Evaluating data collection measurements

Reversing vehicles are not taken into account.

By default, the data for all vehicle classes is entered together. You can also show the data for certain vehicle classes separately in the evaluation (Configuring evaluations of the result attributes for lists).

Saving results of data collection measurements

You can save the following data and data formats:

Output

ASCII file

MDB table

Attribute file from attribute list

Aggregated data

-

-

Raw data

*.mer

-

-

Result of evaluation of Data collection measurements

The results list Data Collection Results contains the following attributes:

Result attribute Long name

Short name

Description

Simulation run SimRun

Number of simulation run

Time interval TimeInt Duration of the evaluation intervals in which the data is aggregated
Data Collection Measurement DataCollMeas Number of data collection measurement and name of its data collection point

The following result attributes refer to all vehicles in the network that have been recorded during data collection measurement:

Acceleration Acceleration Average acceleration of the vehicles
Distance Dist Distance covered [m] by the vehicles
Length Length Average length [m] of the vehicles
Vehicles Vehs Total number of vehicles
Persons Pers Total number of occupants of the vehicles
Queue delay QueueDelay Total time in [s] that the vehicles have spent so far stuck in a queue, if the queue conditions are met.
Speed Speed Average speed of the vehicle at the data collection point
Speed (arithmetic mean) SpeedAvgArith Arithmetic mean of speed of the vehicles
Speed (harmonic mean) SpeedAvgHarm Harmonic mean of speed of the vehicles
Occupancy rate OccupRate Share of time [0% bis 100%] in the last simulation step, during which at least one data collection point of this data collection measurement was busy.

The *.mer file contains the following data:

Value

Description

t(enter)

Time at which the front end of the vehicle has passed the data collection point.

Time - 1.00: The front end has already passed the section in a previous time step.

t(leave)

Time at which the rear end of the vehicle has passed the data collection point.

Time -1.00: The rear end of the vehicle has not yet reached the data collection point.

VehNo

Internal number of the vehicle

Type

Vehicle type, for example, 100 = car

Line

PT line, only for PT vehicle types, otherwise = 0

v[km/h]

Speed

b[m/s²]

Acceleration

Occ

Occupancy: Time in s that the vehicle has spent above data collection point in this simulation second

Pers

Number of persons in the vehicle

tQueue

Queue time: Total time in [s] which the vehicles have spent so far stuck in a queue, if the queue conditions are met.

VehLength[m]

Vehicle length in [m]

Example: file *.mer

Measurement protocol (raw data)
 
File:    C:\Users\Public\Documents\PTV Vision\PTV Vissim 2022\Examples Demo\lux3_10.inpx
Comment:  Luxembourg, SC 3-10
Date:    03.01.2023 12:23:33
PTV Vissim 2022.00-00* [238187]
        
Data collection point  3131: Link    46 Lane 1 at  179.168.
Data Collection Point  3151: Link 10065 Lane 1 at    2.568 m.
Data Collection Point  3211: Link    42 Lane 1 at  197.590 m.
Data Collection Point  3231: Link    49 Lane 1 at  197.617 m.
Data Collection Point  3311: Link 10063 Lane 1 at    6.208 m.
Data Collection Point  3321: Link 10062 Lane 1 at    5.514 m.
Data Collection Point  3351: Link 10064 Lane 1 at    3.096 m.
…
 
Measurement; t(enter); t(leave); VehNo; Type; Line; v[km/h]; a[m/s2]; Occ; Pers; tQueue; VehLength[m];
  6311    16.95    -1.00    10    17   0    7.9    -2.83   0.05   1 0.0    4.55
  6311    -1.00    17.60    10    17   0    6.0    -2.83   0.00   1 0.0    4.55
  6312    19.90    -1.00    15    11   0    5.3    -2.68   0.10   1 0.0    4.11
  6321    20.03    -1.00    14    14   0   13.5    -0.99   0.07   1 0.0    4.11
  6321    -1.00    20.34    14    14   0   13.2    -0.99   0.04   1 0.0    4.11
  6312    -1.00    20.94    15    11   0    2.6    -2.68   0.04   1 0.0    4.11
…