Reducing fuel consumption is a unifying goal across the aviation industry. One fuel-saving opportunity for airlines is the possibility of reducing discretionary fuel loading by dispatchers. In this study, we propose a novel discretionary fuel estimation approach that can assist dispatchers with better discretionary fuel loading decisions. Based on the analysis on our study airline, our approach is found to substantially reduce unnecessary discretionary fuel loading while maintaining the same safety level compared to the current fuel loading practice. The idea is that by providing...
Reducing fuel consumption is a unifying goal across the aviation industry. One fuel-saving opportunity for airlines is reducing contingency fuel loading by dispatchers. Many airlines’ flight planning systems (FPSs) provide recommended contingency fuel for dispatchers in the form of statistical contingency fuel (SCF). However, because of limitations of the current SCF estimation procedure, the application of SCF is limited. In this study, we propose to use quantile regression–based machine learning methods to account for fuel burn uncertainties and estimate more reliable SCF values....
This study aims to improve operational performance of a multiple airport region (MAR) by analyzing interdependent capacity scenarios of that MAR airports and redistributing airport traffic to make more efficient use of the available capacity. We propose to shift flights between MAR airports in order to reduce flight delays. Both the deterministic and stochastic versions of a flight shift model are formulated as a mixed-integer linear program (MILP). The proposed methodology is applied to New York MAR, which includes five airports, using data for the year 2015. The deterministic model is...
The aviation sector in California is facing increased pressure to reduce its carbon footprint, leading to a growing interest in alternative fuel aviation (AFA) technologies such as sustainable aviation fuel (SAF), as well as electric- and hydrogen- powered aircraft. The report develops a California Aviation Energy Model (CAVEM), examining various AFA technologies and analyzing possible policy options. The analysis emphasizes the importance of SAF in the short term, with projections indicating sufficient supply for intrastate flights and capped vegetable oil-based fuel consumption. Long-...
Sea level rise (SLR) and storm surge inundation are major concerns along the coast of the San Francisco Bay (the Bay Area), impacting both coastal communities and critical infrastructure networks. The oil industry comprises a complex and critical infrastructure network located in the Bay Area. There is an urgent need to assess consequences and identify risk-based solutions to increase the resilience of this industrial network in the Bay Area to SLR and storm surge. In this study, a comprehensive multi-modal network model representing the fuel supply system was built. A total of 120 coastal...
Interest in residential batteries to supply photovoltaic (PV) electricity on demand is increasing, however they are not profitable yet. Combining applications has been suggested as a way to increase their attractiveness, but the extent to which this can be achieved, as well as how the different value propositions may affect the optimal battery technology, remain unclear. In this study, we develop an open-source optimization framework to determine the best-suited battery technology depending on the size and the applications combined, including PV self-consumption, demand load-shifting,...
The increasing number of electric vehicles (EVs) on the road brings both opportunities and challenges to the power system. For the EV charging stations (EVCSs), it is often difficult to conduct effective operations due to the incomplete information in EVs’ departure times and the opacity of their preference information. To tackle this challenge, we seek to design the optimal deadline differentiated dynamic price menu that offers multiple choice-pairs of deadlines and charging prices. We prove that such price menus can incentivize EVs to truthfully reveal their departure time. We then...
In light of recent events, there has been a surge in discussions of defunding police. On one hand, policy that reduces police presence aims to reduce frequency of police violence. On the other hand, downsizing the police force triggers concerns of public safety and police response time. In this work, we use spatial analysis to examine the impact a reduced police force may have on response time. Modeling the transportation system of Chicago as a network, we simulate the response of police officers from stations to incidents. We then use this simulation to calculate the impacts of resource...
The Fuel-Efficient Traffic Signal Management (FETSIM) Program was initiated in 1982 to help local agencies retime their traffic signals to reduce stops, delays, and fuel consumption. This report presents the results of the fourth and fifth grant cycles of the FETSIM Program. During the two grant cycles, local agency staff and their consultants were provided training, technical assistance and funding necessary to optimize the timing of their signal systems and to put the new timing plans into operation. In the 1986 grant cycle, thirty-one local agencies retimed 1169 signals at a total cost...
Need to develop theory, tools, and methods that allow for self-consistent and transparent comparisons of promising alternative energy and vehicle pathways (hydrogen, biofuels, electricity, and fossil fuels). Also, to inform the public debate and to assist our public and private sponsors on sustainable transportation alternatives.
