Microsimulation of energy and flow effects from optimal automated driving in mixed traffic

Ard, Tyler; Dollar, Robert Austin; Vahidi, Ardalan; Zhang, Yao-Zhong; Karbowski, Dominik

doi:10.1016/j.trc.2020.102806

Cited by 35 publications

(14 citation statements)

References 33 publications

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“…The benefits of connectivity are further exploited by traffic control strategies. Simulation of (1,3,14) with ATC controller (18) in Example 3 is shown in Fig. 1(c).…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Controlling vehicles to drive smoothly achieves significant benefits in energy efficiency, safety and passenger comfort [19,22,70]. While vehicle control guarantees benefits for the individual AVs only, a sufficient number of well-designed AVs may positively influence traffic at large and mitigate traffic jams due to their smooth driving behavior [1,2,15,49]. The influence of vehicle control on traffic is demonstrated in Fig.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Virtual Rings on Highways: Traffic Control by Connected Automated Vehicles

Molnár¹,

Hopka²,

Upadhyay³

et al. 2022

Preprint

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This work gives introduction to traffic control by connected automated vehicles. The influence of vehicle control on vehicular traffic and traffic control strategies are discussed and compared. It is highlighted that vehicle-to-everything connectivity allows connected automated vehicles to access the state of the traffic behind them such that feedback can be utilized to mitigate evolving congestions. Numerical simulations demonstrate that such connectivity-based traffic control is beneficial for smoothness and energy efficiency of highway traffic. The dynamics and stability of traffic flow, under the proposed controllers, are analyzed in detail to construct stability charts that guide the selection of stabilizing control gains.

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“…The benefits of connectivity are further exploited by traffic control strategies. Simulation of (1,3,14) with ATC controller (18) in Example 3 is shown in Fig. 1(c).…”

Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Virtual Rings on Highways: Traffic Control by Connected Automated Vehicles

Molnár¹,

Hopka²,

Upadhyay³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Calibration and validation of the model represents a fundamental phase of microsimulation process, due to the fact that it ensure result validity [20,21]; therefore, it is typically characterized by following phases: Considering that data uploaded into the model are aggregate values (time-based station detected traffic flow, input capacity), in order to obtain model validation, the GEH statistic was used. GEH is a modified chi-squared statistic that incorporates both relative and absolute differences to compare modeled and observed traffic volumes.…”

Section: Calibration Of the Modelmentioning

confidence: 99%

Managed Lane as Strategy for Traffic Flow and Safety: A Case Study of Catania Ring Road

et al. 2022

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According to international traffic statistics, the quantity of daily traveling vehicles amounts to one billion, and it is estimated that in 2050 that amount will reach four billion. Urban population is growing especially in large metropolitan areas. This increase has different outgrowths concerning regular circulation, safety, and climatic perspectives. Therefore, the present and further increase of traffic flow is affecting the operational and safety performance of several roadway categories. Urban ring roads belong to a roadway category that is particularly subjected to congestion phenomena, but in many cases, public administrations are unable to afford required expenses to upgrade or build new roadways. Therefore, an intervention is needed that increases the capacity of existing infrastructures with limited cost results to be fundamental. In such a framework, the dynamic use of hard shoulder running (HSR) would represent a valid solution that both exploits existing infrastructures and facilitates traffic outflow by implementation of smart digital roads, with limited interventions on the physical infrastructure. Despite the expected improvements in traffic capacity, the HSR poses safety issues particularly in specific locations (e.g., interchanges) and for the operation of the transition phase for opening and closing the HSR. In this paper, the applicability and usefulness of microsimulation were tested with the Catania (Italy) ring road, as a case study, through the application of VISSIM traffic microsimulation software and SSAM traffic conflict tool, implementing different scenarios for the activation of the HSR.

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“…It is observed that researchers applied numerous logic systems/algorithms, including adaptive dynamic programming [97], optimization-based ramp control strategy [70], Virdi CAV Control Protocol [99], decision-making CAV control algorithm [75], Model Predictive Control [100], Autonomous intersection management [107], Platooning Extension Plexe [108], cooperative scheduling mechanism for CAVs [110], discrete-time occupancies trajectory-based intersection traffic coordination algorithm [113], lane sorting [114], matrix-based intersection management logic [116], and Cooperative Controller and Distributed Algorithm [72].…”

Section: Av Modeling By Externalitiesmentioning

confidence: 99%

Evolution of Traffic Microsimulation and Its Use for Modeling Connected and Automated Vehicles

Raju

Farah

2021

Journal of Advanced Transportation

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Traffic microsimulation has a functional role in understanding the traffic performance on the road network. This study originated with intent to understand traffic microsimulation and its use in modeling connected and automated vehicles (CAVs). Initially, the paper focuses on understanding the evolution of traffic microsimulation and on examining the various commercial and open-source simulation platforms available and their importance in traffic microsimulation studies. Following this, current autonomous vehicle (AV) microsimulation strategies are reviewed. From the review analysis, it is observed that AVs are modeled in traffic microsimulation with two sets of strategies. In the first set, the inbuilt models are used to replicate the driving behavior of AVs by adapting the models’ parameters. In the second strategy, AV behavior is programmed with the help of externalities (e.g., Application Programming Interface (API)). Studies simulating AVs with inbuilt models used mostly VISSIM compared to other microsimulation platforms. In addition, the studies are heavily focused on AVs’ penetration rate impact on traffic flow characteristics and traffic safety. On the other hand, studies which simulated AVs with externalities focused on the communication aspects for traffic management. Finally, the cosimulation strategies for simulating the CAVs are explored, and the ongoing research attempts are discussed. The present study identifies the limitations of present CAV microsimulation studies and proposes prospects and improvements in modeling AVs in traffic microsimulation.

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Microsimulation of energy and flow effects from optimal automated driving in mixed traffic

Cited by 35 publications

References 33 publications

Virtual Rings on Highways: Traffic Control by Connected Automated Vehicles

Virtual Rings on Highways: Traffic Control by Connected Automated Vehicles

Managed Lane as Strategy for Traffic Flow and Safety: A Case Study of Catania Ring Road

Evolution of Traffic Microsimulation and Its Use for Modeling Connected and Automated Vehicles

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