Examining Route Diversion And Multiple Ramp Metering Strategies For Reducing Real-time Crash Risk On Urban Freeways

Recent research at the University of Central Florida addressing crashes on Interstate-4 in Orlando, Florida has led to the creation of new statistical models capable of calculating the crash risk on the freeway (Abdel-Aty et al., 2004; 2005, Pande and Abdel-Aty, 2006). These models yield the rear-end and lane-change crash risk along the freeway in real-time by using static information at various locations along the freeway as well as real-time traffic data that is obtained from the roadway. Because these models use the real-time traffic data, they are capable of calculating the respective crash risk values as the traffic flow changes along the freeway. The purpose of this study is to examine the potential of two Intelligent Transportation System strategies for reducing the crash risk along the freeway by changing the traffic flow parameters. The two ITS measures that are examined in this research are route diversion and ramp metering. Route diversion serves to change the traffic flow by keeping some vehicles from entering the freeway at one location and diverting them to another location where they may be more efficiently inserted into the freeway traffic stream. Ramp metering alters the traffic flow by delaying vehicles at the freeway on-ramps and only allowing a certain number of vehicles to enter at a time. The two strategies were tested by simulating a 36.25 mile section of the Interstate-4 network in the PARAMICS micro-simulation software. Various implementations of route diversion and ramp metering were then tested to determine not only the effects of each strategy but also how to best apply them to an urban freeway. Route diversion was found to decrease the overall rear-end and lane-change crash risk along the network at free-flow conditions to low levels of congestion. On average, the two crash risk measures were found to be reduced between the location where vehicles were diverted and the location where they were reinserted back into the network. However, a crash migration phenomenon was observed at higher levels of congestion as the crash risk would be greatly increased at the location where vehicles were reinserted back onto the network. Ramp metering in the downtown area was found to be beneficial during heavy congestion. Both coordinated and uncoordinated metering algorithms showed the potential to significantly decrease the crash risk at a network wide level. When the network is loaded with 100 percent of the vehicles the uncoordinated strategy performed the best at reducing the rear-end and lane-change crash risk values. The coordinated strategy was found to perform the best from a safety and operational perspective at moderate levels of congestion. Ramp metering also showed the potential for crash migration so care must be taken when implementing this strategy to ensure that drivers at certain locations are not put at unnecessary risk. When ramp metering is applied to the entire freeway network both the rear-end and lane-change crash risk is decreased further. ALINEA is found to be the best network-wide strategy at the 100 percent loading case while a combination of Zone and ALINEA provides the best safety results at the 90 percent loading case. It should also be noted that both route diversion and ramp metering were found to increase the overall network travel time. However, the best route diversion and ramp metering strategies were selected to ensure that the operational capabilities of the network were not sacrificed in order to increase the safety along the freeway. This was done by setting the maximum allowable travel time increase at 5% for any of the ITS strategies considered

Extension and Generalization of Newell's Simplified Theory of Kinematic Waves

Flow of traffic on freeways and limited access highways can be represented as a series of kinemetic waves. Solutions to these systems of equations become problematic under congested traffic flow conditions, and under complicated (real-world) networks. A simplified theory of kinematics waves was previously proposed. Simplifying elements includes translation of the problem to moving coordinate system, adoption of bi-linear speed-density relationships, and adoption of restrictive constraints at the on- and off-ramps. However, these simplifying assumptions preclude application of this technique to most practical situations. This research explores the limitations of the simplified theory of kinematic waves. First this research documents a relaxation of several key constraints. In the original theory, priority was given to on-ramp merging vehicles so that they can bypass any queue at the merge. This research proposes to relax this constraint using a capacity-based weighted fair queuing (CBWFQ) merge model. In the original theory, downstream queue affects upstream traffic as a whole and exiting traffic can always be able to leave as long as it gets to the diverge. This research proposes that this diverge constraint be replaced with a contribution-based weighted splitting (CBWS) diverge model. This research proposes a revised notation system, permitting the solution techniques to be extended to freeway networks with multiple freeways and their ramps. This research proposes a generalization to permit application of the revised theory to general transportation networks. A generalized CBWFQ merge model and a generalized CBWS diverge model are formulated to deal with merging and diverging traffic. Finally, this research presents computational procedure for solving the new system of equations. Comparisons of model predictions with field observations are conducted on GA 400 in Atlanta. Investigations into the performance of the proposed CBWFQ and CBWS models are conducted. Results are quite encouraging, quantitative measures suggest satisfactory accuracy with narrow confidence interval.Ph.D.Committee Chair: Leonard, John D.; Committee Member: Amekudzi, Adjo; Committee Member: Dixon, Karen; Committee Member: Goldsman, Dave; Committee Member: Hunter, Michae

Physical Health and Architecture: Architecture as a Catalyst for Sustained Health

Obesity has quickly become the largest contributor to health issues in America. The issue facing society is not only how to combat and address the concerns of preventable chronic disease, but to also find ways to improve health for the individual and the collective. Through architecture, this thesis is intended to design a community health and physical wellness center that has a focus on sustaining improved health. By evaluating the spaces for physiological needs of eating and exercising along with education, this facility is intended to serve as a catalyst for fostering a system of evaluation to reflect an entire lifestyle condition and improve an understanding of health and wellness issues within the community. The program elements of eating, exercising and educating create the spaces that frame the program and the spaces between these functions are where the inadvertent experience with health and wellness takes place. Ultimately, this is a space of recovery and learning; recovering a healthy self-image and physical being through learning ways to sustain and maintain a healthy lifestyle and how to ultimately motivate people into engaging with the facility, whether actively or passively

A Smart, Flexible Energy System : The UK Energy Research Centre's (UKERC) Response to the Ofgem / BEIS Call for Evidence

We welcome the attention being paid by Ofgem and BEIS to the need for flexibility in Britain’s electricity system. In our view the main reason to support electricity system flexibility is that it can help minimise the costs of meeting the UK’s statutory climate targets whilst ensuring that system security is not compromised. The electricity system’s ability to adapt to changing demand in timescales of years down to minutes and varying availability of power from different resources will be extremely important to meeting these policy goals. Furthermore, action is needed so that those consumers that are best able to adapt their patterns of use of electricity have sufficient incentives and rewards for doing so. One manifestation of the main goal in accommodating future generation and demand is an objective to maximise the utilisation (across each year of operation) of electricity system assets, i.e. generators, network components and storage facilities. Whilst the title of the call for evidence focuses on ‘a smart, flexible energy system’, most of the raised relate to the electricity system. We have therefore focused most of our responses on electricity rather than the energy system as a whole. Our responses are selective. We have only answered those questions where we can offer relevant evidence, based on our research and expertise

Demand Response in Smart Grids

The Special Issue “Demand Response in Smart Grids” includes 11 papers on a variety of topics. The success of this Special Issue demonstrates the relevance of demand response programs and events in the operation of power and energy systems at both the distribution level and at the wide power system level. This reprint addresses the design, implementation, and operation of demand response programs, with focus on methods and techniques to achieve an optimized operation as well as on the electricity consumer

The Measurement & Verification of Energy Conservation Measures at a Coal-fired Power Plant

The aim of this dissertation was to use Measurement & Verification (M&V) to determine the improvements in net heat rate at a South African coal-fired power plant (CFPP) following an extensive refurbishment programme. The CFPP consisted of multiple subcritical pulverised fuel generating units and the refurbishment programme aimed to improve the overall net heat rate by 1%. The purpose of using M&V is isolate the performance changes attributable to specific energy conservation measures from those changes brought about by other factors, or that would have occurred anyway for other reasons. An extensive literature review was undertaken, firstly into M&V and secondly into CFPP design and performance. The conventionally accepted methods for determining plant performance are the ‘direct method’ in which a measurement boundary is drawn around the entire plant, and the ‘components method’ which evaluates the boiler, the turbine-condenser cycle and the auxiliary loads separately. Caution is drawn to the fact that plant performance may be expressed in many ways depending on how HR is defined and on which coal measurement base is used. The physical factors affecting plant performance were classified as either fixed or variable. Fixed factors included vintage and design, size, condition of the major components (boiler, turbine and condenser), cooling water system type and pollutant controls. Variable factors included ambient conditions, flexibility of operations (such as running at part-load and load cycling) and the characteristics of the coal used including heating value, total moisture, hydrogen, ash, volatile matter, sulphur, hardness & abrasiveness. It is clear from the literature that the language used to describe flexible operations is inadequate and poorly defined. Other factors that may affect the calculated heat rate of a plant include coal weighing, stockpile surveys, length of assessment periods, changes to static stockpiles, measurement boundary selection and other assumptions. The literature review was used as a basis to develop an M&V methodology for the specific CFPP involved in the case study. The energy conservation measures were described in detail as well as constraints regarding availability and resolution of plant data. Although all measurement boundary options were considered, the whole facility approach was chosen (Option C). This approach was mainly motivated by the lack of data available and a high potential for interactive effects. Another reason is the fact that assessments need to capture the overall performance which could include deterioration in one part of the plant and simultaneous upgrades in other parts. The primary data required to find heat rate is the electrical energy use (exported, imported and auxiliary), the mass of coal consumed and the coal higher heating value. The M&V methodology included the development of a baseline adjustment model to adjust for changes in plant load, coal moisture and coal ash content. Ideally the model should have included changes in ambient conditions (temperature and relative humidity) but this was not possible as no ambient data was available and the assessment was done retrospectively. The absence of ambient data was mitigated by stipulating that assessment periods need to consist of a minimum of twelve consecutive months to account for changes in performance due to seasonal effects. The methodology also included a Monte Carlo analysis to quantify the combined uncertainties associated with electrical energy use, coal energy use, coal heating value and the adjustment model itself. The methodology was used to assess the change in net heat rate of the plant used in the case study for two separate twelve month reporting periods. The calculated impacts of the energy conservation measures were not as favourable as originally anticipated. A brief analysis of the results is provided with a discussion of potential reasons for the underperformance. A whole facility approach does not allow the reasons for performance changes to be pinpointed. One possibility is simply that the energy conservation measures had not been implemented as originally planned. An important finding was that the performance changes could not be solely attributed to the exclusion of any independent variables from the baseline adjustment model (e.g. ambient conditions). A more general discussion of the merits, shortcomings and limitations of the methodology is provided as well as some comments on the general interpretation of results. The baseline adjustment model is only applicable to the plant in the case study and is only valid for small changes in the independent variables. When calculating part-load operation, special attention must be given to generating units that have been derated. The application of a single part-load adjustment model to a multi-unit plant is discussed and found to result in conservative reporting. Factors which contribute to uncertainty, but which are unknown include staithe coal level changes, unknown stockpile dynamics, uncalibrated instruments, unrecorded coal movements and inaccuracy of aerial stockpile surveys. The dissertation concludes that the original hypothesis is supported: that a credible M&V methodology may be developed and applied to determine the heat rate improvements resulting from the refurbishment programme at a coal-fired power plant. Recommendations include an upfront agreement on which measurement reporting bases to use (both for heat rate and for coal), selection of a whole facility measurement boundary, a minimum assessment period of twelve months, installation of at least one accurate instrument to measure actual coal consumption (as opposed to coal delivered to the plant and then moved within the plant), sampling of coal, determination of heating value and collection of accurate ambient condition data from the start of the baseline period. Further recommendations are made to reduce uncertainty, determine static factors and to better interpret reported impacts

Modelling mixed autonomy traffic networks with pricing and routing control

Connected and automated vehicles (CAVs) are expected to change the way people travel in cities. Before human-driven vehicles (HVs) are completely phased out, the urban traffic flow will be heterogeneous of HVs, CAVs, and public transport vehicles commonly known as mixed autonomy. Mixed autonomy networks are likely to be made up of different route choice behaviours compared with conventional networks with HVs only. While HVs are expected to continue taking individually and selfishly selected shortest paths following user equilibrium (UE), a set of centrally controlled AVs could potentially follow the system optimal (SO) routing behaviour to reduce the selfish and inefficient behaviour of UE-seeking HVs. In this dissertation, a mixed equilibrium simulation-based dynamic traffic assignment (SBDTA) model is developed in which two classes of vehicles with different routing behaviours (UE-seeking HVs and SO-seeking AVs) are present in the network. The dissertation proposes a joint routing and incentive-based congestion pricing scheme in which SO-seeking CAVs are exempt from the toll while UE-seeking HVs have their usual shortest-path routing decisions are subject to a spatially differentiated congestion charge. This control strategy could potentially boost market penetration rate of CAVs while encouraging them to adopt SO routing behaviour and discouraging UE-seeking users from entering congested areas. The dissertation also proposes a distance-based time-dependent optimal ratio control scheme (TORCS) in which an optimal ratio of CAVs is identified and selected to seek SO routing. The objective of the control scheme is to achieve a reasonable compromise between the system efficiency (i.e., total travel time savings) and the control cost that is proportional to the total distance travelled by SO-seeking AVs. The proposed modelling frameworks are then extended to bi-modal networks considering three competing modes (bus, SO-seeking CAVs, and UE-seeking HVs). A nested logit-based mode choice model is applied to capture travellers’ preferences toward three available modes and elasticity in travel demand. A dynamic transit assignment model is also deployed and integrated into the mixed equilibrium SBDTA model to generate equilibrium traffic flow under different scenarios. The applicability and performance of the proposed models are demonstrated on a real large-scale network of Melbourne, Australia. The research outcomes are expected to improve the performance of mixed autonomy traffic networks with optimal pricing and routing control