Empirical investigation of the emission-macroscopic fundamental diagram

Vehicle emissions are a major contributor of air pollution in urban areas, with severe consequences for public health and the environment. This paper focuses on analyzing vehicle emissions in a multimodal urban context to better understand its determinants and investigate relations between emissions and congestion patterns. Thousands of naturalistic trajectories collected with a swarm of drones during the pNEUMA experiment are analyzed and EPA's microscopic emission model, project level MOVES, is implemented to estimate vehicular emissions. The method is developed and illustrated with a CO2 analysis. The results empirically show the aggregated relationships between congestion and vehicular emissions, while accounting for the individual characteristics of each trajectory. These systematic relationships on a network scale with the use of empirical data, allow us to extend the macroscopic fundamental diagram (MFD) to the emissions-MFD (e-MFD). The spatiotemporal distribution of emissions is also studied, highlighting areas with high concentration over the urban area.

City size, network structure and traffic congestion

Nikolaos Geroliminis

This paper presents an alternative approach for analyzing the relationship between land use and traffic congestion by employing the Macroscopic Fundamental Diagram (MFD). The MFD is an empirically observed relationship between traffic flow and traffic density at the level of an urban region, including hypercongestion, where flow decreases as density increases. This approach is consistent with the physics of traffic and allows the parsimonious modeling of intra-day traffic dynamics and their connection with city size, land use and network characteristics. The MFD can accurately measure the inefficiency of land and network resource allocation due to hypercongestion, in contrast with existing models of congestion. The findings reinforce the 'compact city' hypothesis, by favoring a larger mixed-use core area with greater zone width, block density and number of lanes, compared to the peripheral area. They also suggest a new set of policies, including the optimization of perimeter controls and the fraction of land for transport, which constitute robust second-best optimal strategies that can further reduce congestion externalities. (C) 2013 Elsevier Inc. All rights reserved.

Elsevier2013

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.

Elsevier2014

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

Konstantinos Ampountolas, Nikolaos Geroliminis, Nan Zheng

Elsevier2014