A Study on The Relationship Between Driver Expectancy and Variable Speed Limit Under the Adverse Weather Conditions By Using A Driving Simulator

In 2015, the U.S. Department of Transportation (U.S. DOT) selected Wyoming as one of three sites to develop, test, and deploy a suite of connected vehicle (CV) applications on a 402-mi Interstate 80 corridor. One of the Wyoming’s key CV applications is the variable speed limit (VSL) warning, which aimed to provide commercial truck drivers with real-time regulatory and advisory speed limits to help in better managing speeds under adverse weather conditions, and reducing potential speed variances that may cause traffic collisions. This paper developed a driving simulator testbed to assess the impact of the Wyoming’s CV-based VSL (CV-VSL) application on truck drivers’ behavior under adverse weather conditions. A total of 18 professional truck drivers were recruited to participate in the driving simulator experiment. Participants’ instantaneous speeds at various locations were collected to reveal the impact of the CV-VSL warnings on their driving behavior. Simulation results showed that when the advisory speed limits were lower than 55 mph, participants generally followed the VSLs displayed on the CV human–machine interface (HMI). In addition, traffic flows utilizing CV-VSL technology tend to exhibit lower average speeds and speed variances compared with baseline scenarios. These effects of CV-VSL warnings can bring potential safety benefits, as reduction in average speeds and speed variances are effective surrogate measures of safety, that is, lower risk of crashes, under adverse weather conditions.

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Safety Effectiveness of Variable Speed Limit System in Adverse Weather Conditions on Challenging Roadway Geometry

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2521-05 ◽

2015 ◽

Vol 2521 (1) ◽

pp. 45-53 ◽

Cited By ~ 10

Author(s):

Promothes Saha ◽

Mohamed M. Ahmed ◽

Rhonda Kae Young

Keyword(s):

Quantitative Measure ◽

Weather Conditions ◽

Speed Limit ◽

Variable Speed ◽

Variable Speed Limit ◽

Explanatory Variables ◽

Safety Performance Function ◽

Distinct Variable ◽

Adverse Weather Conditions ◽

Adverse Weather

This paper examined the interaction between roadway geometric characteristics and adverse weather conditions and their impact on crash occurrence on rural variable speed limit freeway corridors through mountainous terrain. As a quantitative measure of the effect of geometrics in adverse weather conditions, a crash frequency safety performance function that used generalized linear regression was developed with explanatory variables including snow, ice, frost, wind, horizontal curvature, and steep grades. This research concluded that the interaction between grades and horizontal curves with weather variables had a significant impact on crash occurrence. The research suggested that distinct variable speed limit strategies should be implemented on segments with challenging roadway geometry.

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A study of the relationship between adverse weather conditions and flight delay

Journal of Advances in Technology and Engineering Research ◽

10.20474/jater-2.4.2 ◽

2016 ◽

Vol 2 (4) ◽

Keyword(s):

Weather Conditions ◽

Adverse Weather Conditions ◽

Adverse Weather ◽

Flight Delay ◽

The Relationship

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Influence of adverse weather on drivers’ perceived risk during car following based on driving simulations

Journal of Modern Transportation ◽

10.1007/s40534-019-00197-4 ◽

2019 ◽

Vol 27 (4) ◽

pp. 282-292 ◽

Cited By ~ 2

Author(s):

Chen Chen ◽

Xiaohua Zhao ◽

Hao Liu ◽

Guichao Ren ◽

Xiaoming Liu

Keyword(s):

Perceived Risk ◽

Traffic Accidents ◽

Driving Simulator ◽

Weather Conditions ◽

Entropy Weight ◽

Car Following ◽

Adverse Weather Conditions ◽

Adverse Weather ◽

Entropy Weight Method ◽

Four Levels

Abstract Adverse weather has a considerable impact on the behavior of drivers, which puts vehicles and drivers in hazardous situations that can easily cause traffic accidents. This research examines how drivers’ perceived risk changes during car following under different adverse weather conditions by using driving simulation experiment. An expressway road scenario was built in a driving simulator. Eleven types of weather conditions, including clear sky, four levels of fog, four levels of rain and two levels of snow, were designed. Furthermore, to simulate the car-following behavior, three car-following situations were designed according to the motion of the lead car. Seven car-following indicators were extracted based on risk homeostasis theory. Then, the entropy weight method was used to integrate the selected indicators into an index to represent the drivers’ perceived risk. Multiple linear regression was applied to measure the influence of adverse weather conditions on perceived risk, and the coefficients were considered as indicators. The results demonstrate that both the weather conditions and road type have significant effects on car-following behavior. Drivers’ perceived risk tends to increase with the worsening weather conditions. Under conditions of extremely poor visibility, such as heavy dense fog, the measured drivers’ perceived risk is low due to the difficulties in vehicle operation and limited visibility.

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An Analysis on Compliance of Variable Speed Limit under Foggy Conditions using Driving Simulator

The Journal of The Korea Institute of Intelligent Transport Systems ◽

10.12815/kits.2017.16.2.116 ◽

2017 ◽

Vol 16 (2) ◽

pp. 116-127 ◽

Cited By ~ 1

Author(s):

Soullam Kim ◽

◽

Sukki Lee ◽

Yongseok Kim

Keyword(s):

Driving Simulator ◽

Speed Limit ◽

Variable Speed ◽

Variable Speed Limit

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Proactive Strategy for Variable Speed Limit Operations on Freeways Under Foggy Weather Conditions

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2551-04 ◽

2016 ◽

Vol 2551 (1) ◽

pp. 29-36 ◽

Cited By ~ 8

Author(s):

Saerona Choi ◽

Cheol Oh

Keyword(s):

Weather Conditions ◽

Speed Limit ◽

Variable Speed ◽

Variable Speed Limit

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Safety Performance Assessment of Connected Vehicles in Mitigating the Risk of Secondary Crashes: A Driving Simulator Study

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/03611981211027881 ◽

2021 ◽

pp. 036119812110278

Author(s):

Sherif M. Gaweesh ◽

Arash Khoda Bakhshi ◽

Mohamed M. Ahmed

Keyword(s):

Driving Simulator ◽

Weather Conditions ◽

Safety Performance ◽

Operating Speed ◽

Connected Vehicle ◽

The Road ◽

Adverse Weather Conditions ◽

Adverse Weather ◽

Traffic Volumes ◽

Secondary Crashes

Traffic crashes can be divided into primary and secondary crashes. Secondary crashes occur as a consequence of primary crashes within their spatiotemporal distances. Secondary crashes comprise nearly 20% of all crashes and 18% of fatal crashes, in which they can possibly have a higher crash severity than the primary crash. Interstate-80 in Wyoming is a major rural corridor with a high freight traffic volumes. The Federal Highway Administration selected Wyoming in which to deploy connected vehicle (CV) technology with a focus on commercial truck safety. Distress and rerouting applications were among the suite of CV pilot applications. Very few studies have investigated the safety performance of CVs in mitigating the risk of secondary crashes on heavy trucks, more specifically under adverse weather conditions. This study filled this gap by conducting a driving simulator experiment to assess the effectiveness of CV distress and rerouting applications in mitigating the effects of secondary crashes. A total of 23 truck drivers were recruited to this study. The analysis was conducted on the vehicle kinematics obtained from the driving simulator. A CV and a nonCV scenario were designed to compare the participants’ driving behavior under adverse weather conditions. The results showed that the tested CV applications succeeded in enhancing driving behaviors by reducing the operating speed as well as the speed variation, and all the participants avoided a secondary crash in the CV environment. In addition, the distress notification coupled with the road closure reduced the average operating speed by 26% from the provided speed limit.

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REVIEW OF TRAFFIC DATA COLLECTION METHODS FOR DRIVERS’ CAR – FOLLOWING BEHAVIOUR UNDER VARIOUS WEATHER CONDITIONS

Jurnal Teknologi ◽

10.11113/jt.v78.7996 ◽

2016 ◽

Vol 78 (4) ◽

Author(s):

Mey Shariff ◽

Othman Che Puan ◽

Nordiana Mashros

Keyword(s):

Data Collection ◽

Driving Simulator ◽

Weather Conditions ◽

Traffic Data ◽

Car Following ◽

Advantages And Disadvantages ◽

Adverse Weather Conditions ◽

Traffic Data Collection ◽

Comparative Review ◽

Adverse Weather

Adverse weather conditions have considerable impact on traffic operation and safety as it affects drivers’ car-following behaviour. However, the quality of traffic data and its related methodologies to address these effects are under continuous enhancement. This paper intends to provide an overview of various empirical traffic data collection methodologies widely used to investigate drivers car-following behaviour under various weather conditions. These methodologies include video cameras, pneumatic tubes, floating car data, instrumented vehicle and driving simulator. Moreover, the advantages and disadvantages related to methodologies have been discussed with emphasis on their suitability to work under adverse weather conditions. Furthermore, conclusion also comprises on table format of comparative review of facilities concerned with the methodologies.

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A national retrospective study of the association between serious operational problems and COVID-19 specific intensive care mortality risk

PLoS ONE ◽

10.1371/journal.pone.0255377 ◽

2021 ◽

Vol 16 (7) ◽

pp. e0255377

Author(s):

Harrison Wilde ◽

John M. Dennis ◽

Andrew P. McGovern ◽

Sebastian J. Vollmer ◽

Bilal A. Mateen

Keyword(s):

Intensive Care ◽

Weather Conditions ◽

Credible Interval ◽

Bayesian Hierarchical ◽

Adverse Weather Conditions ◽

Trust Level ◽

Adverse Weather ◽

The Relationship ◽

Overall Mortality

Objectives To describe the relationship between reported serious operational problems (SOPs), and mortality for patients with COVID-19 admitted to intensive care units (ICUs). Design English national retrospective cohort study. Setting 89 English hospital trusts (i.e. small groups of hospitals functioning as single operational units). Patients All adults with COVID-19 admitted to ICU between 2nd April and 1st December, 2020 (n = 6,737). Interventions N/A Main outcomes and measures Hospital trusts routinely submit declarations of whether they have experienced ‘serious operational problems’ in the last 24 hours (e.g. due to staffing issues, adverse weather conditions, etc.). Bayesian hierarchical models were used to estimate the association between in-hospital mortality (binary outcome) and: 1) an indicator for whether a SOP occurred on the date of a patient’s admission, and; 2) the proportion of the days in a patient’s stay that had a SOP occur within their trust. These models were adjusted for individual demographic characteristics (age, sex, ethnicity), and recorded comorbidities. Results Serious operational problems (SOPs) were common; reported in 47 trusts (52.8%) and were present for 2,701 (of 21,716; 12.4%) trust days. Overall mortality was 37.7% (2,539 deaths). Admission during a period of SOPs was associated with a substantially increased mortality; adjusted odds ratio (OR) 1.34 (95% posterior credible interval (PCI): 1.07 to 1.68). Mortality was also associated with the proportion of a patient’s admission duration that had concurrent SOPs; OR 1.47 (95% PCI: 1.10 to 1.96) for mortality where SOPs were present for 100% compared to 0% of the stay. Conclusion and relevance Serious operational problems at the trust-level are associated with a significant increase in mortality in patients with COVID-19 admitted to critical care. The link isn’t necessarily causal, but this observation justifies further research to determine if a binary indicator might be a valid prognostic marker for deteriorating quality of care.

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