Travel Choice Inertia: The Joint Role of Risk Aversion and Learning

This paper shows how travellers that are faced with a series of risky choices become behaviourally inert due to a combination of risk aversion and learning. Our theoretical analyses complement other studies that conceive inertia as resulting from the wish to save cognitive resources. We first present a model of risky travel mode choice. We show that if travellers dislike risk, and part of the quality of travel alternatives is only revealed upon usage, inertia emerges due to a learning-based lock-in effect. We extend our analyses to capture forward-looking behaviour and the provision of travel information

The long road to automated trucking: Insights from driver focus groups

With the rapid progress of automated driving technology, self-driving vehicles are on the horizon. In this study, we look at what is likely to be the first implementation of a form of automated driving on public roads, i.e., truck platooning, where virtually connected trucks drive at short headways to save fuel and associated emissions. With progressing technology, we may see platoons with drivers resting while being in the truck or even platoons in which not all trucks require drivers. Hence, platooning technology has a significant impact on the jobs of truck drivers. Driver acceptance of this emerg- ing technology is therefore an important factor in the implementation of platooning and, consequently, automated driving in general. In this study, we explore the range of per- spectives that exist among drivers by conducting focus groups in the Netherlands. These discussions indicate that drivers foresee that platooning will eventually become a reality but believe it will have a negative impact on the quality of their work and their job satisfaction

Individuals' Decisions in the Presence of Multiple Goals

This paper develops new directions on how individuals’ use of multiple goals can be incorporated in econometric model

Impact of integrated multimodal traveler information on auto commuter's mode switching propensity

Aim: Real-time traveler information affects auto commuter’s travel behavior. Method: An ordered probit model is used to analyze auto commuter’s mode switching propensity under influence of simulated real-time multimodal traveler information. A travel preference survey is administered to car drivers to gather individual commuter’s travel decisions under integrated multimodal traveler information. Result: It is shown that integrated multimodal traveler information can influence willingness of car drivers to switch mode of travel, while socio-economic characteristics also influence the mode choice decision

How to keep your AV on the right track? An obfuscation-based model of decision-making by autonomous agents

Transport and Logistic

The practice of strategic journal self-citation: It exists, and should stop (a note from the editor-in-chief)

This note highlights how journal self-citation practices substantially influence impact factor-based journal rankings in the field of Transportation. Furthermore, by means of analyzing Thomson Reuters’ most recent Journal Citation Report (JCR), I show that a substantial share of these self-citations is likely to be the result of strategic behavior by editors of journals. I conclude with a call to editors to stop requesting or nudging authors to add journal self-citations to their papers; and a call to authors to stop giving in to editors when being asked to provide such citations.Engineering, Systems and ServicesTechnology, Policy and Managemen

Open Access Symposium: Opening & An editor-in-chief’s perspective

Engineering, Systems and ServicesTechnology, Policy and Managemen

Turning the light on in Virginia: New perspectives on choice behavior modeling

Engineering, Systems and ServicesTechnology, Policy and Managemen