Can Public Transportation Compete with Automated and Connected Cars?

Buehler, Ralph

doi:10.5038/2375-0901.21.1.2

Cited by 36 publications

(19 citation statements)

References 8 publications

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“…Finally, researchers and practitioners should partner in studies to apply emerging knowledge to future challenges. For instance, the transportation safety implications of automated vehicles could be enormous (Fagnant and Kockelman 2014;Crayton and Meier 2017;Buehler 2018;Guerra and Morris 2018). However, many studies to date use simulated data and conjecture to forecast potential safety impacts.…”

Section: Discussionmentioning

confidence: 99%

Mitigating Bias in Big Data for Transportation

Griffin

Mulhall

Simek

et al. 2020

J. Big Data Anal. Transp.

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Emerging big data resources and practices provide opportunities to improve transportation safety planning and outcomes. However, researchers and practitioners recognise that big data from mobile phones, social media, and on-board vehicle systems include biases in representation and accuracy, related to transportation safety statistics. This study examines both the sources of bias and approaches to mitigate them through a review of published studies and interviews with experts. Coding of qualitative data enabled topical comparisons and reliability metrics. Results identify four categories of bias and mitigation approaches that concern transportation researchers and practitioners: sampling, measurement, demographics, and aggregation. This structure for understanding and working with bias in big data supports research with practical approaches for rapidly evolving transportation data sources.

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Section: Discussionmentioning

confidence: 99%

Mitigating Bias in Big Data for Transportation

Griffin

Mulhall

Simek

et al. 2020

J. Big Data Anal. Transp.

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“…The share of public transport travel per capita per day in the United States is 2%, Austria 17%, Sweden 14%, Germany 12%, the United Kingdom 10%, Norway 10%, France 8%, Finland 8%, and Switzerland 24% [2]. Several factors explain the lower passenger traffic of public transport in the United States than in Europe and Canada.…”

Section: Methodsmentioning

confidence: 99%

Survey Method Improvement of Urban Passenger Transport Works

Nikiforov¹,

Safronov²,

Mochalin³

et al. 2020

Transport Problems

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The article presents the implementation in the Omsk region of the project "Safe and high-quality roads," which is currently being implemented in various regions of Russia. Studies included the development and implementation of programs for the development of roads and municipalities, bringing the urban agglomeration network into a normative transport and operational state, eliminating the congestion of the urban agglomeration road network, including by transferring passenger traffic to public transport, optimizing traffic flows, and improving the efficiency of the traffic management system. To this end, a number of surveys of passenger and traffic flows have been carried out. The results of the surveys formed the basis of the transport model, through which programs were developed to optimize the route and transport networks of agglomerate cities. A proposal was made to use a survey of public transport drivers to obtain competent opinions on the need for appropriate changes and improvements.

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“…Transit-oriented development (TOD) can be adopted to reduce the overburden on personalised vehicle transit, and encourage PT uptake if mixed-use, high-density, residential developments are clustered around efficient, fast and reliable PT [68,69]. Lu et al [70] performed a choice modelling study for the residents of Atlanta, GA, USA.…”

Section: Urbanism and Urban Sprawlmentioning

confidence: 99%

A Review of the Transformation of Road Transport Systems: Are We Ready for the Next Step in Artificially Intelligent Sustainable Transport?

Hasan

Whyte

Jassmi

2019

ASI

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Mobility is experiencing a revolution, as advanced communications, computers with big data capacities, efficient networks of sensors, and signals, are developing value-added applications such as intelligent spaces and autonomous vehicles. Another new technology that is both promising and might even be pervasive for faster, safer and more environmentally-friendly public transport (PT) is the development of autonomous vehicles (AVs). This study aims to understand the state of the current research on the artificially intelligent transportation system (ITS) and AVs through a critical evaluation of peer-reviewed literature. This study’s findings revealed that the majority of existing research (around 82% of studies) focused on AVs. Results show that AVs can potentially reduce more than 80% of pollutant emissions per mile if powered by alternate energy resources (e.g., natural gas, biofuel, electricity, hydrogen cells, etc.). Not only can private vehicle ownership be cut down by bringing in ridesharing but the average vehicle miles travelled (VMT) should also be reduced through improved PT. The main benefits of AV adoption were reported in the literature to be travel time, traffic congestion, cost and environmental factors. Findings revealed barriers such as technological uncertainties, lack of regulation, unawareness among stakeholders and privacy and security concerns, along with the fact that lack of simulation and empirical modelling data from pilot studies limit the application. AV–PT was also found to be the most sustainable strategy in dense urban areas to shift the heavy trip load from private vehicles.

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Can Public Transportation Compete with Automated and Connected Cars?

Cited by 36 publications

References 8 publications

Mitigating Bias in Big Data for Transportation

Mitigating Bias in Big Data for Transportation

Survey Method Improvement of Urban Passenger Transport Works

A Review of the Transformation of Road Transport Systems: Are We Ready for the Next Step in Artificially Intelligent Sustainable Transport?

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