How do the recognizability and driving styles of automated vehicles affect human drivers’ gap acceptance at T- Intersections?

Reddy, Nagarjun; Hoogendoorn, Serge P.; Farah, Haneen

doi:10.1016/j.trf.2022.09.018

Cited by 14 publications

(2 citation statements)

References 28 publications

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“…The coexistence and interaction of AVs and HVs was investigated as well in [50], through a field test conducted on 18 participants, focusing on gap acceptance, car-following, and overtaking behaviors, showing that drivers interacting with recognizable AVs adopt smaller critical gaps, and after overtaking, merge closer in front of those. The work in [51] is devoted to understanding HVs behavior in mixed traffic at un-signaled priority T-intersections, through a driving simulator experiment on 95 human drivers, whose findings suggest that human drivers change their gap acceptance behavior in mixed traffic depending on AVs recognizability and driving style. Finally, the authors of [52] aimed at quantifying the behavioral changes caused by human drivers following either an AV or an HV, and their impact on safety, fuel consumption and pollution, by analyzing data from a field experiment on 9 drivers.…”

Section: A Avs-hvs Interactionmentioning

confidence: 99%

Autonomous and Human-Driven Vehicles Interacting in a Roundabout: A Quantitative and Qualitative Evaluation

Ferrarotti,

Luca,

Santin

et al. 2024

IEEE Access

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Optimizing traffic dynamics in an evolving transportation landscape is crucial, particularly in scenarios where autonomous vehicles (AVs) with varying levels of autonomy coexist with human-driven cars. While optimizing Reinforcement Learning (RL) policies for such scenarios is becoming more and more common, little has been said about realistic evaluations of such trained policies. This paper presents an evaluation of the effects of AVs penetration among human drivers in a roundabout scenario, considering both quantitative and qualitative aspects. In particular, we learn a policy to minimize traffic jams (i.e., minimize the time to cross the scenario) and to minimize pollution in a roundabout in Milan, Italy. Through empirical analysis, we demonstrate that the presence of AVs can reduce time and pollution levels. Furthermore, we qualitatively evaluate the learned policy using a cutting-edge cockpit to assess its performance in nearreal-world conditions. To gauge the practicality and acceptability of the policy, we conduct evaluations with human participants using the simulator, focusing on a range of metrics like traffic smoothness and safety perception. In general, our findings show that human-driven vehicles benefit from optimizing AVs dynamics. Also, participants in the study highlight that the scenario with 80% AVs is perceived as safer than the scenario with 20%. The same result is obtained for traffic smoothness perception.

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Section: A Avs-hvs Interactionmentioning

confidence: 99%

Autonomous and Human-Driven Vehicles Interacting in a Roundabout: A Quantitative and Qualitative Evaluation

Ferrarotti,

Luca,

Santin

et al. 2024

IEEE Access

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“…In the afternoon, the probability of 18 veh/m is 0.18. This study is important to evaluate the density behavior throughout survey as it can be used in simulation models [39][40][41]. The stochastic fundamental diagram is based on speed-density data [42].…”

Section: Parameter Statisticsmentioning

confidence: 99%

Modeling Sustainable Traffic Behavior: Avoiding Congestion at a Stationary Bottleneck

Badshah

Khan²,

Gulliver³

et al. 2022

Civ Eng J

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Sustainable traffic behaviour is increasing in importance as traffic volume rises due to population growth. In this paper, a model for traffic flow at a stationary bottleneck is developed to determine the parameters that cause congestion. Towards this goal, traffic density, speed, and delay were acquired during peak and off-peak periods in the morning and afternoon at a stationary bottleneck in Peshawar, KPK, Pakistan. The morning and afternoon peak periods have high densities, low speeds, and considerable delays. Regression models are developed using this data. These results indicate that there is a linear relationship between density and time at the stationary bottleneck and a negative linear relationship between density and speed. Thus, an increase in density increases the time delay and reduces the speed. I comprehensive traffic delay model is characterized by a stationary bottleneck. The Kolmogorov-Smirnov (KS) test and P-values were used to identify the best-fit distribution for speed and density. The binomial and generalized extreme values are considered the best fits for density and speed. The results presented can be used to develop accurate simulation models for stationary bottlenecks to reduce congestion. Doi: 10.28991/CEJ-2022-08-11-02 Full Text: PDF

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Evaluation of Human Interaction with Fleets of Automated Vehicles in Dynamic Underground Mining Environments

Mironenko,

Banaee,

Loutfi

2024

Communications in Computer and Information Science

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How do the recognizability and driving styles of automated vehicles affect human drivers’ gap acceptance at T- Intersections?

Cited by 14 publications

References 28 publications

Autonomous and Human-Driven Vehicles Interacting in a Roundabout: A Quantitative and Qualitative Evaluation

Autonomous and Human-Driven Vehicles Interacting in a Roundabout: A Quantitative and Qualitative Evaluation

Modeling Sustainable Traffic Behavior: Avoiding Congestion at a Stationary Bottleneck

Evaluation of Human Interaction with Fleets of Automated Vehicles in Dynamic Underground Mining Environments

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