A combined statistical model for the travel comfort determination in ground urban passenger transportation

Abstract Passenger transportation is crucial to the daily life of modern city residents. The mass transit operation quality is first demonstrated through the travel comfort experienced by passengers every time they use this transportation mode. The passenger’s subsequent decision on continuing or refusing to take the public transport services is made depending on how comfortable the trip is. Thus, it is necessary to identify the factors influencing the ride comfort with evaluating and improving purposes. In this regard, in the study there was an attempt to associate the travel comfort scale and the transportation environment indicators aiming at the developing a statistical comfort model. To acquire the passenger cabin environment raw data from various transportation modes, a crowdsourced questionnaire survey was conducted along with statistical data processing. At the same time, a simple five-point comfort scale with the verbal description of comfort rank was proposed. As a result, the statistic interrelation between the travel convenience and the in-vehicle environment parameters was adequately determined by the power-law model. The summarizing model identified the invehicle time, crowding, and acceleration as the most important ride comfort factors.