Preamble What is new in PTV Vissim/Viswalk 11 © PTV AG 3 Content Preamble 4 1 Visualization 5 1.1 2D Labels for Vehicles 5 1.2 3D Information Signs 5. VISSIM 5.30 -05 User Manual (PTV, 2011) 2. Traffic Modelling Guidelines (TfL, 2010) 3. Calibration of VISSIM to the traffic conditions of Khobar and 4. Calibration of VISSIM for a Congested Freeway (Gomes et al., 2004) 5. Calibration of VISSIM for Bus Rapid Transit Systems in Beijing Using GPS Data (Yu et al., 2006) 6. Jan 10, 2020 The PTV Vissim User Manual is recommended as a reference to supplement this user guide. 1.2 VDOT VISSIM USER GUIDE MAINTENANCE AND UPDATES VDOT is responsible for maintaining and updating the user guide on a regular basis. Future updates are expected as Vissim and PTV Suite software change and the VDOT Traffic Operations and Safety Analysis Manual.

1. Search for jobs related to Ptv vissim manual or hire on the world's largest freelancing marketplace with 18m+ jobs. It's free to sign up and bid on jobs.
2. Welcome to the PTV Vissim Knowledge Base. This area offers you a wide range of learning materials, training courses and customer support, as well as downloads and add-ins for PTV Vissim. Learning: Your Self-Service Knowledge Base.
3. For this the Vissim-COM interface manual (PTV, 2017) used to provide a detailed help until Vissim version 5 but since then the official offline help is significantly less detailed. Instead of that you can use the online help (in the Vissim GUI click on Help Online Help) or the official examples provided for Vissim.

Introduction

Following PJA’s attendance at the PTV User Group in London on 4^th November 2019, one of the key messages that we took away from the conference was the importance of model convergence and understanding the levels of convergence achieved before running for results. Download gta san andreas full game for android apk.

At PJA, we use PTV VISSIM on a daily basis and are all too familiar with model convergence, the difficulties faced as models get bigger and more complex. As a result, we have produced this post to go into detail on what the current convergence guidance is, what methodology we adopt, the limitations with it and a proposed revised approach to demonstrate model convergence.

VISSIM Model Convergence

Current Guidance

As a recap, convergence criteria for VISSIM models is best summarised in TfL’s MAP Engineer Guide v3.5 (http://content.tfl.gov.uk/map-v3-5-engineer-guide.pdf), P140 as shown in Figure 1.

Current Approach

Whilst VISSIM has a built-in ‘pop-up message’ for to highlight when convergence has been achieved, we rarely see this! This is likely due to our convergence method focusing on more than one parameter, which is required following TfL’s guidance – see set-up in Figure 2).

Figure 2 – Covergence Set-Up in Dynamic Assignment

Our microsimulation models also contain elements such as vehicle actuated signals and pedestrian demand inputs. These can cause slight variances in signal timings from seed run to see run, which in turn affects the level of convergence.

As a result of the above, our current approach to assess convergence is to use two outputs:

• The *CVA file generated by VISSIM to check the volume and travel time differences
• The ‘Total Travel Time’ value from the Network Performance evaluation to check the overall network difference.

The volume and travel time differences from the *CVA file are compared against the criteria in Figure 1. The 1% difference check for Total Travel Time is based on previous DMRB guidance which required the “change in user costs or time spent within the network should be less than 1% for four consecutive iterations”. We acknowledge that this has now been withdrawn but it is still a useful measure to demonstrate model stability, and has never been queried at audit.

Figure 2 shows an example of the summary convergence table we produce and Figure 3 shows an example of how the path/edge volume and travel time percentages are created (using Seed Run 20 from Figure 2).

Figure 4 – Example Calculation of Convergence Levels – Seed Run 20

Ptv Vissim 11 User Manual Pdf Manual

The main reason for using this method is that it allows the volume and travel time differences to be checked for both paths and edges, which in turn can be compared against the TfL criteria.

The built-in VISSIM convergence checks allows the travel time on paths to be compared but doesn’t have the option of checking the volumes on paths (only a comparison on edges).

Convergence Method Limitations

Whilst our convergence methodology allows the travel time and volume differences for paths and edges to be determined, there are caveats associated with this.

From Figure 3, the immediate query with the calculations is why the percentages generated by VISSIM at the bottom of the file (ShConvPathTT and ShrConvEdgeVol) are not the same as those that we have manually calculated.

In reference to the PTV VISSIM FAQs link (http://vision-traffic.ptvgroup.com/en-uk/training-support/support/ptv-vissim/faqs/, Dynamic Assignment – #VIS29422), the differences are explained as follows:

“Note: A path is converged if the convergence criterion is met in all time intervals. From the *.cva file, you cannot recognize if the paths that converged in one time interval are the same that converged in another.”

This implies that the *CVA file only shows the numbers of paths/edges that fall within the travel time/volume differences, but these edges/paths could be different between the different time intervals.

As a result, the VISSIM-defined percentage at the bottom of the *CVA file should be considered a more accurate measure of the model convergence as this accounts for edges/paths that converge between successive time intervals.

The remaining barrier to overcome is how to deal with the comparison of the path volumes, which is not automatically calculated within the *CVA file.

Revised Methodology

Introduction

In light of the limitations highlighted above, we have spent some time researching into other ways to check the level of convergence of our models. The result of this is a revised methodology that uses both the built-in tools from VISSIM and some additional manual calculations.

Research Undertaken

Our first port of call was to review the PTV VISSIM help document and the online FAQS link to understand.

The VISSIM FAQ link (Dynamic Assignment – #VIS29422) provides the following advice:

“…you can open the Paths list in PTV Vissim (Traffic > Dynamic Assignment > Paths), and if you add the attribute Converged (Conv) to this list, then you can see if the path is converged or not.”

We looked into what the ‘Converged’ attribute entailed within the Paths list and from the VISSIM User Manual, the following definition is given:

“If this option is selected, the travel time of the path is converged. The path fulfils the convergence criterion Travel time on paths for all completed time intervals.”

It is important at this stage to note that this ‘converged’ attribute only considers the travel time on paths and does not account for the volume on paths.

However, the Paths list within VISSIM does allow you to select a range of other attributes – most importantly the Volume (new) and Volume (old) attributes for each evaluation interval, which is the additional convergence check recommended by TfL.

From Figure 5, it should be noted that, in order to correctly calculate the same ShConvPathTT value as in the *CVA file, you need to compare the ‘Path travel time (old)’ and ‘Path travel time (raw data)’ across all evaluation intervals.

Revised Approach

As a result of a review of information available, we have revised our approach to checking convergence of Path Travel Times and Volumes.

In the first instance, instead of using the *CVA file, we now utilise the Paths list. This is output for each convergence run (using the ‘autosave after simulation’ function) with the list layout as shown in Figure 5. It should be noted that the Network Performance outputs will continue to be collected to check the Total Travel Time differences between each seed run.

Path Travel Times

For the Travel Times, five different checks are undertaken and two of these are used for reporting purposes.

Check 1 – this simply uses the built-in ‘Converged’ check within VISSIM and calculates the percentage of all the paths that meet this criterion. This is NOT used for reporting as the calculation includes detours, which are not strictly a path within the model.

Figure 6 – Path Travel Times – Check 1

Check 2 – this expands on Check 1 and considers if the path is a detour or not. If a path is converged and NOT a detour, then it is considered as part of the analysis. The outcome of this check is a more refined percentage of paths which converge and IS used for reporting.

Check 3 – for each of the various evaluation intervals (defined in the Dynamic Assignment tab), a check is made of each path (which is NOT a detour) to identify if the difference in travel times is within 20% when considering the ‘Travel Time Old’ and the ‘Travel Time Raw’. This check returns a simple ‘YES’ or ‘NO’ for each evaluation interval and for each Path.

Figure 8 – Path Travel Times – Check 3

Check 4 – this expands on Check 3 and assesses if a Path has a travel time difference within 20% for each evaluation interval. If this is ‘YES’ for all the evaluation intervals, then the overall outcome is ‘YES’. If one of the travel times is greater than 20%, then the outcome is ‘NO’. An indicative percentage is also provided on the numbers of paths that converge in all evaluation intervals.

Check 5 – this further expands on Checks 3 and 4 and looks at the ‘NEW’ path volumes for each evaluation interval, with a ‘NEW’ total flow calculated for each path. The outcomes of Check 4 are then used, with each path that converges across all evaluation intervals added together to give a total number of converged paths. This is then divided by the total flow to give the ‘Share of Converged Path Travel Times’. This IS used for reporting.

An example format of Checks 1-5 is shown in Figure 10.

Figure 10 – Path Travel Times – Example of Check 1-5 Calculations

Path Volume Checks

For the Volume checks, two different checks are undertaken and one of these is used for reporting purposes.

Check 1 – this looks at paths which are not detours and for each evaluation interval, calculates if the difference between ‘Volume NEW’ and ‘Volume OLD’ is within 5% . This returns a ‘YES’ or ‘NO’ for each evaluation interval and each path. This is NOT used for reporting.

Check 2 – this expands on Check 1 and checks if there is a ‘YES’ for each evaluation interval for each path. This gives a result of either ‘YES’ or ‘NO’. A summary percentage of paths which have a flow difference of less than 5% for each evaluation interval can then be calculated. This IS used for reporting.

An example format of Checks 1 and 2 is shown in Figure 12.

Figure 12 – Path Volumes – Example of Checks 1 & 2 Calculations

An example of the revised summary table can be seen in Figure 13.

This summary table now takes into account two checks of the Path Travel Times, using both manual calculations of the ‘ShrConvPAthTT’ percentages and also a check of the built-in ‘Convergence’ check in the Paths list. It also calculates the Path Volume Difference percentages, using manual calculations of the ‘NEW’ and ‘OLD’ volumes. Finally, there remains a check of the Total Travel Time within the network. This is taken from the Network Performance outputs and a 1% difference is checked. This is retained as a legacy DMRB convergence criterion and is seen as a good way of further demonstrating model stability.

There are two important notes to consider.

Other Convergence Considerations

Depending on how complex your model is, there is a chance that your model will not achieve the required percentages to be considered ‘converged’.

The VISSIM FAQ link (Dynamic Assignment – #VIS29421) provides the following advice:

From the points above, the are two in particular which we would recommend trying to help with model convergence.

• Using longer evaluation intervals – we typically ensure these are at least 900s (15 minutes). This allows vehicles to complete their journeys, so that the complete journey time can be considered in further evaluation intervals. In the PTV Manual, values of 900-3600s (15-60 minutes) are recommended to account for delays and variance in journey times. Where signals are modelled, the evaluation interval should also be significantly longer than the cycle times used.
• Reducing the traffic volume in congested networks – whilst we think that reducing to 70% of the demand may be a bit too extreme, we would suggest values of 80-85% would be more suitable. This is still likely to give a suitable distribution of traffic around the network, whilst also improving the percentages met of the convergence criteria. It should be noted that we have not explicitly used this method in any project work to date, but is something we will look to use in future (subject to approval from any external auditors of the model).

Outside of the PTV Manual, we can also offer the following suggestions for models that do not fully converge.

• It’s worth spending time up front to set up your Path pre-selection criteria correctly. Depending on the size of the network, you need to consider how many realistic alternative routes there are and how likely it is that drivers will deviate away from the main route. It may take a few iterations when initially creating your path file to get this right, but this should help further down the line. Also, always ensure that ‘Correction of overlapping paths’ is ticked to avoid any unrealistic routes from being included.

• If after a significant number of runs (say 100) and a review of the convergence percentages show that the model has still not converged, there are still options available. You can continue to run the model for more runs to see if this improves the convergence levels. Alternatively, if the review of the convergence percentages shows little variance from run-to run, this suggests that the model has reached a ‘best as it’s going to be’ In this case, depending on how close the percentages are to the target criterion, another approach is to run a greater number of results runs to counteract the reduced convergence. The reasoning behind this is that the more results there are to take an average from, the lesser the effect of any significant variance in the seed runs. As TfL now require 20 seed runs as a minimum for reporting, we would look to run for 30-40 seed runs (or more), depending on the convergence levels achieved.

Summary & Conclusions

We hope this post has provided some insight into general VISSIM model convergence, as well as providing details on our current methodology and how we can improve upon this further with better manipulation of the Paths list.

As VISSIM models become more complex and more detailed (for example, including Vehicle Actuated (VA) signals, pedestrian inputs, multiple route choice), we hope that this post has provided some thoughts and suggestions on different techniques to improve the convergence levels.

As always, we welcome any comments and feedback from other users so that we can continuously improve how we converge models and analysis the outputs to demonstrate a suitably stable model.

PTV Vissim is a microscopic multi-modal traffic flow simulation software package developed by PTV Planung Transport Verkehr AG in Karlsruhe, Germany. The name is derived from 'Verkehr In Städten - SIMulationsmodell' (German for 'Traffic in cities - simulation model'). PTV Vissim was first developed in 1992 and is today a global market leader.

Scope of application[edit]

The scope of application ranges from various issues of traffic engineering (transport engineering,^[1]transportation planning, signal timing), public transport, urban planning over fire protection (evacuation simulation) to 3d visualization (computer animation, architectural animation) for illustrative purpose and communication to the general public.

PTV Vissim is part of the PTV Vision Traffic Suite which also includes PTV Visum (traffic analysis and forecasting) and PTV Vistro (signal optimisation and traffic impact).

Modelling[edit]

Microscopic simulation[edit]

The basic traffic model ruling the movement of vehicles was developed by Rainer Wiedemann in 1974 at Karlsruhe University.^[2] It is a car-following model that considers physical and psychological aspects of the drivers.

The model underlying pedestrian dynamics is the Social Force Model by Dirk Helbing et al. from 1995.^[3]

'Microscopic simulation', sometimes called microsimulation, means each entity (car, train, person) of reality is simulated individually, i.e. it is represented by a corresponding entity in the simulation, thereby considering all relevant properties. The same holds for the interactions between the entities. The opposite would be a 'macroscopic simulation', in which the description of reality is shifted from individuals to 'averaged' variables like flow and density. The corresponding product from the same manufacturer is called Visum.

Transport modes[edit]

In Vissim the following types of traffic can be simulated, and mutually interact:

• Vehicles (cars, buses, and trucks)
• Public transport (trams, buses)
• Cycles (bicycles, motorcycles)

Vehicle interactions[edit]

In VISSIM, vehicle conflict points can be modelled using Priority Rules, Conflict Areas^[4] or Signal Heads.^[5]

Signals can be modelled with fixed-time plans, or various modules such as VAP (Vehicle Actuated Programming) are available to model on-demand signals and other types of control and coordination.

Versions and associated files[edit]

Versions up to 5.40 created .INP files which used a proprietary language. Versions 6 and later created .INPX files which use an XML-based language. Both produce human-readable code:

.INP example[edit]

.INPX example[edit]

References[edit]

1. ^Mahmud, Khizir; Town, Graham E. (June 2016). 'A review of computer tools for modeling electric vehicle energy requirements and their impact on power distribution networks'. Applied Energy. 172: 337–359. doi:10.1016/j.apenergy.2016.03.100.
2. ^R. Wiedemann, Simulation des Straßenverkehrsflusses. Schriftenreihe des IfV, 8, 1974. Institut für Verkehrswesen. Universität Karlsruhe. (In German language).
3. ^D. Helbing and P. Molnar, Social force model for pedestrian dynamics. Phys. Rev. E, 51:4282–4286, 1995. arXiv:cond-mat/9805244v1
4. ^Georgia Department of Transportation http://www.dot.ga.gov/PartnerSmart/DesignSoftware/TrafficSoftware/Getting%20Started%20VISSIM%206.pdf
5. ^TfL Traffic Modelling Guidelines v3 http://content.tfl.gov.uk/traffic-modelling-guidelines.pdf

Ptv Vissim 11 User Manual Pdf Download

Further Literature[edit]

• R. Wiedemann, Modelling of RTI-Elements on multi-lane roads. In: Advanced Telematics in Road Transport edited by the Commission of the European Community, DG XIII, Brussels, 1991.
• M. Fellendorf, VISSIM: A microscopic simulation tool to evaluate actuated signal control including bus priority. 64th ITE Annual Meeting, 1994. PDF^{[permanent dead link]}
• L. Bloomberg and J. Dale, Comparison of VISSIM and CORSIM Traffic Simulation Models on a Congested Network. Transportation Research Record 1727:52-60, 2000. PDF^{[permanent dead link]}
• D. Helbing, I. Farkas, and T. Vicsek, Simulating dynamical features of escape panic. Nature, 407:487–490, 2000. arXiv:cond-mat/0009448v1
• M. Fellendorf and P. Vortisch, Validation of the microscopic traffic flow model VISSIM in different real-world situations. Transportation Research Board, 2001. PDF
• D. Helbing, I.J. Farkas, P. Molnar, and T. Vicsek, Simulation of Pedestrian Crowds in Normal and Evacuation Situations. In Schreckenberg and Sharma editors. Pedestrian and Evacuation Dynamics, Duisburg, 2002. Springer-Verlag Berlin Heidelberg.
• B.B. Park and J.D. Schneeberger, Microscopic Simulation Model Calibration and Validation: Case Study of VISSIM Simulation Model for a Coordinated Actuated Signal System. Transportation Research Record 1856:185-192, 2003. PDF
• T. Werner and D. Helbing, The Social Force Pedestrian Model Applied to Real Life Scenarios. In E. Galea (editor) Pedestrian and Evacuation Dynamics: 2nd International Conference, Old Royal Naval College, University of Greenwich, London, 2003. CMS Press.
• G. Gomes, A. May, and R. Horowitz, Congested Freeway Microsimulation Model Using VISSIM. Transportation Research Record 1876:71-81, 2004. PDF
• R. Jagannathan and J.G. Bared, Design and Operational Performance of Crossover Displaced Left-Turn Intersections Transportation Research Record 1881:1-10, 2004.
• K.Y.K. Leung T.-S. Dao C.M. Clark, and J.P. Huissoon, Development of a microscopic traffic simulator for inter-vehicle communication application research. In Intelligent Transportation Systems Conference 1286-1291, 2006.
• M.M. Ishaque and R.B. Noland, Trade-offs between vehicular and pedestrian traffic using micro-simulation methods. Transport Policy 14(2):124-138, 2007.
• W. Burghout, J. Wahlstedt, Hybrid Traffic Simulation with Adaptive Signal Control Transportation Research Record 1999:191-197, 2007. PDF
• A. Johansson, D. Helbing, and P.K. Shukla, Specification of the Social Force Pedestrian Model by Evolutionary Adjustment to Video Tracking Data. Advances in Complex Systems 10(4):271–288, 2007. arXiv:0810.4587v1

External links[edit]

Ptv Vissim 11 User Manual Pdf Free

• Animated PTV Vissim example of a roundabout created by BrennerPlan GmbH.