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Learning and Inferr ing Transportation Routines

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Learning and Inferring Tra

nsportation Routines

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Outline

Introduction Hierarchical Activity Model Inference, Learning, and Error Detection

InferenceLearningDetection of User Errors

Experimental Results

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Introduction A hierarchical Markov model that can learn and infer a u

ser’s daily movements through the community The model allows :

Infer the locations of usual goals, such as home or workplace Infer a user’s mode of transportation, such as foot, car, or bus,

and predict when and where she will change modes Predict her future movements, both in the short term and in ter

ms of distant goals Infer when a user has broken his ordinary routine in a way that

may indicate that he has made an error, such as failing to get off his bus at his usual stop on the way home

Robustly track and predict locations even in the presence of total loss of GPS signals and other sources of noise

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Hierarchical Activity Model

Locations and transportation modes

Trip segments

Goals

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Inference

GPS-based tracking on street maps

Goal and trip segment estimation

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The factorization (1) separates the state space of our estimation problem into its continuous and discrete parts

The left term on the right hand side of (1) , (2) follows by applying Bayes rule and the independences in our estimation problem

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Learning

Finding goals

Finding mode transfer locations

Estimating transition matrices

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Finding mode transfer locations

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Detection of User Errors

The hierarchical tracker has “expensive” particles, each containing much state information, but requires few particles for accurate tracking

The flat, untrained tracker needs more particles to maintain tracking, but each particle is cheaper to compute

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Experimental Results

Activity model learning

Detection of user errors

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(a) Probability of the true goal (work place) during an episode from home to work, estimated using the flat and the hierarchical model

(b,c) Probability of an activity being normal or abnormal, estimated by the concurrent trackers

(b) Normal activity: driving from home to work

(c) Abnormal activity: missing to get off the bus at time t2

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Thank you