Traffic&Transportation Journal
Sign In / Sign Up
SUBMIT
FOLLOW THE JOURNAL

Article

Quantifying Travel Physical Energy Expenditure for Urban Travellers – A Case Study of Beijing
Xin Hong, Lingyun Meng, Jian An
Keywords:travellers’ physical energy expenditure, travel behaviour, travel mode choice

Abstract

Travel physical energy expenditure for travellers has impact on travel mode choice behaviour. However, quantitative study on travel physical energy expenditure is rare. In this paper, the concept of travel physical energy expenditure coefficient has been presented. A case study has been carried out of young travellers in Beijing to get the value of physical energy expenditure per unit time under three transport modes, walking, car and public transportation. A series of experiments have been designed and conducted, which consider influence factors including age, gender, travel mode, riding posture, luggage level and crowded level. By analysing the travel data of money, travel time and physical energy expenditure, we determined that the value of travel physical energy expenditure coefficient δ is 0.058 RMB/KJ, which means that travellers can pay 0.058 RMB to reduce 1 KJ physical energy expenditure. Next, a travel mode choice model has been proposed using a multinomial logit model (MNL), considering economic cost, time cost and physical energy cost. Finally, the case study based on OD from Xizhimen to Tiantongyuan in Beijing was conducted. It is verified that it will be in better agreement with the actual travel behaviour when we take the physical energy expenditure for different types of travellers into account.

References

Stradling S, Carreno M, Rye T, Noble A. Passenger perceptions and the ideal urban bus journey experience. Transport Policy. 2007;14(4): 283-292.

Cox T, Houdmont J, Griffiths A. Rail passenger crowding, stress, health and safety in Britain. Transportation Research Part A. 2006;40(3): 244-258.

Hanying G. Study on Travelers’ Behavior Based on the Physiology and Psychology in Urban Passenger Transportation. MSc thesis. Chengdu: Southwest Jiaotong University; 2007.

Yang XG, An J, Liu HD, Teng J, Zhang D. Evaluation Architecture Discussion of Route-Level Transit Service Quality. Journal of Transportation Systems Engineering and Information Technology. 2010;10(4): 13-21.

An J, Sun MZ, Guo JF. Analysis of Travel Energy Expenditure Based on Subjective Perception and Objective Measurement. Urban Transport of China. 2013;11(2): 73-82.

Thorhauge M, Haustein S, Cherchi E. Accounting for the Theory of Planned Behaviour in departure time choice. Transportation Research Part F. 2016;38: 94-105.

Hood VL, Granat MH, Maxwell DJ, Hasler JP. A new method of using heart rate to represent energy expenditure: the total heart beat index. Archives of Physical Medicine and Rehabilitation. 2002;83(9): 1266-1273.

Wang SS, Huang W, Lu ZB. Deduction of link performance function and its regression analysis. Journal of Highway and Transportation Research and Development. 2006;23(4): 107-110.

Beijing Municipul Committee of Communication. Beijing Forth Comprehensive Traffic Survey Report. Beijing's Traffic Development Research Centre, 2012.

Zhao WT. Research on model of time value of commuter travel. MSc thesis. Beijing: Beijing Jiaotong University; 2013.

Javanmardi M, Fasihozaman M, Shabanpour R, Mohammadian A. Mode choice modelling using personalized travel time and cost data. International Conference on Travel Behaviour Research; 2015.

Published
26.03.2020
Copyright (c) 2023 Xin Hong, Lingyun Meng, Jian An

Published by
University of Zagreb, Faculty of Transport and Traffic Sciences
Online ISSN
1848-4069
Print ISSN
0353-5320
SCImago Journal & Country Rank
Publons logo
© Traffic&Transportation Journal