conference paper
Phd Dissertation
published journal article
published journal article
Opinions regarding emergent sustainable transportation alternatives, such as bikeshare and e-scooters, and more traditional green alternatives like public transit, spread through social networks via opinion diffusion mechanisms, like word-of-mouth and mass media. The impact of social media on diffusion of sustainable mobility opinions is not well-understood given the present lack of data. To address this gap, this paper introduces a modeling framework for the impact of social media on opinion diffusion. Inspired by Roger’s diffusion theory, the framework applies different learning mechanisms (e.g., word-of-mouth and mass media) in network architectures to explore the effects of network topology on acceptance of green travel alternatives using conceptual idealizations of the complex processes involved in diffusion interactions. We present a dynamic agent-based simulation methodology capturing the impact of information and communications technology (ICT) like social media on diffusion of environmentally friendly travel mode consideration through social networks. The agent-based models provide visual comparisons of the effects of network structure and social media influence on opinion diffusion, the way opinions spread, and which agents exhibit the strongest influence. We identify types of social media influencers that most effectively encourage adoption of sustainable transportation alternatives and present an illustrative framework of the mechanisms that drive opinion diffusion. Exploratory findings suggest that: (1) scale-free networks provide the slowest initial diffusion rate but the greatest overall diffusion over time, (2) the most effective behavior incentivization strategies depend on network structure, (3) in scale-free networks, increasing the number of initial opinion leaders improves diffusion, while increasing the number of communication encounters within the network over the first year following product deployment does not noticeably improve diffusion, and (4) providing smaller financial incentives to a greater number of opinion leaders is the best strategy.
published journal article
Traffic exposure assessments could misclassify the extent and locations of exposure if traditional recall surveys and self-reported travel diaries do not record all participant activities. The Harbor Communities Time Location Study (HCTLS) examines the nature, extent and implications of underreported locations/trips in a case study which used portable Global Positioning Systems (GPS) devices to track the diurnal patterns and traffic exposure of 47 residents of communities near the Los Angeles-Long Beach port complex. Participants were similar to adults nationwide in time spent indoors, in-vehicle, and outdoors, but spent more time indoors at home (78% vs. 66%). Overall, participants did not report nearly half (49%) of the locations and trips identified in GPS-enhanced data on their activity diaries, resulting in about 3 h/day in unreported locations and 0.6 h/day in unreported trips. The probability of a location/trip being underreported was systematically correlated with participant and location/trip characteristics. Self-reported data missed about 50 min of heightened air pollution exposures during the 5 h/day on average participants spent in high-traffic areas and about 30 min during the 4 h/day near truck routes. GPS-enhanced methods provide opportunities to more precisely characterize exposure periods and tools to identify facility, roadway, and land use types of the greatest concern for mitigation efforts. Published by Elsevier Ltd.
published journal article
conference paper
This research reveals statistical characteristics of speed dispersion and its relationships with fundamental traffic flow parameters in northern California. Nearly a quarter million vehicle observations of a five-lane urban freeway are examined individually by lane and aggregately for a total of seven categories. Speed dispersion is measured by coefficient of variation of speed (CVS) and standard deviation of speed (SDS). CVS displays an exponential form of occupancy or space mean speed, and is two-phase linear to flow. Variation of CVS is stable and similar across lanes during light traffic, and afterward increases and diverges into three groups. SDS in contrast does not present any simple equation of the fundamental parameters. Both CVS and SDS of the all lane mix are greater than those of other categories given fixed occupancy or mean speed.
policy brief
Understanding how residents feel about neighborhood changes due to new development along transit corridors (often referred to as transit-oriented development) remains understudied despite growing concerns over displacement and gentrification. Studies that examined these concerns are largely based on analyzing land use, housing values, and socio-economic shifts (i.e., who is moving in and out of neighborhoods), and do not provide conclusive evidence that transit-oriented development (TOD) is linked to neighborhood gentrification and displacement. Prior surveys of residents living near transit indicate a generally positive assessment of TOD in terms of improved walkability and accessibility but also express concerns over pedestrian safety and parking related to increased traffic and new commercial development. However, recent studies counter this relatively positive assessment of TOD, particularly among activists and community organizers in low-income communities of color.
published journal article |
Jun 2021
published journal article |
Jun 2024
research report
working paper |
Jun 1986