Probabilistic Description of Traffic Breakdowns

We analyze the characteristic features of traffic breakdown. To describe this phenomenon we apply to the probabilistic model regarding the jam emergence as the formation of a large car cluster on highway. In these terms the breakdown occurs through the formation of a certain critical nucleus in the metastable vehicle flow, which enables us to confine ourselves to one cluster model. We assume that, first, the growth of the car cluster is governed by attachment of cars to the cluster whose rate is mainly determined by the mean headway distance between the car in the vehicle flow and, may be, also by the headway distance in the cluster. Second, the cluster dissolution is determined by the car escape from the cluster whose rate depends on the cluster size directly. The latter is justified using the available experimental data for the correlation properties of the synchronized mode. We write the appropriate master equation converted then into the Fokker-Plank equation for the cluster distribution function and analyze the formation of the critical car cluster due to the climb over a certain potential barrier. The further cluster growth irreversibly gives rise to the jam formation. Numerical estimates of the obtained characteristics and the experimental data of the traffic breakdown are compared. In particular, we draw a conclusion that the characteristic intrinsic time scale of the breakdown phenomenon should be about one minute and explain the case why the traffic volume interval inside which traffic breakdown is observed is sufficiently wide.Comment: RevTeX 4, 14 pages, 10 figure

Developing standard pedestrian-equivalent factors: passenger car–equivalent approach for dealing with pedestrian diversity

Similar to vehicular traffic, pedestrians, despite having diverse capabilities and body sizes, can be classified as heterogeneous. The use of vehicular traffic resolves the diversity issue with a conversion of heterogeneous vehicle flow into an equivalent flow with the use of passenger car–equivalent (PCE) factors. Analysis of pedestrian flow has yet to incorporate pedestrian diversity analysis implicitly into the design of pedestrian facilities, although some form of adjustment has been suggested. This paper introduces the concept of PCE-type factors for mixed pedestrian traffic called standard pedestrian-equivalent (SPE) factors. Estimates of SPE factors are made relative to the average commuter. The equivalent total travel time approach for PCE estimation was adapted to consider the effects of the differences in physical and operational characteristics of pedestrians, particularly walking speed and body size. Microsimulation of pedestrians was employed to evaluate hypothetical pedestrian proportions so as to generate corresponding flow relationships. Walking speeds and body sizes were varied across different flow conditions, walkway widths, and proportions of other pedestrian types. The first part of this paper explores how the two pedestrian characteristics (walking speed and body size) influence estimated SPE factors. The second part is a case study in which field-collected data illustrate SPE factors calculated for older adults, obese pedestrians, and their combination. An application of SPE factors demonstrates the robustness of the methodology in bridging the gap between pedestrian compositions and planning practice

Traffic and Related Self-Driven Many-Particle Systems

Since the subject of traffic dynamics has captured the interest of physicists, many astonishing effects have been revealed and explained. Some of the questions now understood are the following: Why are vehicles sometimes stopped by so-called ``phantom traffic jams'', although they all like to drive fast? What are the mechanisms behind stop-and-go traffic? Why are there several different kinds of congestion, and how are they related? Why do most traffic jams occur considerably before the road capacity is reached? Can a temporary reduction of the traffic volume cause a lasting traffic jam? Under which conditions can speed limits speed up traffic? Why do pedestrians moving in opposite directions normally organize in lanes, while similar systems are ``freezing by heating''? Why do self-organizing systems tend to reach an optimal state? Why do panicking pedestrians produce dangerous deadlocks? All these questions have been answered by applying and extending methods from statistical physics and non-linear dynamics to self-driven many-particle systems. This review article on traffic introduces (i) empirically data, facts, and observations, (ii) the main approaches to pedestrian, highway, and city traffic, (iii) microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models. Attention is also paid to the formulation of a micro-macro link, to aspects of universality, and to other unifying concepts like a general modelling framework for self-driven many-particle systems, including spin systems. Subjects such as the optimization of traffic flows and relations to biological or socio-economic systems such as bacterial colonies, flocks of birds, panics, and stock market dynamics are discussed as well.Comment: A shortened version of this article will appear in Reviews of Modern Physics, an extended one as a book. The 63 figures were omitted because of storage capacity. For related work see http://www.helbing.org

“Field Data Collection and Analysis for Freeway Work Zone Capacity Estimation”

A previous Florida Department of Transportation (FDOT) (FDOT BD 545-51) developed analytical models for estimating the capacity of freeway work zones based entirely on simulated data. Simulation was used because there were no freeway work zone field data available at the time. As that project was nearing completion, it was determined that field data could be obtained from a recently installed freeway work zone along I-95 in Jacksonville, Florida, using the Jacksonville Traffic Management Center (TMC) cameras. Therefore this project was initiated to collect field data and based on these re-calibrate the models previously developed. To achieve the objective of the project, field data were collected at the freeway work zone identified, for a total of 15 days. Various capacity-related measures were obtained from the field data, including the maximum pre-breakdown flow, the breakdown flow, and the maximum and average discharge flow during congested conditions

Estimation of Arterial Work Zone Capacity Using Simulation

Numerous states have policies that provide guidance for the institution of short term lane closures on arterial streets based on capacity estimates, however it is not clear how the existing values were developed, and there are currently no tools to estimate the capacity of arterial lane closures. Capacity is estimated as a function of various factors including the percent of left turning vehicles, the distance of the work zone to the downstream intersection, and the g/C (effective green to cycle length) of each lane group. The following were concluded from the research: 1) Simulation of arterial work zones showed that the distance of the work zone to the downstream intersection affects the capacity of the entire arterial work zone. Increasing the available storage between the signal and the work zone models results in better utilization of the green time at the intersection approach. 2) The capacity is reduced when one of the movements are blocked by the other. 3) Comparison of the arterial work zone capacity to the respective configurations with no work zone showed that there are selected cases when installing a work zone may increase capacity. Those increases typically occur when the intersection (prior to the work zone installation) is congested

Impact of Trucks on Arterial LOS and Freeway Work Zone Capacity Part B:Freeway Work Zone Capacity

The existing FDOT lane closure analysis method was developed several years ago, and it is the desire of the Department to evaluate and update it accordingly. The objective of this research was to develop analytical models and procedures for estimating the capacity of a freeway work zone considering various geometric and traffic parameters. Due to the Unavailability of real-world work zone data, the study was based on simulation. CORSIM (version 5.1) was used to develop a comprehensive database which was used in the analytical model development. Models were developed for three types of work zone configurations (2-to-1, 3-to-2, and 3-to-1 lane closures). Two different types of models were developed for each lane closure configuration; a planning model and an operational model. The Planning model is the simplest once and it applies when a capacity estimate is required, but the work zone is not in place. The operational model requires more data as input, and it may be used for estimating the capacity of an existing work zone