Urban Network-Wide Traffic Variables and Their Relations

Abstract

Time-lapse aerial photography over the Central Business Districts (CBD) of Austin and Dallas, Texas, has been employed to determine the averages of concentration, speed and fraction of vehicles stopped and to examine the relations among such network-wide averages including the flow which was measured on the ground simultaneously. The results have indicated that the average flow in a street network may indeed be expressed as the product of the space mean speed and concentration. Simultaneous ground experiments have also been conducted in the Austin CBD to investigate the reasonableness of the assumptions of the “two-fluid model,” a curvilinear relation between the trip time and stop time per unit distance, which may be used in characterizing the quality of traffic service in urban street networks. As a result of these simultaneous ground experiments and aerial observations, the assumptions of the model have been verified. Moreover, relations between the fraction of vehicles stopped and concentration as well as between speed and concentration have allowed the two-fluid model to be used to compare the quality of traffic service in various street networks under the same level of concentration. The two-fluid model may then be used to predict, for a given change in vehicular concentration in a street network, the resulting changes in the averages of speed, fraction of vehicles stopped, flow, etc. This is particularly useful as a performance model in urban planning where for a given concentration it is desirable to predict the resulting traffic conditions.

The Spatial Variability of Vehicle Densities as Determinant of Urban Network Capacity

“…Earlier studies looked for macro-scale traffic patterns in data of lightly congested real-world networks (Godfrey 1969;Ardekani & Herman 1987;Olszewski et al 1995) or in data from simulations with artificial routing rules and static demand Williams et al 1987;Mahmassani & Peeta 1993). However, the data from all these studies were too sparse or not investigated deeply enough to demonstrate the existence of an invariant MFD for real urban networks.…”

Multi-gated perimeter flow control of transport networks

“…This discretetime linear model is completely controllable and reachable. The sample time interval T is literally selected to be a common multiple of cycle lengths of all controlled gates at the periphery of the protected network, while T ∈ [3,5] min is usually appropriate for constructing a well-defined outflow function O(n(t)), given experimental data. In principle, origin link dynamics (2) are much faster than the dynamics of the protected network (1) (governed by the NFD, which evolves slowly in time).…”

“…In an attempt to assess the performance of urban networks at a macroscopic level, a parsimonious but not accurate model is often used, which primarily shows the relationship between average network flow and vehicle accumulation or density. A macroscopic model of steady-state urban traffic was proposed by [1], [2], further developed by [3], [4], [5], [6] and fitted to experimental data by [7], [8] and others. This model is the socalled Macroscopic or Network Fundamental Diagram (MFD or NFD) of urban road networks; it presumes (under certain regularity conditions) that traffic flows dynamics can be treated macroscopically as a single-region dynamic system with vehicle accumulation n as a single state variable.…”

Assessing the Demand Vulnerability of Equilibrium Traffic Networks via Network Aggregation

“…At one extreme, this class contains an analysis of traffic flow dynamics on a single link, leading to theory on the aggregation of individual car-following models to give fluid flow PDEs (Lighthill & Whitham, 1955). Recent work in this category: following Herman and Prigogine (1979) and Ardekani and Herman (1987), Daganzo (2007) employs the two-fluid model to aggregate dynamic urban flow into zones, resulting in a multiple-reservoir model. This representation approaches aspects of the area speed-flow and continuum models mentioned below.…”