A study of the compliance level of connected vehicle warning information in a fog warning system based on a driving simulation

2021 ◽  
Vol 76 ◽  
pp. 215-237
Author(s):  
Xiaohua Zhao ◽  
Yufei Chen ◽  
Haijian Li ◽  
Jianming Ma ◽  
Jia Li
Keyword(s):  
Warning System ◽  
Driving Simulation ◽  
Connected Vehicle ◽  
Compliance Level

scholarly journals Overview of Intelligent Vehicle Infrastructure Cooperative Simulation Technology for IoV and Automatic Driving

2021 ◽  
Vol 12 (4) ◽  
pp. 222
Author(s):  
Zirui Ding ◽  
Junping Xiang
Keyword(s):  
Driving Simulation ◽  
Connected Vehicle ◽  
Intelligent Network ◽  
Internet Of Vehicles ◽  
New Era ◽  
Vehicle Simulation ◽  
Automatic Driving ◽  
Collaborative Simulation ◽  
Simulation Process ◽  
Intelligent Networking

This paper reviews the development of vehicle road collaborative simulation in the new era, and summarizes the simulation characteristics of two core technologies in the field of transportation after entering the era of Intelligent Networking: Internet of Vehicles technology and automatic driving technology. This paper analyzes and compares the mainstream Internet of Vehicles (IoV) simulation and automatic driving simulation platforms on the market, deeply analyzes the model-based IoV simulation, and explores a new mode of IoV simulation in the era of big data. According to the latest classification standard of automatic driving in 2020, we summarize the simulation process of automatic driving. Finally, we offer suggestions on the development directions of intelligent network-connected vehicle simulation.

scholarly journals Warning System Using Multicast Transmission for Pedestrian and Pedal-Cyclist Safety Against the Electric-Powered Driving Means in CVCN Network

2018 ◽  
Vol 7 (3.33) ◽  
pp. 139
Author(s):  
Bachyun Kim ◽  
Yoseop Woo ◽  
Iksoo Kim
Keyword(s):  
New Technology ◽  
Warning System ◽  
Artificial Noise ◽  
Connected Vehicle ◽  
Multicast Transmission ◽  
Vehicle Accidents ◽  
The Road ◽  
Vehicle Communication ◽  
Safety Warning ◽  
On The Road

This paper deals with a warning system for the safety of pedestrians/pedal-cyclists against electric-powered driving means including hybrid/PHEV/EV/FCEV and electric wheel on minor roads. These roads are a subset of connected-vehicle communication network(CVCN). The fatalities of pedestrians/pedal-cyclists declined recently compared to the early 2000s, but fatality rate of vehicle accidents is increasing. Clearly, this phenomenon will continue because of the increasing number of virtually silent hybrid/PHEV/EV/FCEV and electric wheels on the road.The hybrid/PHEV/EV/FCEV such as green electric-powered ones that can reduce environmental pollution are much more dangerous than traditional vehicles to pedestrians/pedal-cyclists on minor roads. The main risk factor of the electric-powered vehicles is that they are very quiet on the road because of the use of electric motor instead of engine. Thus, the safety warning system that can notify pedestrians/pedal-cyclists the dangerous approaches of vehicles from their behind have to be provided on minor roads.The proposed framework for safety warning system using multicast informs pedestrians/pedal-cyclists through smartphone when electric powered driving means are closing from their behind on minor roads. This is a new technology that uses vibration or sound of smartphone instead of artificial noise generation which is equipped to the electric powered driving means recently.  

Guidance-oriented advanced curve speed warning system in a connected vehicle environment

2020 ◽  
Vol 148 ◽  
pp. 105801
Author(s):  
Song Wang ◽  
Yi Wang ◽  
Qi Zheng ◽  
Zhixia Li
Keyword(s):  
Warning System ◽  
Connected Vehicle

Evaluating the Benefits of Red-Light Violation Warning System in a Connected Vehicle Simulation Environment

2021 ◽  
pp. 036119812110266
Author(s):  
Mohammed Hadi ◽  
Kamar Amine ◽  
Thodsapon Hunsanon ◽  
Mahmoud Arafat
Keyword(s):  
Rapid Development ◽  
Red Light ◽  
Warning System ◽  
Simulation Models ◽  
Signalized Intersections ◽  
Utilization Rate ◽  
Connected Vehicle ◽  
Microscopic Simulation ◽  
Vehicle Simulation ◽  
Study Results

The rapid development of connected vehicle (CV) and cooperative automated vehicle (CAV) technologies in recent years calls for the assessment of the impacts of these technologies on system performance. Microscopic simulation can play a major role in assessing these impacts, particularly during the early stages of the adoption of the technologies and associated applications. This study develops a method to evaluate the safety benefits of red-light violation warning (RLVW), a CV-based vehicle-to-infrastructure (V2I) application at signalized intersections, utilizing simulation. The study results confirm that it is critical to calibrate the probability to stop on amber in the utilized simulation model to reflect real-world driver behaviors when assessing RLVW impacts. Without calibration, the model is not able to assess the benefits of RLVW in reducing RLR and right-angle conflicts. Based on a surrogate safety assessment, the calibrated simulation models result shows that the CV-based RLVW can enhance the safety at signalized intersections by approximately 50.7% at 100% utilization rate of the application, considering rear-end, and right-angle conflicts.

Developing a Crash Warning System for the Bike Lane Area at Intersections with Connected Vehicle Technology

2019 ◽  
Vol 2673 (4) ◽  
pp. 47-58 ◽  
Author(s):  
Yina Wu ◽  
Mohamed Abdel-Aty ◽  
Ou Zheng ◽  
Qing Cai ◽  
Lishengsa Yue
Keyword(s):  
Traffic Safety ◽  
Warning System ◽  
Threshold Value ◽  
Vehicle Speed ◽  
Connected Vehicle ◽  
Trajectory Data ◽  
Vehicle Trajectories ◽  
Connected Vehicle Technology ◽  
Turning Maneuver ◽  
The Right

A common type of bike lane at intersections is between the through lane and the right lane. With such design, right-turning drivers need to cross the bike lane to merge into the right lane, which could cause conflicts with bicycles on the keyhole bike lane. This study aims to develop a warning system for drivers to avoid vehicle–bicycle crashes in the bike lane area under a connected vehicle environment. To propose a reasonable warning system, 118 right-turning vehicle trajectories were collected by an unmanned aerial vehicle. Drivers’ right-turning behaviors are investigated based on the trajectory data. Then, a vehicle–bicycle crash warning algorithm is proposed to calculate the post-encroachment time (PET) under different situations. By comparing the threshold value and the PET value, potential vehicle–bicycle crash locations in the bike lane area could be identified. The proposed algorithm is designed to be displayed on front windshields with an augmented reality display. The results suggested that the proposed algorithm could provide high prediction accuracy. Moreover, vehicle speed, vehicle location, bicycle speed, and bicycle location were found to have significant impact on the locations of dangerous areas. It is expected that the proposed warning system could be used to identify the dangerous areas and deliver warning information for right-turning drivers when they are approaching an intersection. The warning system could help drivers be more prepared for the upcoming right-turning maneuver, and thus improve traffic safety for both drivers and cyclists at intersections.

scholarly journals Effect of Warning System on Interactive Driving Behavior at Unsignalized Intersection under Fog Conditions: A Study Based on Multiuser Driving Simulation

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Yunfan Zhang ◽  
Xuedong Yan ◽  
Jiawei Wu ◽  
Ke Duan
Keyword(s):  
Collision Avoidance ◽  
Warning System ◽  
Driving Behavior ◽  
Driving Simulation ◽  
Driving Safety ◽  
Collision Warning ◽  
Action Point ◽  
Increased Risk ◽  
Simulation Scenario ◽  
Further Development

The intersection collision warning system (ICWS) is an emerging technology designed to assist drivers in avoiding collisions at intersections. ICWS has an excellent performance in reducing the number of collisions and improving driving safety. Previous studies demonstrated that when visibility was low under fog conditions, ICWS could help drivers timely detect hazardous conflicting vehicles. However, the influences of ICWS on interactive driving behavior at unsignalized intersection between different vehicles have barely been discussed. This study aimed to investigate the patterns of drivers’ interactive behaviors with the assistance of a new kind of ICWS under fog conditions based on Multiuser Driving Simulation. The Multiuser Driving Simulation allowed multiple drivers to operate in the same simulation scenario at the same time, and it could capture drivers’ interactions preferably. Forty-eight licensed drivers completed the driving simulation experiment in three fog conditions (no fog, light fog, and heavy fog) and two warning conditions (warning and no warning), in which the drivers drove in a straight-moving situation at unsignalized intersection with potential collision risks caused by the encounter of two vehicles. The results verified that warning and fog conditions were significant factors that affected the interactive driving behavior in the unsignalized intersection collision avoidance process, including the driver’s decision, TTC of action point, average acceleration (deceleration) rate, and postencroachment time. Compared to conditions without ICWS, the ICWS could help drivers make collision avoidance actions earlier and change the speed more smoothly. In addition, with the help of Multiuser Driving Simulation, associations between decision driving behaviors of vehicles were discussed with caution. The results revealed the decision-making mechanism of drivers in the process of interaction with other drivers. Under the influence of fog, interactive driving processes were fraught with increased risk at unsignalized intersection. However, the ICWS helped drivers interact more harmoniously, safely, and efficiently. The findings shed some light on the further development of ICWS and the study on interactive driving behavior.

scholarly journals Active Warning System for Highway-Rail Grade Crossings Using Connected Vehicle Technologies

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Xu Wang ◽  
Jiangchen Li ◽  
Can Zhang ◽  
Tony Z. Qiu
Keyword(s):  
Safety Concern ◽  
Warning System ◽  
Assessment Model ◽  
Connected Vehicle ◽  
Road Users ◽  
Proposed Model ◽  
Grade Crossing ◽  
Grade Crossings ◽  
Safety Countermeasures ◽  
Vehicle Technologies

Highway-rail grade crossing (HRGC) collisions are a significant safety concern around the world. HRGC collisions have a high risk of injuries and fatalities. To mitigate that risk, safety countermeasures for both active and passive HRGCs have been implemented. Leveraging the latest developments in connected vehicle (CV) technologies, CV-based warning systems perform well in safety applications for roadway networks. However, few have been developed to focus on safety improvements specifically for HRGCs. To bridge this gap, this paper proposes a novel active warning system that was created with readily available CV technologies and devices. A crossing risk assessment model was developed and evaluated in simulation and field applications. The proposed model predicts the crossing risk probabilities in the near future. When road users are in great risk of a collision, the warning system sends out auditory and visual alerts and displays the estimated waiting time. The test results reveal that the proposed warning system is promising for field implementation to improve safety at grade crossings.

scholarly journals Safety Evaluation of Fog Warning Systems in a Connected Vehicle Environment Based on Sample Entropy

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Xuewei Li ◽  
Yuchen Jia ◽  
Yufei Chen ◽  
Guanyang Xing ◽  
Xiaohua Zhao ◽  
...  
Keyword(s):  
Evaluation Method ◽  
Safety Evaluation ◽  
Warning System ◽  
Sample Entropy ◽  
Driving Behavior ◽  
Driving Safety ◽  
Vehicle Speed ◽  
Connected Vehicle ◽  
General Evaluation ◽  
Speed Stability

Changes in driving behavior caused by reduced visibility in fog can lead to crashes. To improve driving safety in fog weather, a fog warning system based on connected vehicle (CV) technology is proposed. From the perspective of human factors, this study evaluates the driving safety based on drivers’ speed change under different fog levels (i.e., no fog, light fog, and heavy fog) and different technical levels (i.e., normal, with a dynamic message sign (DMS), and with a human-machine interface (HMI)). The driving behavior data were collected by a driving simulation experiment. The experimental road was divided into three zones: clear zone, transition zone, and fog zone. To quantify the change of vehicle speed comprehensively, the speed and acceleration were selected. Meanwhile, the vehicle speed safety entropy and acceleration safety entropy were proposed based on sample entropy theory. Furthermore, the changes of each index in different zones were analyzed. The results show that the use of fog warning system can improve speed stability and driving safety in fog zones and can make the driver decelerate in advance with a smaller deceleration before entering the fog zones. The higher the technical level is, the earlier the driver decelerates. Under the condition of light fog, the fog warning system with HMI has a better effect in terms of improving speed stability, while under the condition of heavy fog, there is little difference between the two technical levels. In general, this study proposed a novel safety evaluation index and a general evaluation method of the fog warning system.

Food Safety Security: A new Concept for Enhancing Food Safety Measures

2012 ◽  
Vol 82 (3) ◽  
pp. 216-222 ◽  
Author(s):  
Venkatesh Iyengar ◽  
Ibrahim Elmadfa
Keyword(s):  
Food Safety ◽  
Hazard Analysis ◽  
Warning System ◽  
Shared Responsibility ◽  
Fine Tuning ◽  
Strategic Action ◽  
Surveillance Network ◽  
Measurement Systems ◽  
Critical Control Points ◽  
The Impact

The food safety security (FSS) concept is perceived as an early warning system for minimizing food safety (FS) breaches, and it functions in conjunction with existing FS measures. Essentially, the function of FS and FSS measures can be visualized in two parts: (i) the FS preventive measures as actions taken at the stem level, and (ii) the FSS interventions as actions taken at the root level, to enhance the impact of the implemented safety steps. In practice, along with FS, FSS also draws its support from (i) legislative directives and regulatory measures for enforcing verifiable, timely, and effective compliance; (ii) measurement systems in place for sustained quality assurance; and (iii) shared responsibility to ensure cohesion among all the stakeholders namely, policy makers, regulators, food producers, processors and distributors, and consumers. However, the functional framework of FSS differs from that of FS by way of: (i) retooling the vulnerable segments of the preventive features of existing FS measures; (ii) fine-tuning response systems to efficiently preempt the FS breaches; (iii) building a long-term nutrient and toxicant surveillance network based on validated measurement systems functioning in real time; (iv) focusing on crisp, clear, and correct communication that resonates among all the stakeholders; and (v) developing inter-disciplinary human resources to meet ever-increasing FS challenges. Important determinants of FSS include: (i) strengthening international dialogue for refining regulatory reforms and addressing emerging risks; (ii) developing innovative and strategic action points for intervention {in addition to Hazard Analysis and Critical Control Points (HACCP) procedures]; and (iii) introducing additional science-based tools such as metrology-based measurement systems.

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