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

A Tabu Search Based Metaheuristic for Dynamic Carpooling Optimization

International audienceThe carpooling problem consists in matching a set of riders' requests with a set of drivers' offers by synchronizing their origins, destinations and time windows. The paper presents the so-called Dynamic Carpooling Optimization System (DyCOS), a system which supports the automatic and optimal ridematching process between users on very short notice or even en-route. Nowadays, there are numerous research contributions that revolve around the carpooling problem, notably in the dynamic context. However, the problem's high complexity and the real time aspect are still challenges to overcome when addressing dynamic carpooling. To counter these issues, DyCOS takes decisions using a novel Tabu Search based metaheuristic. The proposed algorithm employs an explicit memory system and several original searching strategies developed to make optimal decisions automatically. To increase users' satisfaction, the proposed metaheuristic approach manages the transfer process and includes the possibility to drop off the passenger at a given walking distance from his destination or at a transfer node. In addition, the detour concept is used as an original aspiration process, to avoid the entrapment by local solutions and improve the generated solution. For a rigorous assessment of generated solutions , while considering the importance and interaction among the optimization criteria, the algorithm adopts the Choquet integral operator as an aggregation approach. To measure the effectiveness of the proposed method, we develop a simulation environment based on actual carpooling demand data from the metropolitan area of Lille in the north of France

The Merits of Sharing a Ride

The culture of sharing instead of ownership is sharply increasing in individuals behaviors. Particularly in transportation, concepts of sharing a ride in either carpooling or ridesharing have been recently adopted. An efficient optimization approach to match passengers in real-time is the core of any ridesharing system. In this paper, we model ridesharing as an online matching problem on general graphs such that passengers do not drive private cars and use shared taxis. We propose an optimization algorithm to solve it. The outlined algorithm calculates the optimal waiting time when a passenger arrives. This leads to a matching with minimal overall overheads while maximizing the number of partnerships. To evaluate the behavior of our algorithm, we used NYC taxi real-life data set. Results represent a substantial reduction in overall overheads

Mobility on Demand in the United States

The growth of shared mobility services and enabling technologies, such as smartphone apps, is contributing to the commodification and aggregation of transportation services. This chapter reviews terms and definitions related to Mobility on Demand (MOD) and Mobility as a Service (MaaS), the mobility marketplace, stakeholders, and enablers. This chapter also reviews the U.S. Department of Transportation’s MOD Sandbox Program, including common opportunities and challenges, partnerships, and case studies for employing on-demand mobility pilots and programs. The chapter concludes with a discussion of vehicle automation and on-demand mobility including pilot projects and the potential transformative impacts of shared automated vehicles on parking, land use, and the built environment

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