The extensive development of autonomous vehicles (AVs) is set to revolutionise the way of travelling. Research suggests that the introduction of AVs may affect travel behaviour and choices, resulting in long-term changes in land use. Accessibility is an important concept that connects transportation and land use, providing a holistic performance measure for the transport-land use system. However, this concept has not been adequately capitalised in studies that attempt to understand the impact of AVs on location choice decisions. To explore this knowledge gap, we proposed an agent-based simulation framework that integrates with accessibility constraints to study how AVs influence behavioural and location choices. The framework consists of an activity-based travel demand model with accessibility constraints and a dynamic transport assignment model. The accessibility constraints are derived from individuals’ travel time budgets based on activity-travel survey data. We applied the agent-based simulation framework to Clayton, Australia, and focused on discretionary activity location choices. Various values of travel time and vehicle running costs underpinned by the use of AVs were examined. While most studies have concluded that AVs can significantly increase trip lengths for daily activities, our results demonstrate that even when AVs are used, the movement of individuals is still limited by spatio-temporal constraints of accessibility. As a result, we predict that the increase in discretionary trip lengths and their impact on traffic congestion is modest.

自动驾驶汽车 (AV) 的广泛发展必将彻底改变出行方式。研究表明，自动驾驶汽车的引入可能会影响出行行为和选择，从而导致土地利用的长期变化。可达性是连接交通和土地利用的重要概念，为交通-土地利用系统提供了整体绩效衡量标准。然而，在试图了解自动驾驶汽车对位置选择决策影响的研究中，这一概念尚未得到充分利用。为了探索这一知识差距，我们提出了一个基于代理的模拟框架，该框架与可访问性约束相结合，以研究自动驾驶汽车如何影响行为和位置选择。该框架由具有可达性约束的基于活动的出行需求模型和动态交通分配模型组成。可达性限制源自基于活动旅行调查数据的个人旅行时间预算。我们将基于代理的模拟框架应用于澳大利亚克莱顿，并重点关注自主活动地点的选择。研究人员对使用自动驾驶汽车所带来的各种出行时间和车辆运行成本进行了研究。虽然大多数研究得出的结论是自动驾驶汽车可以显着增加日常活动的行程长度，但我们的结果表明，即使使用自动驾驶汽车，个人的移动仍然受到可达性的时空限制。因此，我们预测可自由支配的出行长度的增加及其对交通拥堵的影响是适度的。