Towards an Multilevel Agent-based Model for Traffic Simulation (original) (raw)
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An Agent-Based Simulation Model for Urban Traffic System
Computer and Information Science, 2011
In this paper, we propose a model for vehicle traffic based on multi-agent systems and account suppositions and its issues. Traffic is an ever-growing problem as population and the number of drivers around the world increase exponentially. Previously, fluid flow models have been used in an attempt to model traffic. Based on recent studies, only agent based models can accurately model a traffic scenario. This is because small perturbations could have a butterfly-like effect, which causes a rapid change in the entire system.
Hierarchical Agent-Based Modeling for Improved Traffic Routing
Applied sciences, 2019
Agent-based model (ABM) simulation is a bottom-up approach that can describe the phenomena generated from actions and interactions within a multiagent system. An ABM is an improvement over model simulations which only describe the global behavior of a system. Therefore, it is an appropriate technology to analyze emergent phenomena in social sciences and complex adaptive systems such as vehicular traffic and pedestrian crowds. In this paper, a hybrid agent-based modeling framework designed to automate decision-making processes during traffic congestion is proposed. The model provides drivers with real-time alternative routes, computed via a decentralized multi-agent model, that tries to achieve a system-optimal traffic distribution within an entire system, thus reducing the total travel time of all the drivers. The presented work explores a decentralized ABM technique on an autonomous microgrid that is represented through cellular automata (CA). The proposed model was applied to high-density traffic congestion events such as car accidents or lane closures, and its effectiveness was analyzed. The experimental results confirm the efficiency of the proposed model in not only accurately simulating the driver behaviors and improving vehicular traffic flows during congestion but also by suggesting changes to traffic dynamics during the simulations, such as avoiding obstacles and high-density areas and then selecting the best alternative routes. The simulation results validate the ability of the proposed model and the included decision-making sub-models to both predict and improve the behaviors and intended actions of the agents.
Computers, Environment and Urban Systems, 2014
Urban road traffic dynamics are the product of the behaviours and interactions of thousands, often millions of individuals. Traditionally, models of these phenomena have incorporated simplistic representations of individual behaviour, ensuring the maximisation of simulation scale under given computational constraints. Yet, by simplifying representations of behaviour, the overall predictive capability of the model inevitably reduces. In this work a hybrid agent-based modelling framework is introduced that aims to balance the demands of behavioural realism and computational capacity, integrating a descriptive representation of driver behaviour with a simplified, collective model of traffic flow. The hybridisation of these approaches within an agent-based modelling framework yields a representation of urban traffic flow that is driven by individual behaviour, yet, in reducing the computational intensity of simulated physical interaction, enables the scalable expansion to large numbers of agents. A real-world proofof-concept case study is presented, demonstrating the application of this approach, and showing the gains in computational efficiency made in utilising this approach against traditional agent-based approaches. The paper concludes in addressing how this model might be extended, and exploring the role hybrid agent-based modelling approaches may hold in the simulation of other complex urban phenomena.
Multi-Agent Based Simulation of Individual Traffic in Berlin
2005
Multi-agent simulations of traffic are widely expected to become an important tool for transportation planning in the mid-term future. This paper reports on the first steps of a project which aims to apply such a tool to a large real world scenario based on datasets create in the normal transportation planning process for use with established transportation planning tools. As the first steps of the implementation show, many problems related to different data semantics and the different modelling concepts can occur. In most cases, theses problems can be resolved by minor adoptions of the software or the data. The evaluation of a large scenario of several hundred thousand agents shows that performance issues do no longer hinder applications of this kind. Thereby, the implementation of this scenario helps to push multi-agent traffic simulation tools forward to real world applications.
A Model-Driven Engineering Process for Agent-based Traffic Simulations
2015
Traffic has an important impact in many aspects of our everyday life, from healthcare to transport regulation or urban planning. Given its complexity, the study in real settings is frequently limited, so researchers resort to simulations. However, realistic simulations are still complex systems. Its development frequently requires multidisciplinary groups, where misunderstandings are frequent, and there is a great variety of potential theories and platforms to consider. In order to reduce the impact of these issues, the Model-Driven Engineering (MDE) of simulations has been proposed. It is focused on developing mainly through models and their semi-automated transformation. Nevertheless, an effective approach of this kind requires the availability of infrastructures that include modelling languages, transformations, tools, and processes to use them. This work presents a MDE process for traffic simulations. It introduces a modelling language and makes uses of available infrastructures in its tasks. The process guides users in creating tailored models for their simulations, and transforming these to code. A case study that uses an existing model for drivers' behaviour and an already available platform to develop a simulation illustrates the approach.
Traffic simulation using agent-based models
… and Automation Technologies, 2009. ICAT 2009. …, 2009
AbstractIn this paper we will build a computer traffic model simulating movement of each individual vehicle through the traffic network and the interactions of that vehicle with other vehicles and semaphores (an agent based model). It will model a simple traffic network (a two way coordinated semaphore system a.k.a. "green wave") to test certain hypotheses on different kinds of semaphore systems. We will show that, with certain limitations , such a model can run on an average PC computer at speed up to ten times the realtime. In order to validate this model, a twoway coordinated semaphore system will be statistically compared to a noncoordinated system, hopefully proving the advantage of semaphore coordination.
HAL (Le Centre pour la Communication Scientifique Directe), 2007
Traffic phenomena come on the one hand from supply / demand mechanisms and on the other hand from the interactions between the various actors involved. Simulation models have been developed for several decades by traffic engineers to reproduce the phenomena. Based on the identification of observed traffic, they are unfortunately limited when the study is related to future situations (i.e. non existing, thus non observable, ones). Driver models have also been developed for decades by psychologists, but these models are also often very limited (i.e. they deal with very few and very specific driving tasks) and not operational (i.e. they are conceptual models). The simulation of the impact of a change in the traffic system is nevertheless a key issue, both from the safety and the capacity standpoints. The behaviour of drivers facing a new situation is extremely difficult to forecast, since human beings easily adapt their behaviour in response to infrastructure and equipments. They will not always use them according to designers' expectations (a rational use for collective optimisation) but, on the contrary, they very often follow individual issues, such as minimisation of constraints or economy of manoeuvres. These different standpoints often lead to incoherences between design and uses, which have a negative impact on safety as well as on capacity. Designing tools allowing a systemic approach of changes in the traffic system is the main objective of the INRETS MSIS department. Based on the joint use of a driving simulator and behavioural traffic simulation, the proposed approach (called "integrated approach") consists of a four stage iterative process which jointly uses a driving simulator and a behavioural microscopic traffic simulation model. To carry on studies according to this approach, MSIS team has designed a behavioural traffic simulation model and a driving simulator architecture, both novel.
2007
Traffic phenomena come on the one hand from supply / demand mechanisms and on the other hand from the interactions between the various actors involved. Simulation models have been developed for several decades by traffic engineers to reproduce the phenomena. Based on the identification of observed traffic, they are unfortunately limited when the study is related to future situations (i.e. non existing, thus non observable, ones). Driver models have also been developed for decades by psychologists, but these models are also often very limited (i.e. they deal with very few and very specific driving tasks) and not operational (i.e. they are conceptual models). The simulation of the impact of a change in the traffic system is nevertheless a key issue, both from the safety and the capacity standpoints. The behaviour of drivers facing a new situation is extremely difficult to forecast, since human beings easily adapt their behaviour in response to infrastructure and equipments. They will not always use them according to designers' expectations (a rational use for collective optimisation) but, on the contrary, they very often follow individual issues, such as minimisation of constraints or economy of manoeuvres. These different standpoints often lead to incoherences between design and uses, which have a negative impact on safety as well as on capacity. Designing tools allowing a systemic approach of changes in the traffic system is the main objective of the INRETS MSIS department. Based on the joint use of a driving simulator and behavioural traffic simulation, the proposed approach (called "integrated approach") consists of a four stage iterative process which jointly uses a driving simulator and a behavioural microscopic traffic simulation model. To carry on studies according to this approach, MSIS team has designed a behavioural traffic simulation model and a driving simulator architecture, both novel.
Extending a generic traffic model to specific agent platform requirements
Computer Science and Information Systems, 2017
Road traffic and its influence over individuals is an important aspect of our life nowadays. Its study in order to understand its dynamics and the factors that affect it is a relevant field of research. Traffic simulations have become a fundamental tool for these studies. They provide a controlled environment to analyse traffic settings. However, they present some shortcomings. One of the main ones is the need of multidisciplinary groups of experts to work with complex models. Communication problems and misunderstandings frequently appear in them, which produce mistakes and bring increased costs. Some works have addressed these issues adopting abstract concepts that can act as bridges among different groups to model and implement simulations. Works that use intelligent agents to represent individuals, and their related simulation platforms, belong to this category. Nevertheless, these platforms are still programmer-oriented, so other experts find difficult to ground their abstract m...
International Journal of Engineering Research and Technology (IJERT), 2020
https://www.ijert.org/a-review-paper-on-modeling-of-traffic-simulation-system-for-dynamic-traffic-with-multi-agent-framework https://www.ijert.org/research/a-review-paper-on-modeling-of-traffic-simulation-system-for-dynamic-traffic-with-multi-agent-framework-IJERTV9IS090205.pdf Traffic in developing and developed countries mostly having heterogeneous traffic conditions. It comprises with wide range of physical dimension of vehicles and its weight. Due to dynamic traffic it causes series stain on road infrastructure and also effect the road condition (Structure & Surface condition), this affect the increasing the road accident. At intersection point due to heavy traffic jam density increases and it reflect the increasing of travelling time (Time & Distance Headway) for the driver it also affect the total cost of the trip as the vehicles always starting in position during jam occur at intersection. For better traffic movement traffic simulation need to be implemented for distribution the traffic lane wise or by size of the vehicles. This article focuses on the study and modeling of dynamic traffic using multi-agent framework. In this review paper different keywords have been consider by every individual researcher, which can be useful for the improvement of traffic condition and reduction of accidents at intersection point or at crossing. There are different types of modal used by the researcher like single regime linear modal, dual regime modal, polynomial modal, exponential modal for the distribution of traffic by considering vehicular characteristic on and geometric design. Intelligent transport can be used for the improvement of traffic condition and it uses the multi agent can be maintained or utilized according to the traffic conditions.