SPaT data¶
Section author: Zhen Yang <zhenyang@umich.edu>
Overview¶
The Signal Phasing and Timing (SPaT) module is used to load and process the SPaT data. The SPaT data is very important for the trajectory data at signalized intersections. By matching the SPaT data with the trajectory data, the traffic state and the vehicle behaviours can be analyzed. The SPaT information of each movement at each signalized intersection is stored in a Pandas data framework, and can be visualized and queried depending on the research needs.
Structure¶
The MTLDP structures SPaT data in a three-level framework:
In this UML diagram, each block in the figure represents a class, and the links show the aggregation relationship. The
SPaTCollection class includes a dictionary of NodeSPaT objects. A major class function in the SPaTCollection class is
add_node_spat(), which append the dictionary with a given NodeSPaT object.
It also includes the function of load_spat_csv(), which
loads predefined standard csv files. The format of the standard csv file is introduced in the next section. The function
of output_spat_csv() is the inverse function of load_spat_csv(), which output the SPaT data from the SPaTCollection to a
standard csv file. The NodeSPaT class includes a dictionary of MovementSPaT objects. It also includes the function of
add_movement_signal_state(), which append the dictionary with a given MovementSPaT object.
The MovementSPaT class includes the Pandas dataframe that stores the SPaT data of each movement in a tabular fashion.
This is also the fundamental class that includes several key functions. Given a specific timestamp, get_signal_state()
can output the corresponding signal state. Given a sorted list of timestamp, get_signal_states() can output the
corresponding list of signal state. In the traffic state estimation or traffic signal optimization, it is also important
to know the corresponding start of the green time for a given timestamp, so get_green_start() function is designed
accordingly.
Standard csv file format for SPaT data¶
The figure below shows the standard csv file format for SPaT data. Raw SPaT data needs to be first converted into this
format, since the SPaT data in this format can be fast retrieved by Pandas dataframe in the SPaT data structure of this
project. The standard csv file includes the entries of node_id, movement_id, start_time, end_time, duration, and
signal_state. start_time and end_time represents the start time and the end time of the phase associated
with the movement of movement_id at the node of node_id. duration is equal to end_time - start_time.
signal_state should be a string, chosen from “Red”, “Yellow” or “Green”.
The SPaT data should be aggregated by node_id and movement_id, so the csv table can be easily partitioned
to sub tables. For the SPaT data of each movement, they should be sorted by the start_time. Examples of generating such
standard csv file format can be found in mtldp.adapters.aacvte_spat.
