A Smart Solution to Rush-Hour Traffic Congestion: Effects of Dockless Bike-Sharing Entry on Ride-Sharing

2019 ◽  
Author(s):  
Juan Qin ◽  
Stephanie Lee ◽  
Yong Tan
2020 ◽  
Vol 25 (3) ◽  
pp. 868-875
Author(s):  
Mária Holienčinová ◽  
Zdenka Kádeková ◽  
Tomáš Holota ◽  
Ľudmila Nagyová

2018 ◽  
Vol 48 ◽  
pp. 07001 ◽  
Author(s):  
Jirarat Pinthong ◽  
Korb Limsuwan ◽  
Boonchai Stitmannaithum

Chulalongkorn University (CU) is located at the heart of Bangkok, which is one of the most traffic congested cities in the world. It is very crucial for the university to develop a green and clean transportation system that is good for both the CU community and the whole society. To reduce on-campus traffic, the university provides four parking buildings on the edge of four corners of the campus to serve visitors, students, faculties and staffs who travel by private cars. While providing added convenience, these parking garages reduce traffic congestion on campus and, thus, pollutions from harmful emissions and traffic noises. To promote eco-friendly transportation in the campus, the university provides “CU Shuttle Bus” - an electric shuttle bus service that cover not only campus area, but also reach out to public sky train and subway stations around the campus. The CU Shuttle Bus’s mobile application, developed by engineering students, helps improve user experience by showing all useful information including campus map, bus routing, and real-time locations of all buses. To encourage walking and cycling within the campus and to promote good health and fitness, the university has been constructing covered walkways and bike lanes throughout the campus. In addition, “CU Bike” - a bike sharing program, was first introduced in 2014 and has quickly grown in popularity among CU students since. A new “CU Toyota Hamo”, an electric vehicle rental program, is another great option of green transportations for those who cannot ride a bicycle and for older people of the aging society. All these projects help promote the development of innovations and practices that are both sustainable and protective of the environment of Chulalongkorn University, as well as the surrounding community, the country and planet as a whole.


Urban Studies ◽  
2016 ◽  
Vol 54 (15) ◽  
pp. 3423-3445 ◽  
Author(s):  
Yuting Hou

This study mainly addresses two main questions: (1) whether traffic congestion negatively affects single-family house price by constraining accessibility to jobs; (2) whether congestion effects and accessibility effects vary by income groups within a metropolitan area. This study uses a multilevel hedonic price model to estimate the marginal price of accessibility while controlling for other neighbourhood attributes and the correlation of proximal housing sales. The congestion effects are identified by comparing the implicit price of accessibility between congested-flow and free-flow. The results show that the accessibility measured with congested time yields higher marginal price, suggesting that households are willing to pay more to avoid locations with high congestion delays and accessibility loss. The results also suggest that accessibility effects are more valued by homebuyers in middle-income neighbourhoods, compared with those in the lowest or highest income neighbourhoods.


2020 ◽  
Vol 9 (3) ◽  
pp. 445-456
Author(s):  
Deepika Upadhyay ◽  
Geetanjali Purswani ◽  
Pooja Jain

The rapidly rising rate of urbanization, which is closely linked to economic growth, has exposed the world to several challenges such as inequality, environmental degradation, traffic congestion, infrastructural concerns and social conflicts. Therefore, urban sustainability has emerged as one of the most debatable discussions across the world. The existing network of transportation can no longer keep up with the growing demand in metropolitan cities. Short distance travel has become an unresolved issue for daily commuters. The case presents how MMVs have emerged as an alternative mode of transport for resolving issues of daily commuters regarding the first-mile connectivity, last-mile connectivity and short distance travel to reach their final destination. MMVs are basically light-weight vehicles which occupy less space on road. These vehicles include bicycles, e-bikes, skateboards, hoverboards and other battery-operated vehicles. The case narrates the journey of Yulu, a dockless bike-sharing venture which promoted the concept of green consumerism among the daily commuters at affordable rates. The venture initially started in the IT city of Bangalore and later expanded its operations to other cities such as Pune, Navi Mumbai, Gurugram and Bhubaneswar. The speciality of this venture is that it offers a sustainable solution to ever-increasing problems of traffic congestion and aggravating air pollution issues in metropolitan cities. Dilemma: How to offer a sustainable solution to the ever-increasing problem of traffic congestion and aggravating air pollution due to rising vehicular traffic? How to make short distance travel affordable and more convenient for daily commuters? Theory: Three pillars of sustainable development. Type of Case: Problem solving applied case. Protagonist: Present. Discussion and Case Questions: What strategies should be employed by the start-up to make it a more popular form of commute? How can the increasing rate of damage to the vehicles be brought down? How does organization structure and cluster management practices of Yulu help it to become more sustainable? How can the regulatory bodies and government promote and adopt such start-ups in their urban planning projects?


Traffic congestion has been one of the major issues faced by most urbanization around the world. Traffic congestion can be define as the vehicles that travels at a certain place with slower speed. This is because there are many vehicles using that road at the same time. This problem has resulting to the delay, pollution and increased fuel consumption. The aims of this study are to determine the factors that contribute to this problem, identify the impacts have been occurred and give the recommendation on reducing the issue. Each data and information in this research is strengthen with the support from several sources of reading and knowledge gained through past studies and journals. The researcher using the quantitative method in order for describe and generalize collecting data from the respondents. Then, the collected data has been analyze by using the SPSS software. After that, the researcher has used the descriptive statistics in order to identify the most significant factors and impacts based on the mean values respectively. The highest mean value shows that those factors and impacts were strongly significant. From that, it can show that the objectives of this research successfully achieved. Furthermore, in this research study the researcher has gave the recommendation to reducing traffic congestion at Jalan Bertingkat Skudai, Johor Bahru. Those are implement Vehicle Quota System (VQS), reduced parking spaces strategy, implement Electronic Road Pricing (ERP) system, Tidal-Flow operation and provide bike-sharing system at this area.


2017 ◽  
Vol 10 (1) ◽  
pp. 219-226 ◽  
Author(s):  
Purnima Sachdeva ◽  
K N Sarvanan

Bike sharing systems have been gaining prominence all over the world with more than 500 successful systems being deployed in major cities like New York, Washington, London. With an increasing awareness of the harms of fossil based mean of transportation, problems of traffic congestion in cities and increasing health consciousness in urban areas, citizens are adopting bike sharing systems with zest. Even developing countries like India are adopting the trend with a bike sharing system in the pipeline for Karnataka. This paper tackles the problem of predicting the number of bikes which will be rented at any given hour in a given city, henceforth referred to as the problem of ‘Bike Sharing Demand’. In this vein, this paper investigates the efficacy of standard machine learning techniques namely SVM, Regression, Random Forests, Boosting by implementing and analyzing their performance with respect to each other.This paper also presents two novel methods, Linear Combination and Discriminating Linear Combination, for the ‘Bike Sharing Demand’ problem which supersede the aforementioned techniques as good estimates in the real world.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Taraneh Askarzadeh ◽  
Raj Bridgelall

Micromobility is an evolving form of transportation modality that uses small human- or electric-powered vehicles to move people short distances. Planners expected that bike sharing, the first form of micromobility, would reduce traffic congestion, cut travel cost, reduce pollution, enable connectivity with other modes of transport, and promote public health. However, micromobility options also brought new challenges such as the difficulty of placement decisions to encourage adoption and to minimize conflict with other transport modes. Sound deployment decisions depend on the unique environmental characteristics and demographics of a location. Most studies analyzed deployments in high-density urban areas. This research determines the best locations for 5 new bike-sharing stations in Fargo, North Dakota, a small urban area in the rural United States. The workflow combines a geographic information system (GIS), level of traffic stress (LTS) ratings, and location-allocation optimization models. The spatial analysis considered 18 candidate station locations and eliminated those that fell within the 700-meter isochrone walking distance of the 11 existing stations. This case study demonstrates a scalable workflow that planners can repeat to achieve sustainable micromobility deployments by considering the land use, population density, activity points, and characteristics of the available pathways in their unique setting.


Author(s):  
John Wamburu ◽  
Stephen Lee ◽  
Mohammad H. Hajiesmaili ◽  
David Irwin ◽  
Prashant Shenoy

While ride-sharing has emerged as a popular form of transportation in urban areas due to its on-demand convenience, it has become a major contributor to carbon emissions, with recent studies suggesting it is 47% more carbon-intensive than personal car trips. In this paper, we examine the feasibility, costs, and carbon benefits of using electric bike-sharing---a low carbon form of ride-sharing---as a potential substitute for shorter ride-sharing trips, with the overall goal of greening the ride-sharing ecosystem. Using public datasets from New York City, our analysis shows that nearly half of the taxi and rideshare trips in New York are shorts trips of less than 3.5km, and that biking is actually faster than using a car for ultra-short trips of 2km or less. We analyze the cost and carbon benefits of different levels of ride substitution under various scenarios. We find that the additional bikes required to satisfy increased demand from ride substitution increases sub-linearly and results in 6.6% carbon emission reduction for 10% taxi ride substitution. Moreover, this reduction can be achieved through a hybrid mix that requires only a quarter of the bikes to be electric bikes, which reduces system costs. We also find that expanding bike-share systems to new areas that lack bike-share coverage requires additional investments due to the need for new bike stations and bike capacity to satisfy demand but also provides substantial carbon emission reductions. Finally, frequent station repositioning can reduce the number of bikes needed in the system by up to a third for a minimal increase in carbon emissions of 2% from the trucks required to perform repositioning, providing an interesting tradeoff between capital costs and carbon emissions.


2021 ◽  
Vol 145 ◽  
pp. 212-246
Author(s):  
Negin Alisoltani ◽  
Ludovic Leclercq ◽  
Mahdi Zargayouna

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