Drivers’ adaptive travel behaviors towards green transportation development: a critical review

The transportation professionals integrated the concept Green in various dimensions of transportation, such as, green vehicle, green highway. The current study has established a new dimension to green transportation, which is called Green Driver as whom substantially contributes to less emission and fuel consumption, and higher-safety. The research established the driver’s Green Adaptive Travel Behaviors (GATB), in particular, that is referred to voluntary personal and lifestyle behaviors on less energy consumption and emission. The methodology was designed into two phases. Phase one was to investigate driver’s GATBs through systematic literature review process and content analysis method. The second phase was to verify greenery value impact (GVI) of the finalized list of drivers’ GATBs through an expert input study and Grounded Group Decision Making (GGDM) method. Total twenty six (26) GATB factors have been determined. Amongst, the factor ‘F27- Dangerous overtaking’ has received the highest value (97%) followed with ‘F3- Slow once realizing bike lanes for cyclist crossing’ (91%). In contrast, ‘F4- Realize visual Obstacles to manage the speed’ and ‘F21- Brake with smooth deceleration’ has received the lowest value (77%) among other factors. Two of the initial factors;‘F5-Use traffic calming devices’ (55%), and ‘F24- Change highest possible gear’ (69%) could not reach the 70% saturation; hence, they have been dropped from the list of GATB factors. Indeed, the GATB efforts are not limited to technology and practice; but also can include education and enforcement to driving regulations in order to interconnect driver, technology, environment, and vehicle. The research concluded with an innovative technique used as the decision support tool to evaluate the greenery grade of any individual driver on committing to less emission, less fuel consumption, and higher safety in traveling. As future study, the Green driver behaviour index assessment model will be developed based on this study outputs.