Dynamic Ride Sharing as an Alternative Transportation Mode for Commuting Among METU Campus and Eryaman

2022 ◽  
pp. 485-498
Author(s):  
Mehmet Erdi Özgürlük ◽  
Ismail Yavuz Paksoy
Keyword(s):  
Transportation Mode ◽  
Alternative Transportation ◽  
Ride Sharing

scholarly journals The Characteristic of Online Transportation Services and Provision in Semarang City

2018 ◽  
Vol 20 (2) ◽  
pp. 90-97 ◽  
Author(s):  
Novi Kartika Dewi ◽  
Anita Ratnasari Rakhmatulloh
Keyword(s):  
Public Transportation ◽  
Transportation Mode ◽  
Transportation Services ◽  
Alternative Transportation

The complex mobility in Semarang city requires the efficient and effective provision and services of public transportation. Due to the condition of public transportation services is not proper, so it requires the presence of online transportation. Online transportation services have a flexibility (in routes and time) and it seems the society has their own private vehicles. Online transportation prices is more expensive than private vehicles or public transportation. But it provides flexibility and convenience as one of the alternative transportation mode.

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 Association of Physical Activity and Sitting Time with Overweight/Obesity in Chinese Occupational Populations

Obesity Facts ◽  
2021 ◽  
pp. 1-7
Author(s):  
Fan Yuan ◽  
Weiyan Gong ◽  
Caicui Ding ◽  
Hui Li ◽  
Ganyu Feng ◽  
...  
Keyword(s):  
Physical Activity ◽  
Lower Risk ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Active Transportation ◽  
Sitting Time ◽  
Work Time ◽  
Transportation Mode ◽  
Activity Intensity ◽  
Female Employees

<b><i>Abstract:</i></b> The aim of this study was to explore association of physical activity and sitting time with overweight/obesity in Chinese occupational populations for the development of intervention and prevention strategies for obesity. <b><i>Methods:</i></b> A total of 23,112 participants were selected from the 2010–2012 China National Nutrition and Health Survey (CNNHS). A logistics regression model was used to examine the associations of physical activity and sitting time with overweight/obesity by gender after adjusting for age, educational level, marital status, and family economic level. <b><i>Results:</i></b> The prevalence of overweight/obesity based on the WHO definition and the WGOC definition was 30.8% and 41.3%, respectively. Male employees with moderate and heavy occupation activity intensity had a lower risk for overweight/obesity than those with light occupation activity intensity (moderate: OR 0.90, 95% CI 0.82–0.98; heavy: OR 0.75, 95% CI 0.65–0.86), and the risk of overweight/obesity of male employees with long work-time spent sitting was higher than those with short work-time spent sitting (2–4.9 h/day: OR 1.26, 95% CI 1.14–1.40; ≥5 h/day: OR 1.29, 95% CI 1.15–1.44). The risk of overweight/obesity of male employees with active transportation mode was lower than those with inactive transportation mode (OR 0.91, 95% CI 0.84–0.99), while the risk of overweight/obesity of female employees with active transportation mode was higher (OR 1.14, 95% CI 1.04–1.25). Female employees with leisure-time physical activity (LTPA) for ≥150 min/week had lower risk of overweight/obesity than those with LTPA for &#x3c;150 min/week (OR 0.69, 95% CI 0.56–0.84). There was no significant association of leisure-time sitting and housework time with overweight/obesity in Chinese occupational populations. <b><i>Conclusion:</i></b> Occupation activity intensity, LTPA, transportation mode, and work sitting time were associated with overweight/obesity. Reducing work sitting time, moderate and heavy occupation activity intensity, and an active transportation mode could help male employees decrease the risk of overweight/obesity. Increasing leisure-time physical activity could reduce the risk of overweight/obesity in women. Our findings provided insight into the association of physical activity and sitting time with overweight/obesity. It will be necessary to carry out workplace-based interventions, have an active transportation mode, and increase leisure-time physical activity to decrease the risks of overweight/obesity.

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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