Assess the impacts of different autonomous trucks’ lateral control modes on asphalt pavement performance

Chen, Feng; Song, Mingtao; Ma, Xiaoxiang; Zhu, Xingyi

doi:10.1016/j.trc.2019.04.001

Cited by 83 publications

(77 citation statements)

References 29 publications

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“…Michaels [15] established a model of convergence point location by analyzing the angle variation between the merged vehicle of the ramp and the rear vehicle from the main line. Feng [16] and Zhu [17] studied the impacts of vehicles' lateral control modes on asphalt pavement performance, and a framework was proposed for different conditions.…”

Section: Literature Reviewmentioning

confidence: 99%

Driving behavior and safety analysis at OSMS section for merged, one-way freeway based on simulated driving safety analysis of driving behaviour

Lyu

Cao

et al. 2020

PLoS ONE

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In order to study driving performance at the opening section of median strip (hereafter OSMS) on the freeway capacity expansion project, this study separately controlled 9 different simulated experimental scenarios of OSMS length and freeway traffic flow. 25 participants were recruited to perform 225 simulated driving tests using the driving simulator, and the analysis of variance (ANOVA) was used to analyze the driving characteristics which can represent the safety context. The results show that the safety parameters of driving are different when the length of OSMS and the traffic flow are different. When the traffic flow is low or moderate, the OSMS length can significantly affect the speed of the vehicle and the maximum values of time to collision. The higher the traffic flow, the smaller the minimum values of time headway. As the length of the OSMS decreases, the vehicles are more generally concentrated at the end of the opening area with the minimum values of time headway. The study also found that when the traffic volume is high, the impact of the OSMS length on driving performance will be weakened. In addition, the OSMS length and the traffic flow have little impact on driving comfort. Additionally, when the traffic flow is low or moderate, the opening length can significantly affect the driving behavior and safety of the vehicle. However, when the traffic volume is high, the impact of the opening length on them will be relatively weakened to some extent. Therefore, it is advised that in the case of freeways with large traffic volume, merely extending the length of the opening section does not necessarily optimize safety. Rather, the actual traffic density of the road should be carefully considered before a design length is adopted.

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Section: Literature Reviewmentioning

confidence: 99%

Driving behavior and safety analysis at OSMS section for merged, one-way freeway based on simulated driving safety analysis of driving behaviour

Lyu

Cao

et al. 2020

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…In references [19][20][21], the driver's psychological load also has a greater impact on travel time, especially at intersections [22][23][24]. For semiautonomous vehicles [25], the humanmachine sharing technology allows the driver and the OBU to share control of the vehicle, reducing the driver's psychological load [26][27][28]. In addition, intelligence, networking, and electrification have become the trend of the current automotive industry.…”

Section: Related Workmentioning

confidence: 99%

Physiological Characteristics and Nonparametric Test for Master-Slave Driving Task’s Mental Workload Evaluation in Mountain Area Highway at Night

Wang

Liu

Feng

2019

Journal of Advanced Transportation

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With the rapid development of advanced mobile intelligent terminals, driving tasks are diverse, and new tra c safety problems occur. We propose a new research on physiological characteristics and nonparametric tests for the master-slave driving task, especially for evaluation of drivers' mental workload in mountain area highway in nighttime scenario. First, we establish the experimental platform based driving simulator and design the master-slave driving task. Second, based on the physiological data and subjective evaluation for mental workload, we use statistical methods to composite the physical changes evolution analysis in a driving simulator. Finally, we nished nonparametric test of the drivers' psychological load and road test. e results show that in compassion with the daytime scenario, drivers should pay much e ort to driving skills and risk identi cation in the nighttime scenario. us, in the same driving condition, drivers should bear the higher level of mental workload, and it has been subjected to even greater pressures and intensity of emotions.

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“…Tour-based models have been developed using an optimization concept [2][3][4][5], set of rational discrete choice models [6,7], phenomenological model [8], and activity-based model concept [4,5,9,10]. Besides modeling, truck trajectory-tracking research has been attempted with various purposes to assess the impact of truck operations [11,12]. Most tour-based models are built on the decision-making process behind vehicle operations or maximizing vehicle operational utilities.…”

Section: Introductionmentioning

confidence: 99%

Tour-Based Truck Demand Modeling with Entropy Maximization Using GPS Data

You

Ritchie

2019

Journal of Advanced Transportation

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An approach is presented to determine the most likely tour distributions and model behavior for investigating drayage truck movements in a coastal region. This was done by implementing a revised form of entropy maximization based on truck tours to model and better understand drayage truck tour behavior at the San Pedro Bay Ports (SPBPs) complex in Southern California. The drayage trucks at the SPBPs have features that are distinct from other commercial trucks. The tour-based entropy maximization model proposed in this paper provides an opportunity to incorporate periodically updated GPS data collected in Southern California into a large-scale tour-based model. With the dataset, four models were estimated by cargo movement: (1) year-based, (2) low period, (3) medium period, and (4) high period models. The findings were consistent with the tour patterns varying by season and by cargo movement. Furthermore, the medium period, which represented relatively steady cargo movement, indicated a better MAPE (mean absolute percent error) than did other models. This proposed approach provides a significant advantage in that the most recent touring information obtained from advanced technologies could be directly applied to the tour-based model and subsequently used to assess various strategies.

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Assess the impacts of different autonomous trucks’ lateral control modes on asphalt pavement performance

Cited by 83 publications

References 29 publications

Driving behavior and safety analysis at OSMS section for merged, one-way freeway based on simulated driving safety analysis of driving behaviour

Driving behavior and safety analysis at OSMS section for merged, one-way freeway based on simulated driving safety analysis of driving behaviour

Physiological Characteristics and Nonparametric Test for Master-Slave Driving Task’s Mental Workload Evaluation in Mountain Area Highway at Night

Tour-Based Truck Demand Modeling with Entropy Maximization Using GPS Data

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