The influence of combined alignments on lateral acceleration on mountainous freeways: a driving simulator study

Wang, Xuesong; Wang, Ting; Tarko, Andrew P.; Tremont, Paul J.

doi:10.1016/j.aap.2015.01.003

Cited by 65 publications

(32 citation statements)

References 14 publications

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“…Besides, since the objective of this paper is to explore the effects of LSRMs on driving behavior, a simulation study not only collects speed data, but also records drivers’ operating performance data, such as gas and brake pedal use, steering, and shifting gears more directly and safely, compared to field tests. Moreover, the driving simulator study could help us better control various variables, isolate other confounding factors and allow us to observe the effect of SRMs alone on vehicle status or drivers’ performance, and there are a series of current studies focusing on driving simulator method [17,18,19]. …”

Section: Introductionmentioning

confidence: 99%

Evaluation Research of the Effects of Longitudinal Speed Reduction Markings on Driving Behavior: A Driving Simulator Study

Ding

Zhao

et al. 2016

IJERPH

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The objective of this paper is to explore the effects of longitudinal speed reduction markings (LSRMs) on vehicle maneuvering and drivers’ operation performance on interchange connectors with different radii. Empirical data were collected in a driving simulator. Indicators—relative speed change, standard deviation of acceleration, and gas/brake pedal power—were proposed to characterize driving behavior. Statistical results revealed that LSRMs could reduce vehicles’ travel speed and limit drivers’ willingness to increase speed in the entire connector. To probe the impacts of LSRMs, the connecter was split into four even sections. Effects of LSRMs on driving behavior were stronger in the second and the final sections of connectors. LSRMs also enhanced drivers’ adaptability in the first three quarters of a connector when the radius was 50 m. Drivers’ gas pedal operation would be impacted by LSRMs in the entire connector when the radius was 50 m. LSRMs could only make drivers press brake pedal more frequently in the second section with 80 m and 100 m radius. In the second quarter section of a connector—from the FQP (the first quartile point) to the MC (the middle point of curve)—LSRMs have better effects on influencing vehicle maneuvering and drivers’ operation performance.

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Section: Introductionmentioning

confidence: 99%

Evaluation Research of the Effects of Longitudinal Speed Reduction Markings on Driving Behavior: A Driving Simulator Study

Ding

Zhao

et al. 2016

IJERPH

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“…Additionally, the silhouette coefficients for various numbers of clusters were calculated. e silhouette coefficients for k of 2, 3, and 4 were found to be 0.44, 0.37, (1) int r ⟵ k-means number of clusters (2) For int t � 1 to r − 1 (3) int a t ⟵ Safety entropy value of the center of the t th cluster (4) int b t ⟵ Safety entropy value of the center of the (t + 1)th cluster (5) int s t ⟵ Sum of the data in the tth and (t + 1) th clusters (6) int f � 1 (7) For float e tf � a t to b t (8) int c tf ⟵ Volume of data in the tth cluster that is misclassified (9) int d tf ⟵ Volume of data in the (t + 1)th cluster that is misclassified (10) g tf � 1 − ((c tf + d tf )/s t )//Calculation of accuracy (11) e tf � etf + 0.01 (12) B t (f, 1: 2) � [e tf , g tf ]// e threshold and accuracy are stored in the matrix B t (13) f � f + 1 (14) End for (15) C t ⟵ Generation of the threshold corresponding to the highest accuracy (16) End for (17) C � [C 1 , C 2 , . .…”

Section: Determination Of the Number Of Risk Levelsmentioning

confidence: 99%

“…Regarding establishment of road traffic safety evaluation indices based on the different characteristics of people, vehicles, road, and environment, Wang et al used an eightdegree-of-freedom driving simulator to replicate the full range of combined alignments used on a mountainous freeway in China [14]; additionally, multiple linear regression models were developed to estimate the effects of the combined alignments on the lateral acceleration. Li et al examined the effects of subjective and objective safety indices on road safety and analyzed the relationships between an objective safety index, which comprises road linearity, pavement, traffic facilities, and natural environment and road safety [15].…”

Section: Introductionmentioning

confidence: 99%

Road Traffic Safety Risk Estimation Method Based on Vehicle Onboard Diagnostic Data

Cai

Lei

Peng

et al. 2020

Journal of Advanced Transportation

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Currently, research on road traffic safety is mostly focused on traffic safety evaluations based on statistical indices for accidents. There is still a need for in-depth investigation on preaccident identification of safety risks. In this study, the correlations between high-incidence locations for aberrant driving behaviors and locations of road traffic accidents are analyzed based on vehicle OBD data. A road traffic safety risk estimation index system with road traffic safety entropy (RTSE) as the primary index and rapid acceleration frequency, rapid deceleration frequency, rapid turning frequency, speeding frequency, and high-speed neutral coasting frequency as secondary indices is established. A calculation method of RTSE is proposed based on an improved entropy weight method. This method involves three aspects, namely, optimization of the base of the logarithm, processing of zero-value secondary indices, and piecewise calculation of the weight of each index. Additionally, a safety risk level determination method based on two-step clustering (density and k-means clustering) is also proposed, which prevents isolated data points from affecting safety risk classification. A risk classification threshold calculation method is formulated based on k-mean clustering. The results show that high-incidence locations for aberrant driving behaviors are consistent with the locations of traffic accidents. The proposed methods are validated through a case study on four roads in Chongqing with a total length of approximately 38 km. The results show that the road traffic safety trends characterized by road safety entropy and traffic accidents are consistent.

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“…A study by Miaou and Lum (1993) revealed that as vertical grade increases, accidents involving trucks also increase. Wang et al (2015) developed multiple linear regression models to estimate the effects of combinations of horizontal and vertical alignments on lateral acceleration.…”

Section: Effects Of Road Alignments On Safetymentioning

confidence: 99%

Impact of combined alignments on lane departure: A simulator study for mountainous freeways

Chen¹,

Quddus²,

Wang³

2018

Transportation Research Part C: Emerging Technologies

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The influence of combined alignments on lateral acceleration on mountainous freeways: a driving simulator study

Cited by 65 publications

References 14 publications

Evaluation Research of the Effects of Longitudinal Speed Reduction Markings on Driving Behavior: A Driving Simulator Study

Evaluation Research of the Effects of Longitudinal Speed Reduction Markings on Driving Behavior: A Driving Simulator Study

Road Traffic Safety Risk Estimation Method Based on Vehicle Onboard Diagnostic Data

Impact of combined alignments on lane departure: A simulator study for mountainous freeways

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