Evacuation plan of the city of almere: simulating the impact of driving behavior on evacuation clearance time

Tu, Huizhao; Tamminga, Guus; Drolenga, Hans; Wit, Jeroen de; Berg, Wouter van der

doi:10.1016/j.proeng.2010.07.008

Cited by 34 publications

(21 citation statements)

References 13 publications

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“…In a number of studies using microscopic models, model parameters describing driving behaviour (such as headway, acceleration, reaction time) have been adjusted for the case of emergency evacuation (e.g., Tu et al 2010). Other than that, the model structure and parameter settings are typically not changed.…”

Section: Past and Current Evacuation Traffic Simulation Modelsmentioning

confidence: 99%

A review on travel behaviour modelling in dynamic traffic simulation models for evacuations

2011

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Dynamic traffic simulation models are frequently used to support decisions when planning an evacuation. This contribution reviews the different (mathematical) model formulations underlying these traffic simulation models used in evacuation studies and the behavioural assumptions that are made. The appropriateness of these behavioural assumptions is elaborated on in light of the current consensus on evacuation travel behaviour, based on the view from the social sciences as well as empirical studies on evacuation behaviour. The focus lies on how travellers' decisions are predicted through simulation regarding the choice to evacuate, departure time choice, destination choice, and route choice. For the evacuation participation and departure time choice we argue in favour of the simultaneous approach to dynamic evacuation demand prediction using the repeated binary logit model. For the destination choice we show how further research is needed to generalize the current preliminary findings on the location-type specific destination choice models. For the evacuation route choice we argue in favour of hybrid route choice models that enable both following instructed routes and en-route switches. Within each of these discussions, we point at current limitations and make corresponding suggestions on promising future research directions.

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Section: Past and Current Evacuation Traffic Simulation Modelsmentioning

confidence: 99%

A review on travel behaviour modelling in dynamic traffic simulation models for evacuations

2011

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“…In research reported in Tu et al (2010) it was for example assumed that drivers during an emergency situation express anxious behavior due to a mentally demanding situation. Tu et al (2010) subscribe to the assumptions made in Hamdar and Mahmassani (2008).…”

Section: Empirical Driving Behavior In Case Of Emergency Situationsmentioning

confidence: 99%

“…Tu et al (2010) subscribe to the assumptions made in Hamdar and Mahmassani (2008). In their research it is assumed that driving behavior under emergency situations ('extreme conditions') is characterized by an aggressive driving style.…”

Section: Empirical Driving Behavior In Case Of Emergency Situationsmentioning

confidence: 99%

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Longitudinal driving behavior in case of emergency situations: An empirically underpinned theoretical framework

Hoogendoorn

Arem

Brookhuis

2013

Transportation Research Part C: Emerging Technologies

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Adverse conditions have been shown to have a substantial impact on traffic flow operations. It is however not yet clear to what extent emergency situations actually lead to adaptation effects in empirical longitudinal driving behavior, what the causes of these adaptation effects are and how these can best be modeled. In this paper we show using an elaborate driving simulator experiment that emergency situations lead to significant adaptation effects in longitudinal driving behavior. Furthermore we introduce a new theoretical framework. In this framework adaptation effects in longitudinal driving behavior are assumed to consist of compensation effects and performance effects. In order to empirically underpin this framework we show in this paper that compensation effects are reflected in parameter value changes in the Intelligent Driver Model, while performance effects are reflected in a reduction in model performance. Furthermore we show that compensation effects following an emergency situation are reflected in a change in the position of perceptual thresholds in a psycho-spacing model while performance effects are reflected in a reduced sensitivity of acceleration towards lead vehicle related stimuli at the action points. The paper concludes with a discussion as well as recommendations for future research.

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“…及时有效的渔船回港避风是一个不容忽视的终于环节。在应急疏散中涉及人员众多，难以在短时间内让大规模群众完全听从指挥，极易出现个体按照自我意愿自主行动的现象。因此在应急中应充分考虑个体行动的意愿和偏好， Helbing 等人（2000） [4] 在《 Nature》上发表了研究成果，通过人群在恐慌状态下的行为构建了恐慌状态下的人群逃散模型。Hao-Che Wu 等（2012） [5] 在美国卡特里娜和丽塔飓风之后以调查问卷的形式分析疏散时人们的路径选择行为。胡红等（2007） [6] 根据将驾驶员对突发事件的心理行为反应调查，对 GIPPS 跟驰模型进行了改进，建立了车速与安全车距的关系模型。HuizhaoTu 等（2010） [7] 为研究疏散人员的驾驶行为对整个疏散过程的作用，采用 Paramics 微观仿真软件对疏散人员的驾驶行为进行不同情景的模拟仿真，研究车辆加速度、最大行驶速度、平均距离、最小间距等因素对仿真结果的影响。Stern 等人（1989） [8] 利用行为模拟研究了不同类型家庭的行动（外出、在家或睡觉）为整体预警信息传播的影响。Uchida（2012） [9] 研究了在滑坡与预警中人群疏散概率变化的现象。考虑个体行为因素后，系统建模则多数采用基于多主体仿真（Agent-Based Simulation：ABS）手段模拟人群疏散行为。ABS 是一种微观仿真技术，仿真模型中主体具有自主性和目标性，可以与环境和其他主体进行交互（Railsback 等人，2006） [10] 。ABS 技术在应急响应建模中已经有了广泛的应用，Chen 和 Zhan （2008） [11] 研究了城市交通疏散模型；Banerjee 等（ 2009 ） [12] 针对大规模拥堵问题建立仿真模型； Magesh 等（2012） [13] 提出基于 ABS 的预警信息扩散下疏散仿真的框架，其中利用概率原理模拟了疏散中警示邻居的行为。Hui 等人（2008） [14] 利用 …”

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Agent-Based Simulation of Fish Boats Evacuation

Zhao¹,

Huiyan²,

Wang³

2015

JRACR

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Emergency management agencies will organize people to evacuee when disasters are forecasted. However, contradictions between individual behavior and group objective appear frequently during large-scale evacuations, the problem is obviously in the process of fisher boats evacuation. So, this paper set up fisher boats evacuation simulation model considering individual desire of back harbor.In the agent-based model, Typhoon and harbor are inactive agents, government and fisher boats are active agents. Fisher boats make decisions whether back to harbor and which harbor to be choose according of typhoon forecast information and government instruction. The model uses the harbors of Zhejiang province as a case.

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Evacuation plan of the city of almere: simulating the impact of driving behavior on evacuation clearance time

Cited by 34 publications

References 13 publications

A review on travel behaviour modelling in dynamic traffic simulation models for evacuations

A review on travel behaviour modelling in dynamic traffic simulation models for evacuations

Longitudinal driving behavior in case of emergency situations: An empirically underpinned theoretical framework

Agent-Based Simulation of Fish Boats Evacuation

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