Why Would You Use a Traffic Simulation?

It is one of the main challenges of our time: The growing need for good mobility - and thus for reliable and responsible means of transportation. We are all familiar with the problems that arise in overloaded transport networks: cities in particular struggle with traffic jams, congested roads, and air and noise pollution.

Our mobility and transportation systems are becoming increasingly complex. Making them efficient and sustainable is in turn becoming an ever-greater challenge. What are the best measures to reduce traffic-related emissions? How can traffic be managed safely for all road users? How to choose between a roundabout or adaptive traffic lights to guarantee a good traffic flow? How to coordinate public transport service with smooth traffic operations?  What impact will new technologies like autonomous driving have on the network?

Traffic simulation is an important tool to investigate these questions. It enables planners to use available budgets and resources as efficiently as possible when expanding or reconstructing transportation systems. Simulation models help to understand the effects that different measures have on traffic volume and traffic flow under different circumstances. So, simulating traffic creates a solid basis for good and cost-effective decisions - making traffic and mobility safe, sustainable, equitable and resilient. In short, it helps to create future-oriented mobility.

Microscopic simulation, mesoscopic and macroscopic simulation

There are different resolutions of simulation models:

• Macroscopic simulation considers only aggregated traffic flow volumes, and not individual agents (vehicle, road user).
• Mesoscopic simulation is based on individual agents, whose behaviour is determined from aggregated traffic flow attributes, like the density or the average speed. Direct reaction of agents to other agents happens only at nodes (intersections).
• In a microscopic simulation, each individual agent reacts on their current environment, i.e. the distances and speed differences to nearby agents. The movement is modelled continuously in time and space. Decisions about change of speed and direction happen usually in small time steps of <1 second. The overall traffic state results from the individual decisions of the agents.

The combination of mesoscopic simulation and microscopic simulation in certain network sections is known as hybrid simulation.

What are traffic simulation models used for?

As with an architectural model, a transport simulation model helps to gain a better understanding of a complex system. In cities, pedestrians, cyclists,  public transport and motorized vehicles meet in a very narrow space. And multimodal transport systems do not only consist of different kind of road users, modes, and mobility providers. Aspects like people changing mobility behavior or new services entering the market – such as autonomous driving – also come into play. Simulation models enable traffic planners to understand this highly complex and dynamic system and develop efficient strategies to solve current and future traffic problems.

How is traffic simulation used?

Traffic planners and engineers, companies and researchers use traffic flow simulations, e.g., PTV Vissim,  for a wide variety of applications – always with the aim to provide a sound basis for planning decisions. Here are some examples:

Design of traffic infrastructure

The verification and improvement of the road network capacity and the performance of traffic infrastructure is a classic use case for traffic simulation. Changes in urban design impact the traffic situation on site. For example, building a new stadium or shopping mall will certainly change the traffic load in that area. A traffic flow simulation provides a clear overview of how the predicted (increased) traffic can best be handled, and whether the mobility infrastructure needs to be adapted or even rebuilt. Issues such as the effects of two or three lanes on traffic flow can be analyzed.

Non-standardized transportation infrastructure

If a traffic infrastructure design (e.g., a road design or traffic signal timing) does not meet the standards specified in appropriate guidelines, it’s recommended to simulate the planned infrastructure. In this way, it is possible to evaluate the quality of traffic flows that occur at complex and non-standardized intersections or through intelligent traffic control systems.

Advanced Traffic Management Systems

Advanced Traffic Management Systems can be installed in both motorway and urban environments to increase and maintain transportation capacity through the more efficient use of existing infrastructure.

Smart traffic signal control can improve the traffic flow, for example by reducing waiting times at traffic lights. But which control option is the best for a specific node? In the simulation model, various options can be evaluated and optimized before the implementation.

On a highway, traffic control systems - by means of display boards, dynamic traffic signs, variable message signs - are used to optimize the traffic flow and to prevent congestion as far as possible. Within a simulation, planners can model all operational interventions and assess their effect on overall traffic flow.

New technologies in the automotive industry

Traffic simulations play a crucial role in the automotive industry. New vehicles are tested many times before they go into actual production - in real road traffic, but also virtually with the help of simulations. A traffic simulation provides complex traffic flows in a virtual environment. The tested vehicle can interact with other road users. In virtual traffic, tests of driver assistance systems (ADAS) and technologies for connected and autonomous vehicles (CAV) can be carried out realistically.

Infrastructure planning for vulnerable road users

Multimodal traffic simulation is ideal for studying the movement of all modes of transport and their interactions. This also applies to the so-called vulnerable road users, such as cyclists and pedestrians. How do pedestrian- and bicycle-friendly urban designs look like? Where are new bike lanes needed? How do you enable green waves for cyclists in a meaningful way? A traffic simulation can be used to analyze measures and their effects. 

Pedestrian simulation

Simulating pedestrians can optimize much more than just sidewalks. The simulation of pedestrian flows also helps in the pedestrian-friendly and safe design of train stations, airports, and other locations. Additionally, crowd and evacuation simulations are an important tool in in the planning of major events.

Public transport planning

Traffic simulations also support public transport planning. Various public transport lines, vehicle types, timetables and routes can be modelled. Connections can be optimized, for example by selecting the most suitable stop designs and especially measures related to intersections. Measures for local public transport prioritization can be applied at the operational and vehicle-based level.

Using a traffic simulation, planers can evaluate the optimal timetables, how many bus parking bays a bus station should have, and whether the planned connection times are sufficient for passengers.

Emission calculation

In addition to typical parameters such as travel times, speeds or queue lengths, a microscopic traffic flow simulation also enables the calculation of emissions based on individual vehicle trajectories. Emissions can be precisely assigned in terms of time and location, which means planners can see the quantities of emissions that occur in different areas. City and traffic planners can immediately see how different traffic measures, such as adaptive traffic signal control, will affect vehicle emissions and air quality.

How to set up a traffic model

Which software is used for traffic simulation?

Traffic experts worldwide rely on PTV Visum for macroscopic traffic simulation. PTV Vissim is the world-leading solution for microscopic simulation, mesoscopic or hybrid simulation.

Decades of research, continuous development and close cooperation with customers make PTV solutions stable simulation tools.

What data is needed for a traffic simulation? 

Input data for a simulation model consist of three main parts:

• Traffic network: Roads, intersections, railroad tracks, walkable ground
• Traffic demand: How many agents of which type want to get from which origin and to which destination.
• Intersection control: Yield signs, stop signs, and traffic signal control.

The route choice can be either additional input data, or a part of the results which is determined by a network assignment (route choice) procedure. The quality of data is critical. A virtual model can only be as good as the input data.

Where does traffic simulation data come from?

Important data sources are traffic counts as well as data from traffic monitoring or control from various detectors. If future scenarios are to be modeled, a traffic forecast is needed - including all expected changes in supply and demand. Larger macroscopic traffic models using PTV Visum or other tools are often used to provide data to smaller microscopic models.

How long does it take to build a simulation model?

If all data and information are available, a traffic model with a simple intersection with traffic lights can be modeled within 30 minutes (find out more in this webinar). Complex traffic models are more time-consuming. They need to be calibrated and validated, scenarios need to be created and evaluated. This can take several days or weeks, or even several months for highly complex ones.

Can you automate the building of a simulation model?

It is possible to create networks for microscopic traffic simulations from scratch. However, they can also be imported, or at least partially generated. Often, smaller sections of larger macroscopic simulation models are imported. Other possibilities include importing map data such as OpenStreetMap, HERE or TomTom Maps, or using data formats used in the industry such as OpenDrive.

How does traffic flow simulation work?

Mesoscopic and microscopic simulation are stochastic. The behavior parameters and the time of entry in the network are drawn randomly from given distributions for each individual agent. The result of a single simulation run must be understood as just one possible real traffic flow on a single random day. Therefore, this could be an extreme outlier. To get a meaningful impression of the possible distribution of results, it is necessary to execute multiple simulation runs (with different random seeds). Assuming correct modelling of the network and suitable calibration, the distribution of the simulation results should then be similar to the distribution of real traffic states on different days. Average values over all simulation runs are usually not the most interesting indicators but rather the relative frequency of breakdowns, e.g. “a large traffic jam is to be expected at 70% of days”.

How fast are simulation models? How long do they run?

The simulation’s speed depends on various factors. For example, on the time step resolution (i.e. the number of time steps simulated per second) and the model complexity (i.e. the number of interactions and objects).

Microsimulation models - i.e., traffic models in which road users are represented individually - potentially produce an immense amount of data during each simulation run, as attribute values - most importantly position and speed - are recalculated several times per second for each driver and each pedestrian.

Also, the hardware - processor, memory, or video card – affect the speed of traffic simulation runs. 

In simple traffic models it is possible to simulate up to 10 000 vehicles in real time. One second in the simulation corresponds to one second in reality. With a smaller number of vehicles/pedestrians, the simulation can run 20 or 50 times faster. 

How accurate is traffic simulation?

An important aspect of ensuring the accuracy of a traffic model is calibration. Models cannot simply be transferred from one city to another. They must be calibrated, i.e., adapted to local conditions. Standard statistical methods such as GEH statistics or goodness of fit, must be used to prove agreement with real data.   

Traffic simulations - especially when considering future scenarios - work with different assumptions. Since the future is full of uncertainties, several scenarios are created to take into account the different development of infrastructure, land use, social and economic development. The model results must then be considered and evaluated with these assumptions in mind.