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Ride-hailing services like Uber and Lyft are changing the way that people move around cities, affecting transit use, active transportation and congestion. Due to the rapid rise in popularity and lack of available data, city and transportation planners have been limited in their ability to make long-term decisions about transportation infrastructure.
This article examines bicyclists’ travel behavior for transportation and for recreational purposes based on preferences, physical and social environmental factors, and perceived safety.
This white paper discusses the forces affecting U.S. passenger travel, the permanence of which is often unclear. We explore travel demand’s relationship with explanatory factors such as economic activity, gas prices, urban form, socio-demographic traits and generational effects, the expanding availability of travel options (including electronic alternatives to travel) and technological innovations in the transportation sector (including the advent of emerging transportation and shared mobility services). We discuss how these factors modify the alternatives available to travelers, the characteristics of each alternative, and the way travelers perceive and evaluate these characteristics.
"Automated driving technologies are currently penetrating the market, and the coming fully autonomous cars will have far-reaching, yet largely unknown, implications. A critical unknown is the impact on traveler behavior, which in turn impacts sustainability, the economy, and well-being. Most behavioral studies, to date, either focus on safety and human factors (driving simulators; test beds), assume travel behavior implications (microsimulators; network analysis), or ask about hypothetical scenarios that are unfamiliar to the subjects (stated preference studies). Here we present a different approach, which is to use a naturalistic experiment to project people into a world of self-driving cars. We mimic potential life with a privately-owned self-driving vehicle by providing 60 h of free chauffeur service for each participating household for use within a 7-day period. We seek to understand the changes in travel behavior as the subjects adjust their travel and activities during the chauffeur week when, as in a self-driving vehicle, they are explicitly relieved of the driving task. In this first pilot application, our sample consisted of 13 subjects from the San Francisco Bay area, drawn from three cohorts: millennials, families, and retirees. We tracked each subject’s travel for 3 weeks (the chauffeur week, 1 week before and 1 week after) and conducted surveys and interviews. During the chauffeur week, we observed sizable increases in vehicle-miles traveled and number of trips, with a more pronounced increase in trips made in the evening and for longer distances and a substantial proportion of “zero-occupancy” vehicle-miles traveled."
"This paper presents findings from a comprehensive travel and residential survey deployed in seven major U.S. cities, in two phases from 2014 to 2016, with a targeted, representative sample of their urban and suburban populations. The purpose of this report is to provide early insight on the adoption of, use, and travel behavior impacts of ride-hailing. The report is structured around three primary topics, key findings of which are highlighted below."
For 50 years, American geography and land use has been centered on the personal car. The three revolutions in vehicle sharing, automation and electrification present new challenges and also great opportunities for land use and transportation planners. Absent policy reform, the three revolutions may contribute to more sprawl, but a sustainable planning approach that supports both higher-density development and lower single-occupant (or zero-occupant) driving can once again put people first rather than their cars.
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