Transport Modelling – an aid to planning and prevention

Defined as the digital replica of the real-world multi-modal transport system, a digital playground of sorts to assess the impact of various transportation options and identify how they are likely to perform in the future, the transport model is a powerful tool for enabling decision-making based on what-if analysis and scenario planning. Rajesh Krishnan, CEO, ITS Planners & Engineers, elaborates on the different levels of developing a model, wide range of applications, and the benefits in terms of enabling authorities to take right traffic management measures.

The development of a model involves setting up a base model which reproduces the mobility in the planning regions at a given time, the base year. It is built from various data sources all relating to the same year. By adjusting various parameters and inputs, the model is calibrated to match traffic counts and survey data, such as number and type of vehicles, public transit passenger boardings, trip distance distributions etc., which are also collected for the base model. Once calibrated and verified, this model is then used by different applications to develop test scenarios.

However, such models are under utilised for a number of reasons ranging from lack of technical expertise, lack of manpower, lack of awareness about model availability and lack of institutional culture in making data driven decisions to name a few.

Depending on the level of detailing required, transport models are created at four levels of granularity – macroscopic, mesoscopic, microscopic and sub-microscopic. Macroscopic models deal with aggregate quantities such as traffic flows at link levels and are typically used to assess traffic in large scale networks at the expense of detail for strategic modelling. In contrast, microscopic models simulate the movement of individual vehicles with their acceleration, deceleration and precise movements along links and intersections and traffic signal states.

Mesoscopic models combine aspects of both, by simulating traffic in large scale networks through simplified vehicle movement models which omit aspects like acceleration or deceleration and sometimes simulating vehicle movements over multiple real-world timesteps at a time. Mesoscopic models provide enough detail for assessment of traffic management measures while still being applicable to large scale networks. Sub-microscopic models on the other hand may involve a more detailed representation of vehicle dynamics such as engine RPM with respect to speed and more representative simulation of vehicle dynamics.

Transport models can be used in a wide range of contexts. Traditionally, macroscopic transport models have been used to aid long term transport planning. A calibrated and validated model updated with predicted future transport demand is combined with planned road network enhancements to determine the impact of such planned schemes. The output data of a transport model can be fed into various other tools to assess pollution dissipation, air quality and climate change as road traffic is responsible for a large share of carbon emissions and other pollutants. Traffic volumes computed by transportation models can also be fed into noise emission models.

Thus, these models help to quantitatively evaluate transport schemes before they are built. They help decision makers answer questions such as what the economic benefits of the proposed scheme are or how much improvement in travel time is the scheme likely to achieve. Their outputs can also be fed into 3-D visualisation and Virtual Reality (VR) models that provide qualitative inputs to aid decision making for high-level stakeholders.

The models can also be applied to evaluate schemes that are planned to be implemented in the short to medium term. Traffic Impact Analysis studies for new developments fall into this category. A detailed simulation analysis of complex ITS schemes are often carried out before they are implemented to validate the technical design and performance parameters. Such simulation models often involve custom software modules that emulate the ITS system working in tandem with established simulation software through their APIs.

An example of such a model is the microsimulation of the DartCharge scheme on the M25 ring-road around London. The scheme involved removing barriers for toll payment before a tunnel that went under the river Thames. However, vehicles not allowed in the tunnel such as those carrying dangerous goods were identified and removed from the highway. A microsimulation model of the motorway section including a detailed emulation of the proposed ITS system was made. A bespoke software module that emulated the ITS system was developed and interfaced with micro-simulation software using APIs. The model was used to determine the performance parameters of the proposed ITS design under various traffic conditions before it was implemented. DartCharge is currently running successfully.

Transport models are also used to support traffic operations. Many cities build and maintain up-to-date microsimulation models of traffic control regions consisting of a group of junctions in their cities, including several smart cities in India. They can be used to carry out what-if scenario analysis that aid decision making around maintenance activities. If a lane or road is to be closed for a certain period, an analysis is carried out to determine the best time for it that will result in least disruption to the traffic. Such analyses will also provide insights into the locations that are likely to experience increased congestion due to the roadwork, enabling operational managers to make informed decisions about traffic diversions.

What-if analysis around natural disasters is another transport model use case. If the competent authority has access to a transport model and information about the spatial distribution of population, transport models can be used to work out how fast one can evacuate the population when a disaster strikes a particular location. Decisions about where to move the evacuated population also can be made with confidence based on model supported analysis. Such model-based analysis also can provide estimates about how soon to give early warnings for disasters and help determine the performance parameters for early warning systems.

Most large cities in India have access to macroscopic transport models that are developed as a part of Comprehensive Mobility Plan studies and Comprehensive Traffic and Transportation Studies. Many Smart Cities have access to microscopic transport models that are developed as part of Area Traffic Control System deployments.

All this begs the question, why are our cities congested and why is our country still vulnerable to devastation by annual monsoon floods, landslides, recurrent potholes on roads and other man-made and natural disasters when available technology can be used for prevention and planning? We need more transport models and they should be widely used by transport professionals and decision makers in order to scientifically manage our transport networks.