Microscopic Modeling of the Effects of Autonomous Vehicles on Motorway Performance

Mesionis, George; Brackstone, Mark; Gravett, Natalie

doi:10.1177/0361198120949243

Cited by 11 publications

(7 citation statements)

References 23 publications

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“…This may explain the slightly higher improvements achieved in throughput, delay and speed of ACC vehicles with a headway range at 50% penetration as opposed to 100% penetration. This was similarly reported by the authors in [31] concluding their study by the observation that AVs appear to provide more benefits in congested situations than in free flow situations as a result of lower speed acceptance.…”

Section: Shladover-based Acc Simulation Resultssupporting

confidence: 79%

Quantitative Evaluation of the Impacts of the Time Headway of Adaptive Cruise Control Systems on Congested Urban Freeways Using Different Car Following Models and Early Control Results

Elmorshedy

Abdulhai

Kamel

2022

IEEE Open J. Intell. Transp. Syst.

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The impact of driving automation and adaptive cruise control (ACC) on traffic performance has been increasingly studied in recent years. This paper focuses on two widely used ACC car following models and investigates the impact of the time headway parameter on traffic operation and performance on one of the busiest freeway corridors in Ontario, Canada. Using Aimsun microsimulation, we compare two commonly used ACC car following models; the intelligent driver model (IDM) and Shladover's model which has been recently adopted in Aimsun Next 20. Several experiments have been conducted to evaluate the freeway performance for different desired headway settings and market penetration rates of ACC-equipped vehicles. Simulations results confirm the reported IDM drawbacks of having a slow response leading to headway errors which are less pronounced with Shladover's model thereby leading to more accurate quantification by the latter. This study further presents a simple on-off ACC-based traffic control strategy which aims to adapt in real time the driving behavior of ACC-equipped vehicles to the prevailing traffic conditions so that freeway performance is improved. The simulation results demonstrate that, even for low penetration rates of ACC vehicles, the proposed control concept improves the average network throughput, delay, and speed compared to the case of only manually driven or uncontrolled ACC vehicles.INDEX TERMS Adaptive cruise control systems, traffic control, traffic modeling.

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Section: Shladover-based Acc Simulation Resultssupporting

confidence: 79%

Quantitative Evaluation of the Impacts of the Time Headway of Adaptive Cruise Control Systems on Congested Urban Freeways Using Different Car Following Models and Early Control Results

Elmorshedy

Abdulhai

Kamel

2022

IEEE Open J. Intell. Transp. Syst.

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“…Based on the selected parameter values for AVs, the AV type can be characterized as aggressive. For a detailed description of the aforementioned models and parameters, see Mesionis et al ( 23 ).…”

Section: Methodsmentioning

confidence: 99%

Autonomous Vehicles in Urban Networks: A Simulation-Based Assessment

Tympakianaki¹,

Nogués²,

Casas³

et al. 2022

Transportation Research Record: Journal of the Transportation R

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The paper proposes a general framework for the assessment of the impacts of the introduction of Connected and Automated Transport Systems (CATS) on traffic. The main objective is to address the question of scalability and transferability of the identified impacts of Autonomous Vehicles (AVs) in particular, focusing on network performance of urban areas. A combination of microscopic and macroscopic simulations as well as statistical methods are applied. Microscopic simulation is conducted to measure the changes in network capacities by utilizing the concept of the Macroscopic Fundamental Diagram (MFD), under different AV penetration rates. The resulting capacities are used to estimate the effects on the Passenger Car Units (PCU) under different AV penetration rates and derive functional relationships, which are further introduced to travel demand models to forecast the macroscopic impacts on network performance. The results indicate a positive impact in relation to capacity changes resulting from the presence of AVs which vary with penetration rate. Analysis of three different urban networks, Barcelona, Bilbao (Spain), and Athens (Greece), reveals consistent trends. However, notable differences are observed on the estimated PCUs for Athens, potentially because of the different mixed-traffic composition. Further exploration of the critical AV modeling specifications and network characteristics is therefore required for deriving transferable PCU functional relationships across networks. Nevertheless, the static assignment results verify the expected trends in network performance impacts in relation to the applied PCU relationships. Finally, the transferability of the proposed methodology across networks is demonstrated.

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“…Zhang et al [22] used a value of 0.5 s while simulating CAVs with an external driver model extension. Other studies that have used the Aimsun Next platform assumed that CAVs should react within 0.1 s [20,21]. In a sensitivity analysis study, Xie et al [19] applied different values (2.0, 1.5, 1.0, 0.5, and 0.0 s for CAV levels from Level 0 to Level 4, respectively).…”

Section: Literature Reviewmentioning

confidence: 99%

“…However, the value reported by Zhang et al [22] for CAVs is lower than that for human driving. Regarding the maximum deceleration, it was assumed to be the same for humans and autonomous driving in several studies (e.g., [9,11,[18][19][20][21][22][23]). They explained that it should not be affected by technology; it is the capacity of the vehicle's motor, which is an extreme value that is followed within both cases with the same magnitude [18].…”

Section: Literature Reviewmentioning

confidence: 99%

“…These values are specified as a range in the Aimsun model to randomise the behaviour. Different values have been assumed in the Aimsun calibration of CAV studies (1.25, 1.5 [21], 1-1.25, and 1.1-1.3 [25]). Since CAVs are expected to exhibit high cooperation during lane-changing, the values in both studies are higher than the human driving range for both cautious and aggressive driving styles.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Traffic Safety Sensitivity Analysis of Parameters Used for Connected and Autonomous Vehicle Calibration

Miqdady

Oña

2023

Sustainability

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Recently, the number of traffic safety studies involving connected and autonomous vehicles (CAVs) has been increasing. Due to the lack of information regarding the real behaviour of CAVs in mixed traffic flow, traffic simulation platforms are used to provide a reasonable approach for testing various scenarios and fleets. It is necessary to analyse how traffic safety is affected when key parameter assumptions are changed. The current study conducts a sensitivity analysis to identify the parameters used in CAV calibration that have the highest influence on traffic safety. Using a microsimulation-based surrogate safety assessment model approach (SSAM), traffic conflicts were identified, and a ceteris paribus analysis was conducted to measure the effect of gradually changing each parameter on the number of conflicts. Afterwards, a two-at-a-time sensitivity analysis was performed to explore the influence of simultaneously varying two parameters. The results revealed that reaction time, clearance, maximum acceleration, normal deceleration, and the sensitivity factor are key parameters. Studying these parameters two at a time revealed that low maximum acceleration, when combined with other parameters, consistently resulted in the highest number of conflicts, while combinations with short reaction time always yielded the best traffic safety results. This investigation broadens the understanding of CAV behaviour for future implementation for both manufacturers and researchers.

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Microscopic Modeling of the Effects of Autonomous Vehicles on Motorway Performance

Cited by 11 publications

References 23 publications

Quantitative Evaluation of the Impacts of the Time Headway of Adaptive Cruise Control Systems on Congested Urban Freeways Using Different Car Following Models and Early Control Results

Quantitative Evaluation of the Impacts of the Time Headway of Adaptive Cruise Control Systems on Congested Urban Freeways Using Different Car Following Models and Early Control Results

Autonomous Vehicles in Urban Networks: A Simulation-Based Assessment

Traffic Safety Sensitivity Analysis of Parameters Used for Connected and Autonomous Vehicle Calibration

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