Police traffic services, management information system, (phase I). Final report.

National Highway Traffic Safety Administration, Washington, D.C.

The Pennsylvania Turnpike Commission's Incident Management Team.

Transportation Department, Washington, D.C.

Traffic lights management using belief propagation

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

En Route Speed Reduction Concept for Absorbing Air Traffic Flow Management Delays

This paper proposes an en route speed reduction to complement current ground delay practices in air traffic flow management. Given a nominal cruise speed, there exists a bounded range of speeds that allows aircraft to fly slower with the same or lower fuel consumption than the nominal flight. Therefore, flight times are increased and delay can be partially performed in the air, at no extra fuel cost for the operator. This concept has been analyzed in an initial feasibility study, computing the maximum amount of delay that can be performed in the air in some representative flights. The impact on fuel consumption has been analyzed, and two scenarios are proposed: the flight fuel remains the same as in the nominal flight, and some extra fuel allowance is permitted in order to face uncertainties. Results show significant values of airborne delay that may be useful in many situations, with the exception of short hauls where airborne delay may be too short. If cruise altitude is changed, the amount of airborne delay increases, since changes in cruise speed modify the optimal flight altitudes. From the analyzed flights, a linear dependency is found relating the airborne delay with the amount of extra fuel allowance.

Pico Cell Integration to Operator’s Incident Management Process

Mobile network coverage is traditionally provided by outdoor macro base stations, which have a long range and serve several of customers. Due to modern passive houses and tightening construction legislation, mobile network service is deteriorated in many indoor locations. Typically, solutions for indoor coverage problem are expensive and demand actions from the mobile operator. Due to these, superior solutions are constantly researched. The solution presented in this thesis is based on Small Cell technology. Small Cells are low power access nodes designed to provide voice and data services.. This thesis concentrates on a specific Small Cell solution, which is called a Pico Cell. The problem regarding Pico Cells and Small Cells in general is that they are a new technological solution for the mobile operator, and the possible problem sources and incidents are not properly mapped. The purpose of this thesis is to figure out the possible problems in the Pico Cell deployment and how they could be solved within the operator’s incident management process. The research in the thesis is carried out with a literature research and a case study. The possible problems are investigated through lab testing. Pico Cell automated deployment process was tested in the lab environment and its proper functionality is confirmed. The related network elements were also tested and examined, and the emerged problems are resolvable. Operators existing incident management process can be used for Pico Cell troubleshooting with minor updates. Certain pre-requirements have to be met before Pico Cell deployment can be considered. The main contribution of this thesis is the Pico Cell integrated incident management process. The presented solution works in theory and solves the problems found during the lab testing. The limitations in the customer service level were solved by adding the necessary tools and by designing a working question pattern. Process structures for automated network discovery and pico specific radio parameter planning were also added for the mobile network management layer..

Modelling total duration of traffic incidents including incident detection and recovery time

Traffic incidents are key contributors to non-recurrent congestion, potentially generating significant delay. Factors that influence the duration of incidents are important to understand so that effective mitigation strategies can be implemented. To identify and quantify the effects of influential factors, a methodology for studying total incident duration based on historical data from an ‘integrated database’ is proposed. Incident duration models are developed using a selected freeway segment in the Southeast Queensland, Australia network. The models include incident detection and recovery time as components of incident duration. A hazard-based duration modelling approach is applied to model incident duration as a function of a variety of factors that influence traffic incident duration. Parametric accelerated failure time survival models are developed to capture heterogeneity as a function of explanatory variables, with both fixed and random parameters specifications. The analysis reveals that factors affecting incident duration include incident characteristics (severity, type, injury, medical requirements, etc.), infrastructure characteristics (roadway shoulder availability), time of day, and traffic characteristics. The results indicate that event type durations are uniquely different, thus requiring different responses to effectively clear them. Furthermore, the results highlight the presence of unobserved incident duration heterogeneity as captured by the random parameter models, suggesting that additional factors need to be considered in future modelling efforts.

Modelling the impact of traffic incidents on travel time reliability

Traffic incidents are recognised as one of the key sources of non-recurrent congestion that often leads to reduction in travel time reliability (TTR), a key metric of roadway performance. A method is proposed here to quantify the impacts of traffic incidents on TTR on freeways. The method uses historical data to establish recurrent speed profiles and identifies non-recurrent congestion based on their negative impacts on speeds. The locations and times of incidents are used to identify incidents among non-recurrent congestion events. Buffer time is employed to measure TTR. Extra buffer time is defined as the extra delay caused by traffic incidents. This reliability measure indicates how much extra travel time is required by travellers to arrive at their destination on time with 95% certainty in the case of an incident, over and above the travel time that would have been required under recurrent conditions. An extra buffer time index (EBTI) is defined as the ratio of extra buffer time to recurrent travel time, with zero being the best case (no delay). A Tobit model is used to identify and quantify factors that affect EBTI using a selected freeway segment in the Southeast Queensland, Australia network. Both fixed and random parameter Tobit specifications are tested. The estimation results reveal that models with random parameters offer a superior statistical fit for all types of incidents, suggesting the presence of unobserved heterogeneity across segments. What factors influence EBTI depends on the type of incident. In addition, changes in TTR as a result of traffic incidents are related to the characteristics of the incidents (multiple vehicles involved, incident duration, major incidents, etc.) and traffic characteristics.

Management of Traffic Control — A Computer Oriented Approach

Traffic Management system (TMS) comprises four major sub systems: The Network Database Management system for information to the passengers, Transit Facility Management System for service, planning, and scheduling vehicle and crews, Congestion Management System for traffic forecasting and planning, Safety Management System concerned with safety aspects of passengers and Environment. This work has opened a rather wide frame work of model structures for application on traffic. The facets of these theories are so wide that it seems impossible to present all necessary models in this work. However it could be deduced from the study that the best Traffic Management System is that whichis realistic in all aspects is easy to understand is easy to apply As it is practically difficult to device an ideal fool—proof model, the attempt here has been to make some progress-in that direction.

Development of prediction models for freeway incident durations using data mining techniques

The nation's freeway systems are becoming increasingly congested. A major contribution to traffic congestion on freeways is due to traffic incidents. Traffic incidents are non-recurring events such as accidents or stranded vehicles that cause a temporary roadway capacity reduction, and they can account for as much as 60 percent of all traffic congestion on freeways. One major freeway incident management strategy involves diverting traffic to avoid incident locations by relaying timely information through Intelligent Transportation Systems (ITS) devices such as dynamic message signs or real-time traveler information systems. The decision to divert traffic depends foremost on the expected duration of an incident, which is difficult to predict. In addition, the duration of an incident is affected by many contributing factors. Determining and understanding these factors can help the process of identifying and developing better strategies to reduce incident durations and alleviate traffic congestion. A number of research studies have attempted to develop models to predict incident durations, yet with limited success. ^ This dissertation research attempts to improve on this previous effort by applying data mining techniques to a comprehensive incident database maintained by the District 4 ITS Office of the Florida Department of Transportation (FDOT). Two categories of incident duration prediction models were developed: "offline" models designed for use in the performance evaluation of incident management programs, and "online" models for real-time prediction of incident duration to aid in the decision making of traffic diversion in the event of an ongoing incident. Multiple data mining analysis techniques were applied and evaluated in the research. The multiple linear regression analysis and decision tree based method were applied to develop the offline models, and the rule-based method and a tree algorithm called M5P were used to develop the online models. ^ The results show that the models in general can achieve high prediction accuracy within acceptable time intervals of the actual durations. The research also identifies some new contributing factors that have not been examined in past studies. As part of the research effort, software code was developed to implement the models in the existing software system of District 4 FDOT for actual applications. ^

Design strategies for an artificial neural network based algorithm for automatic incident detection on major arterial streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our nation’s highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Design Strategies for an Artificial Neural Network Based Algorithm for Automatic Incident Detection on Major Arterial Streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our national highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Comparative study : health research on traffic noise pollution vs. Technical research on traffic noise mitigation

Community awareness and the perception on the traffic noise related health impacts have increased significantly over the last decade resulting in a large volume of public inquiries flowing to Road Authorities for planning advice. Traffic noise management in the urban environment is therefore becoming a “social obligation”, essentially due to noise related health concerns. Although various aspects of urban noise pollution and mitigation have been researched independently, an integrated approach by stakeholders has not been attempted. Although the current treatment and mitigation strategies are predominantly handled by the Road Agencies, a concerted effort by all stakeholders is becoming mandatory for effective and tangible outcomes in the future. A research project is underway a RMIT University, Australia, led by the second author to consider the use of “hedonic pricing” for alternative noise amelioration treatments within the road reserve and outside the road reserve. The project aims to foster a full range noise abatement strategy encompassing source, path and noise receiver. The benefit of such a study would be to mitigate the problem where it is most effective and would defuse traditional “authority” boundaries to produce the optimum outcome. The project is conducted in collaboration with the Department of Main Roads Queensland, Australia and funded by the CRC for Construction Innovation. As part of this study, a comprehensive literature search is currently underway to investigate the advancements in community health research, related to environmental noise pollution, and the advancements in technical and engineering research in mitigating the issue. This paper presents the outcomes of this work outlining state of the art, national and international good practices and gap analysis to identify major anomalies and developments.

Automated centralised separation management with onboard decision support

This paper proposes a novel automated separation management concept in which onboard decision support is integrated within a centralised air traffic separation management system. The onboard decision support system involves a decentralised separation manager that can overrule air traffic management instructions under certain circumstances. This approach allows the advantages of both centralised and decentralised concepts to be combined (and disadvantages of each separation management approach to be mitigated). Simulation studies are used to illustrate the potential benefits of the combined separation management concept.

Policy analysis of disaster health management in China

Humankind has been dealing with all kinds of disasters since the dawn of time. The risk and impact of disasters producing mass casualties worldwide is increasing, due partly to global warming as well as to increased population growth, increased density and the aging population. China, as a country with a large population, vast territory, and complex climatic and geographical conditions, has been plagued by all kinds of disasters. Disaster health management has traditionally been a relatively arcane discipline within public health. However, SARS, Avian Influenza, and earthquakes and floods, along with the need to be better prepared for the Olympic Games in China has brought disasters, their management and their potential for large scale health consequences on populations to the attention of the public, the government and the international community alike. As a result significant improvements were made to the disaster management policy framework, as well as changes to systems and structures to incorporate an improved disaster management focus. This involved the upgrade of the Centres for Disease Control and Prevention (CDC) throughout China to monitor and better control the health consequences particularly of infectious disease outbreaks. However, as can be seen in the Southern China Snow Storm and Wenchuan Earthquake in 2008, there remains a lack of integrated disaster management and efficient medical rescue, which has been costly in terms of economics and health for China. In the context of a very large and complex country, there is a need to better understand whether these changes have resulted in effective management of the health impacts of such incidents. To date, the health consequences of disasters, particularly in China, have not been a major focus of study. The main aim of this study is to analyse and evaluate disaster health management policy in China and in particular, its ability to effectively manage the health consequences of disasters. Flood has been selected for this study as it is a common and significant disaster type in China and throughout the world. This information will then be used to guide conceptual understanding of the health consequences of floods. A secondary aim of the study is to compare disaster health management in China and Australia as these countries differ in their length of experience in having a formalised policy response. The final aim of the study is to determine the extent to which Walt and Gilson’s (1994) model of policy explains how disaster management policy in China was developed and implemented after SARS in 2003 to the present day. This study has utilised a case study methodology. A document analysis and literature search of Chinese and English sources was undertaken to analyse and produce a chronology of disaster health management policy in China. Additionally, three detailed case studies of flood health management in China were undertaken along with three case studies in Australia in order to examine the policy response and any health consequences stemming from the floods. A total of 30 key international disaster health management experts were surveyed to identify fundamental elements and principles of a successful policy framework for disaster health management. Key policy ingredients were identified from the literature, the case-studies and the survey of experts. Walt and Gilson (1994)’s policy model that focuses on the actors, content, context and process of policy was found to be a useful model for analysing disaster health management policy development and implementation in China. This thesis is divided into four parts. Part 1 is a brief overview of the issues and context to set the scene. Part 2 examines the conceptual and operational context including the international literature, government documents and the operational environment for disaster health management in China. Part 3 examines primary sources of information to inform the analysis. This involves two key studies: • A comparative analysis of the management of floods in China and Australia • A survey of international experts in the field of disaster management so as to inform the evaluation of the policy framework in existence in China and the criteria upon which the expression of that policy could be evaluated Part 4 describes the key outcomes of this research which include: • A conceptual framework for describing the health consequences of floods • A conceptual framework for disaster health management • An evaluation of the disaster health management policy and its implementation in China. The research outcomes clearly identified that the most significant improvements are to be derived from improvements in the generic management of disasters, rather than the health aspects alone. Thus, the key findings and recommendations tend to focus on generic issues. The key findings of this research include the following: • The health consequences of floods may be described in terms of time as ‘immediate’, ‘medium term’ and ‘long term’ and also in relation to causation as ‘direct’ and ‘indirect’ consequences of the flood. These two aspects form a matrix which in turn guides management responses. • Disaster health management in China requires a more comprehensive response throughout the cycle of prevention, preparedness, response and recovery but it also requires a more concentrated effort on policy implementation to ensure the translation of the policy framework into effective incident management. • The policy framework in China is largely of international standard with a sound legislative base. In addition the development of the Centres for Disease Control and Prevention has provided the basis for a systematic approach to health consequence management. However, the key weaknesses in the current system include: o The lack of a key central structure to provide the infrastructure with vital support for policy development, implementation and evaluation. o The lack of well-prepared local response teams similar to local government based volunteer groups in Australia. • The system lacks structures to coordinate government action at the local level. The result of this is a poorly coordinated local response and lack of clarity regarding the point at which escalation of the response to higher levels of government is advisable. These result in higher levels of risk and negative health impacts. The key recommendations arising from this study are: 1. Disaster health management policy in China should be enhanced by incorporating disaster management considerations into policy development, and by requiring a disaster management risk analysis and disaster management impact statement for development proposals. 2. China should transform existing organizations to establish a central organisation similar to the Federal Emergency Management Agency (FEMA) in the USA or the Emergency Management Australia (EMA) in Australia. This organization would be responsible for leading nationwide preparedness through planning, standards development, education and incident evaluation and to provide operational support to the national and local government bodies in the event of a major incident. 3. China should review national and local plans to reflect consistency in planning, and to emphasize the advantages of the integrated planning process. 4. Enhance community resilience through community education and the development of a local volunteer organization. China should develop a national strategy which sets direction and standards in regard to education and training, and requires system testing through exercises. Other initiatives may include the development of a local volunteer capability with appropriate training to assist professional response agencies such as police and fire services in a major incident. An existing organisation such as the Communist Party may be an appropriate structure to provide this response in a cost effective manner. 5. Continue development of professional emergency services, particularly ambulance, to ensure an effective infrastructure is in place to support the emergency response in disasters. 6. Funding for disaster health management should be enhanced, not only from government, but also from other sources such as donations and insurance. It is necessary to provide a more transparent mechanism to ensure the funding is disseminated according to the needs of the people affected. 7. Emphasis should be placed on prevention and preparedness, especially on effective disaster warnings. 8. China should develop local disaster health management infrastructure utilising existing resources wherever possible. Strategies for enhancing local infrastructure could include the identification of local resources (including military resources) which could be made available to support disaster responses. It should develop operational procedures to access those resources. Implementation of these recommendations should better position China to reduce the significant health consequences experienced each year from major incidents such as floods and to provide an increased level of confidence to the community about the country’s capacity to manage such events.