Search for: All records

Urban street networks are subject to a variety of random disruptions. The impact of movement restrictions (e.g., one-way or left-turn restrictions) on the ability of a network to overcome these disruptions—that is, its resilience—has not been thoroughly studied. To address this gap, this paper investigates the resilience of one-way and two-way square grid street networks with and without left turns under light traffic conditions. Networks are studied using a simplified routing algorithm that can be examined analytically and a microsimulation that describes detailed vehicle dynamics. In the simplified method, routing choices are enumerated for all possible origin–destination (OD) combinations to identify how the removal of a link affects operations, both when knowledge of the disruption is and is not available at the vehicle’s origin. Disruptions on two-way networks that allow left turns tend to have little impact on travel distances because of the availability of multiple shortest paths between OD pairs and the flexibility in route modification. Two-way networks that restrict left turns at intersections only have a single shortest-distance path between any OD pair and thus experience larger increases in travel distance, even when the disruption is known ahead of time. One-way networks sometimes have multiple shortest-distance routes and thus travel distances increase less than two-way network without left turns when links are disrupted. These results reveal a clear tradeoff between improved efficiency and reduced resilience for networks that have movement restrictions, and can be used as a basis to study network resilience under more congested scenarios and in more realistic network structures. 

Network macroscopic fundamental diagrams (MFDs) have recently been shown to exist in real-world urban traffic networks. The existence of an MFD facilitates the modeling of urban traffic network dynamics at a regional level, which can be used to identify and refine large-scale network-wide control strategies. To be useful, MFD-based modeling frameworks require an estimate of the functional form of a network’s MFD. Analytical methods have been proposed to estimate a network’s MFD by abstracting the network as a single ring-road or corridor and modeling the flow–density relationship on that simplified element. However, these existing methods cannot account for the impact of turning traffic, as only a single corridor is considered. This paper proposes a method to estimate a network’s MFD when vehicles are allowed to turn into or out of a corridor. A two-ring abstraction is first used to analyze how turning will affect vehicle travel in a more general network, and then the model is further approximated using a single ring-road or corridor. This approximation is useful as it facilitates the application of existing variational theory-based methods (the stochastic method of cuts) to estimate the flow–density relationship on the corridor, while accounting for the stochastic nature of turning. Results of the approximation compared with a more realistic simulation that includes features that cannot be captured using variational theory—such as internal origins and destinations—suggest that this approximation works to estimate a network’s MFD when turning traffic is present.