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In the last ten years our knowledge about the formation of traffic jams has changed substantially, so that the idea of "phantom traffic jam" could soon seem naive to us. But transforming traffic flows and eliminating traffic jams requires that each individual driver (human or non-human) understands their role in traffic flows, the genesis of traffic jams, and how to behave to avoid them. Based on previous studies we have termed this adaptive, anti-jam behavior Wavedriving. This paper presents the design and structure of an online WaveDriving course (WDC) conceived to teach to avoid traffic jams, as well as its first pilot tests. Although some improvements have been identified after the pilots, the preliminary results confirm that the WDC manages to transform car-following behavior of participants, from ordinary drivers to WaveDrivers.

The rationale behind most car-following (CF) models is the possibility to appraise and formalize how drivers naturally follow each other. Characterizing and parametrizing Normative Driving Behavior (NDB) became major goals, especially during the last 25 years. Most CF models assumed driver propensity for constant, safe distance is axiomatic. This paper challenges the idea of safety distance as the main parameter defining a unique (or natural) NDB. Instead, it states drivers can adapt to reactive and proactive car following. Drawing on recent CF models close to the Nagoya paradigm and on other phenomena (e.g., wave movement in Nature), we conceived car following by Driving to keep Inertia (DI) as an alternative to Driving to keep Distance (DD). On a driving simulator, three studies (N ¼ 113) based on a repeated-measures experimental design explored the efficiency of these elementary techniques by measuring individual driver performance (e.g., accelerations, decelerations, average speed, distance to leader). Drivers easily grasped and applied either technique and easily switched back and forth between the two. As an overall indicator, all the studies revealed DI trips use about 20% less fuel than DD trips do., Support came from Fundación Universitaria Antonio Gargallo y Obra Social Ibercaja, Spain (grant 2015/B011)