scholarly journals Impact of transportation network companies on urban congestion: Evidence from large-scale trajectory data

2020 ◽  
Vol 55 ◽  
pp. 102053 ◽  
Author(s):  
Xinwu Qian ◽  
Tian Lei ◽  
Jiawei Xue ◽  
Zengxiang Lei ◽  
Satish V. Ukkusuri
Keyword(s):  
Large Scale ◽  
Transportation Network ◽  
Trajectory Data ◽  
Transportation Network Companies

scholarly journals Mining Vehicle Trajectories to Discover Individual Significant Places: Case Study using Floating Car Data in the Paris Region

2021 ◽  
pp. 036119812199550
Author(s):  
Danyang Sun ◽  
Fabien Leurent ◽  
Xiaoyan Xie
Keyword(s):  
Large Scale ◽  
City Planning ◽  
Human Mobility ◽  
Work Place ◽  
Trajectory Data ◽  
Floating Car Data ◽  
Vehicle Trajectories ◽  
Activity Types ◽  
Paris Region

In this study we discovered significant places in individual mobility by exploring vehicle trajectories from floating car data. The objective was to detect the geo-locations of significant places and further identify their functional types. Vehicle trajectories were first segmented into meaningful trips to recover corresponding stay points. A customized density-based clustering approach was implemented to cluster stay points into places and determine the significant ones for each individual vehicle. Next, a two-level hierarchy method was developed to identify the place types, which firstly identified the activity types by mixture model clustering on stay characteristics, and secondly discovered the place types by assessing their profiles of activity composition and frequentation. An applicational case study was conducted in the Paris region. As a result, five types of significant places were identified, including home place, work place, and three other types of secondary places. The results of the proposed method were compared with those from a commonly used rule-based identification, and showed a highly consistent matching on place recognition for the same vehicles. Overall, this study provides a large-scale instance of the study of human mobility anchors by mining passive trajectory data without prior knowledge. Such mined information can further help to understand human mobility regularities and facilitate city planning.

Partnerships with Technology-Enabled Mobility Companies

2017 ◽  
Vol 2649 (1) ◽  
pp. 106-112 ◽  
Author(s):  
Marla Westervelt ◽  
Joshua Schank ◽  
Emma Huang
Keyword(s):  
Service Delivery ◽  
Public Transit ◽  
Transportation Network ◽  
Public Agencies ◽  
On Demand ◽  
Transportation Network Companies

The rise and the proliferation of the on-demand economy are creating a new mobility marketplace. This research explored how these new options could be synergistic with public transit models and detailed the experiences of two transit operators that entered into service delivery partnerships with a transportation network company and a micro-transit operator. Based on a series of interviews and the experiences of these two public agencies, this research provides a set of key takeaways and recommendations for transit operators exploring the potential of partnering with new mobility services such as transportation network companies (e.g., Uber or Lyft) and microtransit (e.g., Bridj or Via).

scholarly journals RealTE: Real-time Trajectory Estimation Over Large-Scale Road Networks

2022 ◽  
Author(s):  
Qibin Zhou ◽  
Qingang Su ◽  
Dingyu Yang
Keyword(s):  
Travel Time ◽  
Real Time ◽  
High Speed ◽  
Road Network ◽  
Large Scale ◽  
Road Networks ◽  
Trajectory Data ◽  
Real Time Traffic ◽  
Histogram Estimation ◽  
Traffic Estimation

Real-time traffic estimation focuses on predicting the travel time of one travel path, which is capable of helping drivers selecting an appropriate or favor path. Statistical analysis or neural network approaches have been explored to predict the travel time on a massive volume of traffic data. These methods need to be updated when the traffic varies frequently, which incurs tremendous overhead. We build a system RealTER⁢e⁢a⁢l⁢T⁢E, implemented on a popular and open source streaming system StormS⁢t⁢o⁢r⁢m to quickly deal with high speed trajectory data. In RealTER⁢e⁢a⁢l⁢T⁢E, we propose a locality-sensitive partition and deployment algorithm for a large road network. A histogram estimation approach is adopted to predict the traffic. This approach is general and able to be incremental updated in parallel. Extensive experiments are conducted on six real road networks and the results illustrate RealTE achieves higher throughput and lower prediction error than existing methods. The runtime of a traffic estimation is less than 11 seconds over a large road network and it takes only 619619 microseconds for model updates.

scholarly journals Challenges and Prospects of Entrepreneurship in Bhutan from the Lens of Business Educators

2020 ◽  
pp. 63-71
Author(s):  
Dhanapati Sharma ◽  
Khem Prasad Gautam
Keyword(s):  
Large Scale ◽  
Transportation Network ◽  
Structured Interview ◽  
Good Prospect ◽  
Scale Production ◽  
Entrepreneurial Ventures ◽  
Technological Support ◽  
Business Educators ◽  
Goods And Services ◽  
Undue Advantage

Entrepreneurship plays an important role in generating employment opportunities, enhancing public income and promoting societal change, particularly in a budding economy like Bhutan. Given its importance to the country, this paper investigates the challenges faced by aspiring entrepreneurs and entrepreneurial ventures, and their future prospects in Bhutan. The paper adopts qualitative research methodology to study the perspective of business educators through a semi-structured interview with fifteen participants from Gedu College of Business Studies located at Gedu, Bhutan. The study reveals that, due to a range of challenges the aspiring entrepreneurs and the entrepreneurial ventures face today, the Bhutanese entrepreneurs have a long way to go before they can effectively drive changes in the economy. However, the findings suggest that there is a good prospect for the entrepreneurial ventures in the country, and the ventures will have an undue advantage if it can leverage on the technological support from other countries. To ease the way for entrepreneurs in the country, the study finds it important to encourage the consumption of indigenous products by discouraging the import of the goods and services that can be produced within the country, regulate the price of the home made product, explore market and marketing facilities beyond the country to encourage large scale production, initiate discussion about entrepreneurship and the associated benefits at school levels and also take adequate infrastructural facilities (water, electricity and transportation network) across all parts of the country.

scholarly journals A Two-Phase Gradient Projection Algorithm for Solving the Combined Modal Split and Traffic Assignment Problem with Nested Logit Function

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Seungkyu Ryu ◽  
Anthony Chen ◽  
Songyot Kitthamkesorn
Keyword(s):  
Large Scale ◽  
Traffic Assignment ◽  
Transportation Network ◽  
User Equilibrium ◽  
Gradient Projection ◽  
Projection Algorithm ◽  
Nested Logit ◽  
Two Phase ◽  
Phase Gradient ◽  
Modal Split

This study provides a gradient projection (GP) algorithm to solve the combined modal split and traffic assignment (CMSTA) problem. The nested logit (NL) model is used to consider the mode correlation under the user equilibrium (UE) route choice condition. Specifically, a two-phase GP algorithm is developed to handle the hierarchical structure of the NL model in the CMSTA problem. The Seoul transportation network in Korea is adopted to demonstrate an applicability in a large-scale multimodal transportation network. The results show that the proposed GP solution algorithm outperforms the method of the successive averages (MSA) algorithm and the classical Evan’s algorithm.

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