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相关论文: Uncovering Disparities in Rideshare Drivers Earnin…

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This study examines fairness within the rideshare industry, focusing on both drivers' wages and riders' trip fares. Through quantitative analysis, we found that drivers' hourly wages are significantly influenced by factors such as…

人机交互 · 计算机科学 2024-07-31 Yuhan Liu , Yuhan Zheng , Siyuan Zhang , Lydia T. Liu

Shared mobility-on-demand services are expanding rapidly in cities around the world. As a prominent example, app-based ridesourcing is becoming an integral part of many urban transportation ecosystems. Despite the centrality, limited public…

计算机与社会 · 计算机科学 2020-11-02 J Soria , Y Chen , A Stathopoulos

Despite the potential of online sharing economy platforms such as Uber, Lyft, or Foodora to democratize the labor market, these services are often accused of fostering unfair working conditions and low wages. These problems have been…

物理与社会 · 物理学 2020-09-01 Eszter Bokányi , Anikó Hannák

Several scientific studies have reported the existence of the income gap among rideshare drivers based on demographic factors such as gender, age, race, etc. In this paper, we study the income inequality among rideshare drivers due to…

人工智能 · 计算机科学 2020-12-17 Yifan Xu , Pan Xu

The rapid expansion of ride-sharing services has caused significant disruptions in the transpor-tation industry and fundamentally altered the way individuals move from one place to another. Accurate estimation of ride-sharing improves…

应用统计 · 统计学 2025-08-12 Mohamed Elkhouly , Taqwa Alhadidi

Ridesplitting -- a type of ride-hailing in which riders share vehicles with other riders -- has become a common travel mode in some major cities. This type of shared ride option is currently provided by transportation network companies…

应用统计 · 统计学 2023-05-05 Hao Liu , Saipraneeth Devunuri , Lewis Lehe , Vikash V. Gayah

Recommending routes by their probability of having a rider has long been the goal of conventional route recommendation systems. While this maximizes the platform-specific criteria of efficiency, it results in sub-optimal outcomes with the…

数据结构与算法 · 计算机科学 2025-04-24 Aqsa Ashraf Makhdomi , Iqra Altaf Gillani

Rideshare and ride-pooling platforms use artificial intelligence-based matching algorithms to pair riders and drivers. However, these platforms can induce inequality either through an unequal income distribution or disparate treatment of…

人工智能 · 计算机科学 2021-10-08 Naveen Raman , Sanket Shah , John Dickerson

Ride-pooling systems, despite being an appealing urban mobility mode, still struggle to gain momentum. While we know the significance of critical mass in reaching system sustainability, less is known about the spatiotemporal patterns of…

物理与社会 · 物理学 2023-12-15 Olha Shulika , Michal Bujak , Farnoud Ghasemi , Rafal Kucharski

We study revenue-optimal pricing and driver compensation in ridesharing platforms when drivers have heterogeneous preferences over locations. If a platform ignores drivers' location preferences, it may make inefficient trip dispatches;…

多智能体系统 · 计算机科学 2019-08-14 Duncan Rheingans-Yoo , Scott Duke Kominers , Hongyao Ma , David C. Parkes

Ride-hailing services have skyrocketed in popularity due to the convenience they offer, but recent research has shown that their pricing strategies can have a disparate impact on some riders, such as those living in disadvantaged…

计算机与社会 · 计算机科学 2023-01-10 Nripsuta Ani Saxena , Wenbin Zhang , Cyrus Shahabi

This paper considers the problem of measuring spatial and temporal variation in driver productivity on ride-sourcing trips. This variation is especially important from a driver's perspective: if a platform's drivers experience systematic…

Ride-sharing - the combination of multiple trips into one - may substantially contribute towards sustainable urban mobility. It is most efficient at high demand locations with many similar trip requests. However, here we reveal that…

物理与社会 · 物理学 2021-06-03 David-Maximilian Storch , Marc Timme , Malte Schröder

Many public transportation systems are unable to keep up with growing passenger demand as the population grows in urban areas. The slow or lack of improvements for public transportation pushes people to use private transportation modes,…

数据结构与算法 · 计算机科学 2021-09-15 Qian-Ping Gu , Jiajian Leo Liang

Ride-hailing platforms (e.g., Uber, Lyft) have transformed urban mobility by enabling ride-sharing, which holds considerable promise for reducing both travel costs and total vehicle miles traveled (VMT). However, the fragmentation of these…

综合经济学 · 经济学 2025-08-27 Xin Dong , Jose Ventura , Vikash V. Gayah

Ride-hailing is rapidly changing urban and personal transportation. Ride sharing or pooling is important to mitigate negative externalities of ride-hailing such as increased congestion and environmental impacts. However, there lacks…

机器学习 · 计算机科学 2022-02-23 Morteza Taiebat , Elham Amini , Ming Xu

The emergence of ride-sourcing platforms has brought an innovative alternative in transportation, radically changed travel behaviors, and suggested new directions for transportation planners and operators. This paper provides an exploratory…

系统与控制 · 电气工程与系统科学 2020-11-17 Simon Oh , Daniel Kondor , Ravi Seshadri , Meng Zhou , Diem-Trinh Le , Moshe Ben-Akiva

Although shared rides have the potential to increase vehicle utilization and reduce congestion and emissions, these benefits depend heavily on ridesharing platforms' ability to match riders effectively. As such, shared rides have seen…

最优化与控制 · 数学 2026-04-21 Yifan Shen , Junlin Chen , Julia Yan , Chiwei Yan

The ridesharing economy is experiencing rapid growth and innovation. Companies such as Uber and Lyft are continuing to grow at a considerable pace while providing their platform as an organizing medium for ridesharing services, increasing…

多智能体系统 · 计算机科学 2018-02-22 Joseph A. E. Shaheen

Rideshare platforms, when assigning requests to drivers, tend to maximize profit for the system and/or minimize waiting time for riders. Such platforms can exacerbate biases that drivers may have over certain types of requests. We consider…

人工智能 · 计算机科学 2020-09-08 Vedant Nanda , Pan Xu , Karthik Abinav Sankararaman , John P. Dickerson , Aravind Srinivasan
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