Spatial and Temporal Analysis of Congestion in Urban Transportation Networks

Research on congestion and propagation in large urban city networks has been mainly based on microsimulations of link-level traffic dynamics. However, both the unpredictability of travel behaviors and high complexity of accurate physical modeling remain challenging and simulation results may be far time consuming and not realistic. It has been recently shown that amacroscopic fundamental diagram (MFD) linking space-mean network flow, density and speed exists in the urban transportation networks under some conditions. An MFD is further well defined if the network is homogeneous with links of similar properties. This collective behavior concept can also be utilized to introduce simple control strategies to improve mobility in homogeneous city centers without the need for details in individual links. However many real urban transportation networks are heterogeneous with different levels of congestion. In order to study the existence of MFD and the feasibility of simple control strategies to improve network performance in heterogeneously congested networks, this thesis mainly focuses on three issues: (1) static partitioning of traffic networks, (2) congestion propagation and dynamic partitioning, and (3) the effect of network structure on congestion propagation. Firstly, we study the static partitioning of transportation networks based on the spatial features of congestion during a specific time period. A partitioning mechanism which consists of three consecutive algorithms, is designed to minimize the variance of link densities while maintaining the spatial compactness of the clusters. Secondly we explore the dynamics of traffic conditions and thus the corresponding dynamic partitioning scheme. We reveal the hidden information during the process of congestion formation by exploring empirical data from large-scale urban networks. Specifically, we aim at studying the spatiotemporal relation of congested links, observing congestion propagation from an macroscopic perspective, and finally identifying critical congestion regimes to aid the design of peripheral control strategies. Finally, we study the formation of traffic congestion by simulation in large scale cities with different network structures. A parsimonious model of congestion propagation is developed and validated by real data in San Francisco in US and Shenzhen in China (20000 taxis with 30 million logs per day). The effect of network structure on congestion propagation is investigated by simulations conducted in a variety of network structures.

A Dynamic Cordon Pricing Scheme combining a Macroscopic and an Agent-based traffic Models

Nikolaos Geroliminis, Nan Zheng

Pricing is considered an effective management policy to reduce traffic congestion in transportation networks. In this paper we combine a macroscopic model of traffic congestion in urban networks with an agent-based simulator to study congestion pricing schemes. The macroscopic model, which has been tested with real data in previous studies, represents an accurate and robust approach to model the dynamics of congestion. The agent-based simulator can reproduce the complexity of travel behavior in terms of travelers' choices and heterogeneity. This integrated approach is superior to traditional pricing schemes. On one hand, traffic simulators (including car-following, lane-changing and route choice models) consider travel behavior, i.e. departure time choice, inelastic to the level of congestion. On the other hand, most congestion pricing models utilize supply models insensitive to demand fluctuations and non-stationary conditions. This is not consistent with the physics of traffic and the dynamics of congestion. Furthermore, works that integrate the above features in pricing models are assuming deterministic and homogeneous population characteristics. In this paper, we first demonstrate by case studies in Zurich urban road network, that the output of a agent-based simulator is consistent with the physics of traffic flow dynamics, as defined by a Macroscopic Fundamental Diagram (MFD). We then develop and apply a dynamic cordon-based congestion pricing scheme, in which tolls are controlled by an MFD. And we investigate the effectiveness of the proposed pricing scheme. Results show that by applying such a congestion pricing, (i) the savings of travel time at both aggregated and disaggregated level outweigh the costs of tolling, (ii) the congestion inside the cordon area is eased while no extra congestion is generated in the neighbor area outside the cordon, (iii) tolling has stronger impact on leisure-related activities than on work-related activities, as fewer agents who perform work-related activities changed their time plans. Future work can apply the same methodology to other network-based pricing schemes, such as area-based or distance-traveled-based pricing. Equity issues can be investigated more carefully, if provided with data such as income of agents. Value-of-time-dependent pricing schemes then can also be determined. (C) 2012 Elsevier Ltd. All rights reserved.

2012

Empirical Observations of Congestion Propagation and Dynamic Partitioning with Probe Data for Large-Scale Systems

Nikolaos Geroliminis, Yuxuan Ji

Research on congestion propagation in large urban networks has been based mainly on microsimulations of link-level traffic dynamics. However, both the unpredictability of travel behavior and the complexity of accurate physical modeling present challenges, and simulation results may be time-consuming and unrealistic. This paper explores empirical data from large-scale urban networks to identify hidden information in the process of congestion formation. Specifically, the spatiotemporal relation of congested links is studied, congestion propagation is observed from a macroscopic perspective, and critical congestion regimes are identified to aid in the design of peripheral control strategies. To achieve these goals, the maximum connected component of congested links is used to capture congestion propagation in the city. A data set of 20,000 taxis with global positioning system (GPS) data from Shenzhen, China, is used. Empirical macroscopic fundamental diagrams of congested regions observed during propagation are presented, and the critical congestion regimes are quantified. The findings show that the proposed methodology can effectively distinguish congestion pockets from the rest of the network and efficiently track congestion evolution in linear time O(n).

Natl Acad Sciences2014

A three-dimensional macroscopic fundamental diagram for mixed bi-modal urban networks

Konstantinos Ampountolas, Nikolaos Geroliminis, Nan Zheng

Recent research has studied the existence and the properties of a macroscopic fundamental diagram (MFD) for large urban networks. The MFD should not be universally expected as high scatter or hysteresis might appear for some type of networks, like heterogeneous networks or freeways. In this paper, we investigate if aggregated relationships can describe the performance of urban bi-modal networks with buses and cars sharing the same road infrastructure and identify how this performance is influenced by the interactions between modes and the effect of bus stops. Based on simulation data, we develop a three-dimensional vehicle MFD (3D-nu MFD) relating the accumulation of cars and buses, and the total circulating vehicle flow in the network. This relation experiences low scatter and can be approximated by an exponential-family function. We also propose a parsimonious model to estimate a three-dimensional passenger MFD (3D-pMFD), which provides a different perspective of the flow characteristics in hi-modal networks, by considering that buses carry more passengers. We also show that a constant Bus-Car Unit (BCU) equivalent value cannot describe the influence of buses in the system as congestion develops. We then integrate a partitioning algorithm to cluster the network into a small number of regions with similar mode composition and level of congestion. Our results show that partitioning unveils important traffic properties of flow heterogeneity in the studied network. Interactions between buses and cars are different in the partitioned regions due to higher density of buses. Building on these results, various traffic management strategies in hi-modal multi-region urban networks can then be integrated, such as redistribution of urban space among different modes, perimeter signal control with preferential treatment of buses and bus priority. (C) 2014 Elsevier Ltd. All rights reserved.