shrp2 100car analyses

SHRP2 + 100-Car combined analyses / cross-study comparisons.

2141 papers carry this dataset tag, of 5322 that declare a dataset at all (62594 papers carry any topic). Absence here means undeclared, not absent.

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Papers

Newest 200 shown. For the full set, or to combine this with a topic, use the catalogue search.

Observing Driver Distraction Behaviors at Intersections in Calabar Metropolis, Nigeria ↗ · 2026 · A. Etika, Anderson et al.
Comparative Analysis of Interpretable Data‐Driven and Analytical Car‐Following Models on Highways: Robustness, Sensitivity and Transferability ↗ · 2026 · Adamidis, Filippos et al.
Are we ready for highly automated vehicles? Evaluating automated driving systems’ safety and reliability using inverse probability weighted regression adjustment ↗ · 2026 · Adeel, Muhammad et al.
Modelling driver behaviour as a continuum between defensive and neutral states ↗ · 2026 · Al-Haideri, Rulla et al.
A machine learning model to predict the severity of road traffic injury based on aberrant driving behaviors and driver characteristics ↗ · 2026 · Abdolrazaghi, Alireza et al.
Clustering drivers by demographic and aberrant driving behavior: implications for traffic injury risk and safety interventions ↗ · 2026 · Abdolrazaghi, Alireza et al.
Real-time monitoring of driver cognitive states: linking driving behavior to neural oscillations ↗ · 2026 · Alyan, Emad et al.
Effect of Different Types of Distractions on Driving Behavior and Road Safety Using Naturalistic Driving Data Under Mixed Traffic Conditions ↗ · 2026 · Ameenuddin, Mohammed et al.
Exploring Temporal and Manufacturer-Specific Trends of Automated Vehicle Crashes Using Sequence of Events ↗ · 2026 · Andriola, Cesar et al.
Situation understanding and risk assessment framework for preventive driver assistance ↗ · 2026 · Armand, Alexandre
Impacts of different feedback features on driver behaviour: Findings from a multiphase naturalistic study ↗ · 2026 · Kontaxi, Armira et al.
Long-Term Effects of Driver Feedback on Harsh Braking Behavior: Insights from Survival Models ↗ · 2026 · Kontaxi, Armira et al.
A hybrid statistical-machine learning methodology for addressing endogeneity and temporal instability in speeding-crash frequency relationships ↗ · 2026 · Asadi Ghalehni, Sajad et al.
Modeling behavioral indicators for driver drowsiness detection: a simulator-based study ↗ · 2026 · Azaddel, Rahele et al.
SAE Level 2 ADAS Performance in Specific Crash-Imminent Scenarios ↗ · 2026 · Beale, Gregory et al.
Can Knowledge of Taxi Drivers’ Intentions to Commit Traffic Violations Predict Crash Frequency? ↗ · 2026 · Behnood, Hamid Reza et al.
Clustering of Driver Behavioral Strategies During Speed Cushion Traversal: A Driving Simulator Study ↗ · 2026 · Bosurgi, Gaetano et al.
Unveiling Driver Workload Dynamics and Road Safety Risks in Assistant and Automated Driving Systems ↗ · 2026 · Bosurgi, Gaetano et al.
Visual Mismatch and Adaptation Behaviour Under Unfamiliar Driving Environment: AComparative Eye-Tracking Study of Blind Spot In LHD and RHD ↗ · 2026 · Bu, Yuanyuan et al.
Behavioral adaptation in mixed traffic: the roles of AV penetration rate and human driving style ↗ · 2026 · Chen, Haitao et al.
Comparing Automated Driving Systems’ Safety Data with Human Benchmarks ↗ · 2026 · Chen, Joyce Jiayu et al.
Supervisory Gaze Behaviour Under Different Automation Durations in Level 2 Driving: A First-Order Transition Analysis ↗ · 2026 · Chouchane, Hanna et al.
An Investigation of Drowsy Lane Departures from Driving Simulator Studies ↗ · 2026 · Schwarz, Chris et al.
When does visual distraction become dangerous in car-following? Evidence from naturalistic driving study data with causal inference on time-to-collision and braking intensity ↗ · 2026 · Chun, Uibeom et al.
Catboost - SHapley Additive exPlanations (SHAP) car following model: Explaining model features in mixed traffic conditions ↗ · 2026 · Cui, Tianyang et al.
Driver Behavior Profiling Through Jerk Dynamics and Statistical IMU Descriptors ↗ · 2026 · Damian, Danut Dragos et al.
Inferring Hidden Attentional States in Driving: A Bayesian Approach to Modeling Distraction and Secondary Task Engagement. ↗ · 2026 · Dheeraj Kashyap L et al.
Comparative safety evaluation of ADAS-Equipped electric and gasoline vehicles using real-world crash data ↗ · 2026 · Ding, Shengxuan et al.
Distracted Drivers Differ in Infrastructure Sensitivity, Not Distraction Frequency: A Naturalistic Crosswalk Study ↗ · 2026 · Douglas, Grace et al.
Do Attention-Seeking Safety Messages Shape Driver Behavior or Safety Outcomes? Evidence from Dynamic Message Signs ↗ · 2026 · Dumka, Ashutosh et al.
Modeling Driver Lateral Control Behavior for Human--Machine Shared Takeover During Emergency Collision Avoidance Under Dynamic Traffic Environment ↗ · 2026 · Feng, Shiyong et al.
Determinants of risky driving behaviors in professional bus drivers: A questionnaire investigation ↗ · 2026 · Gao, Zhibo et al.
An Exploratory Analysis of Geometric Alignments on Lane Departure Behaviors at Loop Ramps ↗ · 2026 · Ge, Ting et al.
Signal-Adaptive and Uninhibited Driver Distraction During Crosswalk Approach: Evidence from the SHRP2 Naturalistic Driving Study ↗ · 2026 · Douglas, Grace et al.
From brake lights to beyond – exploring information needed for car-following behaviour ↗ · 2026 · Gu, Feiqi et al.
Optimizing followers’ car-following behaviors using rear-facing eHMIs ↗ · 2026 · Gu, Feiqi et al.
Seeing Through the Leading Vehicle via Rear-Facing eHMIs – An On-Road Study ↗ · 2026 · Gu, Feiqi et al.
Driving behavior and safety performance in spiral tunnel groups: A naturalistic data analysis ↗ · 2026 · He, Shiming et al.
Understanding the risk factors of driving dilemmas at urban tunnel exits adjoining diverging areas: A naturalistic study ↗ · 2026 · He, Shiming et al.
Implicit Driving Cues for Coordinating Actions When Sharing Spaces ↗ · 2026 · Hensch, Ann-Christin et al.
Evaluating Harsh Braking Events as a Surrogate Measure of Crash Risk Using Connected-Vehicle Telematics ↗ · 2026 · Hossain, Md Tufajjal et al.
GENDER DIFFERENCES IN DRIVERS' GAZE BEHAVIOR WHILE DRIVING THROUGH CROSSWALKS ↗ · 2026 · Hristov, Borislav et al.
A Review of Sociodemographic Influences on Car-Following Behavior ↗ · 2026 · Hussain, Zahid et al.
Evaluation of association between observed driving speeds and the occurrence of crashes using naturalistic driving study data ↗ · 2026 · Ivan, John N. et al.
Real-World Driving Behavior, Performance, and Risk Following Alcohol and Cannabis Use in Habitual Cannabis Users ↗ · 2026 · Jain, Sparsh et al.
From emotion to safety-critical events: The temporal causal pathways in naturalistic driving ↗ · 2026 · Jiang, B et al.
Shift the gaze ↗ · 2026 · Illgner, Johannes et al.
Investigating driving behavior characteristics on freeway curves under accumulated sand environments: evidence from a driving simulator study ↗ · 2026 · Zhang, Junjie et al.
Detection of Fine-grained Driver Cognitive Responses for Cross-subject Deep Learning Framework ↗ · 2026 · Kim, Ah-Hyun et al.
Towards Safer Automated Driving: Predicting Drivers with Long Takeover Time Using Random Forest and Human Factors ↗ · 2026 · Kim, Jungsook et al.
Are Drivers More Distracted with Level 2 Automated Technologies? A Naturalistic Driving Study Analysis of Frequency, Duration, and Proportion of Time Drivers Engage in Secondary Tasks ↗ · 2026 · Klauer, Sheila et al.
Driver-Personalized Risk Assessment in Car-Following: Validation of an Optical-Flow-Based Model using SHRP 2 Naturalistic Driving ↗ · 2026 · Kondoh, Takayuki et al.
Simulation Assessment of the Impact of a Partially Operational Vehicle Lighting System on Driving Safety ↗ · 2026 · Kowalski, Sławomir
Mitigating effects of distraction: Drivers adjust speed and glance behaviour during secondary tasks in a driving simulator study ↗ · 2026 · Kummerer, Katharina et al.
Can Digital Road Safety Campaigns Nudge Sustained Safer Riding? Evidence from Behavioural Segmentation of Two-Wheeler Riders using Naturalistic Riding Data ↗ · 2026 · Kurian, Georgeena et al.
Characterizing Driver Behavior during Emergency Vehicle Encounters: An Application of a VR Driving Simulator with Integrated Eye-Tracking ↗ · 2026 · Liu, Lanmin et al.
Classifying interaction patterns of powered two-wheelers during severe conflicts with cars at intersections: a naturalistic driving data study ↗ · 2026 · Liu, Zhenyuan et al.
Driver behavioral and psychological traits as risk factors for traffic accidents: a systematic review and meta-analysis ↗ · 2026 · Liu, Yangyi et al.
Alertness-Related Differences in Car-Following Strategy among Truck Drivers Based on Naturalistic Driving Data ↗ · 2026 · Liu, Yang et al.
Research on Distracted Driving State Recognition and Its Impact Using an Ensemble Learning Model Based on Multimodal Information Fusion ↗ · 2026 · Ma, Dezhong et al.
The Chain of Visual Factors, Visual Characteristics, and Driving Behavior at Highway Tunnel Entrances ↗ · 2026 · Ma, Yanpeng et al.
Assessing the Moderation Effects of Socioeconomic Factors in Predicting Severe Crash Outcomes Based on Road and Environment Characteristics: A Modeling Comparison ↗ · 2026 · Jafari, Mahsa et al.
Assessing the validity of situation awareness measures through visual behaviours in car driving: A comprehensive review ↗ · 2026 · Pelerin, Maëlle et al.
Visual attention and driving behavior of male autistic individuals while encountering driving hazards: A driving simulator study ↗ · 2026 · Mamo, Wondwesen Girma et al.
The Effects of State of Mind, Traffic Rule Knowledge, And Driving Experience on Safe Driving Behaviour in India: Evidence from Smartphone-Based Naturalistic Driving Data ↗ · 2026 · Mathai, Sibi et al.
Cultural factors and context-specific interventions for aberrant driving behaviours in LMICs: a systematic review ↗ · 2026 · Matira, Patrick Simbarashe
Characterization of Motorcyclist Aggressive Driving Behavior in Urban and Suburban Environments: A Case Study of a Single Motorcyclist. ↗ · 2026 · Mendes L et al.
Latent Driving Style Profiles and Road Safety Outcomes Across Generational Extremes: The Role of Driving Exposure in Accidents and Traffic Infractions ↗ · 2026 · Merino-Vivanco, Xavier et al.
Clustering Roadway Departures from Impaired Driving Studies using Derived Features and Shape-Based Methods ↗ · 2026 · Miller, Ryan et al.
Driving behavior recognition and scoring: A Bayesian approach to driving simulator data analytics ↗ · 2026 · Pourghasemi, Mohammad et al.
Modeling vehicle-cyclists' interactions to support automated driving and advanced driving assistance systems ↗ · 2026 · Mohammadi, Ali et al.
Driving Context Sensitivity: An Endogenous Concept for Capturing Intra-driver Heterogeneity ↗ · 2026 · Mohammadian, Saeed et al.
Effects of ADAS Availability on Crash Injury Outcomes: Corridor-Level Evidence from a Principal Arterial in Florida ↗ · 2026 · Mutalemwa, Gabriel Nickson et al.
Validation and analysis of real-world traffic accident black spots in a driving simulator environment ↗ · 2026 · Ünsalan, Kevser et al.
Human Behavioral Factors Influencing Speeding on a High-Risk Inter-Urban Corridor in Nigeria: Evidence for Policy Reform within a Safe System Framework ↗ · 2026 · Owonibi, Sunday et al.
From Car Affinity to Risk Awareness: Understanding Driver Profiles and Shifts in Fatal Five Concerns across West Yorkshire, UK ↗ · 2026 · Ozturk, Ibrahim et al.
Driving Behaviour as a Predictor of Crash Probability and Severity: Insights from a Modified DBQ for Indian Car Drivers ↗ · 2026 · Pandey, Ashutosh et al.
Integrating extreme value theory and the task-capability interface model to estimate crash risk with driver-specific heterogeneity in connected environment ↗ · 2026 · Parashar, Shubham et al.
Linking built environments and pre-crash pedestrian behaviors: A Safe Systems approach to crash severity ↗ · 2026 · Park, Shinah et al.
Behind the Wheel of a Truck Simulator: Comparison of Self-Reported, Performance-Based, and Simulation Methods for Predicting Driver Traffic Offences ↗ · 2026 · Baran, Paulina et al.
An Integrated Open-Source Framework for Automated Analysis of Driver Activity, Glance, and Vehicle Automation Mode ↗ · 2026 · Sahoo, Praneet et al.
Naturalistic driving data extraction and processing for studying driver head scanning behavior at intersections ↗ · 2026 · Pundlik, Shrinivas et al.
Takeover Response Time Prediction Model Based on Observable Behavior ↗ · 2026 · Qian, Tianyi et al.
Eye-Tracking Indices of Cognitive Load Predict Reaction Time to Urban Traffic Hazards: Machine Learning Classification and Regression Across Manual and Level 2 Assisted Driving ↗ · 2026 · Qin, Hao et al.
Driver Behavior in Mixed Traffic with Autonomous Vehicles ↗ · 2026 · Rezwana, Saki et al.
The Influence of Repeated Hazard Exposure on Driving Behavior in a Longitudinal Driving Simulator Study ↗ · 2026 · Rundus, Christopher R. M. et al.
Behavioral adaptation of human drivers in car-following interactions with automated vehicles ↗ · 2026 · Saljoqi, Masoud et al.
Analysis of the influence of traffic variables on lane change manoeuvres decision-making in real-world traffic scenarios ↗ · 2026 · Sanchez-Mateo, Sofia et al.
Evaluating Driver Pedestrian Interactions Under Uncertainty:A Driving Simulator Study ↗ · 2026 · Sekeran, Maya et al.
Driving Behavior Recognition Based on Multimodal Physiological Signals under Negative Emotion ↗ · 2026 · shao, shuyu et al.
From prediction to prevention: safety modeling of driver takeover time with mental workload, risk perception, and driving style in ramp scenarios ↗ · 2026 · Shao, Yichang et al.
Modeling driver lane-changing aggressiveness under target-lane interference: A Bayesian approach using naturalistic trajectory data ↗ · 2026 · Shen, Rui et al.
Predicting Crash Severity using Naturalistic Driving Data and Neural Networks ↗ · 2026 · Somvanshi, Shriyank et al.
Gaze dynamics reveal age-related physiological patterns across driving events ↗ · 2026 · Strle, Gregor et al.
Unsafe driving behavior and safety law support: unraveling the influence of drivers’ demographics ↗ · 2026 · Mishra, Sushreeta et al.
Sensor-Detected Differences in Behaviors of Older Drivers with Pre-MCI and Mild Cognitive Impairment vs. Unimpaired Drivers ↗ · 2026 · Tappen, Ruth M. et al.
Evaluating inattention behaviour of Indian bus drivers using AI-powered driver monitoring systems ↗ · 2026 · Thakur, Dev Singh et al.
Evaluating Risky Driving Behavior Using a Naturalistic Driving Dataset: A Hybrid Modelling Approach ↗ · 2026 · Theodoraki, Eleni Maria et al.
Validation and Analysis of Real-World Traffic Accident Black Spots in a Driving Simulator Environment ↗ · 2026 · Unsalan, Kevser et al.
Uncovering crash narratives: enhancing safety reporting for underprotected road users in transit bus collisions ↗ · 2026 · Usman, Sheikh M. et al.
Interpretable and robust tree-based methodology for imbalanced classification in driving safety assessment ↗ · 2026 · Vannucci, Giulia et al.
What factors influence driver behaviour characteristics when pedestrians cross the road? Insights from the UDRIVE naturalistic driving study ↗ · 2026 · Varotto, Silvia F. et al.
State-of-the-art review on sustainable driving behavior: trade-offs between road safety, fuel consumption and emissions ↗ · 2026 · Petraki, Virginia et al.
Exploring the Role of Driver Emotions and Physiology in Driving Risk Inference: A Multimodal Explainable AI Approach Using Instrumented Vehicle Data ↗ · 2026 · Vullapu, Sai Sesidhar et al.
Driving with Influence: Exploring Crash Factors of Automated Systems in Different Roadway Contexts ↗ · 2026 · Astle, W. Abram et al.
A Study on the Correlation Between Driving Behavior and ECG Data in Driving Fatigue. ↗ · 2026 · Wang J et al.
A visualization-supported, hierarchical, action-learning model for driving behavior in a V2X environment ↗ · 2026 · Wang, Xuantong et al.
Contributing Factors to Lane Departure Crashes: A Data-Driven Multi-Scale Identification Approach Leveraging Heterogeneous Data ↗ · 2026 · Wang, Shuyi et al.
Evaluating the risk factors related to alcohol-impaired driving using the SHRP 2 naturalistic driving study ↗ · 2026 · Wang, Manhua et al.
Exploring the safety impacts of conditionally automated driving vehicles switching control to manual driving mode within mixed traffic ↗ · 2026 · Wang, Changshuai et al.
Improving our understanding of contributing factors in California level 4 autonomous vehicle crashes through latent class analysis and machine learning-SHAP interpretations ↗ · 2026 · Wang, Jiacheng et al.
What Creates Safe and Efficient Pedestrian–Vehicle Interactions? A Naturalistic Study to Design Human-Like Behaviour for Automated Vehicles ↗ · 2026 · Wang, Yuwei et al.
The Role of Nonverbal Communication in Driver Yielding Behavior: A VR-Based Analysis of Pedestrian–Driver Interactions ↗ · 2026 · Won, Jinho et al.
Practical validation of synthetic pre-crash scenarios ↗ · 2026 · Wu, Jian et al.
Evaluating active driver intervention strategies in sequential conflict scenarios: a counterfactual reasoning-based framework ↗ · 2026 · Xie, Shuke et al.
Unsupervised Identification of Driving Styles from Naturalistic Driving Data Through a Context-Normalized Framework ↗ · 2026 · Xu, Cunzhi et al.
A Multi-dimensional Attention-based Framework for Personalized Driver Fatigue Assessment for Proactive Commercial-vehicle Crash Prevention ↗ · 2026 · Yang, Jiayu et al.
A Two-Stage Driving-Style-Stratified Framework for Analyzing and Predicting Car-Following Conflict Risk in Mixed Traffic ↗ · 2026 · Yang, Manli et al.
Assessing autonomous driving performance and environmental influencing factors using real-world operational trajectory data ↗ · 2026 · Yang, Han et al.
Driver behavior analysis at alternative intersection corridors through driving simulator ↗ · 2026 · Yang, Guangchuan et al.
Integrated Analysis of Driver Behavior during Signal Phase Transitions Using Fused Connected Vehicle Trajectory and High-Resolution Signal Event Data ↗ · 2026 · Zhang, Yuhan et al.
Investigation of driving safety in partial driving automation considering driving modes and drivers’ pre-drive states ↗ · 2026 · Zhang, Wei et al.
Unsupervised Driving Behavior Primitive Inference via Hierarchical Segmentation and Context-Aware Clustering. ↗ · 2026 · Zhang L et al.
From Prediction to Design: Using Context-Aware Graph Neural Networks and Explainable AI to Anticipate Transfer-of-Control ↗ · 2026 · Zhao, Zhouqiao et al.
Exploring the heterogeneous relationship between abnormal driving events and freeways crash risk: A two stage analysis framework integrating causal inference and random parameters logit ↗ · 2026 · Zhou, Mo et al.
Uncovering Probabilistic Crash Risk Among Coach Drivers Using a Bayesian Network Based on Violation and Crash Records ↗ · 2026 · Zhou, Yanru et al.
Explicit and implicit HMI for tunnel blind spot: insights from a naturalistic driving experiment ↗ · 2026 · Zhu, Beining et al.
From Human Semantics to Executable Control: Driving Behavior Graph for Automated Emergency Maneuvering ↗ · 2026 · Zhu, Yixin et al.
Random Forest Screening and Association Rule Mining for Crash Pattern Discovery ↗ · 2025 · Abbaszadeh Lima, Mohammad Reza et al.
A strategic framework for road safety analysis in the connected and autonomous vehicle era ↗ · 2025 · Siddiqui, Abdul Basith et al.
Understanding Driving Behaviors and Traffic Crashes among University Commuter Drivers ↗ · 2025 · Alshehri, Abdulaziz H.
Repeated Route Naturalistic Driver Behavior Analysis Using Motion and Gaze Measurements ↗ · 2025 · Adhikari, Bikram et al.
How does distraction affect cyclists’ severe crashes? A hybrid CatBoost-SHAP and random parameters binary logit approach ↗ · 2025 · Agheli, Ali et al.
Multi-source enriched driving behavior models A driving simulator case study in Germany ↗ · 2025 · Al Haddad, Christelle et al.
The Future Driver: Exploring the Safety Challenges of Level 4 Automated Vehicles During Manual Control ↗ · 2025 · Andriola, Cesar et al.
A Model for the Crash Occurrence in Unexpected Incidents ↗ · 2025 · Anna, Pouliou et al.
Driving behavior analytics: an intelligent system based on machine learning and data mining techniques ↗ · 2025 · Arabiat, Areen et al.
Safety Enhancement of Adaptive Cruise Control Adapted to Driver Eyes-Off State ↗ · 2025 · Arai, Norika et al.
The weights of drivers’ on-route concerns in car-following behaviours ↗ · 2025 · Salehikalam, Arsalan et al.
Understanding Driver Perception of Sharpness, Risk, and Speed on Horizontal Curves: An Instrumented Vehicle and Questionnaire Study of Two-Lane Highway ↗ · 2025 · Atif, Mohd et al.
Quantifying truck crash risk under the combined effects of multi-type aberrant driving behaviors: Two probabilistic approaches ↗ · 2025 · Baikejuli, Muladi et al.
Where to Look? VR Gaze-Based Analysis in Adverse Weather Driving ↗ · 2025 · Bang, Junsik et al.
Evaluating defensive driving behaviour based on safe distance between vehicles: A case study using computer vision on UAV videos at urban roundabout ↗ · 2025 · Bhavsar, Yagnik M. et al.
Risk-Aware Car-Following Behavior Characterization in Foggy Weather on Urban Expressways Using Naturalistic Driving Data ↗ · 2025 · Chen, Yanyi et al.
Time-dependent effect of advanced driver assistance systems on driver behavior based on connected vehicle data ↗ · 2025 · Chen, Yuzhi et al.
The influence of driving safety attitudes on risky driving behavior: a driving simulator study ↗ · 2025 · Chrisnatalia, M. et al.
Freeways’ Road Safety Analysis Through Accident Database and Human Behavior ↗ · 2025 · Brasile, Claudia et al.
Human-Centered In-Vehicle Sensing Systems for Identifying Driving Pattern from Cognitive Decline Through Quantitative Analysis ↗ · 2025 · Moshfeghi, Sonia et al.
Road design influence on driving behaviors: The influence of curve design, a case study ↗ · 2025 · Coropulis, Stefano et al.
Analyzing Pedestrian–Automated Vehicle Crash Dynamics: A Comparative Study of Autonomous and Conventional Precrash Mode ↗ · 2025 · Das, Subasish
Integrating Empirical and Subjective Evidence on Young Drivers’ Risk Perceptions and Crash Factors ↗ · 2025 · Das, Subasish
Pattern recognition in crash clusters involving vehicles with advanced driving technologies ↗ · 2025 · Das, Subasish
Uncovering the role of restraint usage in driver ejection: a data mining investigation of fatal and injury crashes ↗ · 2025 · Das, Subasish
Lateral shifting behavior of vehicles at horizontal curves and its influencing factors: application of LightGBM and SHAP ↗ · 2025 · Debbarma, Samrat et al.
Assessing the safety effectiveness of advanced driver assistance systems ↗ · 2025 · Ding, Shengxuan et al.
Characterizing driver fingerprinting of new energy vehicles in risky scenarios: A naturalistic driving study ↗ · 2025 · Ding, Naikan et al.
What Patterns Contribute to Autonomous Vehicle Crashes? A Study of Level 2 and 4 Automation via Association Rule Analysis ↗ · 2025 · Ding, Hongliang et al.
Driver Personalized Lane Change Behavior Analysis Based on Attention Deep Embedding Clustering ↗ · 2025 · Dong, Haomin et al.
Analysis of Driver Takeover Performance in Autonomous Vehicles Based on Generalized Estimating Equations ↗ · 2025 · Duan, Min et al.
Assessing the Ghanaian driver's susceptibility to distraction engagement · 2025 · Sam, Enoch F.
How predictive-forward-collision-warning reduces the collision risk of leading vehicle driver ↗ · 2025 · Fu, Qiang et al.
Enhancement of ADAS with Driver-Specific Gaze Profiling Algorithm—Pilot Case Study ↗ · 2025 · Gogola, Marián et al.
It Matters Who Is Behind The Wheel: Driver Monitoring Feature Analysis Using Explainable AI ↗ · 2025 · Gonçalves, Rafael Cirino et al.
A Comparative Analysis of Lane-Change Data Extraction Methods Based on Naturalistic Driving Data Sets ↗ · 2025 · Gu, Xinyuan et al.
From Brake Lights to Beyond - Assessing Rear eHMI Designs through a Video-Based Survey ↗ · 2025 · Gu, Feiqi et al.
An Experimental Study on Drivers’ Eye Movement Behavior When Using an Automated Lane Change System ↗ · 2025 · Guan, Muhua et al.
Fatigue and Distracted Driving Recognition Method Based on Multimodal Information Fusion ↗ · 2025 · Guan, Deyong et al.
Crash risk associated with eyes-off-road duration by road control type and intersection type · 2025 · Han, Shu et al.
Examination of naturalistic driving behavior and risk events across concussion recovery ↗ · 2025 · Hashida, Kumiko et al.
Impact Analysis of Lane Change Behavior Based on Trajectory Data ↗ · 2025 · He, Yu et al.
Enhanced Driver Profiling Through Clustering of Naturalistic Driving Data for Risk Evaluation and Insights ↗ · 2025 · Hermia, J. Janorious et al.
Prevalence of high-risk behaviors among commercial motor vehicle drivers measured using artificial intelligence for naturalistic data collection ↗ · 2025 · Moran, Ryan et al.
A hybrid data mining framework to investigate roadway departure crashes on rural two-lane Highways: Applying Fast and Frugal Tree with Association Rules Mining ↗ · 2025 · Hossain, Ahmed et al.
A Deep Auto-Encoder Approach for Clustering Cut-in Driving Styles from Naturalistic Data ↗ · 2025 · Hou, Qingqing et al.
Naturalistic driving study data applied to road infrastructure: A systematic review ↗ · 2025 · Howell, Fletcher J. et al.
Framework of Adaptive Driving: Linking Situation Awareness, Driving Goals, and Driving Intentions Using Eye-Tracking and Vehicle Kinetic Data ↗ · 2025 · Lai, Hsueh-Yi
Predicting Takeover Performance and Identifying Behavioral Patterns in Autonomous Vehicles Based on Readiness State and Scenario Complexity ↗ · 2025 · Lai, Hsueh-Yi et al.
The Effect of Advanced Driver Assistance Systems on Truck Drivers’ Defensive Driving Behaviors: Insights from a Preliminary On-Road Study ↗ · 2025 · Huang, Chunxi et al.
Empirical analysis of car-following behavior: Impacts of driver demographics, leading vehicle types, and speed limits on driver behavior and safety ↗ · 2025 · Hussain, Zahid et al.
Investigating patterns of freeway crashes in Jordan: Findings from a text mining approach ↗ · 2025 · Jaradat, Shadi et al.
Challenges and recommendations using surrogates for safety impact assessment: correcting misestimations ↗ · 2025 · Bärgman, Jonas et al.
Life satisfaction, risky and aggressive driving, and crash involvement: Evidence within a contextual-mediated framework ↗ · 2025 · Pérez, Jorge Eduardo Martínez et al.
Defining Preventable Boundaries in Automated Driving Systems: A Driver Behavior Model for Scenario-Based Assessments ↗ · 2025 · Kitajima, Sou et al.
Evaluating In-Car Tasks’ Distraction Effects with Drive-In Lab · 2025 · Kujala, Tuomo et al.
Comparison of Waymo Rider-Only crash rates by crash type to human benchmarks at 56.7 million miles ↗ · 2025 · Kusano, Kristofer D. et al.
A Turn in the Road: Real-life Driving Differences in Obstructive Sleep Apnoea and Excessive Daytime Sleepiness ↗ · 2025 · Lee, Kieran O. et al.
Aggressive driving in ride-hailing: Work hours and road conditions ↗ · 2025 · Lee, Eun Hak et al.
Classifying Advanced Driver Assistance System (ADAS) Activation from Multimodal Driving Data: A Real-World Study ↗ · 2025 · Lee, Gihun et al.
An Empirical Investigation of Speed Patterns on S‐Curves Using Naturalistic Driving Data and Mixed Logit Model ↗ · 2025 · Lei, Cailin et al.
Examination of General Motors Super Cruise system field effects using state police report crash data ↗ · 2025 · Leslie, Andrew J. et al.
Analysis of Driving Behavior Characteristics at Intersections under Active Driving Guidance ↗ · 2025 · Li, Jiazhen et al.
Identifying built environment factors influencing driver yielding behavior at unsignalized intersections: A naturalistic open-source dataset collected in Minnesota ↗ · 2025 · Li, Tianyi et al.
Research on countermeasure of taxi driver's aggressive driving behavior based on text features extraction ↗ · 2025 · Li, Sizhe et al.
Study of Driver's Perception in Driving Tasks Based on Naturalistic Driving Experiments and fNIRS Measurement ↗ · 2025 · Li, Bilu et al.
Driver Injury Prediction and Factor Analysis in Passenger Vehicle-to-Passenger Vehicle Collision Accidents Using Explainable Machine Learning ↗ · 2025 · Liu, Peng et al.
From Route-Level Driving Familiarity to Scenario- and Individual-Level Diversity: A Preliminary Human Gaze Study in Simulated Driving ↗ · 2025 · Liu, Haoji et al.
A perspective from competitive-cooperative driving modes: Identification of vehicle merging behavior models and crash risk factors in merge zone ↗ · 2025 · Lyu, Nengchao et al.
Characterizing the heterogeneities of driver attributes and lane-changing characteristics in lane-changing risks based on reconstructed vehicle trajectories on arterial roads ↗ · 2025 · Ma, Jingfeng et al.
Investigation of factors affecting crash severity of rear-end crashes with high collision speeds in work zones: A South Carolina case study ↗ · 2025 · Madarshahian, Mahyar et al.
Structural Equation Modeling to Investigate Behavioral Factors Contributing to Crash Involvement: A Systematic Review ↗ · 2025 · Jafari, Mahsa et al.