In this study, we present exploratory evidence of how "ridesourcing" services (app-based, ondemand ride services like Uber and Lyft) are used in San Francisco. We explore who uses ridesourcing and for what reasons, how the ridesourcing market compares to that of traditional taxis, and how ridesourcing impacts the use of public transit and overall vehicle travel. In spring 2014, 380 completed intercept surveys were collected from three ridesourcing "hot spots" in San Francisco. We compare survey results with matched-pair taxi trip data and results of a previous taxi user survey. We also compare travel times for ridesourcing and taxis with those for public transit. The findings indicate that, despite many similarities, taxis and ridesourcing differ in user characteristics, wait times, and trips served. While ridesourcing replaces taxi trips, at least half of ridesourcing trips replaced modes other than taxi, including public transit and driving. Impacts on overall vehicle travel are unclear. We conclude with suggestions for future research.

Growing concerns about global motorization and climate change have led to increasing interest in sustainable transportation alternatives such as bikesharing (the shared use of a bicycle fleet). Since 1965, bikesharing has grown across the globe on five continents: Europe, North America, South America, Asia, and Australia. Today, approximately 100 bikesharing programs are operating in an estimated 125 cities, with more than 139,300 bicycles. Bikesharing's evolution is categorized into three generations: (a) white bikes (or free bike systems), (b) coin-deposit systems, and (c) information technology-based systems. In this paper, a fourth generation is proposed: demand-responsive, multimodal systems. A range of existing bikesharing business models (e.g., advertising) and lessons learned are discussed, including (a) bicycle theft and vandalism, (b) bicycle redistribution, (c) information systems (e.g., real-time information), (d) insurance and liability concerns, and (e) prelaunch considerations. Although limited in number, several studies have documented bikesharing's social and environmental benefits, which include reduced auto use, increased bicycle use, and a growing awareness of bikesharing as a daily mobility option. Despite bike-sharing's ongoing growth, obstacles and uncertainty remain: these include future demand, safety, sustainability of business models, limited cycling infrastructure, challenges to integrate with public transportation systems, technology costs, and user convenience (e.g., limited height adjustment on bicycles, lack of cargo space, and exposure to weather). More research is needed for a better understanding of bikesharing's effects, operations, and business models in light of its reported growth and benefits.

Since the late-1990s, numerous ridematching programs have integrated the Internet, mobile phones, and social networking into their services. Online ridematching systems are employing a range of new strategies to create "critical mass:" 1) regional and large employer partnerships, 2) financial incentives, 3) social networking to younger populations, and 4) real-time ridematching services that employ "smartphones" and automated ridematching software. Enhanced casual carpooling approaches, which focus on "meeting places," are also being explored. Today, ridesharing represents approximately 8 to 11% of the transportation modal share in Canada and the United States, respectively. There are approximately 638 ridematching programs in North America.Ridesharing's evolution can be categorized into five phases: 1) World War II car-sharing (or carpooling) clubs; 2) major responses to the 1970s energy crises; 3) early organized ridesharing schemes; 4) reliable ridesharing systems; and 5) technology-enabled ridematching. While ridesharing's future growth and direction are uncertain, the next decade is likely to include greater interoperability among services, technology integration, and stronger policy support. In light of growing concerns about climate change, congestion, and oil dependency, more research is needed to better understand ridesharing's impacts on infrastructure, congestion, and energy/emissions.

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We review the history, current developments, projected future trends and environmental impacts of automated vehicles (AVs) and on-demand mobility, and explore potential synergies. Many automobile manufacturers and Google plan to release AVs between 2017 and 2020, with potential benefits including increased safety, more efficient road use, increased driver productivity and energy savings. Estimates of AV energy use and greenhouse gas (GHG) emissions range from an~80 % or greater decrease to a threefold increase; however, we argue that net decreases are likely. On-demand mobility services exist in many cities around the world, with advances in mobile technology increasing their popularity. On-demand mobility can provide numerous transportation, land use, and environmental and social benefits, and users tend to decrease both vehicle ownership and annual vehicle distances traveled. Combining on-demand mobility and AVs may amplify adoption of both, and further lower energy use and GHG emissions through the use of small, efficient shared AVs.

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Public bikesharing-the shared use of a bicycle fleet-has recently emerged in major North American cities. Bikesharing has been found to decrease driving and increase bicycling. But shifts in public transit have been mixed. The authors evaluate survey data from two U.S. cities to explore who is shifting toward and away from public transit as a result of bikesharing. The authors explore this question by mapping geocoded home and work locations of respondents within Washington DC and Minneapolis. Respondents were mapped by their modal shift toward or away from bus and rail transit. The results show that in Washington DC, those shifting toward bus and rail transit live on the urban periphery, whereas those living in the urban core tend to use public transit less. In Minneapolis, the shift toward rail extends to the urban core, while the modal shift for bus transit is more dispersed. The authors analyze sociodemographics associated with modal shift through cross-tabulations and four ordinal regression models. Common attributes associated with shifting toward public transit include increased age, being male, living in lower density areas, and longer commute distances. The authors conclude with a discussion of the final results in the context of bikesharing's impacts on other cities throughout North America.