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NET2CELL

For any given networks that meet the GMNS standard, net2cell helps users automatically build mesoscopic and lane-by-lane cell-based microscopic transportation networks to accommdate different modelling needs.

imgs/framework.png

Development Support:
Ph.D. Student: Jiawei Lu ([email protected]); Dr. Xuesong (Simon) Zhou ([email protected])
School of Sustainable Engineering and the Built Environment, Arizona State University

Installation

pip install net2cell

Prepare macroscopic network

net2cell is compatible with any networks that meet the GMNS standard. Users can use their networks at hand as inputs of net2cell, but converting networks to GMNS format may be needed before feeding them to net2cell. For a quick start, users are recommended to use osm2gmns to quickly get a macroscopic from OpenStreetMap (OSM). osm2gmns helps users easily convert the OSM map data to node and link network files in the GMNS format.

Use net2cell

Get hybrid networks

>>> import net2cell as nc

>>> macro_net = nc.readMacroNet()
>>> nc.generateHybridNets(macro_net)
Arguments of function readMacroNet()
Argument Type Default Comments
cwd string '' current working directory
coordinate_type enum 'll' 'm': meter; 'll': longitude latitude; 'f': feet
geometry_source enum 'l' the file that stores link geometry. 'n': no geometry; 'l': link.csv; 'g': geometry.csv
unit_of_length enum 'm' unit of link length. 'm': meter; 'km': kilometer: 'mi': mile; 'f': feet
segment_unit enum 'm' unit of segment length. 'm': meter; 'km': kilometer: 'mi': mile; 'f': feet
speed_unit enum 'mph' unit of speed. 'mph'; 'kph'
link_types None or list None None: all links will be imported; list: only links with link_type in the provided list will be imported
connector_type None or int None None: no connector; int: link type id of connector
min_link_length float 3.0 meter. links shorter than min_link_length will be reomved during processing
combine bool False remove two-degree nodes, and combine corresponding two adjacent links
width_of_lane float 3.5 meter. positive value

Function readMacroNet() loads and parses the macroscopic network from cwd. Two necessary network files includes node.csv and link.csv. Other optional files includes movement.csv, segment.csv and segment.csv. Users can check the detailed introduction of these files at GMNS Github homepage.

Arguments of function generateHybridNets()
Argument Type Default Comments
macro_net CInitNet    
length_of_cell float 7.0 meter. positive value
auto_connection bool True True: automatically generate movement information for intersections without that; False: do not generate

Function generateHybridNets() build the mesoscopic and microscopic network for the loaded macroscopic network.

Visualization

You can visualize generated networks using NeXTA or QGis.

  • NeXTA
imgs/nexta-show.png

Open networks and synchronized display

imgs/nexta-net.png

Arizona State University, Tempe Campus

Interested readers can check the link for our online transportation modelling visualization platform, in which network data is provided by net2cell.

Next

The potential next step is to manage OD zone structure and in the NeXTA tool and perform traffic assignment and simulation using DTALite for transportation network simulation and analysis.

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