scholarly journals Coordinated mobility on demand model for taxi fleet management

2021 ◽  
Author(s):  
◽  
Singh Brar Avalpreet
Keyword(s):  
Fleet Management ◽  
Demand Model ◽  
On Demand

Customer Preference and Station Network in the London Bike-Share System

2020 ◽  
Author(s):  
Pu He ◽  
Fanyin Zheng ◽  
Elena Belavina ◽  
Karan Girotra
Keyword(s):  
Network Effects ◽  
Demand Model ◽  
Station Network ◽  
Customer Preference ◽  
On Demand ◽  
Structural Demand ◽  
City Of London ◽  
The City ◽  
Station Density ◽  
Bike Share

We study customer preference for the bike-share system in the city of London. We estimate a structural demand model on the station network to learn the preference parameters and use the estimated model to provide insights on the design and expansion of the bike-share system. We highlight the importance of network effects in understanding customer demand and evaluating expansion strategies of transportation networks. In the particular example of the London bike-share system, we find that allocating resources to some areas of the station network can be 10 times more beneficial than others in terms of system usage and that the currently implemented station density rule is far from optimal. We develop a new method to deal with the endogeneity problem of the choice set in estimating demand for network products. Our method can be applied to other settings in which the available set of products or services depends on demand. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.

scholarly journals From Traditional to Automated Mobility on Demand: A Comprehensive Framework for Modeling On-Demand Services in SimMobility

2019 ◽  
Vol 2673 (12) ◽  
pp. 15-29 ◽  
Author(s):  
Bat-hen Nahmias-Biran ◽  
Jimi B. Oke ◽  
Nishant Kumar ◽  
Kakali Basak ◽  
Andrea Araldo ◽  
...  
Keyword(s):  
Decision Making ◽  
User Satisfaction ◽  
Large Scale ◽  
Network Performance ◽  
Transportation Network ◽  
Behavioral Models ◽  
Demand Model ◽  
Modeling Framework ◽  
On Demand ◽  
Comprehensive Framework

Mobility on demand (MoD) systems have recently emerged as a promising paradigm for sustainable personal urban mobility in cities. In the context of multi-agent simulation technology, the state-of-the-art lacks a platform that captures the dynamics between decentralized driver decision-making and the centralized coordinated decision-making. This work aims to fill this gap by introducing a comprehensive framework that models various facets of MoD, namely heterogeneous MoD driver decision-making and coordinated fleet management within SimMobility, an agent- and activity-based demand model integrated with a dynamic multi-modal network assignment model. To facilitate such a study, we propose an event-based modeling framework. Behavioral models were estimated to characterize the decision-making of drivers using a GPS dataset from a major MoD fleet operator in Singapore. The proposed framework was designed to accommodate behaviors of multiple on-demand services such as traditional MoD, Lyft-like services, and automated MoD (AMoD) services which interact with traffic simulators and a multi-modal transportation network. We demonstrate the benefits of the proposed framework through a large-scale case study in Singapore comparing the fully decentralized traditional MoD with the future AMoD services in a realistic simulation setting. We found that AMoD results in a more efficient service even with increased demand. Parking strategies and fleet sizes will also have an effect on user satisfaction and network performance.

Sign in / Sign up

Export Citation Format

Share Document