Existing Technologies, Novel Benefits: Connecting Non-Motorized Users with Roadway Infrastructure
Amy Wyman, Oregon State University
Show Abstract
Existing technologies like smartphones and Dedicated
Short Range Communication (DSRC) have significant untapped potential to enhance
the experience of non-motorized users as they navigate the transportation
system—and not just their interactions with vehicles. This research project will
explore the near-term opportunity to interface DSRC-enabled infrastructure with
a smartphone-based platform to improve the safety and user experience of
pedestrians and bicyclists via a novel connected countdown timer-based display.
For the bicyclist, this display would indicate the approximate remaining green
time of a downstream traffic signal and enable the bicyclist to request extra
time to make it through a changing signal. For the pedestrian, this display
would non-numerically depict the amount of time remaining before the walk signal
is displayed. The primary research question for both displays is: Does the extra
information provided by the display improve bicyclist and/or pedestrian safety
and compliance with the traffic signal? The research will be conducted in a
three-year phased study: a widescale survey (phase one) will identify display
concepts to be tested in simulator environments for safety and compliance (phase
two), then scaled to field testing (phase three).
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P21-20365
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Change in Vehicle Ownership Rates: The Roles of Lifecycle and Cohort Effects
Julene Paul, University of California, Los Angeles
Show Abstract
Many public agencies and advocacy organizations have
worked to decrease the reliance of Americans on the private automobile. While
Americans routinely use and own automobiles at high rates, researchers have
noted negative consequences, including air pollution, congestion, and deaths and
injuries from collisions. In this context, a better understanding of cohort
influences on travel behavior can help predict future trends in auto ownership
and use.
In this paper, I examine the influence of lifecycle, cohort, and period
effects on vehicle ownership in the U.S. over the last two decades. The analysis
relies on data from the 2000 Census and 2005, 2010, and 2015 one-year American
Community Survey Public Use Microdata Samples (PUMS). I model the likelihood of
living in a zero-vehicle household by generation and year, and then use median
polish analyses to test the presence of cohort effects.
I find that that the Silent Generation (born prior to 1946) are less likely
to live in households with cars than more recent cohorts. However, Millennials
differ from previous generations, as they too are less likely to live in
households with automobiles. Although additional data are needed to draw a
definitive conclusion, the findings suggest that Baby Boomers may represent a
generation of “peak” automobile users.
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P21-20366
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Understanding the effect of cognitive deficits on driving behavior among concussed adolescent driver
Divya Jain, University of Pennsylvania
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P21-20367
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Equity and Demand Implications of Public Transit Fare Policies
Zakhary Mallett, University of Southern California
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P21-20368
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Enhancement of Constructability of Diverse and Unconventional Intersections and Interchanges
Minerva Bonilla, North Carolina State University
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P21-20369
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Optimizing Laboratory Curing Conditions for Hot Mix Asphalt to Better Simulate Field Behavior
Benjamin Arras, University of Texas, El Paso
Show Abstract
The engineering properties of asphalt mixtures change
with time. Shortly after placement, asphalt concrete (AC) layers are more
susceptible to rutting. As the pavement ages, the AC layer becomes stiffer, more
brittle, and thus more susceptible to cracking. Current protocols provide
guidelines for the selection of materials, the determination of the material
proportions (e.g. aggregates and binder content), and the evaluation of the
engineering properties (e.g. cracking and rutting potentials) of any given AC
mix. However, these protocols do not provide any check on the impact of aging on
the mixture. This project seeks to investigate and propose protocols to simulate
realistically the short- and long-term aging states required to evaluate the
asphalt mixture resistance to rutting and cracking, respectively. Such
conditioning protocols must be valid for all types of AC mixes including, but
not limited to mixtures that incorporate reclaimed asphalt pavement (RAP),
reclaimed asphalt shingles (RAS), recycling agents, and other additives. By
investigating existing and novel laboratory methods, this study seeks to propose
protocols that simulate the two critical aging states needed to design properly
an AC mixture, as well as provide a deep understanding of how curing affects the
physical and engineering performance of a mixture. The study leverages existing
research studies and available performance data along with a systematic and
innovative test matrix to optimize the curing conditions.
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P21-20370
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Personal Mobility Behaviors following Large Unexpected Shocks - The Case of COVID-19
Mohamed Amine Bouzaghrane
Show Abstract
COVID-19 has totally disrupted the daily life of almost
all Americans. In addition to the significant loss of life, it has significantly
impacted many economic sectors. Given that transportation is central to the
economy, the impact of COVID-19 on mobility patterns has been unlike anything we
have experienced before and is yet to be fully understood. As the virus
continues to spread around our communities, some of its impacts could become
permanent. As such, it is important to understand which personal mobility
impacts due to the pandemic are temporary and which are long lasting/permanent.
This study aims at understanding the heterogeneity of personal mobility
patterns throughout the COVID-19 pandemic. More specifically, the study aims at
1) identifying any spatiotemporal variations in personal mobility trends
throughout the pandemic and examine whether any changes to regional personal
mobility trends are related to regional spikes in COVID-19 spread, 2) exploring
the dynamics of daily profiles of different trip types across different
socio-demographic groups, and 3) revealing any changes in personal mobility
throughout the pandemic between groups with different pre-COVID19 personal
mobility behavior. This study achieves these goals by using point of interest
(POI) data from approximately 60,000 U.S. panelists. We supplement the POI
dataset with a survey of ~1000 panelists to measure the economic well-being,
mental health, personality, employment status, and social distancing behaviors
throughout the pandemic. These additional dimensions will help further explain
any determinants of change in personal mobility during the
pandemic.
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P21-20371
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Accounting for Streetscape Design in Pedestrian Preferences Using a Mixed Methods Field Experiment
Chester Harvey, University of California, Berkeley
Show Abstract
Transportation planners tend to characterize walkability
based on destination accessibility and pedestrian infrastructures such as
sidewalks and crosswalks. Urban designers, meanwhile, emphasize how streetscape
characteristics such as spatial enclosure and active facades are important for
creating inviting pedestrian environments. The degree to which streetscapes
influence walkers’ preferences in real-world settings, however, remains unclear.
It is difficult to represent streetscapes in stated-preference surveys in ways
that are sufficiently realistic to produce naturalistic responses. At the same
time, it is difficult to disentangle streetscape effects on naturalistic
revealed preferences, such as route choices, amongst confounding factors such as
directness.
This study addressed these challenges by conducting a stated preference
experiment in a field setting, offering subjects choices between real-world
stimuli. Confounding factors were accounted for through semi-structured
interviews conducted alongside the preference experiment. During the experiment,
subjects compared opposing block faces with contrasting streetscapes, choosing
which side of the street they would prefer to walk along and describing which
factors contributed to their choice. They also ranked block faces along the
entire route against one another. This produced a multidimensional dataset
describing preferences in both quantitative and qualitative terms.
Counter to expectations, subjects preferred streetscapes fronted by open
spaces with trees over those with enclosing buildings. However, subjects did
prefer more active facades and particularly disliked long stretches of blank
wall. This suggests that transportation planners aiming to improve walkability
may find it useful to look beyond the roadway and advocate for design codes that
encourage green features and active building facades.
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P21-20372
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To Pool or Not to Pool? Exploring Opportunities to Expand the Market for Pooling Through Multi-Objective Optimization of Pricing Policies
Jessica Lazarus, University of California, Berkeley
Show Abstract
Well-designed transportation demand management (TDM)
strategies are needed to fully leverage the potential of pooled on-demand
mobility to lessen congestion, energy use, and greenhouse gas (GHG) emissions by
reducing private-vehicle ownership and enabling higher vehicle occupancy rates.
While organized ridesharing has historically been focused on commuters, with
large employers playing a central role in incentivization and facilitation,
app-based ridesharing services and on-demand pooling provided by transportation
network companies (TNCs) and microtransit offer the opportunity to drastically
expand the pooling market, particularly in concert with effective incentive
mechanisms. Key findings will be presented from a stated preference survey
distributed in four California metropolitan regions from August to December
2018: Los Angeles, Sacramento, San Diego, and the San Francisco Bay Area.
Important socio-demographic, TNC trip purpose, and general mobility profiles of
TNC users will be examined. In addition, results from a discrete choice analysis
of the choice to use ride-alone TNCs, door-to-door shared rides, or indirect
shared ride services will be discussed, which reveal significant factors in
pooling demand sensitivity including variation across trip contexts,
metropolitan regions, socio-demographics, travel behavior, and attitudes and
perceptions toward sharing. The talk will conclude with a presentation of
preliminary results from a study of congestion pricing optimization using the
Berkeley Integrated System for TRansportation Optimization (BISTRO), in which
the heterogeneity of TNC mode choices are accounted for by implementing this
mode choice model into an agent-based simulation and activity-based travel model
of the City of San Francisco.
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P21-20373
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How can Shared Electric Autonomous Mobility (SEAM) fill mobility gaps for vulnerable populations and what are the barriers to realizing the benefits of SEAM?
William Lyons, University of Massachusetts, Amherst
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P21-20374
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Household provisioning in response to COVID-19: How are online shopping platforms shifting travel behavior?
Gabriella Abou-Zeid, Portland State University
Show Abstract
The rise of e-commerce and availability of fast and/or
free delivery engendered a new wave of online platforms for ordering food and
household goods. Such platforms are evolving the modes and mechanisms through
which grocery shopping occurs given many platforms offer same-day delivery or
curbside pickup options. Such services may help cities, households, and
businesses remain resilient through the COVID-19 pandemic, which has drastically
impacted travel for in-person shopping, global supply chains, and food business
operations. To investigate the role online platforms may play in shifting travel
behavior for household provisioning during and beyond the pandemic, a
longitudinal survey was being administered across five U.S. states—AZ, FL, MI,
WA, and OR. The first wave captured changes in household provisioning before and
after the state-of-emergency declaration for COVID-19, including the use of
online platforms for pickup or delivery. The second wave, fielded in December
2020, focused on adoption of, attitudes toward, and barriers to using online
platforms for household food shopping in response to COVID-19. Initial results
from the first two waves shed light on the variance in effects of online
platforms across demographics and built environments. Further, the complementary
versus substitutional nature of online-ordering and in-person shopping is
explored. The culmination of these survey data pose implications for policy
related to urban freight, public health in access to food, and continued
response to the COVID-19 pandemic.
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P21-20375
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Denver’s Sidewalks: Engineering, Policy, Economics, and Equity
Peyton Gibson, University of Colorado, Denver
Show Abstract
Pedestrian infrastructure plays a critical role in city
life, and many of its flaws have been exposed during the coronavirus pandemic.
As city residents move outdoors to dine, recreate, and social distance the
cracked, inaccessible walkways, or even complete lack of sidewalks has become
much more apparent. There is an apparent need in many American cities for
improving sidewalk quality and quantity to facilitate safer, healthier, and more
accessible communities. Some cities struggle to fund, maintain, and build
sidewalks because of fractured policies. Many leave sidewalk repairs and
maintenance in landowners’ or developers’ hands, which can often raise issues of
equity and right-of-way. My research will answer how cities can most efficiently
and equitably overhaul or upgrade their current sidewalk funding and management
systems. I plan on using spatial analyses and asset management principles to
quantitatively analyze and compare what cities across the United States and
world are doing to determine the most efficient and equitable way to fund and
prioritize sidewalks. With this research, I plan to recommend or rank funding
mechanisms and prioritization hierarchies or tools for city sidewalks. In
addition to preparing a one-page summary and infographic of data to make
available to city departments of transportation and public works, I will
complete and submit a full research to the Transportation Research Board in the
summer of 2021.
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P21-20376
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Potential Access for Common Carrier Parcel Lockers at Transit Facilities in Portland, Oregon
Katherine Keeling, Portland State University
Show Abstract
Transit goals have typically focused on commuter trips
but facilitating urban last-mile freight logistics is a potential strategy to
mitigate the demands of parcel distribution on the transportation network.
Presently, most parcel lockers operate out of private businesses, but consumer
surveys have found that transit users may be interested in locker facilities at
transit connections. The implementation of an unmanned, secure, common carrier
parcel locker system could have benefits for non-transit users as well.
Consolidation of deliveries would benefit courier companies by allowing
operations at increasingly competitive rates; retailers and consumers benefit
from low shipping rates. This evaluation includes a case study of the light rail
stations, transit centers, and transit malls in the greater Portland, OR metro.
Their potential of hosting transit sites is reviewed based on ridership (the
number of ons/offs at transit facilities), selecting a balance of central city
and suburban locations, the size of populations in influence areas (whether
transit users of not), and a framework for prioritizing locations based on
best-practice equity metrics. The suitability of locating lockers at
park-and-ride facilities, transit centers, transit malls, and high volume
bus/light rail stops is presented, with contextual considerations pertinent to
facility type. Particular attention is given to the park-and-ride facilities
outside the urban core for their suitability in reaching populations in
lower-density developments, as well as the potential of consolidated
distribution points in city resiliency plans.
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P21-20377
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Comparative Analysis of Wildfire and Hurricane Evacuations
Fanny Kristiansson, Embry Riddle Aeronautical University
Show Abstract
Mass evacuations, particularly those at a statewide
level, represent the largest single-event traffic movements that exist. These
complex events can last several days, cover thousands of miles of roadway, and
include hundreds of thousands of people and vehicles. Often, they are marked by
enormous delays and heavy congestion and are nearly always criticized for their
inefficiency and lack of management. However, there are no standardized methods
by which to systematically quantify traffic characteristics at the proper scale.
Several recent evacuations have occurred in the United States. Wildfire
evacuations have been ordered in the state of California while Hurricanes have
led to evacuations in the state of Florida. It has generally been accepted that
the evacuation from a regional wildfire is fundamentally different than the
evacuation from a hurricane. Hurricane evacuations generally encompass larger
areas when compared to wildfire evacuations and provide several days of advanced
warning. Whereas, wildfires impact smaller areas with significantly shorter
warning time. On the other hand, at the broadest level, evacuees and their
vehicles move in both time and space. This research seeks to develop a better
understanding of the travel flow principles that govern the evacuation process
and its impact on the mobility of a community, for different hazard types. The
goal of this research is to build upon the prior knowledge and expand the
scientific understanding of the evacuation process by systematically analyzing
evacuations from hurricane and wildfire events.
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P21-20378
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Exploring Factor Relationships Among Driving Simulator Outcome Variables in Horizontal Curves Using a Neurodiverse Sample
Gabriela Sherrod, University of Alabama, Birmingham
Show Abstract
Negotiating horizontal curves is a high-risk tactical
driving maneuver. Drivers must simultaneously and adeptly control their steering
adjustment, speed, and lane positioning, as well as accurately perceive the
curvature of the road segment and adjust to proprioceptive cues. To investigate
driving curve negotiation ability among at-risk populations, researchers often
use driving simulators, which allow for precise collection of numerous outcome
variables in a safe, controlled environment. Published works often include
subsets of variables that capture categories of driving behavior, such as
dynamic movement (e.g., longitudinal velocity, longitudinal acceleration) or
steering control (e.g., variability in lane positioning, number of lane
departures, steering velocity, number of steering reversals). However, to date,
these driving behavior categories have been theoretically but not quantitatively
associated. The proposed study will conduct Principal Components Analyses (PCA)
using a dataset including adolescent and young adult drivers with autism
spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and
neurotypical development (TD) to establish how extracted components of simulated
driving metrics (i.e., quantitative “categories” of data) relate to typically
utilized qualitative variable categories used in driving simulator research
(e.g., dynamic movement, steering control). PCA will be conducted using both the
entire dataset for a global examination of horizontal curve negotiation metrics
as well as diagnostic status subsets to examine if relationships between driving
variables produce differential patterns among different types of drivers.
Improved quantification of horizontal curve negotiation can inform future
training and education protocols to ensure safe driving among drivers, including
those with diagnoses that may put them at higher risk.
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P21-20379
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Safety Verification of Neural Networks for Unmanned Aircraft and Robotics Applications
Joseph Vincent, Stanford University
Show Abstract
We propose a novel method for verifying safety properties
of neural networks. A motivating example is given for verifying safety of neural
networks used to advise aircraft of imminent mid-air collisions. Neural networks
are useful for this purpose because they provide a collision-avoidance policy
that has a small data footprint which is necessary for small unmanned aircraft.
Such collision-avoidance networks should obey certain input-output safety
specifications if an aircraft is to seek certification from the Federal Aviation
Administration (FAA). One such property is that the network should advise an
evasive maneuver if an intruder aircraft is directly ahead. However, certifying
safety of neural networks has only recently been possible. The proposed method
builds on the current literature to provide marked advantages when identifying
the existence of unsafe advisories which the neural network may output. In
addition, the proposed method can be used for safety analysis of a closed-loop
dynamical system by computing forward and backward reachable sets in time. To
accomplish this, we note that neural networks with the ReLU activation are
piecewise-affine (PWA) functions. Forward and backward reachability problems can
be solved exactly for such functions at relatively little computational cost.
Our approach uses linear programming to incrementally define the explicit PWA
representation associated with a neural network, allowing for the incremental
evaluation of safety properties.
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P21-20380
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Establishing Safe Operating Speeds for Autonomous Vehicles: A Case Study from the Automated Skyway Express in Jacksonville, Florida
Andrew Loken, University of Nebraska, Lincoln
Show Abstract
Autonomous vehicles (AV) differ significantly from
traditional passenger vehicles in both their behavior and physical
characteristics. As such, the validity of the guidance provided in the Manual
for Assessing Safety Hardware, Second Edition (MASH 2016) is questionable in AV
applications. Impact angles, speeds, and vehicle weights specified in MASH 2016
are inextricably linked to the traditional vehicles underlying the estimates.
For AV applications, these parameters must be estimated from the ground-up,
stepping outside the guidance of MASH 2016. In this paper, a conservative method
for evaluating existing infrastructure to support AV traffic is proposed. The
method integrates traditional structural analyses with unconventional methods of
estimating impact conditions. This methodology was developed for the
Jacksonville Transportation Authority, who, when faced with unique challenges in
maintaining and expanding their Automated Skyway Express, opted to convert the
system from monorail to AV traffic. Leading AV developers were surveyed to
develop a portfolio of potential candidates for the conversion. Then, estimated
impact conditions were compared against the capacity of the system’s existing
concrete parapets. Ultimately, safe operating speeds for each AV candidate were
recommended on the bases of structural capacity and vehicle stability. All but
one AV candidate were deemed capable of safely operating at the desired speed of
25 mph without any modifications to the barrier. Although the methodology was
developed for a particular case, it is applicable to future implementations of
AVs on existing infrastructure, provided the roadway is confined similarly to
the Skyway deck.
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P21-20381
|
Artificial Intelligence Resilience-Based Infrastructure Management and Maintenance Plan
Julian Jesso, Embry Riddle Aeronautical University
Show Abstract
Over the past two decades, superloads, or vehicles with
gross vehicle weight over 150,000 pounds, have been increasingly utilized to
transport heavy loads, such as prestressed concrete girders, automotive presses,
transformers, wind turbine components, and other substantial loads. Since these
superload have a significant effect on the infrastructure system in comparison
to regularly permitted vehicles, they should be subject to special consideration
in the permitting and operation process. Despite the great research effort that
has been made to improve the superload permitting process, few studies have been
performed on the characterization and prediction of superload. Superload has its
own distinct characteristics that differ from other vehicle loads. Thus, there
is a need to better understand the characteristics of superload and to develop a
procedure to predict vital superload attributes for enhanced accuracy in the
permitting process. In this research, the major focus was to develop an
analytical procedure for the characterization and prediction of superload using
advanced gradient boosting machine (GBM) learning algorithms. A similar study
will be performed on overweight vehicles, which are vehicles between 80,000
pounds and 150,000 pounds. Additionally, artificial intelligence and big data
will be utilized in order to derive the optimal management and maintenance plan
for bridges based on the findings of all permit vehicles. The study will be
using a probability-based algorithm that combines data from multiple bridges,
pavement data, traffic data, environmental data, and human factor data to
provide an objective maintenance plan that ensures the integrity of Florida’s
infrastructure.
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P21-20382
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Algorithmic Challenges in High-Capacity On-Demand Mobility
Juan Carlos Martinez Mori, Cornell University
Show Abstract
High-capacity on-demand mobility has the potential to
overhaul public transportation by closing the gap in the ridership versus
coverage dilemma. However, as evidenced in a recent report by the Eno Center for
Transportation, most microtransit pilot programs in the US have experienced
difficulties with maintaining public reception and quality of service. A key
technical challenge for the successful deployment of a microtransit service is
the optimization of system-level operations. In this research, we bridge theory
and practice by taking a principled approach to tackle the optimization problems
arising in on-demand microtransit (e.g., vehicle routing, passenger matching).
Given the link between system-level performance and quality of service, our
research may enable a better assessment of the potential of this mode of
transportation.
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P21-20383
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Where will upzoning induce changes to the built environment?
Matthew Conway, Arizona State University
Show Abstract
Many cities and regions across the country are
considering reducing or eliminating single-family zoning as a way to
increase housing affordability. An important question brought forth by these
policy changes is how much effect they will have on the built environment.
While large swaths of metropolitan areas may be rezoned to allow more
dense housing, construction of new housing in many of these areas may not be
economically feasible. In this research, I evaluate where development of
new multifamily dwellings would be economically feasible in Southern
California, if single-family zoning were relaxed. I do this by estimating the
construction cost for a number of building plans, ranging from duplexes to
6-unit developments, that could fit on existing single-family lots. For
each residential parcel with a potential zoning change, I evaluate which of
these building plans could be constructed on the lot. I compare the
construction costs of all geometrically feasible buildings to their rental
values in that location. I estimate that 10% of parcels would be
redeveloped under a zoning change, producing 580,000 new units. If zoning
changes were instead confined only to areas within 1/2 mile of transit,
approximately 40% of this redevelopment would occur. The results are
highly sensitive to model assumptions, however, but all results show a spatial
pattern with development concentrated in higher income areas, lessening
gentrification concerns. Ultimately the outputs of this model will be fed into a
travel demand model to understand the transport impacts of this policy
change.
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P21-20384
|
Parameter identifiability of car-following dynamics
Yanbing Wang, Vanderbilt University
Show Abstract
The advancement of in-vehicle sensors provides abundant
datasets to estimate parameters of car-following models that describe driver
behaviors. The question of parameter identifiability of such models (i.e.,
whether it is possible to infer its unknown parameters from the experimental
data) is central to the well-posedness of the inverse problem, and yet still
remains open. This article presents both structural and practical parameter
identifiability analysis on four common car-following models: (i) the
constant-time headway relative-velocity (CTH-RV) model, (ii) the optimal
velocity model (OV), (iii) the follow-the-leader model (FTL) and (iv) the
intelligent driver model (IDM). The structural identifiability analysis is
carried out using a differential geometry approach, which confirms that all of
the tested car-following systems are structurally locally identifiable, i.e.,
the parameters can be uniquely inferred under almost all initial condition and
all inputs by observing the space gap alone. However, the analysis fails to
detect specific initial conditions and parameter sets that cause
non-identifiability. We propose a optimization-based numerical direct test to
determine if the model is identifiable given a specific experimental setup
(initial conditions and input are known). Direct test conclusively finds
distinct parameters under which the CTH-RV and FTL are not identifiable under
the given initial condition and input trajectory. When small deviations in the
output are permitted (e.g., due to measurement error), the numerical test finds
that none of the models are practically identifiable.
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P21-20385
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Roadside Vegetation Design and Management: State Interpretations and Environmental Impacts
Ellen White, Rutgers University
Show Abstract
My research compares the decision-making processes within
highway agencies regarding roadside vegetation management policy. I am
conducting interviews with landscape architects at state highway agencies and
followed a snowball method to continue interviewing personnel in the maintenance
and safety departments, geometric design departments, and others depending on
results that emerged. Roadside vegetation policy runs the gamut among
states, from managing native plantings and pollinator habitat to states that
routinely clear roadsides of both woody and herbaceous growth. As storm
resiliency in the form of tree removal is incorporated into more state
practices, as tree mortality from pests and drought increases, and as
environmental regulations are loosened, the trend among states may bend toward
clear-cutting.
Highway agencies remove trees from roadsides for several reasons, most
frequently with the goal of eliminating run-off-the-road crash fatalities. While
a roadside clear of trees is maintained as an absolute rule of road design, and
has been since the 1960s, its relationship to road safety is still disputed.
Further, if treated as a maintenance project, highway agencies are not required
to analyze the ecological effects of tree removal on habitat reduction, erosion,
carbon sequestration, or any other environmental metrics, even if the removal
constitutes acres of land. Further, agencies generally have no public process to
evaluate tree removal decisions, though some voluntarily engage the community
prior to taking action.
This research offers insights into best practices for collaborative
decision-making among staff at highway agencies, often siloed into engineering,
environmental, and maintenance units.
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P21-20386
|
DDETFP poster 23
Joshua Davidson, University of Pennsylvania
Show Abstract
This poster investigates the ways that
transit users learn about, make decisions around, and ultimately change the
ways they commute via public transit. The setting for this research
is the newly instituted Southeastern Pennsylvania Transportation Authority
(SEPTA) bus Route 49 in Philadelphia – the first new bus route added to SEPTA’s
network in a decade. Using a mixed methods research design that incorporates
quantitative survey data collected onboard, as well as qualitative data from
semi-structured interviews with select users, this poster addresses the
following research questions: 1) How do users learn about the ways they travel
to work via public transit and thereby gain “commute
knowledge”? 2) What role do communications from formal
versus informal actors play in the “commute knowledge” acquisition process? 3)
How did users commute before the new bus? 4) How did users ultimately decide to
change their commute to a new route? Based on initial findings, users
appear to gain substantial levels of “commute knowledge” from informal
mechanisms, such as conversations with coworkers, or merely from seeing the bus
go by. Respondents tend to discuss the new route with their peers, signaling
robust communication networks when it comes to making transit choices.
Overwhelming numbers of Route 49 users switched to this route from another
public transit mode. Users often make decisions around whether or not to use the
Route 49 day-of or even during the commute itself. Together, these findings
describe a universe of social and informal communications and sometimes
spontaneous actions that shape commute knowledge.
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P21-20387
|
The use and influence of health indicators in transportation decision-making
Kelly Rodgers, Portland State University
Show Abstract
Research on health and transport has increased
significantly in the past 20 years, both across health and transportation
fields. Researchers and practitioners have called for the use of health
indicators in transportation, which come amidst the growing emphasis on the use
of indicators for transportation plans and projects in general. The underlying
hope is that new procedural arrangements, such as measuring and tracking
indicators, can turn policy goals into practice. However, it is unclear if these
indicators, if used, have any influence on transportation decisions. Much of the
research on indicators is focused on their development and use rather than their
influence. This research proposal explores the use and influence
of health indicators in transportation using a mixed methods approach. First, an
inventory of municipal health indicators will be undertaken, addressing a gap in
knowledge regarding the extent and use of health indicators. Then, a survey to
municipal actors in a transportation decision-making process will explore which
factors (indicator, user, organizational, and political) best explain use and
influence. Finally, a common case will be selected from among the municipalities
to further explore the leading theories suggested by the survey results and
uncover the mechanisms by which use and influence occur.
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P21-20388
|
Effect of Perceived Driving Styles on Simulated Driving Performance Among Drivers with Developmental Disabilities
Austin Svancara, University of Alabama, Birmingham
Show Abstract
Drivers with autism spectrum disorder (ASD) and
attention-deficit/hyperactivity disorder (ADHD) may be at risk for compromised
driving safety due to unsafe driving behaviors. This study examined perceived
driving styles, how a driver actively chooses to drive, among drivers with ASD
and ADHD relative to typically developing (TD) drivers and how perceived driving
styles may subsequently affect driving behavior. Based on behavioral
manifestations of each disorder, it was hypothesized that compared to TD
drivers, drivers with ASD would report higher levels of anxious and
patient/careful driving while drivers with ADHD would report higher levels of
reckless/careless and anger/hostile driving. 48 participants (nADHD=16, nASD=16,
nTD=16) matched on age, gender, and driving experience completed the
Multidimensional Driving Style Inventory assessing 4 driving styles
(Reckless/Careless, Anxious, Angry/Hostile, Patient/Careful). Participants drove
in a driving simulator along a two-lane bidirectional road in a daytime suburban
setting. Drivers with ADHD reported greater Reckless/Careless driving style
compared to drivers with ASD, t(45) = 3.59, p = .001, but not the TD drivers.
Drivers with ASD drove at higher speeds than drivers with ASD, t(45) = 3.01, p =
.004, and TD drivers, t(45) = 2.17, p = .035. A hierarchical regression
indicated a significant interaction such that drivers with ASD reporting greater
reckless/careless driving style, β = -0.56, p = .048, and greater anxious
driving style, β = -0.56, p = .020, drove at slower speeds compared to TD
drivers. Drivers with ASD who perceive themselves as having maladaptive driving
styles may drive slower to selfcalibrate their driving.
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P21-20389
|
What Causes Change in Travel Behavior? Exploring the Relationship Between Key Events and Travel Behavior Using Social Media
Evan Iacobucci, Rutgers University
Show Abstract
Motivated by concepts employed in travel habits and
mobility biographies research, this project explores the relationship between
key life events and shifts in routine transportation behavior. It uses data
scraped from Reddit, a popular social media and content-sharing website, to
observe real-world conversations about personal travel histories. Specifically,
it focuses on understanding the relationship between changes in travel patterns
and key events that correspond with these changes. Directed content analysis
techniques are used to analyze 437 comments from three US cities: Atlanta,
Boston, and Washington, DC.
The results suggest two distinct pathways through which routine travel
behaviors change: 1) through influence of a key event, and 2) through
reevaluation of available options. In the first pathway, while key events hasten
change by making people consider their options, they play a causal role by
either altering the transportation choices available to a person or altering
their transportation needs. In the second, people reconsider their current
patterns and opt to make a change, but these changes appear to happen unprompted
by a key event.
These results inform a goal of sustainable transport policy in two ways.
First, the best way to leverage key events into less car-dependent behavior is
to ensure that viable alternatives are present when these events happen. Second,
people are capable of noticing and reacting to incremental changes in the
quality of available options and will likely respond to them.
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P21-20394
|
Crowdsourced-focused Distribution Operations in Free-floating Scooter Systems
Lacy Greening, Georgia Institute of Technology (Georgia Tech)
Show Abstract
This work begins to address the problems faced by
free-floating scooter systems that must effectively utilize and maintain the
continued participation of crowdsourced contractors, while also provide an
environmentally friendly, car-free alternative to its users. We show the value
of using simulation-based heuristics to place vehicles into a high-quality
configuration in an attempt to improve fleet utilization. Distribution planning
methods that seek to minimize the total vehicle miles traveled for the set of
independent contractors are then used to achieve the found configuration. We
also introduce the problem of assigning repositioning tasks in such a way that
encourages positive placement decisions by the contractors.
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P21-20395
|
Guidelines for Flaring Approach Guardrail Transitions (AGTs) Away from the Traveled Roadway
Ryan Bickhaus, University of Nebraska, Lincoln
Show Abstract
Approach guardrail transitions (AGTs) are commonly used
to safeguard rigid hazards, including bridge railings and concrete parapets. AGT
installations provide a safe transition in lateral stiffness between semi-rigid
guardrail and rigid bridge rail installations. For many state DOTs, intersecting
roadways or other roadside obstacles create space constraints that limit the
ability to effectively install an AGT within the desired area. Thus, a need
exists to minimize the length of AGTs tangent to the roadway.
My research project will entail a full evaluation of previous AGT crash test
data and flared guardrail studies in addition to simulation studies and
full-scale crash testing, which will be used to identify and evaluate critical
flare rates for AGT installations. The research project is comprised of two
phases. During the first phase, an extensive review of AGT crash test reports
and flared guardrail studies was performed to evaluate AGT performance and
identify a critical AGT design for further evaluation. Computer simulation
studies were then conducted to determine maximum flare rates for the identified
critical AGT design. The second phase of the research effort will use full-scale
crash testing to evaluate the critical flare rate identified by the Phase 1
study. A minimum of three full-scale crash tests will be conducted under the
Manual for Assessing Safety Hardware (MASH) test level three criteria to
evaluate the flared AGT installation. Finally, researchers will develop
recommendations and guidance for flared thrie-beam transitions. If applicable,
the system will be submitted to FHWA for an eligibility letter and Hardware
Guide drawings will be prepared for the system.
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P21-20396
|
Trajectories of Teen Driver Self-Regulation: The Role of Learner Phase Practice
Melanie Albright, University of Alabama, Birmingham
Show Abstract
Previous research suggests that practice in diverse
environments during the pre-licensure phase is related to better driving
performance in novice teen drivers. However, little research has examined the
relationship between pre-licensure practice (PLP) and driver self-regulation
(DSR) of specific driving environments. Objective: to examine the influence of
PLP diversity on DSR over the first six months of licensure.
The sample included fifty-six licensed teen drivers (Mage = 16.17). Baseline
data were collected within two weeks of licensure and at follow-ups 3- and
6-months post-licensure. At baseline, participants reported frequency of PLP in
various environments with a parent; at each timepoint, participants reported
driving exposure and DSR in specific environments. A Principal Component
Analysis extracted factors from the PLP items. Two factors emerged, Complex
Practice and Simple Practice. Longitudinal multi-level models examined impact of
PLP diversity on DSR over time.
DSR decreased over time (p < .001). More Complex Practice = less total DSR
at baseline (p < .001). More bad weather practice = less baseline regulation
of bad weather driving (p < .001). More nighttime practice = less baseline
regulation of driving at night (p < .001) and steeper decrease in night DSR
longitudinally (p < .01).
Some types of practice may better prepare teens for real-world driving.
Practice in complex environments was associated with less DSR at baseline.
Direct relationships between practice in night and bad weather conditions and
post-licensure DSR in those environments was found. Findings may inform teen
driver interventions targeting PLP on DSR post-licensure.
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P21-20397
|
DDETFP poster 30
Gregory Harasym, University of California, Berkeley
|
P21-20398
|
Literature Review on Ridesourcing Users' Travel Behavior in North America
Cassidy Crossland, University of Tennessee, Knoxville
Show Abstract
The rapid growth of ridesourcing services in North
America over the past ten years has introduced a new area of research. Since
this area of research is constantly changing, the objective of this paper is to
provide a comprehensive literature review of the latest research and summarize
findings relating to ridesourcing users’ traveler behavior. In total, 44 studies
were reviewed, and six main traveler-focused categories were identified:
demographics; frequency and time of use; trip purpose; reason for using
ridesourcing services; relationship between ridesourcing and other modes; and
transportation system impacts. The results pertaining to demographics revealed
that ridesourcing users are likely younger with higher incomes and education
levels, are full-time students or employed, and live in urban areas. Most
ridesourcing trips occur on weekends and at night, with the most common trip
purpose being for social events. Common reasons for using ridesourcing were to
avoid driving under the influence, parking difficulties, and faster travel and
wait times. Ridesourcing was found to substitute for taxis and personal
vehicles; however, the results were mixed for public transit. Some studies
suggest that ridesourcing can increase both vehicle miles travelled and the
number of vehicles on the road; however more research is needed in this area to
have conclusive findings. As both the use of ridesourcing services and research
involving ridesourcing continue to grow, it is important to understand the
trends of who is using these services and how travel behavior might be changing
during this period of expansion.
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P21-20400
|
The Role of Transit in the Upward Mobility of Low-Income Indianapolis Residents
Arianna Rambaram, Purdue University
Show Abstract
People with low income generally spend a much larger
proportion of their income on transportation than those who generate higher
incomes, and some may even find the cost of owning a car to be infeasible.
People without access to a personal vehicle are often reliant on pay-per-use
modes, such as public transit, to get to their place of employment. Creating
transit routes that connect residents of low-income neighborhoods to jobs that
pay higher incomes is something that transit agencies can do to help elevate the
socioeconomic statuses of people from these neighborhoods. Indianapolis, Indiana
is an example of a transit-equipped, metropolitan city with pockets of poverty
that have prevailed for years. In 2017, one quarter of Indianapolis’ residents
lived in either low-income neighborhoods or concentrated poverty. This study
seeks to assess the extent to which Indianapolis’ transit system is advantageous
for providing low-income people access to better employment opportunities. This
is done by utilizing ArcGIS tools to examine the proximity of financially
sustainable jobs to bus stops along routes which circulate near low-income and
impoverished Indianapolis neighborhoods. Financially sustainable jobs are
classified as those which pay their employees' wages, which meet the Indiana
Institute of Working Families’ self-sufficiency standards. Findings from this
study can provide transit agencies with additional equity-related criteria to
meet when creating and modifying transit routes. Long-term effects of
implementing these criteria include mitigating and decentralizing poverty,
especially in areas that have been historically plagued by
poverty.
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P21-20402
|
Estimating transportation pollution burden to inform zoning protocols in Oakland, California
Lily MacIver, University of California, Berkeley
Show Abstract
Through an internship with the City of Oakland’s Planning
and Building Department, I am conducting preliminary exploratory research on
zoning protocols to reduce proximity and exposure to air pollution from
transportation. This research must balance the need to support businesses to
maintain a strong industrial economic base with the need to protect the health
of nearby residential communities from the impacts of the emissions from said
businesses. The air pollution sources under City jurisdiction are primarily
mobile sources from permitted businesses that generate transportation activities
within its industrially zoned land. These types of businesses are also called
magnet sources. We hope to create a protocol the City can use to (1) assess and
estimate the impact of a business's air pollution contribution from their magnet
source and (2) inform and improve City policy on its conditional use permitting
process and existing non-conforming magnet sources. Our protocol will be
informed by inventories of traffic volumes from local streets and freeways,
surveys of truck trip volumes in a sample case study neighborhood, and truck
trip estimates for industrial businesses based on academic models. This effort
will include collaboration with the Bay Area Air Quality Management District’s
air modeling team to set pollution thresholds and understand modeled air
pollution estimates per business and land-use type.
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P21-20403
|
DDETFP poster 34
Edgar Mejía, University of California, Los Angeles
|
P21-20404
|
Slow Streets in San Francisco
Lena Rogow, University of California, Los Angeles
Show Abstract
In April, 2020, one month into COVID-19 lockdown, the
San Francisco Municipal Transportation Agency (SFMTA) announced its new Slow
Streets program. This emergency response closed select city streets to thru
traffic, providing more space to physically distance for those who want to
travel by foot, bike, wheelchair and other modes. Since then, the city has added
even more streets for a total of 24 implemented corridors in the program.
Moving forward, the city now has to decide how to build a Slow Streets
program that will be sustainable in the long term. To help with this plan, SFMTA
issued a public questionnaire that asks where respondents live, what their
opinion is of Slow Streets and if they recommend certain corridors for future
Slow Streets. This capstone project will set out to analyze citizen responses to
interpret the project’s effectiveness in communicating to San Francisco
residents. The research will primarily focus on two research questions: What are
San Franciscans’ perceptions of Slow Streets and do they understand how the
program works? How are citizen responses different based on socio-demographic
data in neighborhoods? Based on this analysis, the capstone will recommend
future steps SFMTA can take in communicating about Slow Streets to San
Franciscans.
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P21-20406
|
A Theory of Curb Parking Management
Miriam Pinski, University of California, Los Angeles
Show Abstract
The curb is a monopoly good; network infrastructure
owned entirely by cities. It differs from most network infrastructure,
however, in not being managed by prices. Cities allocate curb space with a
confusing patchwork of metering, time limiting, permitting, and—perhaps most
notably—fines. Urban parking stands out among network infrastructure for its low
quality, low payment, and the large share of its revenue derived from
punishment. I develop a theory of why this is so, which emphasizes the curb’s
public ownership and low production costs. I then use both qualitative and
quantitative methods to examine some of the theory’s implications. I draw on
descriptive data from a variety of US cities, but focus primarily on the city of
Los Angeles. I show that in a politicized parking environment, city
officials are more likely to exempt affluent neighborhoods from payment, and
more likely to levy fines on poorer neighborhoods.
|
P21-20407
|
Ridehail to School: An Analysis of HopSkipDrive and School Transportation Options for Vunerbable Students in Los Angeles County
Samuel Speroni, University of California, Los Angeles
Show Abstract
The Every Student Succeeds Act (2015) gave foster youth
additional legal protections in school, including the right to transportation
and the right to remain at their school despite any moves, similar to
protections already in place for students experiencing homelessness and students
with disabilities. California’s compliance with this mandate was
relatively more difficult than other states’, as only eight percent of students
in California travel by school bus, compared with 35 percent nationally.
Thus, California schools could not simply tap into these existing services to
provide transportation for foster youth.
Ridehailing offers a solution to this gap. HopSkipDrive, a ridehailing
company designed to transport children, engages in contracts with school
districts and counties to provide school transportation for these vulnerable
student populations. In 2018–2019, HopSkipDrive provided 32,796 trips to
school in Los Angeles County, with massive time savings over the logical
alterative: transit. HopSkipDrive offers time savings of nearly 70 percent
compared with the same trips simulated on transit. HopSkipDrive’s trips
average 28 minutes in duration, yet on transit only 30 percent would have taken
less than 45 minutes. This is despite 90 percent of all origins and
destinations being located within a half-mile of a transit stop. This
service has important social equity implications beyond just time savings
offered to vulnerable student populations, as HopSkipDrive contract trips tend
to originate in neighborhoods with high percentages of low-income households and
people of color.
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P21-20408
|
DDETFP poster 38
Edward Forscher, University of California, Berkeley
|
P21-20409
|
Fleet Sizing and Service Region Partitioning for Same-Day Delivery Systems
Dipayan Banerjee, Georgia Institute of Technology (Georgia Tech)
Show Abstract
We study the linked tactical design problems of fleet
sizing and partitioning a service region into vehicle routing zones for same-day
delivery (SDD) systems. Existing SDD studies generally focus on operational
problems, while limited work on SDD tactical design does not consider a priori
customer partitioning or clustering, which have been shown to improve the
efficiency of vehicle routes in other logistics contexts. Using continuous
approximations to capture average-case system behavior, we consider first the
problem of independently maximizing the area of a single-vehicle zone to
minimize fleet size. We characterize area-maximizing dispatching policies and
leverage these results to develop a procedure for calculating optimal areas as a
function of a zone's distance from the depot. We demonstrate how to derive fleet
sizes from optimal area functions and propose an associated Voronoi partitioning
approach. We test our approach in a computational study that examines on two
different service regions, demonstrating efficacy in terms of prediction
accuracy and robustness.
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P21-20410
|
DDETFP poster 40
George Gunter, Vanderbilt University
|
P21-20411
|
Diversifying transportation: Nurturing mobility cultures
Teo Wickland, University of California, Los Angeles
Show Abstract
In recent decades, studies and interventions in
transportation equity have attempted to measure and improve the extent to which
the U.S. transportation system serves and includes diverse groups, such as
women, the elderly, and ethnic and racial minorities. However, rather less study
and intervention has focused on the diversity of the transportation system
itself, including: diversity of modes; diversity of trip purposes; diversity of
ways of experiencing and enacting transportation; and diversity of ways of
valuing, understanding and relating to spatial mobility. In this presentation, I
contrast the relative homogeneity of transportation in the U.S. today with the
relative diversities of transportation in other times and places, while also
highlighting minor mobility subcultures of the contemporary U.S. I critically
analyze barriers to transportation diversity and discuss a politics of
possibility for helping diverse mobility cultures to flourish.
|
P21-20412
|
Evaluating First and Last Mile Access to Transit for People with Disabilities
Kaylyn Levine, University of Texas, Austin
Show Abstract
Access to opportunities measures used in planning
practice and research assume that pedestrians can complete public transit trips
and traverse the first and last mile without difficulty. But physical
accessibility depends on characteristics of the built environment and requires a
full, unbroken path between origin and destination. Due to limitations
associated with data availability and scale, existing access to opportunities
measures generally do not include characteristics like curb cuts and
obstructions even though these features directly affect physical accessibility.
For people with disabilities, these characteristics are extremely important
because they rely on public transit for their everyday mobility and
participation in society. My research uses mixed methods to
understand how first and last mile challenges prevent people with disabilities
from effectively reaching destinations using public transit. I employ a
synthetic population along with detailed sidewalk data to understand how access
to opportunities varies for people with disabilities at a fine scale in Seattle,
Washington. This work demonstrates where sidewalk investments would have the
greatest impact and recommends mitigating policies and strategies that
transportation agencies can implement to enhance conditions for people with
disabilities.
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P21-20413
|
Transit Ridership & Neighborhood Change in Southern California
Hannah King, University of California, Los Angeles
Show Abstract
In the United States, transit is largely a lifeline
social service for low-income people (Taylor & Morris, 2015). This function
has eroded, however, to the extent that low-income people have been displaced
from transit-rich areas (Bardaka, Delgado, & Florax, 2018). We test this
idea using data from Southern California. We do so in two parts. First, we match
changes in Census tract-level rents and housing burdens to changes in
transit boardings, and show that across two time periods—2008-2012 and
2013-2017—as housing prices rise boardings fall. This finding is robust to
a broad array of controls. It only suggests, however, that neighborhood change
is associated with falling neighborhood ridership. It remains possible that
lower-income people no longer living in high-transit neighborhoods ride just as
much once they move elsewhere. To address this possibility, in the second
part of our analysis we will use migration data to follow people who left Census
tracts with large ridership losses disproportionately located in lower-density
census tracts with fewer transit stations and lower transit accessibility. If
our hypothesis holds, these people relocated to tracts with comparatively poor
transit infrastructure that discouraged transit use.
|
P21-20414
|
Make room for buses: A case study of transit revival in Seattle, and lessons for urban America
Madeleine Parker, University of California, Berkeley
Show Abstract
Bus ridership has decreased in major cities across the
United States: it is currently at its lowest level in thirty years. One of the
few exceptions is Seattle, where bus ridership has seen consistent increases the
past few years. The goal of this research is to assess what factors have led to
Seattle’s success with buses, and through that case to provide insight into how
cities can prioritize transit in a way that can attract new riders, change
perceptions of the bus, and compete with other modes. The findings will inform
debate on the sources of transit ridership growth and decline, and lessons for
embattled transit systems. This has significant implications for sustainability,
congestion, and the financial health of transit systems and their ability to
provide service for populations depending on them.
|
P21-20415
|
The Effect of COVID-19 on Routine Mode Choice
Amy Lee, University of California, Davis
Show Abstract
Habit is a key determinant of travel behavior, where
people who have regularly chosen a mode in the past are more likely to use it in
the future (Schneider 2013, Verplanken et al. 2014, et cetera). But mode choice
habits can be interrupted when people experience significant life changes
(Bamberg et al. 2003, Janke & Handy 2019). The abrupt and long-term
workplace closures affected by the COVID-19 pandemic have potential to cause
precisely the type of significant life change that may interrupt routine mode
choices. The extent that pandemic-era workplace closures cause long-term travel
behavior changes will be the subject the study for the next decade and beyond,
but we can already see the resultant short- and medium-term changes in mode
choice. We use in this study both a panel and repeat cross-sectional survey to
model changes in mode share among a university population (undergraduates,
graduate students, faculty, and staff) before and during the 2020 campus closure
due to COVID-19. This university – University of California, Davis – is a
particularly bicycle-friendly campus for the United States; it had a high
pre-pandemic bicycle and transit mode shares and a low vehicle mode share
relative to state- and nationwide patterns (34% bicycled to campus, 20% rode
transit, and 31% drove alone in the fall of 2019). In the second wave of our
panel survey, administered in spring 2020, the share of people commuting by
single-occupancy vehicles had nearly doubled from the fall (57% drove alone) and
in the third wave, administered in fall 2020, 41% of respondents drove alone.
Many of the “new” drivers were people who had regularly bicycled or taken
transit before the pandemic, and we see commensurate drops in bicycle and
transit mode shares. Drawing from travel behavior theory, we explore and
estimate the influence of factors such as habit, attitudes, perceived safety,
and enjoyment on the event of switching routine modes. If these mode switches to
single-occupancy vehicles are sustained and widespread, such trends will
contravene local, state, and national policy goals to reduce driving in the
interests of improving air quality, mitigating climate change, and easing
parking demand.
|
P21-20416
|
Care Coordinators’ Perspectives on Transportation Barriers to Accessing Healthcare in North Carolina During the COVID-19 Pandemic
Lindsay Oluyede, University of North Carolina, Chapel Hill
Show Abstract
Introduction: The onset of the COVID-19 pandemic brought
sudden and drastic changes to daily life. Several trends converged that
influenced changes in travel behavior including loss of income and benefits from
widespread layoffs or reductions in work hours, and reduced transit capacity due
to service cuts or boarding restrictions. Healthcare access was also impacted.
Staff at overwhelmed hospitals were faced with diverting patients or delaying
transfers. Even healthcare facilities with minimal COVID-19 patient loads
postponed elective care. Overall, hospitals and other facilities tightened
restrictions on patients’ visitor/guest policies. This qualitative study
explores how the COVID pandemic impacted transportation access to healthcare and
the innovative solutions used to address those barriers—from the perspective of
care coordinators (social workers, nurses and other professionals in the medical
field who support patients in utilizing medical care, including addressing
transportation issues).
Methods: Fifteen in-depth interviews were conducted in October and November
of 2020 with care coordinators employed at hospitals in two regions in North
Carolina that serve patients in their respective regions and around the state,
as well as treatment centers and social service agencies.
Results/Conclusion (TBD): This project will identify transportation barriers
to accessing healthcare experienced during the COVID-19 pandemic, from a
cross-disciplinary perspective. Moreover, the study will examine the role of
emerging virtual services (e.g., telehealth, etc.) during the pandemic to
address reduced access to healthcare.
|
P21-20417
|
DDETFP poster 47
Vamsi Krishna Vegamoor, Texas A&M University
|
P21-20418
|
COVID-19 and Travel Trends in US Counties
Rachael Panik, Georgia Institute of Technology (Georgia Tech)
Show Abstract
The COVID-19 pandemic disrupted typical travel patterns
across the United States. Governmental responses to the pandemic have varied
from state to state, ranging from stay-at-home orders to non-essential business
closures to, in some cases, nearly no requirements. In addition, authorities
dispersed public health messaging to help people make educated choices about
their behaviors and travel. The “flatten the curve” campaign, for example, was a
wide-spread health education effort; the message encouraged people to take
immediate action to quell the spread of the disease so that the number of cases
did not exceed local hospitals’ capacities to care for COVID-19 patients. Both
emergency governmental action and public health education campaigns have changed
trip making behaviors.
|
P21-20420
|
Midwest Virtual Road Corridor (MVRC): An ultra-compact road map representation for CAVs
Ricardo Jacome, Mid-America Transportation Center
Show Abstract
Many solutions have been presented to assist connected
and automated vehicles (CAVs) interpret the geometries of roadways through
optical means, such as cameras or lidar point cloud maps, or external augmented
global navigation satellite system (GNSS) positioning systems. A new method of
representing road data based on constitutive segment relationships and
GNSS-based anchor points is proposed, called the Midwest Virtual Road Corridor
(MVRC). Critical points of roadways, such as the left-side edge boundary per
travel direction, are extracted along the entire length of the roadway.
Consecutive points of the road are used to develop orthogonal curvature vectors,
road tangent vectors, and continuity relationships based on the Midwest Discrete
Curvature (MDC) method. In this study, road data was smoothed, and characterized
to identify unique road curvature profiles as either curved or straight from any
general curve geospatial dataset. This technique was evaluated by discretizing
three testing road sections from Google Earth: A general highway curve
consisting of multiple spiral transitions, straight, and constant radius curves.
A constant radius curve and a highway interchange. Lastly, a matrix is
constructed by combining the road segment anchor points, road tangent vectors,
curvature vectors, and supplementary road information that can provide an
ultra-compact, high-fidelity, and precise virtual road corridor for CAVs. The
MVRC data matrix can be implemented to assist many of the existing and
in-development CAV guidance solutions.
|
P21-20421
|
Sinkhole Susceptibility Model using Remote Sensing Data
Ronald Rizzo, University of Kentucky
Show Abstract
Determining the location and severity of sinkhole
hazards through geospatial methods is fundamental to predict the risk of
sinkhole occurrence by developing a susceptibility model that is objective and
repeatable. Sinkhole formations are associated with both the geomorphology and
changes in the hydrological conditions. Hence, this research investigates the
use of satellite-based temperature data, precipitation data, volumetric moisture
content data, and the national soil survey data for reliable sinkhole
nowcasting. First, historical time series data of conditional factors
contributing to the triggering of sinkholes was assembled from high-quality
satellite-based precipitation data such as the National Aeronautics and Space
Administration (NASA) Earth and Precipitation Satellite Missions; meteorological
conditions extracted from the Moderate Resolution Imaging Spectroradiometer
(MODIS), Daily Surface Weather and Climatological Summaries (Daymet V3),
and the Global Precipitation Measurement (GPM) mission with Integrated
Multi-satellitE Retrievals (IMERG) for GPM. This data was then combined
with the spatial and temporal hydrological changes in the ratio of water to soil
volume (volumetric water content) from surface water to groundwater recharge
(soil moisture data) that was acquired from the NASA Soil Moisture Active
Passive (SMAP) Earth satellite mission. Lastly, geological data were collected
from the soil survey performed by the USDA National Resource Conservation
Service (NRCS) as collapse tends to be in areas with underlain carbonate
(limestone and dolomite) and evaporate (salt, gypsum, and anhydrite)
rocks. The study also examined the aggregation of satellite data to
downscale resolution errors.
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P21-20422
|
DDETFP poster 51
Alexandra Pan, University of California, Berkeley
|
P21-20423
|
DDETFP poster 52
Robert Pfaff, University of Michigan, Ann Arbor
|
P21-20424
|
DDETFP poster 53
Zhongxia Yan, Massachusetts Institute of Technology (MIT)
|
P21-20426
|
Accurate, multimodal microsimulation of urban air mobility and its impact on travel behavior and land use
Pavan Yedavalli, University of California, Berkeley
Show Abstract
Emergent mobility technologies, such as UAM, must be
understood in the context of urban transportation networks in order to better
inform policy and infrastructure decisions for cities. When evaluating the
impact of new modes and evaluating future infrastructure provision, cities
typically assess the intent, need, possibilities, judgment, tradeoffs, and
investment costs, and simulations can often inform this analysis. However, there
has yet to be a comprehensive simulator of the short- and long-term effects of
UAM on urban environments. This metropolitan-scale transportation and land-use
simulation will leverage powerful parallel computing architectures, advanced
optimization architectures for network design, and extensive multinomial logit
modeling for both activity generation and long-term decision-making
processes.
This project develops an integrated simulation pipeline for air and ground
transportation, to enable door-to-door simulations of multi-modal (ground and
air) transportation. This integrated simulation capability will be used to
support an optimization-based approach for multi-modal transportation, in order
to enable optimized design and placement of a network of vertiports relative to
a number of measures, including cost, capacity, and travel time. These outputs
are then incorporated into long-term land use models to understand the evolution
of cities over time.
Near-completed work includes the development and coupling of both the ground
and air microsimulators, with aerial expertise provided by NASA. In addition,
advanced optimization and clustering techniques, travel time analyses, and
vertiport capacity design have also been conducted. Ongoing work includes
calculating mode choice of UAM, and incorporating the aforementioned simulator
inputs and outputs with long-term land use
simulation.
|
P21-20425
|
Examining Transport Access, Egress, and Heterogeneity at U.S. Community Colleges
Aqshems Meten Nichols, University of California, Berkeley
Show Abstract
Community colleges (CCs) continue to serve as an
important ladder of opportunity for residents in the United States. These
opportunities include, but are not limited to, gaining job training skills,
acquiring educational credits in advance of transferring to a four-year
university, and earning an equivalent of a high school diploma. Travel to CCs is
primarily served by private automobiles as most CCs do not provide on-campus
housing for students. This could serve as a barrier to students initially
enrolling in CCs, establishing successive enrollment at CCs, and achieving
academic success at CCs. This research poster provides a breakdown of the
literature related to transport to and from CCs, existing literature gaps, and a
research plan for investigating the relationship between CC transport access and
egress and academic achievement at CCs. Additionally, the variation in this
relationship across the significantly heterogeneous student populations often
found at CCs will be explored.
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P21-20427
|