Originally done as a signalisation project, this model was further developed to also show VISSIMs 3D visualisation capabilities. This is often used to transfer the results of a simulation study to a political or non-technical audience. The situation shown in this simulation is based on the Mendelssohnplatz in Karlsruhe (Germany). In addition to private traffic (cars) the model features HGVs (trucks), tram services, buses, pedestrians and bikes. The proximity of two large intersections enhances the complexity of the situation so that a micro-simulation study was essential in order understand the signalisation. Testing this solution within the safe environment of a micro-simulation tool enables the traffic engineer to provide an optimised solution. This contributes to an efficient use of available road space, reducing maintenance times and maximising the network.

The model as shown here displays the calibrated base operation. It has been built to be available to test for modifications in detail prior to applying the operations to the real network.

Different vehicles with a variety of widths interact with each other and find their way wherever there is enough space to fit in -- irrespective of the lane marking configuration. At intersections, there is notable lateral movement and vehicles look for such lateral gaps to reach the head of the queue. Traffic situations like this occur for example in India, China and some developing countries. This approach can also be applied for the simulation of bicycle and motorbike behaviour. This form of simulation modelling of traffic is considerably more difficult than North American and European traffic due to consideration of lateral vehicle movements within the same lane.

This demonstration example of a VISSIM simulation shows conditions of pedestrians crossing a street at a signalised, actuated pedestrian crossing. For better illustration, the state of the signals are visualised with coloured protruding stop lines after about 15 seconds. The colour of the pedestrians also change from normal to a colour that depicts their behaviour: Green pedestrians always obey the traffic light: They operate the signal (push the button) and wait for the green light to come in order to cross. Yellow shaded pedestrians also push the button, but when there is a sufficient gap between the vehicles, they proceed. The red pedestrians do not push the button and ignore the red light by simply crossing when conditions allow. The red persons behave as if there were no signals.

The trams and the pedestrians in parallel movements are modelled to have priority at the conflict areas, while the vehicles and pedestrians in perpendicular crossings have to give way. Note that such modelled behaviour as a general rule can be suspended in certain conditions such as in congestion.

In case of a situation where a slow vehicle moves to the fast lane in front of cars with a greater intended speed, the drivers break more significantly producing a chain reaction of reduced speeds. This behaviour is caused by the delay before braking and the reaction time of the drivers, especially if they travel below their safety distances. As a result drivers require enhanced braking than the preceding vehicle. Vehicle speeds drop dramatically, and they can even lead to a complete standstill. Queues then form despite not having an accident. To subsequent drivers it appears that there is a queue "out of nowhere". This phenomenon is called a "phantom jam", "ghost jam" or "shockwave" . A speed limit helps to reduce the overall speeds and the fluctuations(drivers hold more similar speeds) and at lower speeds the safety distances are also more secure. As a consequence, braking activities (especially strong braking activities) are much less frequently triggered. These simulations and visualisations were achieved using the microscopic traffic simulation software VISSIM.

The location for this case study is an arterial road in downtown Abu Dhabi, United Arab Emirates. The upper part of video shows the traffic flows for a BRT scenario, the lower part shows traffic flows for the same corridor without public transport.

(PRT is short for "Personal Rapid Transit". It describes a public transport system with the charm and comfort of private traffic. The trips are demand based rether than schedule based: Typically services wait for passengers and not vice versa - Direct, non-stop trip to destination - Small driverless electric vehicles ("pods") hold 4-6 passengers.These services are faster, more reliable due to dedicated guideway and highly energy efficient. Among the real world PRT applications there are the systems at London Heathrow Airport (Terminal 5) and Masdar City (UAE). http://www.youtube.com/watch?v=PB_5TBZQNRY. This VISSIM example shows a scenario of a small PRT network including 4.7km of guideways, 7 stations, 1 depot and 40 pods (PRT vehicles).
In this example intelligent switches are used. to identify the shortest path to each destination. This way a local re-routing (such as routing a free PRT vehicle to a station) is also possible. An occupied pod travels non-stop from its starting station to the desired destination. Free pods typically return to the depot. However, at every switch in the network they can be re-routed to another station. Due to the flexibility of the system and the relative small vehicles, PRT is particularly suited to handle disperse demand patterns with low to medium passenger volumes

The PRE-DRIVE C2X project is about C2X communication. "C2X" means "car to something" and typically involves other cars or infrastructure. The communication system is called a VANet, (Vehicular Ad-hoc Network). This animation shows the results of using such communication to distribute a warning generated by very slow vehicles on a motorway. The approaching driver’s reaction to this warning is modelled to demonstrate that the communication delay cannot be expected. The corresponding simulation was jointly developed by PTV and the Decentralised Systems and Network Services Research Group of the Karlsruhe Institute of Technology (Germany). PRE-DRIVE C2X is developing a common European system for vehicular communication based on a vehicle to “x” communication system. This is derived from the COMeSafety project task force that included the cooperation of the SAFESPOT, CVIS, COOPERS integrated projects and of the Car 2 Car Communication Consortium. The PRE-DRIVE C2X project is co-funded by the European Commission DG-Information Society and Media in the 7th Framework Programme

VISSIM integrates road traffic, public transport and pedestrian dynamics simulation all in one software solution and integrates the modes of transport with full interaction. As shown in this video the passengers alighting from the arriving trains define the demand on the station infrastructure and the pedestrian's behaviour determines when the train can leave the station again. Train delays may occur from unusually high numbers of alighting passengers and densely populated platforms. This video showing the subway station was recorded directly from the VISSIM software without a post-processing video production tool.

It underlines the idea that - contrary to common assumptions - it is not necessarily the shortest path that leads to smallest average and total travel times in emergency evacuations. Instead it may be that the best performance (with respect to average individual egress times) that the egress strategy includes counterflow (bi-directional flows) in a corridor. This would involve two exits with different capacity and two groups of occupants with varied walking speeds.

Beginning at 01:42, the effect of the method called "dynamic potential" is demonstrated by comparing it to pedestrians who walk along the shortest path (that is they minimise travel distance instead of travel time). In a methid similar to vehicle drivers, pedestrians aim minimise their travel time to the destination and in some situations that desire is stronger than in others The pedestrians in all situations move with approximately the same speed. At time 01:42 is a situation where about 800 passengers alight from two trains arriving simultaneously at the station at the south entrance of Berlin's congress center (ICC). Making a large group of pedestrians walk realistically and efficiently around a sharp corner is one of the main applications of the dynamic potential method. Note that with only a small group of pedestrians both trajectories would be very similar (quickest and shortest path are then almost identical). At time 03:18 a large group of pedestrians has to take a U-turn. This is more difficult and therefore the difference between the two methods (left and right) is even more distinct. At time 04:48 two large groups meet in a straight counterflow. This is a situation where the use of the dynamic potential provides an alternative behaviour that shows up after some seconds. The behavior on the left side is more realistic when the pedestrians assume that the counterflow situation will persist only shortly (eg at a busy traffic light). The right side flow of traffic assumes that it will persist for longer (crowds moving through a city centre festival). At time 06:18 as counterflow occurs at a sharp corner, the dynamic potential (right side) is able to better reproduce that people move efficient in such a situation and most are able to resolve the situation At time 09:18 within a simple station hall some people (red) are urgently rushing for their train whilegreen people have alighted from a train. Some others (blue) have arrived at the station well before departure and now linger around. The red and green pedestrians in the upper left video follow the shortest path. With a growing blue group they get stuck in that group. The upper right and the lower situations were simulated with the quickest path approach but different values for parameter “h”. Note that in the lower two videos the red and green groups manage to establish direction separation respectively spontaneous lane formation, while they do not for h=0 in the upper right example. At time 10:48 This is the first example with a discrete route choice. The pedestrians need to choose if they walk the left or the right corridor. The method of the dynamic potential was not constructed for usage in such a situation. Other methods such as partial routes might be more helpful. At time 12:43 this example includes a sequence of one-dimensional segments (links) for the pedestrians. Therefore the direction of the shortest and the quickest path can differ by 180 degree.

The data for traffic generation is derived from a traffic demand model which includes statistical socio-demographic and traffic behaviour data at a high resolution for a model of this size (10.000 traffic zones). This animation is not a visualisation of measured data but the result of a calculation. The VALIDATE model can be used to assess the impact of new roads under consideration on their whole region in detail. This animation only shows the largest roads (motorways and trunk roads), yet VALIDATE also includes all major regional and inner-city roads.

VISSIM can handle all this in a multi-modal traffic simulation. It includes in one simulation software the ability to simulate individual motorised traffic of any kind, public transport, cyclists, and pedestrians -- and even other vehicles such as rickshaws as well. All these modes of traffic and transportation are not only simulated next to each other, but they can interact. Simply spoken: pedestrians can cross streets, operate traffic lights and board to and alight from buses, trains and trams. This allows for a wide range of applications ranging from signal control optimisation to passenger transfer times in stations; from arterial benefit assessment to emergency egress simulation; from BRT to PRT (Bus Rapid Transit to Personal Rapid Transit); and from C2X to LRT (car-to-infrastructure communication to Light Rail Transit).

This research foundation is funded by the German Ministry for Research (BMBF), headed by the Jolich Research Centre The HERMES project page can be found here: http://www.fz-juelich.de/jsc/hermes Part of the project are extensive experiments (carried out by the Universities of Cologne and Wuppertal) on pedestrian dynamics of which can be found here on http://youtu.be/EoYn4cHOBd4. , PTV continues to support this research and utilise the results for calibration of the pedestrian simulation model. Now for what can be seen in the video on this page. The first part (starting at 0:07) shows a VISWALK simulation of the evacuation of the part of the stadium (the Esprit arena in Dusseldorf) which is in focus of the research project. Microscopic simulations of pedestrian dynamics are part of the evacuation assistant to allow the stadium control as well as the rescue forces a glimpse into how the distribution of occupants can be expected to develop within the next few minutes. Such an online simulation obviously sets a high requirement to the computation speed of a model. In the video the visitors are simulated to leave their place on the grandstands, walk through the gates and down to the floor level of the arena to the areas marked bright green. The grandstand areas are shown in a lighter grey. The four blue areas mark where the remaining part of the arena continues, which are not investigated in the project. The second part of the video (starting at 3:07) shows the result of a VISUM calculation. It shows the visitor flows if all doors and corridors are available. Different to the microscopic simulation with VISSIM the idea is not to compute how the situation is expected to, but to compute what would be an optimal distribution of occupants on exits. This is especially interesting in case that a corridor is blocked and those who normally would use it would then be distributed on other exits. While it is a hypothetical result as the staff guiding the occupants can never be able to exactly implement the result, it nevertheless is helpful to show tendencies, and a big advantage is that such a microscopic computation with VISUM is much faster than any microscopic model can ever be. Furthermore it allows a better understanding of the whole infrastructure with the processes by doing "what if...?" case studies. The third part (starting at 3:47) shows how these and more results (eg of smoke detectors) are displayed all in one graphical user interface -- a communication module. This is the "face" of the evacuation assistant system as it is shown to the heads of the rescue forces and the arena management.

It shows one of the 6 identical segments with 102 parking spaces each. The complete structure features a total of 612 parking spaces on 17 parking levels with a height of 38m. Cars enter and exit through transfer areas. There are 2 transfer areas available per segment (on different levels) with a turntable each and secure passenger access. Drivers park their car in a transfer area on a pallet and then leave the car park. The system then automatically parks the car in the tower using the nearest available slot. As the driver returns to the car park, after personal identification the system fetches the car and provides it in the corresponding transfer area. The simulation control is done through the VISSIM COM interface with extensive programming using Excel VBA (Visual Basic for Applications). The initial filling state of the car park is defined in a spreadsheet and can be changed easily. Evaluation variables and results are displayed in another Excel spreadsheet for a convenience. COM-scripting vastly enhances VISSIM's field of applications as it provides a means of simulating special real- world situations that due to their specifications may not entirely be simulated directly inside VISSIM.

This enables you to investigate and to study the environmental impact of traffic for both existing and modified or future situations. It helps investigations with the dilemma of traffic flow versus emissions by finding the best solution for your situation. More information can be found on www.TNO.nl/EnViVer