. Simulation results of 46.5 thousand agents -with travel plans sampled from the model distributions- show that travel demand model is consistent, but should be improved to correspond with sensor data. The next steps in our project are: extensive validation, calibration and testing of large-scale scenarios, including critical events like the major power outage in the Netherlands (doi:10.1016/j.procs.2015.11.039), and modelling emissions and heat islands caused by traffic jams. |
| first_indexed | 2024-10-01T02:46:25Z |
| format | Journal Article |
| id | ntu-10356/89726 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:46:25Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | ntu-10356/897262020-03-07T11:48:55Z Data-driven travel demand modelling and agent-based traffic simulation in Amsterdam urban area Melnikov, V. R. Krzhizhanovskaya, V. V. Lees, Michael Harold Boukhanovsky, A. V. School of Computer Science and Engineering Transportation Systems Agent-based Modelling DRNTU::Engineering::Computer science and engineering The goal of this project is the development of a large-scale agent-based traffic simulation system for Amsterdam urban area, validated on sensor data and adjusted for decision support in critical situations and for policy making in sustainable city development, emission control and electric car research. In this paper we briefly describe the agent-based simulation workflow and give the details of our data- driven approach for (1) modeling the road network of Amsterdam metropolitan area extended by major national roads, (2) recreating the car owners population distribution from municipality demographic data, (3) modeling the agent activity based on travel survey, and (4) modeling the inflow and outflow boundary conditions based on the traffic sensor data. The models are implemented in scientific Python and MATSim agent-based freeware. Simulation results of 46.5 thousand agents -with travel plans sampled from the model distributions- show that travel demand model is consistent, but should be improved to correspond with sensor data. The next steps in our project are: extensive validation, calibration and testing of large-scale scenarios, including critical events like the major power outage in the Netherlands (doi:10.1016/j.procs.2015.11.039), and modelling emissions and heat islands caused by traffic jams. Published version 2018-12-20T04:02:30Z 2019-12-06T17:32:03Z 2018-12-20T04:02:30Z 2019-12-06T17:32:03Z 2016 Journal Article Melnikov, V. R., Krzhizhanovskaya, V. V., Lees, M. H., & Boukhanovsky, A. V. (2016). Data-driven travel demand modelling and agent-based traffic simulation in Amsterdam urban area. Procedia Computer Science, 80, 2030-2041. doi:10.1016/j.procs.2016.05.523 1877-0509 https://hdl.handle.net/10356/89726 http://hdl.handle.net/10220/47118 10.1016/j.procs.2016.05.523 en Procedia Computer Science © 2016 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 12 p. application/pdf |
| spellingShingle | Transportation Systems Agent-based Modelling DRNTU::Engineering::Computer science and engineering Melnikov, V. R. Krzhizhanovskaya, V. V. Lees, Michael Harold Boukhanovsky, A. V. Data-driven travel demand modelling and agent-based traffic simulation in Amsterdam urban area |
| title | Data-driven travel demand modelling and agent-based traffic simulation in Amsterdam urban area |
| title_full | Data-driven travel demand modelling and agent-based traffic simulation in Amsterdam urban area |
| title_fullStr | Data-driven travel demand modelling and agent-based traffic simulation in Amsterdam urban area |
| title_full_unstemmed | Data-driven travel demand modelling and agent-based traffic simulation in Amsterdam urban area |
| title_short | Data-driven travel demand modelling and agent-based traffic simulation in Amsterdam urban area |
| title_sort | data driven travel demand modelling and agent based traffic simulation in amsterdam urban area |
| topic | Transportation Systems Agent-based Modelling DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/89726 http://hdl.handle.net/10220/47118 |
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