TP4.3: Traffic Management on Major Events

Subproject manager
Prof. Dr. Fritz Busch
Subproject manager
Dr. Antonios Tsakarestos
Researcher (50%)
Sasan Amini
Researcher (50%)
Eftychios Papapanagiotou


The transportation system is a critical infrastructure for the movement of people and goods. However, major events, including both unexpected incidents and planned special events put its reliability at high risk. In order to reduce the adverse impact of such situations, traffic management authorities and emergency reposnce units must make decision and implement measures in a very limited time. These measures are in most cases are derived from checklists and manuals which are not necessarily optimal. Figure 1 implies that better traffic management could eventually expedite the recovery of the network performance back to the pre-incident situation. Admittedly, it is vital to develop traffic management strategies that take into account the spatiotemporal characteristics of the event.


Figrue 1: The impact of management measures on robustness and recovery
Major events are discussed in many studies, but are rarely defined. As discussed in [1] the current approach to define major events is to provide a list of specific example events such as a football match or wildfire. Therefore, the main goal of this subproject is to define major events with respect to their spatiotemporal impacts on the transportation network and generate appropriate traffic management strategies in real-time according to those impacts. To do so, the concept of Network Fundamental Diagram (NFD) is employed to quantify the production (trip completion) in a road network. A probability distribution function which indicates the level of production at a given accumulation (average density) will be used to detect the unlikely situations. Based on such a function a singularity index [2] or resilience index [3] could be defined to quantitively assess the netwrok irrigularity.

Once an extreme congestion has been identified the following 4-step methodology will be employed to generate the management strategies:

Modelling the current situation: development of a mesoscopic traffic simulation to estimate the current situation and evaluation of the implemented strategies


Figure 2: 4-step approach to generate traffic management strategies [3]

Strategy generation: generating strategies by combining the available primary measures such as turning restrictions, alternative routes, contraflow streets, etc.

Strategy Optimization: optimization of the details of the generated strategies e.g. beginning time and duration, spatial attributes, drivers’ reaction to the provided information, etc.

System update: the network will be monitored to assess the effectiveness of the implemented strategy. The whole process will be continued based on a rolling horizon approach to adapt the necessary changes.

Reference
[1] Amini, S.; Papapanagiotou, E. and Busch, F. (2016): Traffic Management for major Events in Digital Mobility Platforms and Ecosystems: State of the art report. Pp. 187-197. http://dx.doi.org/10.14459/2016md1324021
[2] Horiguchi et al. (2010), Traffic Information Provision Suitable for TV Broadcasting Based on Macroscopic Fundamental Diagram from Floating Car Data,13th International IEEE Annual Conference on Intelligent Transportation Systems
[3] Hoogendoorn et al. (2015), Applications of the Generalized Macroscopic Fundamental Diagram, Traffic and Granular Flow ’13, DOI: 10.1007/978-3-319-10629-8_65