The impact of autonomous vehicles on urban traffic network capacity: an experimental analysis by microscopic traffic simulation

Lu, Qiong; Tettamanti, Tamás; Hörcher, Dániel; Varga, István

doi:10.1080/19427867.2019.1662561

Cited by 106 publications

(90 citation statements)

References 24 publications

(32 reference statements)

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“…Macro traffic models have been used to show that traffic capacity would be increased up to 36% if all vehicles were automated. A different study from Lu et al (2019) has found similar figures (23% increase of capacity) but using traffic micro simulation.…”

Section: And What's About the Impact Of Cavs On Traffic?mentioning

confidence: 62%

Are Connected and Automated Vehicles the Silver Bullet for Future Transportation Challenges? Benefits and Weaknesses on Safety, Consumption, and Traffic Congestion

Gruyer

Orfila

Glaser

et al. 2021

Front. Sustain. Cities

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With the growing development of Cooperative, Connected, and Automated Mobility (CCAM), questions arise about the real impact of this innovative mobility on our daily life. CCAM originally promised to improve road safety. It is now a holistic solution for future mobility: the CCAM is there to optimize traffic, which can translate into strategies for reducing energy consumption or polluting emissions, without compromising road safety. The capability of CCAM is dependent on the reliability and robustness of its components, as it will be making life-impacting decisions. It is therefore necessary to be able to guarantee a high-level quality of sensors, communication, software, and hardware architecture. In this mobility ecosystem, the infrastructure and data that it will be able to produce is at the heart of current research issues. This paper addresses the following question: Are the Connected and automated Vehicles (CAVs) the silver bullet solution with which to answer the issues of the current mobility systems? This question is discussed by investigating the technologies used, the digital infrastructures, its robustness to cyber-attack, and their relationship with the claimed benefits on safety, energy and pollution management, traffic optimization, deployment strategy, and a link with the new generation of road infrastructures.

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Section: And What's About the Impact Of Cavs On Traffic?mentioning

confidence: 62%

Are Connected and Automated Vehicles the Silver Bullet for Future Transportation Challenges? Benefits and Weaknesses on Safety, Consumption, and Traffic Congestion

Gruyer

Orfila

Glaser

et al. 2021

Front. Sustain. Cities

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show abstract

“…The challenges of urbanisation, if unmet urgently, would entail grave economic and environmental impacts [43]. FAGVs are expected to improve mobility and traffic conditions in cities [94]. Therefore, it is urgent to develop FAGVs integrated with SC to address those challenges and improve our daily commute.…”

Section: Resultsmentioning

confidence: 99%

A Framework for the Synergistic Integration of Fully Autonomous Ground Vehicles With Smart City

Kuru

Khan

2021

IEEE Access

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“…This equation is only valid for freeways, whereas equations for multi-lane highways, signalized highways and other road types can be found in HCM2016 [43]. It is worth mentioning that the spread of autonomous vehicle will change the capacity formula in the future because the throughput of road segments will be increased due to better resource utilization [44], [45], [46].…”

Section: Flow-speed Ratio-based Congestion Definitionmentioning

confidence: 99%

Traffic congestion propagation identification method in smart cities

Nagy¹,

Simon²

2021

Infocommunications journal

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Managing the frequent traffic congestion (traffic jams) of the road networks of large cities is a major challenge for municipal traffic management organizations. In order to manage these situations, it is crucial to understand the processes that lead to congestion and propagation, because the occurrence of a traffic jam does not merely paralyze one street or road, but could spill over onto the whole vicinity (even an entire neighborhood). Solutions can be found in professional literature, but they either oversimplify the problem, or fail to provide a scalable solution. In this article, we describe a new method that not only provides an accurate road network model, but is also a scalable solution for identifying the direction of traffic congestion propagation. Our method was subjected to a detailed performance analysis, which was based on real road network data. According to testing, our method outperforms the ones that have been used to date.

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The impact of autonomous vehicles on urban traffic network capacity: an experimental analysis by microscopic traffic simulation

Cited by 106 publications

References 24 publications

Are Connected and Automated Vehicles the Silver Bullet for Future Transportation Challenges? Benefits and Weaknesses on Safety, Consumption, and Traffic Congestion

Are Connected and Automated Vehicles the Silver Bullet for Future Transportation Challenges? Benefits and Weaknesses on Safety, Consumption, and Traffic Congestion

A Framework for the Synergistic Integration of Fully Autonomous Ground Vehicles With Smart City

Traffic congestion propagation identification method in smart cities

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