Inferring Social-Demographics of Travellers based on Smart Card Data

Yang Zhang · Tao Cheng

12 citations0/0 files storedInternational Conference on Advanced Research Methods and Analytics (CARMA)

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Human Mobility and Location-Based Analysis Transportation Planning and Optimization Urban Transport and Accessibility

Abstract

With the wide application of the smart card technology in public transit system, traveller's daily travel behaviours can be possibly obtained.This study devotes to investigating the pattern of individual mobility patterns and its relationship with social-demographics.We first extract travel features from the raw smart card data, including spatial, temporal and travel mode features, which capture the travel variability of travellers.Then, travel features are fed to various supervised machine learning models to predict individual's demographic attributes, such as age group, gender, income level and car ownership.Finally, a case study based on London's Oyster Card data is presented and results show it is a promising opportunity for demographic study based on people's mobility behaviour.

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1981The Travel-Activity Patterns of Urban Residents: Dimensions and Relationships to Sociodemographic Characteristics 2016Inferring patterns in the multi-week activity sequences of public transport users 2013Classification of London's public transport users using smart card data

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2019EXPLORING THE RELATIONSHIP BETWEEN TRAVEL PATTERN AND SOCIAL-DEMOGRAPHICS USING SMART CARD DATA AND HOUSEHOLD SURVEY 2022Investigating mandatory and non-mandatory trip patterns based on socioeconomic characteristics and traffic analysis zone features using deep neural networks 2020Modelling socioeconomic attributes of public transit passengers 2022Targeted Advertising in the Public Transit Network Using Smart Card Data

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