Modeling the transport demand of same day visitors, short vacationers and vacationers in large cities

不常见的休闲交通是交通中颗粒物和NOx排放的主要来源之一。不寻常的休闲交通包括当日游客和(短期)度假者的到达和离开，以及他们在目的地的旅行。例如，在卡塞尔市，游客已经进行了七分之一的旅行。因此，参观者占到了大约。卡塞尔所有道路的14%。然而，在以旅游为主的城市，这一比例可能会更高。特别是在过去几年里，不同寻常的休闲交通流量录得高于平均水平的增长，这主要归功于私家车。预计未来(短期)假期和私人一日游的交通量将进一步增长。因此，实现环境和气候变化目标变得越来越重要。然而，在交通规划领域以及机动性和旅游研究领域，由于对机动性行为的调查主要集中在日常机动性上，到目前为止，罕见的休闲交通在很大程度上被忽视了。因此，在基于模型的交通预测中，不常见的休闲交通也被忽视了。本研究的总体目标是开发一种通用的基于模型的规划工具，以提高基于模型的交通预测的质量。它将基于通过因果关系来描述不寻常的休闲交通。因此，将有可能对不常见的休闲交通措施进行基于模型的调查。此外，这些措施对环境和交通的影响也可以估计出来。以下目标来自上述总体目标：-开发一个宏观模型来描述不常见的休闲交通，由理论模型方法(算法)和相应的调查概念组成，-为细分市场开发一种方法，该方法考虑到他们行为的同质性和整体预测能力，-在两个细分市场上示范应用该模型，-基于文献研究、现有数据和我们自己的调查，更详细地了解大城市不常见的休闲交通的结论。通过这个项目的结果，将有可能在战略交通规划领域内更有效地影响不常见的休闲交通。由于模型被认为对措施反应敏感，因此可以模拟不同的措施或一揽子措施。此外，可以更准确地估计这些措施实施后的影响。此外，当地和旅游决策者和管理部门都将受益于预期的调查结果，因为该项目的结果为了解不寻常的休闲交通这一主题提供了重要的见解。

Uncommon leisure traffic constitutes one of the main sources of particulate and NOx-emissions caused in traffic. Uncommon leisure traffic comprises both arrival and departure of same-day visitors and (short) vacationers, and their trips at the destination. In the city of Kassel, for example, visitors already conduct one out of seven trips. Visitors therefore account for approx. 14% of all ways in the city of Kassel. However, this share is likely to be even higher in cities with a predominant tourist orientation. Uncommon leisure traffic in particular has recorded an above-average rise in traffic volume during the last few years which mainly has to be attributed to private cars. A further growth of traffic volume due to (short) vacations and private day trips is expected in the future. Accordingly, the achievement of environmental and climate change objectives is gaining in importance. However, in the field of transportation planning as well as in the area of mobility and tourism research, uncommon leisure traffic has been largely neglected so far, since surveys on mobility behaviour mainly focus on everyday mobility. Accordingly, uncommon leisure traffic has been neglected in model-based traffic forecasts, too.The overall objective of this research project is to develop a universally applicable model-based planning tool that will enhance the quality of model-based traffic forecasts. It will be based on a depiction of uncommon leisure traffic by means of cause-effect correlations. Thus, a model-based investigation of measures concerning uncommon leisure traffic will be made possible. Moreover, the impact of these measures on the environment and traffic can be estimated as well. The following objectives are derived from the abovementioned overall objective:- development of a macroscopic model to depict uncommon leisure traffic, being composed of theoretical model approaches (algorithms) and a corresponding survey concept,- development of an approach for market segments which considers the homogeneity in their behaviour as well as the overall forecasting ability, - exemplary application of the model on two market segments, - gain more detailed knowledge of conclusions on uncommon leisure traffic in big cities, based on literature research, existing data and our own surveys.With the results of this project, it will be possible to influence uncommon leisure traffic more effectively within the field of strategic transportation planning. Since the model is supposed to react sensitively to measures, different measures or packages of measures can be simulated. Also, the impact these measures have after their implementation can be estimated more precisely. Furthermore, both local and touristic decision-makers and administrations will benefit from the expected findings as the results of this project offer important insights into the subject of uncommon leisure traffic.