Exploring Human and Autonomous Vehicle Interactions through Agent-based Simulation

在这项研究中，我将开发基于主体的城市交通模型(ABM)，为行人运动建模和活动规划做出新的贡献。一套更丰富的行人行为将被建模，这将受到与建成环境和其他道路使用者(即车辆)的互动的影响。这些模型将被用来探索自动驾驶汽车可能产生的影响。感兴趣的行人运动行为是指与过马路相关的行为。该项目将结合现有的模拟行人运动的方法，并开发新的算法，以开发显示文献中观察到的道路过马路行为多样性的行人代理。对行人和自动驾驶车辆之间的交叉路口相互作用进行建模将需要开发行人代理，这些代理对道路不同路段的通行权和迎面而来的车辆构成的风险具有不同的感知。为此，我将把行人运动的社会力模型和路线算法(如洪水填充算法)与新的算法相结合，这些算法决定了行人和车辆主体在十字路口事件中相互作用的结果。这些新颖的算法将探索在自动驾驶车辆存在时以及不同代理之间这些交互可能会有所不同的方式。例如，胆小的行人会严格等待，直到他们的通行权得到保证。机会主义的行人会试图利用车流中的空隙进入十字路口。这将允许对自动驾驶车辆的机动性进行比目前文献中更全面的评估。这项研究的另一个贡献将是对这些行为进行建模的地理范围。ABM将由数千名特工组成，他们在一个城镇大小的地理区域内移动。这一规模将允许代理的行为变化对宏观交通模式的影响。这项工作的延伸将开发新的方法来模拟人们在城市地区移动时计划和参与的活动。社会和休闲活动在城市流动性模型中被低估，使城市道路将人们运送到地方的作用与他们作为地方本身的角色相背离。我将开发新的算法，对城市地区人们进行的有计划和无计划的社交和休闲活动进行建模。通过将这些活动纳入城市机动性的ABM，将能够更好地评估交通系统在促进和阻碍这些活动方面的作用。

In this research, I will develop agent-based models (ABM) of urban mobility which make novel contributions to the modelling of pedestrian movement and activity planning. A richer set of pedestrian behaviours will be modelled which will be affected by interactions with the built environment and other road users, namely vehicles. The models will be used to explore the possible impacts of autonomous vehicles. The pedestrian movement behaviours of interest are those related to crossing the road. This project will combine existing methods for modelling pedestrian movement and develop novel algorithms in order to develop pedestrian agents which exhibit the diversity of road crossing behaviour observed in the literature. Modelling road crossing interactions between pedestrians and autonomous vehicles will require developing pedestrian agents with heterogeneous perceptions of right-of-way in different sections of the road and of risk posed by oncoming vehicles. To do this, I will combine social force models of pedestrian movement and routing algorithms such as the flood fill algorithm with novel algorithms which determine the outcome of pedestrian and vehicle agent interactions in road crossing events. These novel algorithms will explore ways in which these interactions are likely to differ in the presence of autonomous vehicles and between different agents. For example, timid pedestrians will strictly wait until their right of way is assured. Opportunistic pedestrians will seek to exploit gaps in traffic to crossroads. This will allow a more holistic appraisal of autonomous vehicle mobility than is currently present in the literature. An additional contribution of this research will be the geographic scale over which these behaviours are modelled. The ABM will consist of thousands of agents moving across a town-sized geographic area. This scale will allow the effects of changes in behaviour of agents on macroscopic traffic patterns. An extension to this work will develop novel methods for modelling the activities people plan and participate in as they move through urban areas. Social and leisure activities are underrepresented in models of urban mobility, biasing the role of urban roads to move people to places against their role as places themselves. I will develop novel algorithms for modelling planned and unplanned social and leisure activities practised by people in urban areas. By including these activities in an ABM of urban mobility, the role of the transport system in facilitating and hindering them will be able to be better evaluated.