UC Davis Institute of Transportation Studies

Headway, namely the distance between vehicles, is a key design factor for ensuring the safe operation of autonomous driving systems. There have been studies on headway optimization based on the speeds of leading and trailing vehicles, assuming perfect sensing capabilities. In practical scenarios, however, sensing errors are inevitable, calling for a more robust headway design to mitigate the risk of collision. Undoubtedly, augmenting the safety distance would reduce traffic throughput, highlighting the need for headway design to incorporate both sensing errors and risk tolerance models. In addition, prioritizing group safety over individual safety is often deemed unacceptable because no driver should sacrifice their safety for the safety of others. In this study, we propose a multi-objective optimization framework that examines the impact of sensing errors on both traffic throughput and the fairness of safety among vehicles. The proposed framework provides a solution to determine the Pareto frontier for traffic throughput and vehicle safety. ComDrive, a communication-based autonomous driving simulation platform, is developed to validate the proposed approach. Extensive experiments demonstrate that the proposed approach outperforms existing baselines.

Our goal is to reduce the negative impacts of bicycle theft by better understanding patterns in bicycle theft and recovery. We analyzed data from 1823 responses to a North American survey on bicycle theft conditions, recovery circumstances, and demographics. Survey recruitment was done in partnership with BikeIndex, a non-profit bicycling registration service. Most bikes were stolen from inside a shed or garage (28%) or from outdoor bicycle racks (18%) and most thefts occur overnight (41%). 15% of stolen bicycles were recovered. Key factors in recovery include police involvement, bike registration, and reporting the theft through multiple channels.

Solar water heating provides domestic hot water with lower greenhouse gas emissions compared to more typical natural-gas water heating. Solar water heating has a long history, particularly in places where the climate is favorable, such as California where state-backed incentive programs have been successful in creating small bursts of adoption. However, widespread adoption of solar water heating has not occurred in California despite these conditions. This research surveyed 227 single-family households with solar water heating across the state of California to understand their motivations and experiences, and draw implications regarding barriers to adoption. The survey explored households’ experiences across five stages of adoption, as outlined in Rogers’ Diffusion of Innovation theory: Knowledge, Persuasion, Decision, Implementation, and Confirmation. Findings revealed challenges at each stage. Most notably, prevalent disappointment in lower-than-expected energy and bill savings (31%) and high rates of technical problems (41%) appear to be the most significant issues.

A major cause of global climate change, human behavior has long been recognized as an essential part of the solution as well. Behavior change methods in turn rely in part on associative learning principles. Some learning principles, such as positive reinforcement and delay discounting, are already integrated into energy research and interventions. However, others remain underutilized. In this paper, we review selected learning principles, suggesting how they can enhance both our understanding of the behavioral challenges and our effectiveness in addressing them. We seek to interest and involve researchers and practitioners in a variety of energy and sustainability specializations.

This study explores the potential to promote lower-emissions air travel by providing consumers with information about the carbon emissions of alternative flight choices in the context of online flight search and booking. We surveyed over 450 employees of the University of California, Davis, asking them to choose among hypothetical flight options for university-related business trips. Emissions estimates for flight alternatives were prominently displayed alongside cost, layovers and airport, and the lowest-emissions flight was labeled “Greenest Flight”. We found an impressive rate of willingness to pay for lower-emissions flights: around $200/ton of CO2E saved, a magnitude higher than that seen in carbon offsets programs. In a second step of analysis, we estimated the carbon and cost impacts if the university were to adopt a flight-search interface that prioritizes carbon emissions information and displays alternatives from multiple regional airports in their employee travel-booking portal. We estimated potential annual savings of 79 tons of CO2E, while reducing airfare costs by $56,000, mainly due to an increased willingness of travelers to take advantage of cheaper nonstop (lower-emissions) flights from a more distant airport in the region over indirect flights from their preferred airport for medium-distance flights. Institutionalizing this “nudge” within organizations with large travel budgets could have an industry-wide impact in aviation.

Recent research suggests there is broader interest in cohousing in the US than its current niche market suggests. However, the lack of ideological diversity among cohousing adopters does not seem malleable. Cohousing adopters are predominately liberal and liberal ideology strongly predicts interest in cohousing. This research explored perceptions (including misperceptions) of cohousing and tested whether framing the concept differently could make it more appealing to Republicans and conservatives. Survey participants were randomly assigned to receive one of two versions of a survey, identical in all ways except in one version the term pocket neighborhoods was substituted for cohousing. Results revealed substantial misunderstanding of the concept of cohousing, particularly that it involves multiple unrelated households living under the same roof. There was no framing effect; those who identified as Republican or conservative did not find cohousing more appealing when it was called pocket neighborhoods. The most cited perceived benefits of cohousing were social interaction, relationships, and support, while lack of privacy and personal space topped the list of drawbacks. Understanding these common perceptions about cohousing can help stakeholders communicate more effectively about this model that promises many benefits to an apparently untapped prospective market.

California's goal to reduce greenhouse gas (GHG) emissions to a level that is 80 % below 1990 levels by the year 2050 will require adoption of low-carbon energy sources across all economic sectors. In addition to reducing GHG emissions, shifting to fuels with lower carbon intensity will change concentrations of short-lived conventional air pollutants, including airborne particles with a diameter of less than 2.5 µm (PM_2.5) and ozone (O₃). Here we evaluate how business-as-usual (BAU) air pollution and public health in California will be transformed in the year 2050 through the adoption of low-carbon technologies, expanded electrification, and modified activity patterns within a low-carbon energy scenario (GHG-Step). Both the BAU and GHG-Step statewide emission scenarios were constructed using the energy–economic optimization model, CA-TIMES, that calculates the multi-sector energy portfolio that meets projected energy supply and demand at the lowest cost, while also satisfying scenario-specific GHG emissions constraints. Corresponding criteria pollutant emissions for each scenario were then spatially allocated at 4 km resolution to support air quality analysis in different regions of the state. Meteorological inputs for the year 2054 were generated under a Representative Concentration Pathway (RCP) 8.5 future climate. Annual-average PM_2.5 and O₃ concentrations were predicted using the modified emissions and meteorology inputs with a regional chemical transport model. In the final phase of the analysis, mortality (total deaths) and mortality rate (deaths per 100 000) were calculated using established exposure-response relationships from air pollution epidemiology combined with simulated annual-average PM_2.5 and O₃ exposure. Net emissions reductions across all sectors are −36 % for PM_0.1 mass, −3.6 % for PM_2.5 mass, −10.6 % for PM_2.5 elemental carbon, −13.3 % for PM_2.5 organic carbon, −13.7 % for NO _x , and −27.5 % for NH₃. Predicted deaths associated with air pollution in 2050 dropped by 24–26 % in California (1537–2758 avoided deaths yr⁻¹) in the climate-friendly 2050 GHG-Step scenario, which is equivalent to a 54–56 % reduction in the air pollution mortality rate (deaths per 100 000) relative to 2010 levels. These avoided deaths have an estimated value of USD 11.4–20.4 billion yr⁻¹ based on the present-day value of a statistical life (VSL) equal to USD 7.6 million. The costs for reducing California GHG emissions 80 % below 1990 levels by the year 2050 depend strongly on numerous external factors such as the global price of oil. Best estimates suggest that meeting an intermediate target (40 % reduction in GHG emissions by the year 2030) using a non-optimized scenario would reduce personal income by USD 4.95 billion yr⁻¹ (−0.15 %) and lower overall state gross domestic product by USD 16.1 billion yr⁻¹ (−0.45 %). The public health benefits described here are comparable to these cost estimates, making a compelling argument for the adoption of low-carbon energy in California, with implications for other regions in the United States and across the world.

Within the Home Energy Management (HEM) space, there are a variety of stakeholders who are integral to technology development and end user adoption. While there has been an increased emphasis on integrating customer research and perspectives, less work in this field has incorporated these various stakeholders and their perspectives. In order to understand the emerging HEM market and fully realize its potential for demand side management, a deeper understanding of the various stakeholders and their respective roles is required. This paper leverages three methods of stakeholder analysis (Delphi, online survey, and semi-structured interviews) to synthesize and discuss perspectives on HEM technology. Findings both reveal implications for the HEM space and present an exemplar methodology that can be used in other areas within the energy sector.

How do small businesses experience energy reports that benchmark their performance relative to similar businesses and provide recommendations to save energy? There is a large body of research focused on energy feedback in the residential sector, but significantly less in the commercial sector. Studies in both sectors have focused on the effectiveness of feedback in terms of savings outcomes, while relatively little is known about how customers experience the interface itself. This paper presents a synthesis of results from a series of user research studies conducted with small- and medium-sized enterprises (SMEs) in Canada, the United States, and Australia. Results provide insights into aspects of energy reports business customers attend to or ignore, what information they value, whether and how they take action based on the reports, and barriers to taking action. Our findings highlight distinct areas utilities can focus on to improve business energy reports, including ways to reduce barriers to action and the need for energy reports to be carefully and precisely tailored.