Connected vehicle real-time traveler information messages for freeway speed harmonization under adverse weather conditions: Trajectory level analysis using driving simulator

2020 ◽  
Vol 146 ◽  
pp. 105707 ◽  
Author(s):  
Guangchuan Yang ◽  
Mohamed Ahmed ◽  
Sherif Gaweesh ◽  
Eric Adomah
Keyword(s):  
Real Time ◽  
Driving Simulator ◽  
Weather Conditions ◽  
Connected Vehicle ◽  
Traveler Information ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
Time Traveler ◽  
Level Analysis ◽  
Speed Harmonization

Impact of Variable Speed Limit in a Connected Vehicle Environment on Truck Driver Behavior under Adverse Weather Conditions: Driving Simulator Study

2019 ◽  
Vol 2673 (7) ◽  
pp. 132-142 ◽  
Author(s):  
Guangchuan Yang ◽  
Mohamed M. Ahmed ◽  
Sherif Gaweesh
Keyword(s):  
Driving Simulator ◽  
Weather Conditions ◽  
Truck Drivers ◽  
Connected Vehicle ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
Advisory Speed ◽  
The Impact

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.

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

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.

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

2019 ◽  
Vol 27 (4) ◽  
pp. 282-292 ◽  
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.

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

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.  

Use of a Driving Simulator to Assess Performance under Adverse Weather Conditions in Adults with Albinism

2012 ◽  
Vol 114 (2) ◽  
pp. 679-692 ◽  
Author(s):  
Gwen M. Hofman ◽  
Nicholas Ward ◽  
C. Gail Summers ◽  
Esha Bhargav ◽  
Michael E. Rakauskas ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Weather Conditions ◽  
Adverse Weather Conditions ◽  
Adverse Weather
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