research report

Environmental Design for Micromobility and Public Transit

Abstract

Micromobility has the potential to reduce greenhouse gas emissions, traffic congestion, and air pollution, particularly when replacing private vehicle use and working in conjunction with public transit for first- and last-mile travel. The design of the built environment in and around public transit stations plays a key role in the integration of public transit and micro-mobility. This research presents a case study of rail stations in the San Francisco Bay Area, which are in the operation zone of seven shared micro-mobility operators. Nineteen stations and their surroundings were surveyed to inventory design features that could enable or constrain the use of micromobility for first- and last-mile access. Shared mobility service characteristics, crime records, and connections to underserved communities were also documented. An interactive Bay Area Micromobility Transit ArcGIS map tool was created to aid analysis and provide a useful resource to stakeholders. The map shows layers such as train stations, bike lanes, bike share kiosks, and micromobility operation zones that vary between Oakland, Emeryville, Berkeley, San Francisco, and San Jose. Key design solutions were identified based on the findings, including protected bike lanes, increased shared bike and scooter fleet size and service area, and clear signage indicating bike rack parking corral and docking points.

research report

Mobile Device Data Analytics for Next-Generation Traffic Management

Abstract

Quality data is critically important for research and policy-making. The availability of device location data carrying rich, detailed information on travel patterns has increased significantly in recent years with the proliferation of personal GPS-enabled mobile devices and fleet transponders. However, in its raw form, location data can be inaccurate and contain embedded biases that can skew analyses. This report describes the development of a method to process, clean, and enrich location data. Researchers developed a computational framework for processing large-scale location datasets. Using this framework, several hundred days of location data from the San Francisco Bay Area were (a) cleaned, to identify and discard inaccurate or problematic data, (b) enriched, by filtering and annotating the data, and (c) matched to links on the road network. This framework provides researchers with the capability to build link-level metrics across large-scale geographic regions. Various applications for this enriched data are also discussed in this report (including applications related to corridor planning, freight planning, and disaster and emergency management) along with suggestions for further work.

white paper

What Happened and Will Happen with Biofuels? Review and Prospects for Non-Conventional Biofuels in California and the U.S.: Supply, Cost, and Potential GHG Reductions

Abstract

This paper examines past and future trends for non-conventional biofuels in transportation in the next decade and beyond in California and the U.S., drawing on existing literature. It finds policy was geared toward expanding the use of technology-ready biofuels in the 2010s; hydro-processed renewable diesel from lipid feedstocks and biogas were beneficiaries alongside conventional ethanol and biodiesel. Cellulosic ventures largely failed due to a lack of technological readiness, high cost, and an uncertain and insufficient policy environment. Policy goals for competitive cellulosic fuels remain, yet fuels from technologies already in the market may suffice to meet low carbon fuel policy targets, at least in California until 2030, considerably more oilcrop-based biofuels. How much biofuel will be needed there and elsewhere to meet climate targets hinges critically on the pace and scope of zero-emission vehicles, and particularly electric vehicles, rollout. Analysis of unintended market consequences like indirect land use change has evolved over the decade but remains uncertain; current policy structures do not comprehensively safeguard against increased emissions. Market activity for non-conventional fuels has targeted jets. Pioneer plants using new conversion technologies, if successful, will take some time to scale. Technoeconomic analyses (TEAs) for such non-conventional fuels point to no clear biofuel conversion technology winner as yet, given uncertainties. techno-economic analyses are evolving to reduce uncertainty by concentrating more on robust returns in the face of uncertain policies, potential additional cost-cutting for new technologies given what is known about processes involved, and potential revenue-raising through new coproducts or shifting product slates. Policies are needed to make initial financing more secure. Additional policy and societal attention to the appropriate use of biomass, and land more generally, in a low-carbon future is needed to clarify the likely feedstock supply for biofuels that will enhance climate goals with a low risk of unintended consequences.

published journal article

Estimating short-term travel demand models that incorporate personally owned autonomous vehicles

Abstract

We estimated travel demand models that incorporate a private autonomous vehicle (AV) option using revealed preference data in which personal chauffeurs simulated a personally owned AV. We investigated four components of activity-based models (ABM): activity pattern and primary destination choice, mode choice, and time of day. We compared the chauffeur week models (“AV future”) to the non-chauffeur week models (current conditions). We found no statistically significant differences in parameters of the individual activity pattern, time of day, or destination choice. For mode choice, however, while the auto constant did not change, the mean value of time decreased by 60%. As the destination choice model included the mode choice log sum, this results in longer average tour lengths. Moreover, while the trip-making propensity of individuals did not change significantly, there was a 25% increase in systemwide trips due to “AVs” (chauffeurs) being sent on errands. This points to the importance of incorporating zero-occupancy vehicle (ZOV) trips into the ABM framework. Our findings suggest that these can be incorporated via the standard ABM development process by adding as additional model components ZOV home-based tours and ZOV subtours. Relatedly, as inter-regional travel is modeled outside the ABM framework, our results indicated that modifications should be made to account for the increase in inter-regional tours, which were 54% more frequent during chauffeur weeks. While these results are from a relatively small sample of 71 individuals, they are the first such travel demand estimation results available from a field experiment, and further studies can build on our framework.

policy brief

Wildfire Evacuation Planning Can Be Greatly Enhanced by Considering Fire Progression, Communication Systems, and Other Dynamic Factors

Abstract

Wildfires have become a perpetual crisis for communities across California. For life-threatening wildfires, mass evacuation often becomes the only viable option to protect lives. Yet, looking back at recent events, including the devastating 2018 Camp Fire in Northern California, there are significant challenges associated with the evacuation process, such as multi-agency coordination, agency-resident communication, and management of extraordinarily high amounts of traffic within a short period of time. Currently, emergency planners use evacuation models that are typically based on existing traffic simulation models; however, it is increasingly clear that other factors need to be considered, such as fire progression and communication systems. To address this gap, UC Berkeley researchers constructed a framework and set of models that include the combined impacts of three dynamic processes on evacuations – fire progression, communication systems, and traffic flow. The framework and models were applied to two case studies in California: the town of Paradise and the unincorporated community of Bolinas. In the Paradise case, the scenarios were based on the 2018 Camp Fire event. For the Bolinas case, the scenarios were based on hypothetical wildfire events.

policy brief

Real-World Simulations of Life with an Autonomous Vehicle Suggest Increased Mobility and Vehicle Travel

Abstract

Fully autonomous vehicles are expected to have a profound effect on travel behavior. The technology will provide convenience and better mobility for many, allowing owners to perform other tasks while traveling, summon their vehicles from a distance, and send vehicles off to complete tasks without them. These travel behaviors could lead to increases in vehicle miles traveled that will have major implications for traffic congestion and pollution. To estimate the extent to which travel behavior will change, researchers and planners have typically relied on adjustments to existing travel simulations or on surveys asking people how they would change their behavior in a hypothetical autonomous vehicle future. Researchers at UC Berkeley and UC Davis used a new approach to understand the potential influence of autonomous vehicles on travel behavior by conducting the first naturalistic experiment mimicking the effect of autonomous vehicle ownership. Private chauffeurs were provided to 43 households in the Sacramento, California region for one or two weeks. By taking over driving duties for the household, the private chauffeurs served the household as an autonomous vehicle would. Researchers tracked household travel prior to, during, and after the week(s) with access to the chauffeur service.

policy brief

Key Challenges in Sanitizing Transportation Data to Protect Sensitive Information

Publication Date

November 1, 2021

Author(s)

Areas of Expertise

Abstract

As new mobility services such as ridehailing and shared micromobility have grown, so has the quantity of data available about how and where people travel. Transportation data provides government agencies and transportation companies with valuable information that can be used for identifying traffic patterns, predicting infrastructure needs, informing city planning, and other purposes. However, the data may also contain sensitive information that can identify individuals, the beginning and ending points of their trips, and other details that raise concerns about personal privacy. Even if a traveler’s name and address is suppressed, adversaries could use other parts of the information such as trip origin and destination to learn an individual’s identity and their habits. Similarly, another transportation company competing with the company that collected the data could potentially steal their customer base if they can use the data to obtain proprietary information such as frequent dropoff/pick-up locations, vehicle positioning, travel routes, or algorithms for assigning vehicles to clients.

research report

Sanitization of Transportation Data: Policy Implications and Gaps

Publication Date

November 1, 2021

Author(s)

Areas of Expertise

Abstract

Data about mobility provides information to improve city planning, identify traffic patterns, detect traffic jams, and route vehicles around them. This data often contains proprietary and personal information that companies and individuals do not wish others to know, for competitive and personal reasons. This sets up a paradox: the data needs to be analyzed, but it cannot be without revealing information that must be kept secret. A solution is to sanitize the data—i.e., remove or suppress the sensitive information. The goal of sanitization is to protect sensitive information while enabling analyses of the data that will produce the same results as analyses of unsanitized data. However, protecting information requires that sanitized data cannot be linked to data from other sources in a manner that leads to desensitization. This project reviews typical strategies used to sanitize datasets, the research on how some of these strategies are unsuccessful, and the questions that must be addressed to better understand the risks of desensitization.

research report

Assessing the Incorporation of Racial Equity into Analytical and Modeling Practices in Transportation Planning

Abstract

This report examines if and to what extent state-level transportation departments in four states incorporate race and equity considerations into transportation planning technical analyses and modeling practices, particularly for long-range transportation plans, and how such equity-infused practices can be improved. The research team examined relevant literature, reviewed statewide long-range transportation plans for California and three other states, consulted with other experts, and conducted interviews with scholars and knowledgeable agency staff and practitioners. The findings indicate widespread acknowledgment that racial disparities in transportation exist, and state agencies have expressed a strong commitment to redressing the inequalities. However, while there has been progress in creating analytical equity tools to assess transportation projects and programs, they lack standardization. There have also been few noticeable revisions to existing regional transportation planning models to incorporate equity, and the profession lags behind what is technically possible based on the work of academic researchers. Technical staff need better training in regard to equity issues and agencies should encourage greater collaboration between equity and analytical units to develop and improve frameworks to assess equity performance in plans, programs, and projects.

published journal article

Glimpse of the Future: Simulating Life with Personally Owned Autonomous Vehicles and Their Implications on Travel Behaviors

Abstract

To explore potential travel behavior shifts induced by personally owned, fully autonomous vehicles (AVs), we ran an experiment that provided personal chauffeurs to 43 households in the Sacramento region to simulate life with an AV. Like an advanced AV, the chauffeurs took over driving duties. Households were recruited from the 2018 Sacramento household travel survey sample. Sampling was stratified by weekly vehicle miles traveled (VMT), and households were selected to be diverse by demographics, modal preferences, mobility barriers, and residential location. Thirty-four households received 60 hours of chauffeur service for 1 week, and nine households received 60 hours per week for 2 weeks. Smartphone-based travel diaries were recorded for the chauffeur week(s), 1 week before, and 1 week after. During the chauffeur week, the overall systemwide VMT (summing across all sampled households) increased by 60%, over half of which came from “zero-occupancy vehicle” (ZOV) trips (when the chauffeur was the only occupant). The number of trips made in the system increased by 25%, with ZOV trips accounting for 85% of these additional trips. There was a shift away from transit, ride-hailing, biking, and walking trips, which dropped by 70%, 55%, 38%, and 10%, respectively. Households with mobility barriers and those with less auto dependency had the greatest percent increase in VMT, whereas higher VMT households and families with children had the lowest. The results highlight how AVs can enhance mobility, but also caution against the potential detrimental effects on the transportation system and the need to regulate AVs and ZOVs.