Examination of staggered shifts impacts on travel behavior: a case study of Beijing, China

Abstract

Staggered shifts is one of the popular TDM (Transportation Demand Management) policies, which can reduce commute travel volume during the AM and PM peak periods, and relieve traffic congestion. In order to make effective staggered shifts program, it is necessary to examine the effect of the program on commute travel behavior. This paper takes Beijing (China) as an example to evaluate the validity of staggered shifts policy. Based on data investigation, the commute travel behavior and the commuters’ preference for staggered shifts are analyzed. This paper makes four staggered shifts programs, and develops a commute departure time choice model with Multinomial Logit method to predict the influence of the programs on commute departure time, and develops a commute travel duration model to analyze the influence of the programs on commute travel time. Departure time prediction shows that Program B can reduce the traffic volumes in 6:30–8:30 period by 15.24%, and commute travel duration analysis indicate that Program B can reduce the home-to-work travel time by 21.73%. Therefore, Program B is proven to be the best staggered shifts program for Beijing. The results of this paper can provide valuable information on how to develop an effective staggered shifts program.

First Published Online: 16 Jul 2013