Michael J. Cassidy

Bio: Michael J. Cassidy is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Traffic flow & Bottleneck. The author has an hindex of 42, co-authored 154 publications receiving 5855 citations. Previous affiliations of Michael J. Cassidy include Purdue University & University of California.

Some traffic features at freeway bottlenecks

Abstract: Observations from two freeway bottlenecks in and near Toronto, Canada indicate that the average rate vehicles discharge from a queue can be 10% lower than the flow measured prior to the queue's formation. Absent any influences from downstream, the queue discharge flows exhibited nearly stationary patterns that alternated between higher and lower rates. These alternating flow patterns were especially evident at one of the two sites, although the feature occurred at both sites during periods that immediately followed the onset of upstream queueing; i.e. a queue's formation was always accompanied by a relatively low discharge rate followed later by a temporary surge in the discharge flow. When plotted cumulatively over time, however, the counts of discharging vehicles generally did not deviate by more than about 50 vehicles from a trend line of constant slope. Thus, the discharge flows are described as being `nearly' constant; i.e. they varied (slightly) about a fixed rate. At each site, this average discharge rate exhibited little deviation from day to day. The present findings came by visually comparing transformed curves of cumulative vehicle arrival number vs time and cumulative occupancy vs time measured at neighboring loop detectors. This treatment of the data provided clear presentations of some important traffic features and this facilitated a detailed study of bottleneck flows.

Increasing Capacity of an Isolated Merge by Metering Its On-Ramp

Abstract: In this paper, the authors demonstrate the queue formation mechanism at an active merge bottleneck in San Diego, California. Breakdown was a reproducible feature at the merge, triggered daily by a queue that formed in the freeway shoulder lane. Once vehicle accumulation in the queue reached a critical value, lane change maneuvers increased as drivers sought to avoid slow traffic. The maneuvering spread the queue laterally across the freeway and breakdown ensued. By restrictively metering the on-ramp to diminish shoulder lane accumulation between the critical value, high outflows often returned to the median lane Outflow could then be fully recovered by relaxing the metering rate and allowing greater inflows from the on-ramp to return.

Increasing the Capacity of an Isolated Merge by Metering Its On-Ramp

Abstract: Measurements taken downstream of freeway/on-ramp merges have previously shown that discharge flow diminishes when a merge becomes an isolated bottleneck. By means of observation and experiment, we show here that metering an on-ramp can recover the higher discharge flow at a merge and thereby increase the merge capacity. Detailed observations were collected at a single merge using video. These data revealed that the reductions in discharge flow are triggered by a queue that forms near the merge in the freeway shoulder lane and then spreads laterally, as drivers change lanes to maneuver around slow traffic. Our experiments show that once restrictive metering mitigated this shoulder lane queue, high outflows often returned to the median lane. High merge outflows could be restored in all freeway lanes by then relaxing the metering rate so that inflows from the on-ramp increased. Although outflows recovered in this fashion were not sustained for periods greater than 13 min, the findings are the first real evidence that ramp metering can favorably affect the capacity of an isolated merge. Furthermore, these findings point to control strategies that might generate higher outflows for more prolonged periods and increase merge capacity even more. Finally, the findings uncover details of merge operation that are essential for developing realistic theories of merging traffic.

Relation between traffic density and capacity drop at three freeway bottlenecks

Abstract: Three freeway bottlenecks, each with a distinct geometry, are shown to share a relation between vehicle density and losses in discharge flow. Each bottleneck suffered reductions in discharge once queues formed just upstream. This so-called “capacity drop” was related to the density measured over some extended-length freeway segment near each bottleneck. Pronounced increase in this density always preceded a capacity drop. For each bottleneck, the densities that coincided with capacity drops were reproducible. When normalized by a bottleneck’s number of travel lanes and averaged across observation days, the density that coincided with capacity drop was even similar across bottlenecks. (These densities were nearly identical for two of the bottlenecks and the more notable difference observed for the third may be only an artifact of how the data were collected.) The findings indicate that traffic-responsive schemes to control density hold promise for increasing bottleneck discharge flows. Standardized control logic might even suffice for bottlenecks of various forms. With an eye toward future testing and deployment of such control schemes, we present and validate in an Appendix A to this paper a simple algorithm for the real-time measurement of density over freeway links of extended lengths.

Bivariate relations in nearly stationary highway traffic

Abstract: This paper demonstrates that reproducible bivariate relations exist among traffic variables, such as flow and occupancy, when traffic conditions are approximately stationary. The inspection of cumulative curves of vehicle arrival number and vehicle occupancy has revealed that sustained periods of nearly stationary conditions do arise in the traffic stream. By plotting average values of the data corresponding to each nearly stationary condition, well-defined relations are observed. These scatterplots of near-stationary data are contrasted with plots of data that were measured over consecutive time intervals of fixed duration and this reveals that data from certain conditions do not necessarily fall on a curve describing near-stationary traffic.

Traffic and related self-driven many-particle systems

Abstract: Since the subject of traffic dynamics has captured the interest of physicists, many surprising effects have been revealed and explained. Some of the questions now understood are the following: Why are vehicles sometimes stopped by ``phantom traffic jams'' even though drivers 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 in the volume of traffic cause a lasting traffic jam? Under which conditions can speed limits speed up traffic? Why do pedestrians moving in opposite directions normally organize into lanes, while similar systems ``freeze by heating''? All of these questions have been answered by applying and extending methods from statistical physics and nonlinear dynamics to self-driven many-particle systems. This article considers the empirical data and then reviews the main approaches to modeling pedestrian and vehicle traffic. These include 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, such as a general modeling framework for self-driven many-particle systems, including spin systems. While the primary focus is upon vehicle and pedestrian traffic, applications to biological or socio-economic systems such as bacterial colonies, flocks of birds, panics, and stock market dynamics are touched upon as well.

Fundamentals of Queueing Theory

Abstract: Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Review of road traffic control strategies

Abstract: Traffic congestion in urban road and freeway networks leads to a strong degradation of the network infrastructure and accordingly reduced throughput, which can be countered via suitable control measures and strategies. After illustrating the main reasons for infrastructure deterioration due to traffic congestion, a comprehensive overview of proposed and implemented control strategies is provided for three areas: urban road networks, freeway networks, and route guidance. Selected application results, obtained from either simulation studies or field implementations, are briefly outlined to illustrate the impact of various control actions and strategies. The paper concludes with a brief discussion of future needs in this important technical area.

The economics of urban transportation

Abstract: 1 Introduction 2 Travel Demand 3 Costs 4 Pricing 5 Investment 6 Industrial Organization of Transportation Providers 7 Conclusion