3,279 research outputs found
Synergistic Interactions of Dynamic Ridesharing and Battery Electric Vehicles Land Use, Transit, and Auto Pricing Policies
It is widely recognized that new vehicle and fuel technology is necessary, but not sufficient, to meet deep greenhouse gas (GHG) reductions goals for both the U.S. and the state of California. Demand management strategies (such as land use, transit, and auto pricing) are also needed to reduce passenger vehicle miles traveled (VMT) and related GHG emissions. In this study, the authors explore how demand management strategies may be combined with new vehicle technology (battery electric vehicles or BEVs) and services (dynamic ridesharing) to enhance VMT and GHG reductions. Owning a BEV or using a dynamic ridesharing service may be more feasible when distances to destinations are made shorter and alternative modes of travel are provided by demand management strategies. To examine potential markets, we use the San Francisco Bay Area activity based travel demand model to simulate business-as-usual, transit oriented development, and auto pricing policies with and without high, medium, and low dynamic ridesharing participation rates and BEV daily driving distance ranges.
The results of this study suggest that dynamic ridesharing has the potential to significantly reduce VMT and related GHG emissions, which may be greater than land use and transit policies typically included in Sustainable Community Strategies (under California Senate Bill 375), if travelers are willing pay with both time and money to use the dynamic ridesharing system. However, in general, large synergistic effects between ridesharing and transit oriented development or auto pricing policies were not found in this study. The results of the BEV simulations suggest that TODs may increase the market for BEVs by less than 1% in the Bay Area and that auto pricing policies may increase the market by as much as 7%. However, it is possible that larger changes are possible over time in faster growing regions where development is currently at low density levels (for example, the Central Valley in California). The VMT Fee scenarios show larger increases in the potential market for BEV (as much as 7%). Future research should explore the factors associated with higher dynamic ridesharing and BEV use including individual attributes, characteristics of tours and trips, and time and cost benefits. In addition, the travel effects of dynamic ridesharing systems should be simulated explicitly, including auto ownership, mode choice, destination, and extra VMT to pick up a passenger
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
A Decomposition Algorithm to Solve the Multi-Hop Peer-to-Peer Ride-Matching Problem
In this paper, we mathematically model the multi-hop Peer-to-Peer (P2P)
ride-matching problem as a binary program. We formulate this problem as a
many-to-many problem in which a rider can travel by transferring between
multiple drivers, and a driver can carry multiple riders. We propose a
pre-processing procedure to reduce the size of the problem, and devise a
decomposition algorithm to solve the original ride-matching problem to
optimality by means of solving multiple smaller problems. We conduct extensive
numerical experiments to demonstrate the computational efficiency of the
proposed algorithm and show its practical applicability to reasonably-sized
dynamic ride-matching contexts. Finally, in the interest of even lower solution
times, we propose heuristic solution methods, and investigate the trade-offs
between solution time and accuracy
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
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