Characterizing the impact of production adaptive cruise control on traffic flow: an investigation

James, Rachel; Melson, Christopher L.; Hu, Jia; Bared, Joe

doi:10.1080/21680566.2018.1540951

Cited by 34 publications

(19 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, Calvert et al (18) found initially negative effects, with positive effects only showing above a penetration rate of 70% (similar to a 75% threshold for meaningful benefit noted by Bierstedt et al [19]). However, others (20) determined that a small number of ACC vehicles, less than 25%, would be beneficial, while more than 75% harms capacity. One reason for these seemingly contradictory findings may be the underlying assumptions used.…”

mentioning

confidence: 99%

“…One reason for these seemingly contradictory findings may be the underlying assumptions used. This has been amply illustrated by James et al (20) who also examined how these results varied through the use of four different controller models gleaned from field trials. While the controllers themselves were found to vary minimally, the use of differing parameter settings within these functional forms was found to cause simulated capacity to vary (by + /-4% at low penetrations up to almost twice that at 100%), which, in the marginal situations to be found at lower penetrations, may mean the difference between capacity gain or capacity loss.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Microscopic Modeling of the Effects of Autonomous Vehicles on Motorway Performance

Mesionis

Brackstone

Gravett

2020

Transportation Research Record

View full text Add to dashboard Cite

Autonomous vehicles (AVs) have been the subject of extensive research in recent years and are expected to completely transform the operation of transport networks and revolutionize the automotive industry in the coming decades. Modeling detailed interactions among vehicles with varying levels of penetration rates is essential for evaluating the potential effects. One such investigation is being performed within the ‘HumanDrive’ Project in the U.K. This work has required the development of a behavioral model that incorporates microscopic level interactions and has been based on a pre-existing adaptive cruise control and lane-changing model that has been adapted to better replicate the limitations of AVs and allow the investigation of differing levels of intelligence or assertiveness. The model has been implemented on the M1 Motorway near Sheffield in the U.K. This has allowed the investigation of the effects of AVs on the operation of a real network under various traffic conditions where the overall effects may be revealed, both as advantages to AV drivers, and potentially disadvantages to non-AV traffic. Additionally, it has been possible to examine how these affect junction operations and net emissions. Preliminary results have allowed us to quantify the positive effects of AVs which increase with the penetration. However, it is clear that there are points of inflection where benefits start to slow. It is at these (high) penetration rates that initial operational assumptions may become increasingly stretched and additional infrastructure and cooperative systems are likely to have to become prevalent.

show abstract

mentioning

confidence: 99%

mentioning

confidence: 99%

Microscopic Modeling of the Effects of Autonomous Vehicles on Motorway Performance

Mesionis

Brackstone

Gravett

2020

Transportation Research Record

View full text Add to dashboard Cite

show abstract

“…According to Equations (14) and (24), the tra c ow stability distribution is shown in Figures 4(a) and 4(b), respectively. In Figure 4(a), the space above the neutral stable surface is the stable space, and the space below is the unstable space.…”

Section: Journal Of Advanced Transportationmentioning

confidence: 99%

“…With the development of connected vehicles (CVs), research on tra c ow theory has gradually evolved from traditional tra c ow modeling to connected tra c ow [10][11][12][13][14][15][16]. A CV can share its status (e.g., position, speed, and acceleration) with other CVs within a certain range via vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) communication.…”

Section: Introductionmentioning

confidence: 99%

Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect

Hui

Liu

et al. 2020

Journal of Advanced Transportation

View full text Add to dashboard Cite

The existing model of sudden acceleration changes, referred to as the traffic jerk effect, is mostly based on theoretical hypotheses, and previous research has mainly focused on traditional traffic flow. To this end, this paper investigates the change in the traffic jerk effect between inactive and active vehicle-to-vehicle (V2V) communications based on field experimental data. Data mining results show that the correlation between the jerk effect and the driving behavior increases by 50.6% on average when V2V messages are received. In light of the data analysis results, a new car-following model is proposed to explore the jerk effect in a connected environment. The model parameters are calibrated, and the results show that the standard deviation between the new model simulation data and the observed data decreases by 38.2% compared to that of the full velocity difference (FVD) model. Linear and nonlinear analyses of the calibrated model are then carried out to evaluate the connected traffic flow stability. Finally, the theoretical analysis is verified by simulation experiments. Both the theoretical and simulation results show that the headway amplitude and velocity fluctuations are reduced when considering the jerk effect in a connected environment, and the traffic flow stability is improved.

show abstract

“…Thus, a critical question is investigating the penetration effect of CAVs under mixed traffic conditions. It is beneficial to the promotions and applications of CAVs by understanding their penetration effect, which helps us to find a transitional solution under mixed traffic [8].…”

Section: Introductionmentioning

confidence: 99%

Penetration effect of connected and automated vehicles on cooperative on‐ramp merging

Ding

Peng

Zhang

et al. 2019

IET Intelligent Transport Systems

View full text Add to dashboard Cite

Characterizing the impact of production adaptive cruise control on traffic flow: an investigation

Cited by 34 publications

References 17 publications

Microscopic Modeling of the Effects of Autonomous Vehicles on Motorway Performance

Microscopic Modeling of the Effects of Autonomous Vehicles on Motorway Performance

Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect

Penetration effect of connected and automated vehicles on cooperative on‐ramp merging

Contact Info

Product

Resources

About