Hierarchical Agent-Based Modeling for Improved Traffic Routing

Abstract

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.

Completion Rate on Informatic Studies- Prague University of Economics and Business

“…The car driver behaviour is modelled using the state chart (Figure 2), which is based on research presented in (Markkula et al, 2012). In complex scenarios such as a traffic accident, ABM can effectively simulate human perception and decision making and consequently help understand and improve transport systems (Alqurashi & Altman, 2019;Tchappi Haman et al, 2017).…”

A Microservices based Approach for City Traffic Simulation

“…Author in [1] describes an Agent Based Model (ABM) for improved traffic routing and achieve a system-optimal traffic flow. The similarity with the current paper is that the data is generating at the agent level and the decision remains at the same level, although there are two layers in total.…”

“…The second layer is the macroscopic layer which facilitates the communications between agents. However, the main difference is that in [1] an agent is able communicate only with the surrounding ones through the use of cellular automata approach. Agents are communicating a handful of data with their co-participants within a certain range: position, velocity, route and type.…”

Guiding crowds when facing limited compliance: Simulating strategies

“…They assume that every pedestrian perfectly follows instructions. Alqurashi et al [ 38 ] describe an agent-based traffic simulator for cars and pedestrians. The goal is to offer an environment to test guiding strategies.…”