Modelling Driver Interdependent Behaviour in Agent-Based Traffic Simulations for Disaster Management

Handford, David; Rogers, Alex

doi:10.1007/978-3-642-19875-5_21

Cited by 9 publications

(5 citation statements)

References 9 publications

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“…The problem here with such centralized system is that the control is on only one system(central server), which is very vulnerable in practice. David Handford and Alex Rogers [3] have used utility based path trees to represent the factors which affect agent decisions. A multi agent approach especially a holonic approach [6] is very useful to describe such units.…”

Section: Related Workmentioning

confidence: 99%

Multi agent based railway scheduling and optimization

Dalapati

Singh

Dutta

et al. 2014

TENCON 2014 - 2014 IEEE Region 10 Conference

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This paper proposes a multi agent based timetable scheduling algorithm for railway system which handles the in−between time delay of the newly introduced train. The delay management indeed optimizes the total journey time, hence increases the total utility of the whole railway system as well.Here we show that schedule generated by our proposed algorithm is the most optimized schedule. It is done by using the notion of DCOP(Distributed Constraint Optimization Problem), where we define some metric to analyze the system to achieve our goals. We use JADE(Java Agent DEvelopment Framework) platforms to simulate our work and test it using a small network. We also take a small case study to compare our proposed work with the existing one and the results are therefore presented.

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Section: Related Workmentioning

confidence: 99%

Multi agent based railway scheduling and optimization

Dalapati

Singh

Dutta

et al. 2014

TENCON 2014 - 2014 IEEE Region 10 Conference

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“…ABM have been applied for building and testing theories in stock markets [45][46][47], consumer behaviors [48][49][50][51][52][53], and psychological cooperation [54][55][56][57]. For driver behaviors in particular [58][59][60][61][62][63][64][65][66], ABMs are used to simulate how the behavior of a driver (an individual agent) will affect other drivers (other agents) and the evolving traffic patterns (emergent population behavior). Rather than individual isolated decisions, social behaviors often resulted from interactions among people with diverse backgrounds over time.…”

Section: Computer Simulation Of Social Networkmentioning

confidence: 99%

Larger social networks may increase stigma against vocal illness: An integrated empirical and computational study of deciphering help-seeking behaviors and vocal stigma

Glick,

Jones,

Martignetti

et al. 2023

Preprint

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BackgroundIndividuals with a stigmatized medical condition are often reluctant to seek medical help. Among professionals, singers and actors often experience stigma associated with voice disorders. Scientific evidence for vocal stigma is, however, limited and primarily anecdotal. No quantitative research has explored the impact that vocal stigma may have on help-seeking behavior in professional vocal performers. This study deployed and integrated empirical and computational tools to (1) quantify the experience of vocal stigma and help-seeking behaviors and (2) predict their modulations with peer influences in social networks.MethodsExperience of vocal stigma and information-motivation-behavioral (IMB) skills were prospectively profiled using online surveys from a total of 403 Canadians (200 vocal performers and 203 controls). The survey data were used to formulate an agent-based network model that numerically simulates the effect of social interactions on vocal stigma and help-seeking behaviors. Each virtual agent updates their IMB states via social interaction, which in turn changes their self- and social-stigma states. Profiles from vocal performers and non-vocal performers were compared as a function of network size. Network analysis was performed to evaluate the effect of social network structure on the flow of information and motivation among virtual agents.ResultsOver 4000 simulation runs in each context, larger social networks are more likely to contribute to an increase in vocal stigma. For small social networks, total stigma was reduced with higher total IMB but much less so for large networks with around 400 agents. For the agent population of vocal performers with high social-stigma and risk for voice disorder, their vocal stigma is resistant to large changes in IMB. Agents with extreme IMB and stigma values are also likely to polarize their networks faster in larger social groups.ConclusionsWe used empirical surveys to contextualize vocal stigma and IMB in real world populations and developed a computational model to theorize and quantify the interaction among stigma, health-seeking behavior and influence of social interactions. This work establishes an effective, predictable experimental platform to provide scientific evidence in developing public policy or social interventions of reducing health stigma in voice disorders and other medical conditions.

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“…The model is divided into two main levels ( Figure 2): First, the low level which contains mostly processing and calculations. This simulates the real transportation network ü ü ü SUMO 3,4 ü ü ü VSimRTI 5 ü ü ü Al-Dmour 6 ü ü ü Araujo et al 7 ü ü ü Cajias et al 8 ü ü ü Certicky et al 9 ü ü ü Frick 10 ü ü ü Grether and Nagel 11 ü ü ü Handford and Rogers 12 ü ü ü Holmgren et al 13 ü ü ü Mounir et al 14 ü ü ü Ramos et al 16 ü ü ü Taha and Ibrahim 17 ü ü ü Xiao et al 18 ü ü ü Xu and Tan 19 ü ü ü Zacharewicz et al 20 ü ü ü Zhang et al 21 ü ü ü Vietnamese circulation situation -ü ü ü ü throughout the day and then calculates the level of congestion in the streets of the network. This data could be saved into storage and then displayed at a later time.…”

Section: Agent-based Model For Simulation Of Traffic Network Statusmentioning

confidence: 99%

An agent-based model for simulation of traffic network status: Applied to Hanoi city

Nguyễn

2016

SIMULATION

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In recent times there have been many agent-based simulation models proposed for transportation network simulation. Intuitively, these models are applicable for the transportation simulation of modern cities in developed countries where the transportation network is very well organized: Roads are separated into lanes; most transportation occurs using vehicles; and almost all drivers respect the circulation rule. However, these models are not suitable for developing countries where the transportation network is unorganized. The reasons for this are as follows: (1) there is no lane on the road; (2) most vehicles are motorbikes; and (3) not many drivers respect the circulation rule. This paper introduces an agent-based model for transportation network simulation in which each form of transport is modeled as an agent exhibiting full features of unorganized circulation behavior. The model is designed for a large scale and instead of displaying the circulation for all individual modes of transport, the model displays only the status of the traffic network. The simulation of circulation is therefore considered as a background process. The simulation is launched and the results are obtained before being displayed. This model is applied to the traffic network of Hanoi to analyze the hot or bottle neck points on the transportation network during rush hours in the city.

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Modelling Driver Interdependent Behaviour in Agent-Based Traffic Simulations for Disaster Management

Cited by 9 publications

References 9 publications

Multi agent based railway scheduling and optimization

Multi agent based railway scheduling and optimization

Larger social networks may increase stigma against vocal illness: An integrated empirical and computational study of deciphering help-seeking behaviors and vocal stigma

An agent-based model for simulation of traffic network status: Applied to Hanoi city

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