An Analysis of issues against the adoption of Dynamic Carpooling

Using a private car is a transportation system very common in industrialized countries. However, it causes different problems such as overuse of oil, traffic jams causing earth pollution, health problems and an inefficient use of personal time. One possible solution to these problems is carpooling, i.e. sharing a trip on a private car of a driver with one or more passengers. Carpooling would reduce the number of cars on streets hence providing worldwide environmental, economical and social benefits. The matching of drivers and passengers can be facilitated by information and communication technologies. Typically, a driver inserts on a web-site the availability of empty seats on his/her car for a planned trip and potential passengers can search for trips and contact the drivers. This process is slow and can be appropriate for long trips planned days in advance. We call this static carpooling and we note it is not used frequently by people even if there are already many web-sites offering this service and in fact the only real open challenge is widespread adoption. Dynamic carpooling, on the other hand, takes advantage of the recent and increasing adoption of Internet-connected geo-aware mobile devices for enabling impromptu trip opportunities. Passengers request trips directly on the street and can find a suitable ride in just few minutes. Currently there are no dynamic carpooling systems widely used. Every attempt to create and organize such systems failed. This paper reviews the state of the art of dynamic carpooling. It identifies the most important issues against the adoption of dynamic carpooling systems and the proposed solutions for such issues. It proposes a first input on solving the problem of mass-adopting dynamic carpooling systems.Comment: 10 pages, whitepaper, extracted from B.Sc. thesis "Dycapo: On the creation of an open-source Server and a Protocol for Dynamic Carpooling" (Daniel Graziotin, 2010

Carpooling Liability?: Applying Tort Law Principles to the Joint Emergence of Self-Driving Automobiles and Transportation Network Companies

Self-driving automobiles have emerged as the future of vehicular travel, but this innovation is not developing in isolation. Simultaneously, the popularity of transportation network companies functioning as ride-hailing and ride-sharing services have altered traditional conceptions of personal transportation. Technology companies, conventional automakers, and start-up businesses each play significant roles in fundamentally transforming transportation methods. These transformations raise numerous liability questions. Specifically, the emergence of self-driving vehicles and transportation network companies create uncertainty for the application of tort law’s negligence standard. This Note addresses technological innovations in vehicular transportation and their accompanying legislative and regulatory developments. Then, this Note discusses the implications for vicarious liability for vehicle owners, duties of care for vehicle operators, and corresponding insurance regimes. This Note also considers theoretical justifications for tort concepts including enterprise liability. Accounting for the inevitable uncertainty in applying tort law to new invention, this Note proposes a strict and vicarious liability regime with corresponding no-fault automobile insurance

Sharing economy and socio-economic transitions: an application of the multi-level perspective on a case study of carpooling in the USA (1970-2010)

The study deals with the emerging concept of sharing economy using the development of carpooling as example. It is based on the multi-level perspective framework, developed by Frank Geels, which is designed to explain and analyze processes of novel technology development. The present paper analyzes the new institution, carpooling, through the lens of this framework in order to understand its potential to be a landscape-changing innovation. This case study also attempts to illustrate how the multi-level perspective can be used to analyze not only technological innovations, but also novel ways of doing business, which can arguably be viewed as radical innovations on their own. The aim is thus to find out whether the emergence of carpooling follows the same patterns and shows the same features as emergence of conventional technological radical innovations

Swerve

Carpooling yields great benefits environmentally, socially, and economically for carpooling, however there is no easy to use, safe, and enjoyable application for people to connect with others who are both close in proximity and have schedules that match currently. By creating a database and visual mock ups, our senior project creates the basis for an application called Swerve that matches users by location and schedules and has social and economic incentives. Our research allowed us to further understand the social, environmental and economic benefits and incentives of carpooling. We also looked into current carpooling websites and applications and could not find a successful platform for carpooling that involves both matching and social profile components. Through surveys and interviews we confirmed our belief that there is a great student interest in a social carpooling application as well as gain an understanding of what users would want and need in the application. Based off of all of this knowledge we were able to build an Access database that matches drivers and passengers based off of location and schedules and a visual mock up of the application screens that show how the social matching would work

What influences people to choose ridesharing? An overview of the literature

Ridesharing is a shared mobility service in which passengers and drivers with similar origins and destinations are matched to travel in the same vehicle. This service utilises unused seats in vehicles and multi-passenger rides to reduce the cost of travel. To promote ridesharing, both service providers and policymakers should carefully analyse passenger adoption behaviour to support future decision-making and planning. In this paper, 80 studies on passenger ridesharing behaviour published since 2004 are reviewed. The motivating factors and barriers are analysed and classified in terms of demographic factors, psychological factors, and situational factors, and boundary conditions are included. The work provides a corresponding research framework on ridesharing behaviour. Finally, the current literature gaps are summarised and research recommendations are provided. This study provides a comprehensive and systematic research basis for ridesharing studies, and presents important theoretical and practical contributions to guide sustainable ridesharing behaviour

The Governance of Risks in Ridesharing: A Revelatory Case from Singapore

Recently we have witnessed the worldwide adoption of many different types of innovative technologies, such as crowdsourcing, ridesharing, open and big data, aiming at delivering public services more efficiently and effectively. Among them, ridesharing has received substantial attention from decision-makers around the world. Because of the multitude of currently understood or potentially unknown risks associated with ridesharing (unemployment, insurance, information privacy, and environmental risk), governments in different countries apply different strategies to address such risks. Some governments prohibit the adoption of ridesharing altogether, while other governments promote it. In this article, we address the question of how risks involved in ridesharing are governed over time. We present an in-depth single case study on Singapore and examine how the Singaporean government has addressed risks in ridesharing over time. The Singaporean government has a strong ambition to become an innovation hub, and many innovative technologies have been adopted and promoted to that end. At the same time, decision-makers in Singapore are reputed for their proactive style of social governance. The example of Singapore can be regarded as a revelatory case study, helping us further to explore governance practices in other countries. Keywords: risk; ridesharing; transport; governance; innovative technologies; case study; Singapor

Exploration of the Current State and Directions of Dynamic Ridesharing

Dynamic ridesharing (DRS) is an emerging transportation service based on the traditional concept of shared rides. DRS makes use of web-based real-time technologies to match drivers with riders. Enabling technologies include software platforms that operate on mobile communication devices and contain location-aware capabilities including Global Positioning Systems (Agatz, Erera, Savelsberg, & Wang, 2012). The platforms are designed to provide ride-matching services via smartphone applications differing from early systems that used non-real time services such as internet forums, or telecommunications, where responses were not immediate. The study of DRS is important when considering its role as an emerging transportation demand management strategy. DRS reduces travel demand on singleoccupancy vehicles (SOVs) by filling vehicle seats that are typically left vacant. The most recent statistics of vehicle occupancy rates were measured in 2009 by the National Household Travel Survey (NHTS), conducted by the U.S. Department of Transportation. According to the NHTS, the 2009 occupancy rate for all purposes was a meager 1.67 persons per vehicle (Federal Highway Administration, 2015). Vehicle occupancy rates examined against the total of all registered highway vehicles in the U.S. as of 2012, calculated at 253,639,386 (Bureau of Transportation Statistics, 2015), reveals the magnitude of the impact of SOVs. Left unattended, the ramifications for environmental outcomes is substantial. Among the major energy consuming sectors, transportation\u27s share is largest in terms of total CO2 emissions at 32.9% (Davis, Diegel, & Boundy, 2014, p. 11-15). DRS offers promise to fill empty vehicle seats. Evidence indicates that specific demographic subgroups are inclined to use DRS services. For example, data suggest that the subgroup of 18 to 34-year-olds, the so-called millennials , have negative attitudes towards private car ownership unlike previous age groups (Nelson, 2013). Data collected for this study revealed that the millennial subgroup represents half of all DRS users. Millennials also revealed they tended to use DRS more than other subgroups to replace a private vehicle. Further research is needed to determine if the trend towards DRS by 18 to 34-year-olds represents current economic factors or a fundamental cultural shift away from the SOV transportation model

Incorporate Emerging Travel Modes in the Regional Strategic Planning Model (RSPM) Tool

Performance-based planning helps local and state decision makers to understand the potential impacts of policy decisions, supporting cost-effective investments and policy choices that can help achieve policy goals. In addition, it can enable monitoring of progress and facilitate needed adjustments, help them communicate to the public, and assist them with meeting federal regulations and the intent of MAP21. The Regional Strategic Planning Model (RSPM) is a performance-based planning tool first developed by Oregon State DOT (as GreenSTEP) and later adapted for use by other states in the form of the Federal Highway Administration (FHWA) Emissions Reduction Policy Analysis Tool (EERPAT) and the underlying basis of the SHRP2 C16 Smart Growth Area Planning software (SmartGAP). As the popularity of the RSPM tool grows and application cases expand, there is recognition that a deeper understanding is needed to determine how mode choices and mode share may be impacted by policy and investment decisions and how these mode choices further influence performance outcomes of the transportation system. This is particularly important when the tool is applied in a broader base of planning and decision-making processes to truly understand what may be the best decisions for the entire multi-modal and inter-modal transportation system. ODOT is sponsoring a first phase research project led by this research team to incorporate broad stroke multi-modal travel choices in the RSPM tool. This proposed project hopes to leverage the ODOT and NITC funding to further study, along with existing modes, emerging travel modes, including car sharing, bike sharing, and autonomous vehicles, with stated preference (SP) experiments, and incorporate these new options into the RSPM tool. These modes have been rapidly gaining popularity worldwide, which will have long-term implications for car ownership decisions, fleet characteristics, travel patterns, and further system-wide performance outcomes. By incorporating these modes in the mode choice module, this project will make the RSPM tool sensitive to policies and investment targeted to shift mode share and enable it to evaluate futures in which these modes may become the mainstream, besides contributing to the emerging body of research that aims to better understanding these modes