Optimal Policies for Platooning and Ride Sharing in Autonomy-Enabled Transportation

2020 ◽  
pp. 848-863
Author(s):  
Aviv Adler ◽  
David Miculescu ◽  
Sertac Karaman
Keyword(s):  
Ride Sharing ◽  
Optimal Policies

scholarly journals Pricing and Optimization in Shared Vehicle Systems: An Approximation Framework

2021 ◽  
Author(s):  
Siddhartha Banerjee ◽  
Daniel Freund ◽  
Thodoris Lykouris
Keyword(s):  
Resource Allocation ◽  
Optimization Problems ◽  
High Dimensional ◽  
Optimal Management ◽  
Markovian Models ◽  
Ride Sharing ◽  
Vehicle Systems ◽  
Optimal Policies ◽  
Future Supply ◽  
Optimality Gap

The optimal management of shared vehicle systems, such as bike-, scooter-, car-, or ride-sharing, is more challenging compared with traditional resource allocation settings because of the presence of spatial externalities—changes in the demand/supply at any location affect future supply throughout the system within short timescales. These externalities are well captured by steady-state Markovian models, which are therefore widely used to analyze such systems. However, using Markovian models to design pricing and other control policies is computationally difficult because the resulting optimization problems are high dimensional and nonconvex. In our work, we design a framework that provides near-optimal policies, for a range of possible controls, that are based on applying the possible controls to achieve spatial balance on average. The optimality gap of these policies improves as the ratio between supply and the number of locations increases and asymptotically goes to zero.

Concatenation of Circumstances or Historical Regularity?

2009 ◽  
pp. 75-84
Author(s):  
V. Popov
Keyword(s):  
Transition Economies ◽  
Government Expenditure ◽  
Previous History ◽  
Shock Therapy ◽  
Economic Liberalization ◽  
Institutional Capacity ◽  
Government Failure ◽  
Stage Of Development ◽  
Optimal Policies ◽  
Cis Countries

Why have many transition economies succeeded by pursuing policies which are so different from the radical economic liberalization (shock therapy) that is normally credited for the economic success of countries of Central Europe? First, optimal policies are context dependent, they are specific for each stage of development and what worked in Slovenia cannot be expected to work in Mongolia. Second, even for the countries with the same level of development reforms that are necessary to stimulate growth are different; they depend on the previous history and on the path chosen. The reduction of government expenditure as a share of GDP did not undermine significantly the institutional capacity of the state in China, but in Russia and other CIS countries it turned out to be ruinous. The art of the policymaker is to create markets without causing government failure, as happened in many CIS countries.

Deep Reinforcement Learning for Ride-sharing Dispatching and Repositioning

2019 ◽  
Author(s):  
Zhiwei (Tony) Qin ◽  
Xiaocheng Tang ◽  
Yan Jiao ◽  
Fan Zhang ◽  
Chenxi Wang ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Human Computer Interaction ◽  
Ride Sharing ◽  
Simulation Based ◽  
Computer Interaction

In this demo, we will present a simulation-based human-computer interaction of deep reinforcement learning in action on order dispatching and driver repositioning for ride-sharing.  Specifically, we will demonstrate through several specially designed domains how we use deep reinforcement learning to train agents (drivers) to have longer optimization horizon and to cooperate to achieve higher objective values collectively. 

Urban Transport

2018 ◽  
Author(s):  
José van
Keyword(s):  
Urban Areas ◽  
Urban Transport ◽  
Transport Sector ◽  
Public And Private ◽  
Transport Services ◽  
Ride Sharing ◽  
The World ◽  
Private And Public ◽  
Selection Mechanisms

Platformization affects the entire urban transport sector, effectively blurring the division between private and public transport modalities; existing public–private arrangements have started to shift as a result. This chapter analyzes and discusses the emergence of a platform ecology for urban transport, focusing on two central public values: the quality of urban transport and the organization of labor and workers’ rights. Using the prism of platform mechanisms, it analyzes how the sector of urban transport is changing societal organization in various urban areas across the world. Datafication has allowed numerous new actors to offer their bike-, car-, or ride-sharing services online; selection mechanisms help match old and new complementors with passengers. Similarly, new connective platforms are emerging, most prominently transport network companies such as Uber and Lyft that offer public and private transport options, as well as new platforms offering integrated transport services, often referred to as “mobility as a service.”

Working Time under Alternative Pay Contracts in the Ride-Sharing Industry

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Filippo Belloc
Keyword(s):  
Network Effects ◽  
Network Externalities ◽  
Profit Sharing ◽  
Static Model ◽  
Peer To Peer ◽  
Working Time ◽  
Intensive Margin ◽  
Hours Worked ◽  
Ride Sharing ◽  
Transportation Sector

AbstractWe study hours worked by drivers in the peer-to-peer transportation sector with cross-side network effects. Medallion lease (regulated market), commission-based (Uber-like pay) and profit-sharing (“pure” taxi coop) compensation schemes are compared. Our static model shows that network externalities matter, depending on the number of active drivers. When the number of drivers is limited, in the presence of positive network effects, a regulated system always induces more hours worked, while the commission fee influences the comparative incentives towards working time of Uber-like pay versus profit-sharing. When the number of drivers is infinite (or close to it), the influence of network externalities on optimal working time vanishes. Our model helps identifying which is the pay scheme that best remunerates longer working times and offers insights to regulators seeking to improve the intensive margin of coverage by taxi services.

scholarly journals A Dynamic Mobility Traffic Model Based on Two Modes of Transport in Smart Cities

Smart Cities ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 253-270
Author(s):  
Mohammed Bin Hariz ◽  
Dhaou Said ◽  
Hussein T. Mouftah
Keyword(s):  
Data Exchange ◽  
Smart Cities ◽  
Time Data ◽  
School Bus ◽  
The Public ◽  
Ride Sharing ◽  
Dynamic Mobility ◽  
Proposed Model ◽  
Loading System ◽  
Suitable Combination

This paper focuses on transportation models in smart cities. We propose a new dynamic mobility traffic (DMT) scheme which combines public buses and car ride-sharing. The main objective is to improve transportation by maximizing the riders’ satisfaction based on real-time data exchange between the regional manager, the public buses, the car ride-sharing and the riders. OpenStreetMap and OMNET++ were used to implement a realistic scenario for the proposed model in a city like Ottawa. The DMT scheme was compared to a multi-loading system used for a school bus. Simulations showed that rider satisfaction was enhanced when a suitable combination of transportation modes was used. Additionally, compared to the other scheme, this DMT scheme can reduce the stress level of car ride-sharing and public buses during the day to the minimal level.

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