2,234 research outputs found
Air Taxi Skyport Location Problem for Airport Access
Witnessing the rapid progress and accelerated commercialization made in
recent years for the introduction of air taxi services in near future across
metropolitan cities, our research focuses on one of the most important
consideration for such services, i.e., infrastructure planning (also known as
skyports). We consider design of skyport locations for air taxis accessing
airports, where we present the skyport location problem as a modified
single-allocation p-hub median location problem integrating choice-constrained
user mode choice behavior into the decision process. Our approach focuses on
two alternative objectives i.e., maximizing air taxi ridership and maximizing
air taxi revenue. The proposed models in the study incorporate trade-offs
between trip length and trip cost based on mode choice behavior of travelers to
determine optimal choices of skyports in an urban city. We examine the
sensitivity of skyport locations based on two objectives, three air taxi
pricing strategies, and varying transfer times at skyports. A case study of New
York City is conducted considering a network of 149 taxi zones and 3 airports
with over 20 million for-hire-vehicles trip data to the airports to discuss
insights around the choice of skyport locations in the city, and demand
allocation to different skyports under various parameter settings. Results
suggest that a minimum of 9 skyports located between Manhattan, Queens and
Brooklyn can adequately accommodate the airport access travel needs and are
sufficiently stable against transfer time increases. Findings from this study
can help air taxi providers strategize infrastructure design options and
investment decisions based on skyport location choices.Comment: 25 page
A dynamic ridesharing dispatch and idle vehicle repositioning strategy with integrated transit transfers
We propose a ridesharing strategy with integrated transit in which a private
on-demand mobility service operator may drop off a passenger directly
door-to-door, commit to dropping them at a transit station or picking up from a
transit station, or to both pickup and drop off at two different stations with
different vehicles. We study the effectiveness of online solution algorithms
for this proposed strategy. Queueing-theoretic vehicle dispatch and idle
vehicle relocation algorithms are customized for the problem. Several
experiments are conducted first with a synthetic instance to design and test
the effectiveness of this integrated solution method, the influence of
different model parameters, and measure the benefit of such cooperation.
Results suggest that rideshare vehicle travel time can drop by 40-60%
consistently while passenger journey times can be reduced by 50-60% when demand
is high. A case study of Long Island commuters to New York City (NYC) suggests
having the proposed operating strategy can substantially cut user journey times
and operating costs by up to 54% and 60% each for a range of 10-30 taxis
initiated per zone. This result shows that there are settings where such
service is highly warranted
The concept and impact analysis of a flexible mobility on demand system
This paper introduces an innovative transportation concept called Flexible Mobility on
Demand (FMOD), which provides personalized services to passengers. FMOD is a demand
responsive system in which a list of travel options is provided in real-time to each passen-
ger request. The system provides passengers with flexibility to choose from a menu that is
optimized in an assortment optimization framework. For operators, there is flexibility in
terms of vehicle allocation to different service types: taxi, shared-taxi and mini-bus. The
allocation of the available fleet to these three services is carried out dynamically so that
vehicles can change roles during the day. The FMOD system is built based on a choice
model and consumer surplus is taken into account in order to improve passenger satisfac-
tion. Furthermore, profits of the operators are expected to increase since the system adapts
to changing demand patterns. In this paper, we introduce the concept of FMOD and present
preliminary simulation results. It is shown that the dynamic allocation of the vehicles to
different services provides significant benefits over static allocation. Furthermore, it is
observed that the trade-off between consumer surplus and operator’s profit is critical.
The optimization model is adapted in order to take into account this trade-off by control-
ling the level of passenger satisfaction. It is shown that with such control mechanisms
FMOD provides improved results in terms of both profit and consumer surplus
The Concept and Impact Analysis of a Flexible Mobility on Demand System
This paper introduces an innovative transportation concept called Flexible Mobility on Demand (FMOD), which provides personalized services to passengers. FMOD is a demand responsive system in which a list of travel options is provided in real-time to each passenger request. The system provides passengers with flexibility to choose from a menu that is
optimized in an assortment optimization framework. For operators, there is flexibility in terms of vehicle allocation to di erent service types: taxi, shared-taxi and mini-bus. The allocation of the available fleet to these three services is carried out dynamically and based on demand and supply so that vehicles can change roles during the day. The FMOD system is built based on a choice model and consumer surplus is taken into account in order to
improve the passenger satisfaction. Furthermore, pro fits of the operators are expected to increase since the system adapts to changing demand patterns. In this paper, we introduce the concept of FMOD and present preliminary simulation results that quantify the added value of this system.Fujitsu Laboratories funding under the OSP account 6925717
Fujitsu Laboratories funding under the OSP account 6927900
Fujitsu Laboratories funding under the OSP account 692960
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