scholarly journals Value of demand information in autonomous mobility-on-demand systems

2019 ◽  
Vol 121 ◽  
pp. 346-359 ◽  
Author(s):  
Jian Wen ◽  
Neema Nassir ◽  
Jinhua Zhao
Keyword(s):  
Demand Systems ◽  
On Demand ◽  
Demand Information ◽  
Autonomous Mobility

scholarly journals Analysis and Control of Autonomous Mobility-on-Demand Systems

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Gioele Zardini ◽  
Nicolas Lanzetti ◽  
Marco Pavone ◽  
Emilio Frazzoli
Keyword(s):  
Performance Metrics ◽  
Transportation Systems ◽  
Demand Systems ◽  
Annual Review ◽  
Publication Date ◽  
Systematic Analysis ◽  
On Demand ◽  
Trade Offs ◽  
Autonomous Mobility ◽  
And Control

Challenged by urbanization and increasing travel needs, existing transportation systems need new mobility paradigms. In this article, we present the emerging concept of autonomous mobility-on-demand, whereby centrally orchestrated fleets of autonomous vehicles provide mobility service to customers. We provide a comprehensive review of methods and tools to model and solve problems related to autonomous mobility-on-demand systems. Specifically, we first identify problem settings for their analysis and control, from both operational and planning perspectives. We then review modeling aspects, including transportation networks, transportation demand, congestion, operational constraints, and interactions with existing infrastructure. Thereafter, we provide a systematic analysis of existing solution methods and performance metrics, highlighting trends and trade-offs. Finally, we present various directions for further research. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Routing and Rebalancing Intermodal Autonomous Mobility-on-Demand Systems in Mixed Traffic

2021 ◽  
pp. 1-13
Author(s):  
Salomon Wollenstein-Betech ◽  
Mauro Salazar ◽  
Arian Houshmand ◽  
Marco Pavone ◽  
Ioannis Ch. Paschalidis ◽  
...  
Keyword(s):  
Demand Systems ◽  
Mixed Traffic ◽  
On Demand ◽  
Autonomous Mobility

A Congestion-aware Routing Scheme for Autonomous Mobility-on-Demand Systems

2019 ◽  
Author(s):  
Mauro Salazar ◽  
Matthew Tsao ◽  
Izabel Aguiar ◽  
Maximilian Schiffer ◽  
Marco Pavone
Keyword(s):  
Demand Systems ◽  
On Demand ◽  
Routing Scheme ◽  
Autonomous Mobility ◽  
Congestion Aware

scholarly journals Rebalancing Autonomous Vehicles using Deep Reinforcement Learning

2022 ◽  
Vol 16 ◽  
pp. 646-652
Author(s):  
Jiajie Dai ◽  
Qianyu Zhu ◽  
Nan Jiang ◽  
Wuyang Wang
Keyword(s):  
Reinforcement Learning ◽  
Autonomous Vehicles ◽  
Supply And Demand ◽  
Efficient Operation ◽  
Demand And Supply ◽  
On Demand ◽  
Demand Information ◽  
Autonomous Mobility ◽  
Demand Patterns

The shared autonomous mobility-on-demand (AMoD) system is a promising business model in the coming future which provides a more efficient and affordable urban travel mode. However, to maintain the efficient operation of AMoD and address the demand and supply mismatching, a good rebalancing strategy is required. This paper proposes a reinforcement learning-based rebalancing strategy to minimize passengers’ waiting in a shared AMoD system. The state is defined as the nearby supply and demand information of a vehicle. The action is defined as moving to a nearby area with eight different directions or staying idle. A 4.6 4.4 km2 region in Cambridge, Massachusetts, is used as the case study. We trained and tested the rebalancing strategy in two different demand patterns: random and first-mile. Results show the proposed method can reduce passenger’s waiting time by 7% for random demand patterns and 10% for first-mile demand patterns.

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