Accounting for cognitive and perceptual biases in computational models of human movement Thomas J....
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Accounting for cognitive and perceptual biases in computational models of human movement Thomas J. Pingel Department of Geography University of California,
Accounting for cognitive and perceptual biases in computational
models of human movement Thomas J. Pingel Department of Geography
University of California, Santa Barbara February 10, 2012
Department of Geosciences, University of Arkansas
Slide 2
My Focus Science that helps us understand and visualizations
that help support spatial decision making.
Slide 3
This includes elements of: Spatial Strategy Navigation
Geospatial reasoning Cognitive science Methodology Open source
programming Nonparametric statistics Visual analytics
Geovisualization Automation LIDAR and feature extraction TINs and
other terrain- related data structures Immersion Dynamism &
Interaction
Slide 4
Cognitive and Perceptual Biases & Patterns of Movement How
do human biases in slope perception affect patterns of movement in
mountainous terrain? What role do vision and spatial extent play in
determining how humans search an area? What role do strategic
disposition and attitudes toward risk play in causing asymmetric
patterns of pedestrian movement?
Slide 5
The spatial pattern of movement for humans in mountainous areas
is different than it is in less rugged terrain. This is because
travel on slopes is slower, requires more effort, and is generally
more dangerous than walking on level ground.
Slide 6
The impact of a slope depends somewhat on the direction of
travel. For example, pedestrian travel on slopes is asymmetric with
respect to time. Toblers Hiking Function kph = 6 { exp -3.5 * abs
(dh/dx + 0.05) }
Slide 7
Incidentally, it is probably time to update the hiking function
using GPS measurements.
Slide 8
Humans greatly overestimate geographic slope. Following data
presented in Proffitt et al. (1995). Slope / Cost Translation
Uphill / Downhill Energy, fatigue, safety Abilities, limitations of
agents Anticipated vs. actual costs
Slide 9
Decisions can be modeled by shortest-path algorithms operating
on cost-transformed slope values. A slope raster is often the basis
for the cost surface.
Slide 10
It is important to distinguish between linear and areal slope.
I think linear slope is more important, though both matter.
Slide 11
Observations of existing tracks and trails provide frequency
distributions of selection patterns. Routes may be asymmetric but
paths are not.
Slide 12
The frequency distributions are transformed to cost functions.
The cost functions are applied to the linear slope values.
Slide 13
The type of cost transformation function greatly affects the
location of the selected path.
Slide 14
The method is adaptable to different agents and constraints,
and seems to perform well at a variety of scales. Model of Rory
Stewarts walk in Places in Between.
Slide 15
I am also very interested in digital navigation systems. How do
people choose routes? Preferences Heuristics Strategies How can we
help them find those routes? Profile development Expressed Revealed
Algorithms Visualizations & Interactions
Slide 16
If existing methods generate least cost paths (in terms of time
or distance) why would we want to modify that? 1.Purely economic
concerns dont capture the full range of criteria that go into route
selection. 2.These other criteria are important for overall
utility.
Slide 17
Preference rankings depend on mode of travel.
Slide 18
Characteristics of the traveler - in this example, sex matter
as well.
Slide 19
A clearer concept of strategy could be helpful in helping us
ask the right questions and to interpret the data. Strategy has
many meanings in the literature. Style Route vs. Orientation (or
Landmark vs. Survey) (Lawton, 1994) Explicit Techniques Look-back
strategy, edge following (Cornell, Heth & Rowat, 1992) Reliance
on external aids Maps or knowledge (Hutchins, 1995; Ishikawa et
al., 2008) Digital vs. analog Task-related Search vs. Access
(Passini, 1992)
Slide 20
I think the idea of a strategic disposition is useful.
Strategic disposition reflects the degree to which an individual
cares about reasoning strategically about a problem, without
necessarily suggesting what strategy that individual might use. It
is important to distinguish between strategy, strategic
disposition, and performance.
Slide 21
How can we measure strategic disposition? Self-report is
crucial Not directly observable Instrument 40 initial items 101
participants Factor analysis 10 Items Affinity, frequency, latency,
externalizability, & conditional thinking Strategic Disposition
Index 1)I enjoy playing games that involve a great deal of
strategy. 2)I am not very good at finding the shortest or quickest
route to a place. 3)When driving, I consciously try to find the
best route for the circumstances. 4)I don't often play games that
involve a great deal of strategy. 5)When driving, I don't typically
think about my route. 6)I enjoy activities that involve strategic
thinking. 7)When walking, I don't consciously try to find the best
route for the circumstances. 8)I am not very good at explaining the
strategies I use. 9)I often think about route planning in a way
that I would characterize as strategic. 10)When parallel parking on
a street, I am careful to park so that as many vehicles as possible
can fit in a given block of spaces.
Slide 22
The distribution of SDI is fairly normal.
Slide 23
Men tend to a report a higher SDI than women.
Slide 24
Search Strategy Idea from a series of articles Tellevik, 1992
Hill et al.,1993 Gaunet & Thinus-Blanc, 1996 Blindfolded or
blind subjects search for objects in a small room Search Strategies
Perimeter Gridline (aka Parallel) Memorization Strategies
Object-to-wall Object-to-home Object-to-object (Hill et al.,
1993)
Slide 25
Finding the Invisible Animals Audio cues Movement tracking
Assessment Object learning Route efficiency
Slide 26
We reason about space differently, depending on the scale (or
extent) in question. Source: Montello, D. R. (1993). Scale and
Multiple Psychologies of Space. In: Frank and Campari (Eds.),
Spatial Information Theory for GIS. Figural Projectively smaller
than the body Pictoral and Object subspaces Vista Larger than the
body Can be apprehended without locomotion Environmental Requires
locomotion Learned from direct experience Geographical Learned
through symbolic representations
Slide 27
Incidentally, we also think about inside spaces and outside
spaces differently. Creating immersive visualizations that support
better inside/outside reasoning is one goal of my current
project.
Slide 28
Slide 29
Slide 30
Gridline searches, localizations, and object-to-object
visits
Slide 31
There was a strong spatial signature, supporting the idea of
decreasing marginal costs.
Slide 32
There was no association between gridline search propensity and
strategic disposition index. Perhaps there is a difference between
being systematic and being strategic. There is evidence to suggest
that strategists differ substantially on the level of detail in
their plans.
Slide 33
Attitude toward risk represents another kind of meta-strategy
that influences wayfinding. Some people like to play it safe,
willing to sacrifice a worse mean result for a lower
variability.
Slide 34
Kahneman and Tversky explored this in the context of Prospect
Theory. Would you take: (a)a sure $20 or (b) a 50-50 chance at $40
or nothing
Slide 35
Wayfinding questions are somewhat trickier to frame. Mode of
travel, mean, variance, and order effects are all important
considerations. People who gamble in walking contexts are also
likely to gamble in driving contexts, but the expression
varies.
Slide 36
Lets use the concepts to shed some light on route asymmetry.
Route asymmetry happens when people take a different route when
traveling from A to B than they do when traveling from B to A. The
same criteria lead to different expressions; local differences and
perspective produce different spatial patterns of movement.
Slide 37
Route Asymmetry Study Design Seven legs between four waypoints
Random order according to several criteria Flagpole / Psychology
excluded Five unique connections (Routes) Position tracked with GPS
Only immediate destination known Subjects radioed for the next
destination Each walk took about 25 minutes n = 65
Slide 38
Measuring Asymmetry Binary (Same / Different) Gate Coding Major
pathways & obstacles Common sequence length CHLQ, AFKP, etc.
Some gates (and Routes) showed more asymmetry than others
Environmental influence Usually on a subset of gates High friction
sites Creation or strengthening of secondary channels
Slide 39
Slide 40
Individual Differences Risk-takers move through high-friction
sites. Fast potentially relevant But not simple Symmetry connected
to SBSOD Strategist Lawtons Orientation Strategy But not
Risk-taking Fast / Simple preferences
Slide 41
Summary We can create better models of human movement if we
understand their cognitive and perceptual biases. 1.Humans select
routes based on more than time, distance, and effort. 2.Humans make
systematic errors in the assessment of these, anyway. 3.More
fundamental aspects like strategic disposition and attitudes toward
risk may ultimately be more useful as classifiers.