Compensatory behavior for mental workload induced by freeway destination signs.

Objective: Exit ramps are accident-prone areas of freeways. One of the reasons for this is the information overload induced by destination signs, which makes them challenging to recognize and may even result in tension or mistakes. This study examined the cognitive workload that destination signs place on drivers and the compensatory behavior they use to counteract the additional workload.

Investigating the impact of HMI on drivers' merging performance in intelligent connected vehicle environment.

Intelligent Connected Vehicle (ICV) is considered one of the most promising active safety technologies to address current transportation challenges. Human-Machine Interface (HMI) plays a vital role in enhancing user driving experience with ICV technology. However, in an ICV environment, drivers may exhibit excessive reliance on HMI, resulting in diminished proactive observation and analysis of the road environment, and subsequently leading to a potential decrease in drivers' situational awareness.

Does a faster takeover necessarily mean it is better? A study on the influence of urgency and takeover-request lead time on takeover performance and safety.

During conditionally automated driving, drivers are sometimes required to take over control of the vehicle if a so-called takeover request (TOR) is issued. TORs are generally issued due to system limitations. This study investigated the effect of different urgency scenarios and takeover-request lead times (TORlts) on takeover performance and safety.

Analyzing the Influencing Factors and Workload Variation of Takeover Behavior in Semi-Autonomous Vehicles.

There are many factors that will influence the workload of drivers during autonomous driving. To examine the correlation between different factors and the workload of drivers, the influence of different factors on the workload variations is investigated from subjective and objective viewpoints. Thirty-seven drivers were recruited to participant the semi-autonomous driving experiments, and the drivers were required to complete different NDRTs (Non-Driving-Related Tasks): mistake finding, chatting, texting, and monitoring when the vehicle is in autonomous mode.

Ego-Lane Index Estimation Based on Lane-Level Map and LiDAR Road Boundary Detection.

Correct ego-lane index estimation is essential for lane change and decision making for intelligent vehicles, especially in global navigation satellite system (GNSS)-challenged environments. To achieve this, we propose an ego-lane index estimation approach in an urban scenario based on particle filter (PF). The particles are initialized and propagated by dead reckoning with inertial measurement unit (IMU) and odometry.

A Bibliometric and Visualized Overview for the Evolution of Process Safety and Environmental Protection.

This paper presents a bibliometric overview of the publications in the principal international journal Process Safety and Environmental Protection (PSEP) from 1990 to 2020 retrieved in the Web of Science (WoS) database to explore the evolution in safety and environmental engineering design and practice, as well as experimental or theoretical innovative research. Therefore, based on the WoS database and the visualization of similarities (VOS) viewer software, the bibliometric analysis and scientometric mapping of the literature have been performed from the perspectives of document types, publication and citation distribution over time, leading authors, countries (regions), institutions, the corresponding collaboration networks, most cited publications and references, focused research fields and topics, research trend evolution over time, etc. The paper provides a comprehensive and quantitative overview and significant picture representation for the journal's leading and evolutionary trends by employing specific aforementioned bibliometric analysis factors.

Novel Time-Delay Side-Collision Warning Model at Non-Signalized Intersections Based on Vehicle-to-Infrastructure Communication.

In complex traffic environments, collision warning systems that rely only on in-vehicle sensors are limited in accuracy and range. Vehicle-to-infrastructure (V2I) communication systems, however, offer more robust information exchange, and thus, warnings. In this study, V2I was used to analyze side-collision warning models at non-signalized intersections: A novel time-delay side-collision warning model was developed according to the motion compensation principle.

Traffic climate and driver behaviors: The moderating role of driving skills in Turkey and China.

Introduction: While road traffic accidents and fatalities are a worldwide problem, the rates of road traffic accidents and fatalities show differences among countries. Similarly, driver behaviors, traffic climate, and their relationships also show differences among countries. The aim of the current study is to investigate the moderating effect of driving skills on the relationship between traffic climate and driver behaviors by country.

Rear-end collision warning of connected automated vehicles based on a novel stochastic local multivehicle optimal velocity model.

Studying the rear-end early warning methods of connected automated vehicles (CAVs) is useful for issuing early warnings and reducing traffic accidents. Establishing a corresponding driving model according to CAV characteristics is necessary when designing intelligent decision and control systems, especially for the safety speed threshold. However, since traffic systems are stochastic, there are random factors that influence car-following behavior.

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

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.

A novel feature extraction model for traffic injury severity and its application to Fatality Analysis Reporting System data analysis.

The prevention of severe injuries during crashes has become one of the leading issues in traffic management and transportation safety. Identifying the impact factors that affect traffic injury severity is critical for reducing the occurrence of severe injuries. In this study, the Fatality Analysis Reporting System data are selected as the dataset for the analysis.

Quick mass-production of MAX (TiAlC) book with pages separated by stacking faults benefiting removal of "A" layer.

A creative and universal technique, magnetism and vortex current coupling growth (MVC), has been developed for the super-rapid mass-production of the layered MAX (TiAlC) phase. The book-like MAX grows from the bottom to the top layer by layer, separated by stacking faults to benefit the removal of the "A" layer from MAX.

Traffic climate, driver behaviour, and accidents involvement in China.

Traffic Climate Scale (TCS) and Positive Driver Behaviours Scale (PDBS) are new measurement tools. The study aims to translate the TCS and PDBS into Chinese and to assess their factor structures in a large sample of licensed motor vehicle drivers in China. A further aim is to investigate the effects of TCS factors on drivers' behaviours and traffic accidents involvement.

The effect of gender, occupation and experience on behavior while driving on a freeway deceleration lane based on field operational test data.

Deceleration lanes improve traffic flow by reducing interference, increasing capacity and enhancing safety. However, accident rates are higher on these interchange segments than on other freeway segments. It is important to attempt to reduce traffic accidents on these interchange segments by further exploring the behavior of different types of drivers on a highway deceleration lane.

Driving style recognition method using braking characteristics based on hidden Markov model.

Since the advantage of hidden Markov model in dealing with time series data and for the sake of identifying driving style, three driving style (aggressive, moderate and mild) are modeled reasonably through hidden Markov model based on driver braking characteristics to achieve efficient driving style. Firstly, braking impulse and the maximum braking unit area of vacuum booster within a certain time are collected from braking operation, and then general braking and emergency braking characteristics are extracted to code the braking characteristics. Secondly, the braking behavior observation sequence is used to describe the initial parameters of hidden Markov model, and the generation of the hidden Markov model for differentiating and an observation sequence which is trained and judged by the driving style is introduced.

Safety and Health Perceptions in Work-related Transport Activities in Ghanaian Industries.

Background: With the recent rapid industrialization, occupational safety and health (OSH) has become an important issue in all industrial and human activities. However, incidents of injuries and fatality rates in the Ghanaian industry sector continue to increase. Despite this increase, there is no evidence regarding the element of OSH management in transport activities in Ghanaian industries.

Perceived enjoyment, concentration, intention, and speed violation behavior: Using flow theory and theory of planned behavior.

Objective: Road accidents are an important public health concern, and speeding is a major contributor. Although flow theory (FLT) is a valid model for understanding behavior, currently the nature of the roles and interplay of FLT constructs within the theory of planned behavior (TPB) framework when attempting to explain the determinants of motivations for intention to speed and speeding behavior of car drivers is not yet known. The study aims to synthesize TPB and FLT in explaining drivers of advanced vehicles intentions to speed and speed violation behaviors and evaluate factors that are critical for explaining intention and behavior.

Modeling Vehicle Collision Angle in Traffic Crashes Based on Three-Dimensional Laser Scanning Data.

In road traffic accidents, the analysis of a vehicle's collision angle plays a key role in identifying a traffic accident's form and cause. However, because accurate estimation of vehicle collision angle involves many factors, it is difficult to accurately determine it in cases in which less physical evidence is available and there is a lack of monitoring. This paper establishes the mathematical relation model between collision angle, deformation, and normal vector in the collision region according to the equations of particle deformation and force in Hooke's law of classical mechanics.

Driver's Cognitive Workload and Driving Performance under Traffic Sign Information Exposure in Complex Environments: A Case Study of the Highways in China.

Complex traffic situations and high driving workload are the leading contributing factors to traffic crashes. There is a strong correlation between driving performance and driving workload, such as visual workload from traffic signs on highway off-ramps. This study aimed to evaluate traffic safety by analyzing drivers' behavior and performance under the cognitive workload in complex environment areas.

Identification of common features of vehicle motion under drowsy/distracted driving: A case study in Wuhan, China.

Drowsy/distracted driving has become one of the leading causes of traffic crash. Only certain particular drowsy/distracted driving behaviors have been studied by previous studies, which are mainly based on dedicated sensor devices such as bio and visual sensors. The objective of this study is to extract the common features for identifying drowsy/distracted driving through a set of common vehicle motion parameters.

Motor vehicle-bicycle crashes in Beijing: irregular maneuvers, crash patterns, and injury severity.

This research presents a comprehensive analysis of motor vehicle-bicycle crashes using 4 years of reported crash data (2004-2007) in Beijing. The interrelationship of irregular maneuvers, crash patterns and bicyclist injury severity are investigated by controlling for a variety of risk factors related to bicyclist demographics, roadway geometric design, road environment, etc. Results show that different irregular maneuvers are correlated with a number of risk factors at different roadway locations such as the bicyclist age and gender, weather and traffic condition.