Ridesharing in North America: Past, Present, and Future (original) (raw)
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The determinants of ridesharing: Literature review
1990
Transportation Center (UC'TC) is one of ten regional units mandated by Congress and established in Fall 1988 to support research, education, and training in surface transportation. The UC Center serves federal Region IX and is supported by matching grants from the U.S. Department of Transportation, the California Department of Transportation (Caltrans), and the University. Based on the Berkeley Campus, UCTC draws upon existing capabilities and resources of the Institutes of Transportation Studies at Berkeley, Davis, Irvine, and Los Angeles; the Institute of Urban and Regional Development at Berkeley; and several academic departments at the Berkeley, Davis, Irvine, and Los Angeles campuses. Faculty and students on other University of California campuses may participate in Center activities. Researchers at other universities within the region also have opportunities to collaborate with UC faculty on selected studies.
Markets for Dynamic Ridesharing? Case of Berkeley, California
University of California Transportation Center, 2011
Ridesharing programs are widespread across the United States. Dynamic ridesharing is a newer way to share rides on the fly or up to several days in advance using cell phone or computer messaging to make arrangements. This paper describes research conducted to assess the potential for dynamic ridesharing for travel to downtown Berkeley, California, and the University of California, Berkeley, campus. The study provides insights about the opportunities and challenges presented by this travel option. Data were collected from statistical and geographic analysis of the downtown and campus travel markets, and surveys and focus groups were administered to employees and graduate students. The study found that about one-fifth of commuters who drive alone to the campus would be interested in using dynamic ridesharing at least occasionally and live in areas where matches could be found. They would prefer to arrange a shared ride at least the night before rather than immediately before the trip is made. Many of these travelers were unaware of current rideshare services, and some would be willing to find a regular carpool partner. Finally, if parking charges are fairly high and parking supply is limited and regulated, financial incentives and carpool parking subsidies greatly increase interest in dynamic ridesharing.
Ride-sharing on the daily home-work-home commute can help individuals save on gasoline and other car-related costs, while at the same time reduce traffic and pollution. This paper presents a quantitative study of the potential of ride-sharing in two European and two US cities based on mobility data extracted from 3G Call Description Records (CDRs) and Online Social Networks (OSN) geo-tagging. We start with ride-sharing among neighbors for which we derive up- per bounds based on the assumption that commutes occur synchronously and that any passenger can be matched with any driver. We show that a small detour distance of 0.8 Km leads to an impressive 55% reduction of traffic. This value reduces to 26% for asynchronous commutes and a pick-up tolerance of 10 minutes. The latter result can be improved to 47% by permitting additional passengers to be picked-up en-route using e.g., smartphone apps. We then introduce social constraints on the relationship between drivers and passengers. Rid...
2021
On-demand mobility services including transportation network companies (also known as ridesourcing and ridehailing) like Lyft and Uber are changing the way that people travel by providing dynamic mobility that can supplement public transit and personal-vehicle use. However, TNC services have been found to contribute to increasing vehicle mileage, traffic congestion, and greenhouse gas emissions. Pooling rides ⎯ sharing a vehicle by multiple passengers to complete journeys of similar origin and destination ⎯ can increase the average vehicle occupancy of TNC trips and thus mitigate some of the negative impacts. Several mobility companies have launched app-based pooling services in recent years including app-based carpooling services (e.g., Waze Carpool, Scoop) that match drivers with riders; pooled on-demand ride services (e.g., Uber Pool and Lyft Shared rides) that match multiple TNC users; and microtransit services (e.g., Bridj, Chariot, Via) that offer on-demand, flexibly routed se...
Investigating the Potential of Ridesharing to Reduce Vehicle Emissions
Urban Planning, 2017
As urban populations grow, cities need new strategies to maintain a good standard of living while enhancing services and infrastructure development. A key area for improving city operations and spatial layout is the transportation of people and goods. While conventional transportation systems (i.e., fossil fuel based) are struggling to serve mobility needs for growing populations, they also represent serious environmental threats. Alternative-fuel vehicles can reduce emissions that contribute to local air pollution and greenhouse gases as mobility needs grow. However, even if alternative-powered vehicles were widely employed, road congestion would still increase. This paper investigates ridesharing as a mobility option to reduce emissions (carbon, particulates and ozone) while accommodating growing transportation needs and reducing overall congestion. The potential of ridesharing to reduce carbon emissions from personal vehicles in Changsha, China, is examined by reviewing mobility ...
Impacts of Ridesourcing on VMT, Parking Demand, Transportation Equity, and Travel Behavior
2019
Ride-haling such as Uber and Lyft is changing the way people travel and is critical to forecasting mode choice demands and providing adequate infrastructure. Despite widespread claims that these services help reduce driving and the need for parking, little research exists on these topics. This research project uses ethnographic methods complemented with passenger surveys where one of the authors drove for Uber and Lyft in the Denver, Colorado, region to collect quantitative and qualitative data on ride-hailing. It also uses the methods to analyze the impacts of ride-hailing on deadheading, vehicle occupancy, mode replacement, vehicle miles traveled (VMT), and parking. The dataset includes actual travel attributes from 416 ride-hailing rides — Lyft, UberX, LyftLine, and UberPool — and travel behavior and sociodemographics from 311 passenger surveys. Section one focuses on changes in driving. The conservative (lower end) percentage of deadheading miles from ride-hailing is 40.8%. The ...
Understanding Ride-Sharing Systems in Urban Areas: The Role of Location, Users and Barriers
2020
The design and development of ride-sharing systems have been urged from the need to improve the performance of transport systems in urban areas and promote sustainability. Despite its significant potential, ride-sharing has demonstrated limited uptake so far, because of a set of barriers (technological and legal). This paper aims to provide a better understanding of ride-sharing systems through an extensive review of definitions, ride-sharing systems, legislation and user characteristics. Identified ride-sharing systems are analyzed in terms of their attributes such as operation status and location, distance of service and payment methods to provide an insight into local conditions. The legislative and regulatory framework related to ride-sharing for the EU27 countries and the UK is reviewed to understand potential barriers in ride-sharing implementation. Furthermore, this research identifies user trip purposes related to ride-sharing and defines ride-sharing user types. Four user t...
Ride Sharing: A Network Perspective
SBP, 2015
Ride sharing's potential to improve traffic congestion as well as assist in reducing CO2 emission and fuel consumption was recently demonstrated by works such as [1]. Furthermore, it was shown that ride sharing can be implemented within a sound economic regime, providing values for all participants (e.g., Uber). Better understanding the utilization of ride sharing can help policy makers and urban planners in modifying existing urban transportation systems to increase their "ride sharing friendliness" as well as in designing new ride sharing oriented ones. In this paper, we study systematically the relationship between properties of the dynamic transportation network (implied by the aggregated rides) and the potential benefit of ride sharing. By analyzing a dataset of over 14 Million taxi trips taken in New York City during January 2013, we predict the potential benefit of ride sharing using topological properties of the rides network only. Such prediction can ease the analysis of urban areas, with respect to the potential efficiency of ride sharing for their inhabitants, without the need to carry out expensive and time consuming surveys, data collection and analysis operations.
Ridesharing as a Green Commute Alternative: A Campus Case Study
International Journal of Sustainable Transportation, 2014
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