Although vehicle automation technology has experienced rapid gains in recent years, little research has been conducted on the potential impacts of self-driving vehicles on long-distance personal travel, a major area of travel growth in the United States. Automated vehicles (AVs) offer flexible trip time and origin–destination pairings at travel time costs perceived to be lower; thus, AVs have the potential to dramatically change how travelers pursue long-distance tours. This study analyzed travel surveys and then developed a statewide simulation experiment of long-distance travel to anticipate the impact of AVs on long-distance travel choices. The research explored the Michigan State 2009 Long-Distance Travel Survey and estimated a long-distance trip generation model and a modal-agnostic long-distance mode-choice model. These models were applied in a statewide simulation experiment in which AVs were introduced as a new mode with lower perceived travel time costs (via lowered values of travel time en route) and higher travel costs (to reflect the initially high price of complete vehicle automation). This experiment highlighted the potential shifts in mode choices across different trip distances and purposes. For travel of less than 500 mi, AVs tended to draw from the use of personal vehicles and airlines equally. Airlines were estimated to remain preferred for distances greater than 500 mi (43.6% of trips greater than 500 mi were by air, and 70.9% of trips greater than 1,000 mi were by air). Additionally, at certain AV travel time valuations, travel cost was not a significant factor. The findings showed that as the perceived travel time benefits from hands-free travel rose, monetary costs became less important.


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    Title :

    Shifts in Long-Distance Travel Mode Due to Automated Vehicles: Statewide Mode-Shift Simulation Experiment and Travel Survey Analysis


    Additional title:

    Transportation Research Record


    Contributors:


    Publication date :

    2016-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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