CUED Publications database

Understanding traveller decision making -A crowd sourced big data analysis of the London Travel Demand Survey

Casey, G and Soga, K and Silva, E and Guthrie, P (2016) Understanding traveller decision making -A crowd sourced big data analysis of the London Travel Demand Survey. In: UNSPECIFIED pp. 741-746..

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© The authors and ICE Publishing: All rights reserved, 2016. Engineers have begun to take interest in the interface between the structures they build and the people that use them. This has resulted in a need to better understand behavioural decision making at the micro scale. An analysis was carried out on the London Travel Demand Survey in order to see what behavioural rules could be derived from the survey data. This analysis attempted to relate the financial cost and time cost of a journey to the socio-economic status of a traveller in order to see what relationship existed. Relating this empirical exhibited data to real-world data is challenging. Crowd sourced big-data avenues were explored in order to derive realistic information that considers factors such as traffic congestion, service time tables and the underlying complexity of the London transport network. It was hypothesised that the socio-economic status of the traveller, the distance and the motivation of the journey would impact on traveller decision making. However, no statistically significant results were found. It is concluded that the use of crude small sample size survey data to analyse fine grained crowd-sourced data is inappropriate and highlights a critical need to find other means of recording actual traveller decisions in order to understand the decision making process better. Such insights are critical if better strategic decisions are to be made on transport infrastructure.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Divisions: Div D > Sustainable Development
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:33
Last Modified: 31 May 2018 02:10