How can traffic simulation predict the impact of new infrastructure projects?

L'utilité de la simulation du trafic est de reproduire et d'évaluer le système de circulation. Elle a pour objectif d'améliorer ou de créer les infrastructures tout en minimisant ou supprimant les goulets d'étranglement. Une simulation continue (modèles macroscopiques) ou simulation à événements discrets(modèles microscopiques) ou mésoscopiques constituent une aide à la décision.

The results of traffic simulation models help lawmakers to assess/prioritise investments based on the outcome of the simulation results. It helps to avoid unnecessary public infrastructure projects and focus on projects with high ROI.

On the other side, the real time simulation which uses the microscopic and mesoscopic/hybrid models; it helps Traffic Management Engineers/Operators in taking quick decisions in managing traffic i.e. performing What if analysis. This returns the impact on the live traffic condition if a certain management strategy is deployed i.e. change in corridor plans, closing certain lanes or road etc.

A traffic simulation used existing travel patterns to project how a new infrastructure will influence and change existing travel patterns with it's associated travel time changes. However as per all simulation, the modeller should be aware of making assumptions that is not grounded in reality. A good practice for a model must be to first assessed it based on all the assumption made within the model and evaluate how the assumption are derived before deciding if the model is appropriate for use in that situation.

Frequently, simulations serve as testing tools for evaluating various scenarios, making them instrumental in assessing the potential outcomes of different traffic management strategies or infrastructure changes. However, they are also powerful tools for persuasion, providing decision-makers with tangible insights into the projected impacts of proposed changes. This dual role positions traffic simulations as invaluable assets in both testing and convincing stakeholders about the efficacy of transportation-related decisions.

Like the environmental study and impact, traffic study and impact analysis of any project is a key in achieving the overall urban mobility and sustainability goal. For this purpose cities build strategic model where the impact of any infrastructure project is studied by simulating the new project on it. It enhance different future scenarios including: car parking modification, new transit line, toll modification, new road building and other outlined proposal. It is developed with information regarding: demographic data, socio-economic data, current policies and future policies. The planners and designers benefits from this kind of simulation to build overall development strategy and making key decision for public investment.

Also, consider that traffic simulation can deliver key information for transportation cost models and geographic-explicit models such as predictive scenarios of land cover change, environment and socioeconomic impacts.

Macroscopic simulation models are created at macroscopic level like city or region or at country level. These models help to understand the overall circulation/flow of traffic in the study area and the impact of large scale transportation projects can be studied or assessed.

Macroscopic models, being the most abstract, treat traffic as a continuous flow, overlooking individual characteristics. They utilize aggregate variables like density, speed, and flow to analyze large-scale and long-term traffic patterns. Effective for assessing peak-hour demand, travel time, and network capacity, these models play a crucial role in anticipating future infrastructure impacts. As we delve into complex planning, the macroscopic perspective contributes strategic insights into the broader dynamics, essential for navigating the intricate landscape of transportation planning amidst evolving economic and environmental conditions.

Microscopic simulation models help in micro managing traffic/pedestrian movement. It is useful in assessing smaller areas and the impact of local interventions can be studied.

While microscopic traffic simulation models excel in capturing intricate details of individual vehicles and drivers, one could argue that their emphasis on granularity might sometimes overshadow the broader systemic factors influencing traffic dynamics. In focusing intensely on specific attributes and preferences, microscopic models might inadvertently downplay the impact of macroscopic elements like city planning, infrastructure design, socio-economic factors, etc., that significantly shape traffic patterns on a larger scale. A holistic understanding of traffic dynamics requires a synergy with macroscopic perspectives to ensure a comprehensive and effective approach to traffic management.

In the strategic and tactical realm, microscopic models offer unparalleled detail by simulating individual vehicles and drivers, considering their specific attributes, preferences, and rules. Employing discrete variables like position, speed, acceleration, lane-changing, and gap acceptance, these models provide a realistic depiction of small-scale and short-term traffic phenomena. Analyzing aspects like vehicle platooning, car-following, lane-merging, and signal timing, microscopic models contribute invaluable insights to both strategic and tactical facets of transportation planning. As we navigate the intricate dynamics, the granularity of microscopic models enhances our ability to formulate comprehensive strategies and responsive tactics.

Meso models strike a balance between the high-level perspective of Macro models & the detailed, individual-level insights provided by Micro models. They excel in their ability to integrate broader systemic factors, such as city planning, infrastructure design, & socio-economic considerations. By assessing the interplay between vehicle groups (& pedestrians) within the network over time, these models offer a comprehensive view that incorporates the impacts of urban development, transportation policies, and societal influences. Thus, this holistic approach allows decision-makers to assess the impact of macro-level strategies on traffic flow & congestion, enabling more informed & effective planning for medium-scale urban environments.

Mesoscopic models bridge the gap between macroscopic and microscopic approaches, blending elements of both. They represent traffic as groups or packets of vehicles rather than a continuous flow or individual units. Using a combination of aggregate and discrete variables, these models offer versatility in analyzing medium-scale and medium-term traffic challenges, including route choice, network assignment, and congestion pricing. Pros: 1. Intermediate Detail 2. Versatility 3. Resource Efficiency Cons: 1. Complexity Trade-off 2. Resolution Limitations

Beyond mere prediction, traffic simulation unveils a realm where the ripple effects of infrastructure metamorphosis can be intricately examined. Imagine dissecting the urban fabric virtually, not just in terms of roads and bridges, but as a living organism pulsating with traffic patterns influenced by the subtleties of human behavior, economic shifts, and societal nuances. It is one of the fundamental concepts of urban planning - "City as an Organism". This nuanced understanding, derived from the amalgamation of data, calibrated models, and analytical scrutiny, transforms the conventional infrastructure assessment into a journey through the intricate tapestry of a city's pulse, where decisions resonate far beyond concrete and steel.

One of the most valuable applications of simulation modeling is to use the visual/ video outputs to show in 4D what the public would be expected to experience with various improvement alternatives including the do nothing alternative. We have used this tool countless times to inform the public and elected officials so they can make more informed decisions regarding the expenditure of tax dollars.

Traffic simulations proved invaluable for me during the implementation of a road diet, specifically when adding a new bicycle lane. Through simulation, various solutions were tested, optimizing service levels in the immediate vicinity. Additionally, diverse scenarios can be tested to enhance intersection functionality when reducing lanes for the introduction of bike lanes. Simulation provides a comprehensive tool for refining urban planning decisions, ensuring improved traffic flow and accommodating evolving transportation needs.

La mise en place de projets d'infrastructures correspond à l'établissement d'un système de transformation de flux de trafic comprenant une entrée, un traitement à l'intérieur du système et une sortie qui entra?ne une différence de flux à chacune des 3 étapes. Il s'agira grace à la simulation d'agir sur la charge (les flux) et la capacité(les infrastructures) tout en tenant compte des données, des variables et des contraintes qui prennent en compte plusieurs domaines d'expertises. L' objectif étant l'établissement de modèles d'infrastructures capables d'assurer une meilleure fluidité.

Traffic simulation models can become self-fulfilling. The predict and provide approach has harmed urban development and encouraged car dependency. They tend to provide decision makers a false sense of confidence due to the fact they are very precise. However this precision is very different to being accurate. I would always treat traffic modelling outputs with a high level of scepticism and only use them as one more perspective to consider in decision making when deciding on infrastructure project investment.

Traffic modelling is a tool as others have said to compare scenarios but they are based on a point of time and just predict the same trends/policies and behaviours forwards in most instances. We are starting to consider predict and provide scenarios but, in my opinion, policy and decision makers are struggling with this concept despite the requirement to meet certain targets such as a reduction in VKT etc. We seem more comfortable to “miss” targets than to understand what we need to do now to meet them in the future.

I would just recommend you to keep in mind that traffic simulation is just a tool, and that it definitely cannot be the only tool you should use for planning transport and mobility in a city. It does give you interesting insights (as long as it is well calibrated), but never forget to use it in addition to some more qualitative analysis, field studies, public participation processes, etc. We’re not planning cities for cars anymore, but cities for people. So, again, traffic simulation will never solve all the issues cities are facing in terms of transport, but we should use it wisely in order to create better cities and make our citizens enjoy the city they live in.

Transport modelling is a tool or software that can be utilised for analysing various infratructure development, simulating real time traffic situations and forecasting future traffic. Modelling is beneficial to see the impact inculcated on the exisiting network due to a infrastructure development. It can utilised for modelling and assessing whether a development is feasible or it would be failure. As a final comment, the model will be realistic or close to realistic based on the quality of data input. The more realistic data, the more realistic will be the output of the modelling.

Traffic simulation plays a pivotal role in forecasting the ramifications of new infrastructure projects on a city’s traffic flow and overall transportation ecosystem. By utilizing sophisticated algorithms, traffic simulations offer a predictive lens to assess the potential impact of proposed infrastructure developments by mimicking real-world traffic scenarios to gauge the potential bottlenecks, congestion points, and changes in travel times. Through these simulations, planners can fine-tune designs, anticipate challenges, and optimise infrastructure to enhance traffic efficiency and alleviate potential issues, thus empowering decision-makers to make informed choices that can positively shape urban mobility and transportation networks.