The Relationship between Traffic Safety and Macroscopic Fundamental Diagram (MFD)

Abstract

The Macroscopic Fundamental Diagram (MFD) is a common tool of choice for evaluating and controlling urban traffic networks. The MFD captures the relationship between traffic parameters that reflect on the network behaviour, including the average network density, speed and flow. Considerable research has been conducted in recent years on the urban MFD and its use for area-wide network monitoring and control purposes to improve a network's operational efficiency. An important consideration in network traffic performance is its safety performance. However, there is an apparent lack of understanding on how the MFD is connected with road safety. This thesis explores the relationship between MFD and safety performance on urban network, through proposing a novel theoretical model, referred to as a "Macroscopic Safety Diagram" (MSD). The MSD relates the probability of crash occurrence in the network with its current state (i.e., average density). The safety of urban networks is vital given the characteristic nature of urban traffic that is dynamically evolving. In this thesis, a theoretical model is presented to show that MSDs exist for networks that have a well-defined network MFD. Furthermore, a proof is provided to show that the density associated with maximum crash propensity is larger than the density associated with maximum network performance. This finding suggests that congested states are not only inefficient in urban networks, but they might also be more unsafe. These theoretical results are validated using a surrogate safety assessment model in a microsimulation for 2 networks: 1) 10 x 10 grid network and 2) city of Bellevue/Redmond, Washington, USA network. Additionally, field empirical data from a small arterial network in Riyadh, the capital and largest city of the Kingdom of Saudi Arabia is adopted to validate the results. The existence of such MSDs can be used to evaluate safety performance at the network level. It can also be used to develop more comprehensive network-wide control policies that can ensure both safe and efficient network operations.