Are routes well that end well? Experienced utility of impeded simulator routes. (April 2021)

• Record Type: Journal Article
• Authors: Koller, Florian
• Is Part Of: Transportation research. Volume 93(2021)
• Publication Date: 2021-04
• Subjects: Intelligent transportation systems -- Route optimization -- Experienced utility -- Order effects -- Aggregation rules; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2021.102719
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: Experimental manipulation of route segmentation related to impedance in a simulator. Examining effects on remembered utility (i.e., global affect, speed, time, flow). Capturing also moment affect through touch-sensitive pad that served as accelerator. Despite equality in mean features, segmentations yielded different subjective experiences. Notably the order of more or less impeding route sections affected global judgments. Suggestive evidence for taking route segmentation into account in route assignment. Abstract: A remaining challenge for optimizing car travel is that route assignments still contain temporary impedance. The question arises as to how the degree and the order of more and less impeding route sections influence experienced utility of routes. On driving simulator routes, participants were assigned one out of two mean speeds and one out of three segmentations (i.e., "Fast Slow, " "Constant, " and "Slow Fast"). Independent of assigned mean speed, routes with the segmentation "Slow Fast" were rated less arousing, more positive, faster and more flowing than routes with the segmentation "Fast Slow." Further differences were revealed by an interaction between mean speed and route segmentation. In summary, optimized segmentation can increase the utility of impeded routes. This may increase the acceptance of traveler information systems and in turn subjective well-being due to more efficient travel. The study warrants further investigations of varying driving cycles under real-world conditions.