Pedestrian Behaviour Monitoring: Methods and Experiences

Modern societies are characterised by a clear tendency towards individualism andindependence. Strategies for promoting independence and quality of life for people of every age areespecially important in the field of mobility. Mobility allows people to perform essential functions,including engaging in social and recreational activities when desired and reaching business and socialservices when needed. Especially people who are restricted in physical mobility due to physicalneuromuscularhandicaps or handicaps caused by limited or missing sensory perception need specialsupport. Pedestrians without physical constraints can also benefit from navigational and environmentalinformation services when walking through unfamiliar environments. In this respect applied researchhas produced a number of emerging technologies and technological services such as e.g. navigationaids implemented on mobile devices that respect individual needs, in order to support self-determinedmobility for completing basic daily tasks without personal assistance.Advances in this field are strongly dependent on broad knowledge about people's behaviour withregard to motion, decisive decision processes and related influencing factors. Efficient assistance andtechnological services can only be developed on the basis of comprehensive investigation of spatiotemporalbehaviour and underlying determinants. Researchers of different disciplines, e.g. sociology,tourism and travel behaviour research, artificial intelligence, or ubiquitous geotechnology andgeoinformation, are therefore applying various methods in order to examine, analyse and interpretpedestrian behaviour.This contribution provides an overview about common methods for monitoring and analysing humanspatio-temporal behaviour. Based on a detailed problem description and definition of related terms andexpressions the chapter comprises two main sections. The first part focuses on dataset generation.Commonly used methods for data collection are presented and discussed with respect to specificstrengths and limitations. Empirical methods presented in this section include e.g. vision-based objecttracking, laser scanning, land-based localisation techniques (e.g. GSM, RFID, Bluetooth), satellitebasedlocalisation (GPS), shadowing and observation methods (unobtrusive observation, participatoryobservation), and interview survey techniques (questionnaires, narrative interviews, trip diaries). Thesecond part focuses on data analysis. Methods for analysing specific datasets are discussed, includinge.g. stop detection, velocity histograms, use of space (density maps), cluster analysis, and descriptiveand inferential statistics.The chapter concludes with a discussion of the applicability of the presented datasets and relatedempirical methods for selected research foci on human spatio-temporal behaviour, e.g. travelbehaviour research, tourism research, crowd dynamics, or the development of agent-based simulationmodels.