The Impact of Real‐Time Information on Choices During the Commute Trip: Evidence from a Travel Simulator

Abstract

In the area of travel behavior, route choice when facing congestion has been widely researched. However, there are other behavioral alternatives based on people's activities and adaptive decision-making strategies that have been overlooked. This paper focuses on how and what kind of information is used when considering a subset of these alternatives. Alternatives examined are the final choice of people's decision-making process when faced with unexpected events during the commute trip in the presence of real-time information collected using GABRIEL (Gis Activity-Based tRavel sImuLator) in Columbus, OH. An empirical analysis of the data set, which includes a limited set of alternatives (six in total) is presented. Bivariate analysis and multinomial logit models are used to identify variables that influence the choice. Results show that people are willing to experiment with other alternatives if provided the information to support their choice. Copyright 2007 Blackwell Publishing.

Travel and Activity Choices for Transit Travelers at Terminals with Dynamic Information Provision

“…The findings of this study affirmed the significance of dynamic information on the behavior of travelers as reported in past studies (e.g., Casas and Kwan 2007;Tseng, Knockaert, and Verhoef 2013;Van der Horst and Ettema 2005). Many studies have investigated the effects of traffic information on individual travel and the problem of scheduling activities.…”

“…The findings of this study affirmed the significance of dynamic information on the behavior of travelers as reported in past studies (e.g., Casas and Kwan 2007;Tseng, Knockaert, and Verhoef 2013;Van der Horst and Ettema 2005). The dynamic information in Tseng, Knockaert, and Verhoef (2013) and Casas and Kwan (2007) refers mainly to traffic information. However, it should be noted that Van der Horst and Ettema (2005) focused on exploring the effects of dynamic information on recreational trips and mode choices.…”

“…The results of our study also support the findings by Van der Horst and Ettema (2005) that younger travelers are more likely to adopt information than are older ones. Although activities are considered in Casas and Kwan (2007), their study emphasized choices during commuter trips and their experiment was executed using a travel simulator. The dynamic information in Tseng, Knockaert, and Verhoef (2013) and Casas and Kwan (2007) refers mainly to traffic information.…”

“…Past studies have shown how travel decisions are affected by dynamic information and the urban environment (e.g., Casas and Kwan 2007;Farag and Lyons 2012;Joh et al 2011;Kenyon and Lyons 2003;Kwan, Dijst, and Schwanen 2007;Lin and Chang 2010;Tracy et al 2011;Zito et al 2011). Past studies have shown how travel decisions are affected by dynamic information and the urban environment (e.g., Casas and Kwan 2007;Farag and Lyons 2012;Joh et al 2011;Kenyon and Lyons 2003;Kwan, Dijst, and Schwanen 2007;Lin and Chang 2010;Tracy et al 2011;Zito et al 2011).…”

Modeling the Impact of Traffic Information Acquisition From Mobile Devices During the Primary Tour of the Day

“…Traffic information influences the choice behavior of travelers, and there is a large amount of literature presenting its possible impacts (Casas & Kwan, 2007;Choocharukul, 2008;Hato, Taniguchi, Sugie, Kuwahara, & Morita, 1999;Politis, Papaioannou, Basbas, & Dimitriadis, 2010;Polydoropoulou & Ben-Akiva, 1998;Tsirimpa, Polydoropoulou, & Antoniou, 2007;Tseng, Knockaert, & Verhoef, 2013;Zhang, Shen, & Clifton, 2008). Several models have been developed in the literature capturing the effect of traffic information on travelers' decisions, such as route choice, mode choice, departure time choice, and destination choice, while research on the impact of traffic information on activity rescheduling is still rather scarce.…”