Integration of automated vehicles in mixed traffic: Evaluating changes in performance of following human-driven vehicles

Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations

Fagnant, D. J., & Kockelman, K. (2015) · Transportation Research Part A: Policy and Practice · doi:10.1016/j.tra.2015.04.003 · Cited by 3,214

The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics

van Arem, B., Driel, C. J. G. V., & Visser, R. (2006) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2006.884615 · Cited by 1,548

Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles

Wadud, Z., MacKenzie, D., & Leiby, P. (2016) · Transportation Research Part A: Policy and Practice · doi:10.1016/j.tra.2015.12.001 · Cited by 859

Research advances in intelligent collision avoidance and adaptive cruise control

Vahidi, A., & Eskandarian, A. (2003) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2003.821292 · Cited by 848

Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments

Stern, R., Cui, S., Monache, M. L. D., Bhadani, R. K., Bunting, M., Churchill, M., Hamilton, N. P., Haulcy, R., Pohlmann, H., Wu, F., et al. (2018) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2018.02.005 · Cited by 848

NEAR-MISS DETERMINATION THROUGH USE OF A SCALE OF DANGER

Hayward, J. C. (1972) · Highway Research Record · Cited by 706

Evaluating the safety impact of connected and autonomous vehicles on motorways

Papadoulis, A., Quddus, M., & Imprialou, M. (2019) · Accident Analysis & Prevention · doi:10.1016/j.aap.2018.12.019 · Cited by 480

Model Predictive Control of Vehicles on Urban Roads for Improved Fuel Economy

Kamal, M. A. S., Mukai, M., Murata, J., & Kawabe, T. (2012) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2012.2198478 · Cited by 451

2018 IEEE Intelligent Vehicles Symposium (IV)

(2018) · doi:10.1109/iv43497.2018 · Cited by 428

Automated Vehicles, On-Demand Mobility, and Environmental Impacts

Greenblatt, J. B., & Shaheen, S. (2015) · Current Sustainable/Renewable Energy Reports · doi:10.1007/s40518-015-0038-5 · Cited by 407

A high-resolution trajectory data driven method for real-time evaluation of traffic safety

Hu, Y., Li, Y., Huang, H., Lee, J. J., Chen, Y., & Zou, G. (2021) · Accident Analysis & Prevention · doi:10.1016/j.aap.2021.106503 · Cited by 163

Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model

Hosseinzadeh, A., Moeinaddini, A., & Ghasemzadeh, A. (2021) · Journal of Safety Research · doi:10.1016/j.jsr.2021.02.012 · Cited by 129

Characterizing car-following behaviors of human drivers when following automated vehicles using the real-world dataset

Wen, X. L., Cui, Z., & Jian, S. (2022) · Accident Analysis & Prevention · doi:10.1016/j.aap.2022.106689 · Cited by 118

The impacts of connected autonomous vehicles on mixed traffic flow: A comprehensive review

Pan, Y., Wu, Y., Xu, L., Xia, C., & Olson, D. L. (2024) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2023.129454 · Cited by 102

Human as AI mentor: Enhanced human-in-the-loop reinforcement learning for safe and efficient autonomous driving

Huang, Z., Sheng, Z., Ma, C., & Chen, S. (2024) · Communications in Transportation Research · doi:10.1016/j.commtr.2024.100127 · Cited by 88

Driver-Automated Vehicle Interaction in Mixed Traffic: Types of Interaction and Drivers’ Driving Styles

Ma, Z., & Zhang, Y. (2022) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208221088358 · Cited by 80

Collision-avoidance lane change control method for enhancing safety for connected vehicle platoon in mixed traffic environment

Ma, Y., Liu, Q., Fu, J., Liufu, K., & Li, Q. (2023) · Accident Analysis & Prevention · doi:10.1016/j.aap.2023.106999 · Cited by 71

Modeling the Effects of Autonomous Vehicles on Human Driver Car-Following Behaviors Using Inverse Reinforcement Learning

Wen, X. L., Jian, S., & He, D. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3298150 · Cited by 66

Car-Following Behavior of Human-Driven Vehicles in Mixed-Flow Traffic: A Driving Simulator Study

Zhou, A., Liu, Y., Tenenboim, E., Agrawal, S., & Peeta, S. (2023) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2023.3257962 · Cited by 58

Decentralized cooperative crossing at unsignalized intersections via vehicle-to-vehicle communication in mixed traffic flows

Bifulco, G. N., Coppola, A., Petrillo, A., & Santini, S. (2022) · Journal of Intelligent Transportation Systems · doi:10.1080/15472450.2022.2124868 · Cited by 55

Real-Time Self-Adaptive Q-Learning Controller for Energy Management of Conventional Autonomous Vehicles

Fayyazi, M., Abdoos, M., Phan, D., Golafrouz, M., Jalili, M., Jazar, R. N., Langari, R., & Khayyam, H. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.119770 · Cited by 44

Real-time crash prediction for a long low-traffic volume corridor using corrected-impurity importance and semi-parametric generalized additive model

Bakhshi, A. K., & Ahmed, M. M. (2021) · Journal of Transportation Safety & Security · doi:10.1080/19439962.2021.1898069 · Cited by 44

Classification of autonomous vehicle crash severity: Solving the problems of imbalanced datasets and small sample size

Kuo, P.-F., Hsu, W.-T., Lord, D., & Putra, I. G. B. (2024) · Accident Analysis & Prevention · doi:10.1016/j.aap.2024.107666 · Cited by 51

Safety in higher level automated vehicles: Investigating edge cases in crashes of vehicles equipped with automated driving systems

Moradloo, N., Mahdinia, I., & Khattak, A. J. (2024) · Accident Analysis & Prevention · doi:10.1016/j.aap.2024.107607 · Cited by 47

Understanding how relationships between crash frequency and correlates vary for multilane rural highways: Estimating geographically and temporally weighted regression models

Mohammadnazar, A., Mahdinia, I., Ahmad, N., Khattak, A. J., & Liu, J. (2021) · Accident Analysis & Prevention · doi:10.1016/j.aap.2021.106146 · Cited by 42

Characterizing Behavioral Differences of Autonomous Vehicles and Human-Driven Vehicles at Signalized Intersections Based on Waymo Open Dataset

Wang, Y., Farah, H., Yu, R., Qiu, S., & van Arem, B. (2023) · Transportation Research Record Journal of the Transportation Research Board · doi:10.1177/03611981231165783 · Cited by 35

Interaction-Aware and Driving Style-Aware Trajectory Prediction for Heterogeneous Vehicles in Mixed Traffic Environment

Zhang, Q., Xing, Y., Wang, J., Fang, Z., Liu, Y., & Yin, G. (2025) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2025.3553697 · Cited by 35

Large Car-Following Data Based on Lyft Level-5 Open Dataset: Following Autonomous Vehicles vs. Human-Driven Vehicles

Li, G., Jiao, Y., Knoop, V. L., Calvert, S. C., & van Lint, H. (2023) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc57777.2023.10422574 · Cited by 32

Bayesian extreme value analysis of kinematic-based surrogate measure of safety to detect crash-prone conditions in connected vehicles environment: A driving simulator experiment

Bakhshi, A. K., & Ahmed, M. M. (2022) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2021.103539 · Cited by 27

Evaluate the Connected Autonomous Vehicles Infrastructure using Digital Twin Model Based on Cyber-Physical Combination of Intelligent Network

Shoukat, M. U., Yu, S., Shi, S., Li, Y., & Yu, J. (2021) · CAA International Conference on Vehicular Control and Intelligence (CVCI) · doi:10.1109/cvci54083.2021.9661190 · Cited by 31

Manual drivers’ experience and driving behavior in repeated interactions with automated Level 3 vehicles in mixed traffic on the highway

Stange, V., Kuhn, M. G., & Vollrath, M. (2022) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2022.04.019 · Cited by 31

Techniques and Models for Addressing Occupational Risk Using Fuzzy Logic, Neural Networks, Machine Learning, and Genetic Algorithms: A Review and Meta-Analysis

Mitrakas, C., Xanthopoulos, A. S., & Koulouriotis, D. E. (2025) · Applied Sciences · doi:10.3390/app15041909 · Cited by 40

Autonomous Vehicles in Mixed Traffic Conditions—A Bibliometric Analysis

Azam, M., Hassan, S. A., & Puan, O. C. (2022) · Sustainability · doi:10.3390/su141710743 · Cited by 30

Evidence on impacts of automated vehicles on traffic flow efficiency and emissions: Systematic review

Aittoniemi, E. (2022) · IET Intelligent Transport Systems · doi:10.1049/itr2.12219 · Cited by 30

Road safety under the environment of intelligent connected vehicles

Lee, J. J., Huang, H., Wang, J., & Quddus, M. (2022) · Accident Analysis & Prevention · doi:10.1016/j.aap.2022.106645 · Cited by 28

Environmental impact estimation of mixed traffic flow involving CAVs and Human-driven vehicles considering the non-equilibrium state

Ge, Y., Jiang, R., Sun, H., Gao, Z., Liu, J., & Wang, J. (2024) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2024.104542 · Cited by 26

Divergent Effects of Factors on Crash Severity under Autonomous and Conventional Driving Modes Using a Hierarchical Bayesian Approach

Ren, W., Yu, B., Chen, Y., & Gao, K. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph191811358 · Cited by 25

Incorporating driving volatility measures in safety performance functions: Improving safety at signalized intersections

Mohammadnazar, A., Patwary, A. L., Moradloo, N., Arvin, R., & Khattak, A. J. (2022) · Accident Analysis & Prevention · doi:10.1016/j.aap.2022.106872 · Cited by 25

Examining pedestrians’ trust in automated vehicles based on attributes of trust: A qualitative study

Zhou, S., Sun, X., Wang, Q., Liu, B., & Burnett, G. (2023) · Applied Ergonomics · doi:10.1016/j.apergo.2023.103997 · Cited by 25

Characterizing the driving behavior of manual vehicles following autonomous vehicles and its impact on mixed traffic performance

Young, J. O., Jung, A., Oh, C. H., & Park, J.-H. (2024) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2024.08.028 · Cited by 24

Analyzing the short- and long-term car-following behavior in multiple factor coupled scenarios

Zong, F., Wang, S., Qin, Y., & Zeng, M. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.126724 · Cited by 24

A new framework for modelling traffic conflict interval time based on correlated random parameter duration model with heterogeneity in means and variances

Li, G., Ji, S., Cheng, W., Wang, W., Yan, X., Yang, Z., Yang, Y., & Zhang, J. (2025) · Accident Analysis & Prevention · doi:10.1016/j.aap.2025.108282 · Cited by 24

The role of drivers’ social interactions in their driving behavior: Empirical evidence and implications for car-following and traffic flow

Mohammadi, S., Arvin, R., Khattak, A. J., & Chakraborty, S. (2021) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2021.04.002 · Cited by 24

Modeling and analysis of mixed traffic flow capacity and stability considering human-driven vehicle drivers' trust attitude towards intelligent connected vehicles

Chen, Y., Li, K., Zhang, L., Chen, Y., & Xiao, X. Q. (2023) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2023.129486 · Cited by 24

Driver behavioural adaptations to simulated automated vehicles, potential implications for traffic microsimulation

de Zwart, R., Kamphuis, K., & Cleij, D. (2022) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2022.11.012 · Cited by 23

Freeway capacity modeling and analysis for traffic mixed with human-driven and connected automated vehicles considering driver behavior characteristics

Guo, M., Bai, Y., Li, X., Zhou, W., Wang, C., Ma, X., Gao, H., & Xiao, Y. (2023) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2023.128894 · Cited by 22

Lateral conflict resolution data derived from Argoverse-2: Analysing safety and efficiency impacts of autonomous vehicles at intersections

Li, G., Jiao, Y., Calvert, S. C., & van Lint, H. (2024) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2024.104802 · Cited by 21

Estimating Freeway Level-of-Service Using Crowdsourced Data

Hoseinzadeh, N., Gu, Y., Han, L. D., Brakewood, C., & Freeze, P. B. (2021) · Informatics · doi:10.3390/informatics8010017 · Cited by 21

Traffic safety evaluation of emerging mixed traffic flow at freeway merging area considering driving behavior

He, Y., Xiang, D., & Wang, D. (2025) · Scientific Reports · doi:10.1038/s41598-025-94658-y · Cited by 20

Mining dockless bikeshare data for insights into cyclist behavior and preferences: Evidence from the Boston region

Sadeghinasr, B., Akhavan, A., Furth, P. G., Gehrke, S. R., Wang, Q., & Reardon, T. G. (2021) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2021.103044 · Cited by 20

Greater prosociality toward other human drivers than autonomous vehicles: Human drivers’ discriminatory behavior in mixed traffic

Sun, H., Ge, Y., & Qu, W. (2024) · Accident Analysis & Prevention · doi:10.1016/j.aap.2024.107623 · Cited by 20

Existence of connected and autonomous vehicles in mixed traffic: Impacts on safety and environment

Wei, S., & Shao, M. (2024) · Traffic Injury Prevention · doi:10.1080/15389588.2023.2291337 · Cited by 19

Evaluation of Autonomous Driving Safety by Operational Design Domains (ODD) in Mixed Traffic

Kim, H., Ko, J., Oh, C., & Kim, S. (2024) · Sustainability · doi:10.3390/su16229672 · Cited by 18

Beyond behavioural change: Investigating alternative explanations for shorter time headways when human drivers follow automated vehicles

Jiao, Y., Li, G., Calvert, S. C., van Cranenburgh, S., & van Lint, H. (2024) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2024.104673 · Cited by 19

Characterizing Human–Automated Vehicle Interactions: An Investigation into Car-Following Behavior

Zhang, Y., & Talebpour, A. (2023) · Transportation Research Record Journal of the Transportation Research Board · doi:10.1177/03611981231192999 · Cited by 16

Scalable evaluation methods for autonomous vehicles

Zhou, J., Wang, L., & Wang, X. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.123603 · Cited by 16

Assessing the impact of passenger compliance behavior in CAVs on environmental benefits

Xu, Z., Zheng, Z., Xiao, D., Tu, R., Ma, W., & Zheng, N. (2024) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2024.104278 · Cited by 17

Sharing the Road: How Human Drivers Interact with Autonomous Vehicles on Highways

Huang, C., Wen, X. L., He, D., & Jian, S. (2022) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181322661165 · Cited by 16

Analysis of discretionary lane-changing behaviours of autonomous vehicles based on real-world data

Wen, X. L., Huang, C., Jian, S., & He, D. (2023) · Transportmetrica A Transport Science · doi:10.1080/23249935.2023.2288636 · Cited by 15

Does recognizability of connected and automated vehicles (CAVs) platoons affect drivers’ behavior and safety?

Sultana, T., & Hassan, H. M. (2024) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2024.04.021 · Cited by 15

Comparing Car-Following Behavior Patterns of Human-Driven Vehicles and Autonomous Vehicles in a Mixed Traffic Environment

Tang, S., Zou, Y., Wu, S., Xie, Y., & Zhang, Y. (2025) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2025.3539757 · Cited by 15

Distributed Nonlinear Model Predictive Control for Heterogeneous Vehicle Platoons Under Uncertainty

Shen, D., Yin, J., Du, X., & Li, L. (2021) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc48978.2021.9565017 · Cited by 15

Effect of autonomous vehicles on car-following behavior of human drivers: Analysis based on structural equation models

Li, X., You, Z., Ma, X., Pang, X., Min, X., & Cui, H. (2023) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2023.129360 · Cited by 14

Autonomous and Human-Driven Vehicles Interacting in a Roundabout: A Quantitative and Qualitative Evaluation

Ferrarotti, L., Luca, M., Santin, G., Previati, G., Mastinu, G. R. M., Gobbi, M., Campi, E., Uccello, L., Albanese, A., Zalaya, P., et al. (2024) · IEEE Access · doi:10.1109/access.2024.3370469 · Cited by 17

Adaptive cruise control design for collision risk avoidance

Jiang, Y., Cong, H., Chen, H., Wu, Y., & Yao, Z. (2024) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2024.129724 · Cited by 14

Energy and Environmental Implications of Automated Vehicles Under Mixed Autonomy Traffic Environment

Wang, Z., Cheng, Q., Liu, P., Yu, W., Wang, J., & Liu, Z. (2024) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2024.3425532 · Cited by 14

How is the duration of distraction related to safety–critical events? Harnessing naturalistic driving data to explore the role of driving instability

Ahmad, N., Arvin, R., & Khattak, A. J. (2023) · Journal of Safety Research · doi:10.1016/j.jsr.2023.01.003 · Cited by 14

Social interactions between automated vehicles and human drivers: a narrative review

Liu, P. (2024) · Ergonomics · doi:10.1080/00140139.2024.2435038 · Cited by 13

Comparative analysis of drowsiness and performance in conditionally automated driving and manual driving considering the effect of circadian rhythm

Zhang, Q., Wu, C., Zhang, H., & Ferreira, S. (2022) · Journal of Intelligent Transportation Systems · doi:10.1080/15472450.2022.2130292 · Cited by 12

Experimental and numerical study on the crashworthiness performance of a hybrid energy absorber with expanding–splitting–bending process

Li, J., Xie, Z., Yu, Y., Gong, X., & Gao, G. (2022) · Thin-Walled Structures · doi:10.1016/j.tws.2022.110122 · Cited by 11

Understanding Human-machine Cooperation in Game-theoretical Driving Scenarios amid Mixed Traffic

Zhang, Y., Awad, E., Frank, M. R., Liu, P., & Du, N. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642053 · Cited by 10

Research Challenges in Self-Driving Vehicle by Using Internet of Things (IoT)

Krishna, K., Karumuri, N., Christopher, C., & Jayapandian, N. (2021) · International Conference on Intelligent Computing and Control Systems (ICICCS) · doi:10.1109/iciccs51141.2021.9432147 · Cited by 10

Learning in Mixed Traffic: Drivers’ Adaptation to Ambiguous Communication Depending on Their Expectations toward Automated and Manual Vehicles

Miller, L., Kraus, J., Koniakowsky, I. M., Pichen, J., & Baumann, M. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2215097 · Cited by 10

Merging Control in Mixed Traffic with Safety Guarantees: A Safe Sequencing Policy with Optimal Motion Control

Sabouni, E., Ahmad, H. M. S., Cassandras, C. G., & Li, W. (2023) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc57777.2023.10422265 · Cited by 9

Microscopic Right-of-Way Trading Mechanism for Cooperative Decision-Making: Theories and Preliminary Results

Sun, Z., Qin, Z., Ma, R., Huang, T., Gao, Z., & Ji, A. (2024) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2024.3498870 · Cited by 9

Environmental impacts and emission reduction methods of vehicles equipped with driving automation systems: An operational-level review

Jiang, H., Xia, K., Zhao, Y., Yao, Z., Jiang, Y., & He, Z. (2025) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2024.104996 · Cited by 8

Human-machine cooperation strategies in game-theoretic scenarios within mixed traffic: A simulator study on driving styles

Zhang, Y., Wu, S., Mubbala, D., & Du, N. (2025) · Accident Analysis & Prevention · doi:10.1016/j.aap.2025.108254 · Cited by 8

A sequel to “Comprehensive analysis of single- and multi-vehicle large truck at-fault crashes on rural and urban roadways in Alabama”: Accounting for temporal instability in crash factors

Biglari, S., Adanu, E. K., & Jones, S. L. (2024) · Accident Analysis & Prevention · doi:10.1016/j.aap.2024.107723 · Cited by 7

Decision-Making of Drivers Following Autonomous Vehicles: Developing a Bayesian Network on the Basis of Field Tests and Questionnaire Data

Zong, F., Huan, W., Zeng, M., Kim, W., Bai, Q., Gong, Y., Duan, R., & Guo, Y. (2025) · Journal of Intelligent and Connected Vehicles · doi:10.26599/jicv.2025.9210057 · Cited by 8

ST-GraphNet: A Spatio-Temporal Graph Neural Network for Understanding and Predicting Automated Vehicle Crash Severity

Mimi, M. S., Islam, M. M., Tusti, A. G., Somvanshi, S., Das, S., & Ye, X. (2025) · doi:10.1145/3764924.3770894 · Cited by 7

Conflict resolution behavior of autonomous vehicles at intersections under mixed traffic environment

Ashraf, M. T., & Dey, K. C. (2024) · Accident Analysis & Prevention · doi:10.1016/j.aap.2024.107897 · Cited by 7

Pattern recognition in crash clusters involving vehicles with advanced driving technologies

Tamakloe, R., Khorasani, M., Das, S., & Kim, I. (2025) · Accident Analysis & Prevention · doi:10.1016/j.aap.2025.108072 · Cited by 7

Influence factors and model selection for conflict risk in different car-following behaviors: Insights from automated and human-driven vehicles

Yang, M., Yang, X., Mu, C., & Zhu, S. (2025) · Accident Analysis & Prevention · doi:10.1016/j.aap.2025.108286 · Cited by 6

Influence of traffic context and information presentation on evaluation of autonomous highway journeys

Ritchie, O. T., Watson, D. G., Griffiths, N., Xu, Z., & Mouzakitis, A. (2021) · Accident Analysis & Prevention · doi:10.1016/j.aap.2021.106385 · Cited by 6

Resilience of connected and autonomous vehicles to cyber–physical disruptions

Murali, P. S., Mohebbi, S., & Zaman, M. (2025) · SIMULATION · doi:10.1177/00375497241308575 · Cited by 5

Spatial Agent-Based Simulation of Connected and Autonomous Vehicles to Assess Impacts on Traffic Conditions

Mohebbi, S., & Murali, P. S. (2022) · Winter Simulation Conference · doi:10.1109/wsc57314.2022.10015452 · Cited by 5

Driving Next to Automated Vehicles: Emergent Human-machine Cooperation in Mixed Traffic

Zhang, Y., Ling, S., Awad, E., Frank, M. R., & Du, N. (2023) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3544549.3585690 · Cited by 5

Mitigating delay due to capacity drop near freeway bottlenecks: Zones of influence of connected vehicles

Jerath, K., Gayah, V. V., & Brennan, S. (2024) · PLoS ONE · doi:10.1371/journal.pone.0301188 · Cited by 5

Effects of connected vehicle (CV) technology on improving driver behavior in the presence of connected and automated vehicle (CAV) platoons

Sultana, T., & Hassan, H. M. (2025) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2025.01.046 · Cited by 5

Emerging Behavioral Adaptation of Human-Driven Vehicles in Interactions with Automated Vehicles: Insights from a Microsimulation Study

Saljoqi, M., Ceccato, R., Orsini, F., Rossi, R., & Gastaldi, M. (2025) · Future Transportation · doi:10.3390/futuretransp5030124 · Cited by 3

Are we ready for highly automated vehicles? Evaluating automated driving systems’ safety and reliability using inverse probability weighted regression adjustment

Adeel, M., Khattak, A. J., Usman, S. M., & Moradloo, N. (2026) · Journal of Intelligent Transportation Systems · doi:10.1080/15472450.2025.2602132 · Cited by 6

Characterizing Heterogeneous Car-Following Behaviors of Human Drivers in Mixed Traffic

Sun, M., Huang, C., & He, D. (2024) · IEEE International Conference on Human-Machine Systems (ICHMS) · doi:10.1109/ichms59971.2024.10555751 · Cited by 4

Exploring HDV Driver–CAV Interaction in Mixed Traffic: A Two-Step Method Integrating Latent Profile Analysis and Multinomial Logit Model

Kong, D., Wang, M., Zhang, K., Sun, L., Wang, Q., & Zhang, X. (2024) · Applied Sciences · doi:10.3390/app14051768 · Cited by 4

A recursive framework of vehicle trajectory planning at mixed‐traffic signalized intersections

Yang, M., Yu, H., & Liu, P. (2024) · IET Intelligent Transport Systems · doi:10.1049/itr2.12544 · Cited by 3

A review of vehicle lane change decisions in human–machine mixed driving environments

Huang, Z., Fang, H., Lin, Y., & Hu, X. (2025) · Digital Transportation and Safety · doi:10.48130/dts-0025-0028 · Cited by 3

Exploitation of String Stability to Predict Disturbance-triggered Platoon Collisions in Mixed Traffic Comprising Automated and Conventional Vehicles

Jia, S., Cai, Y., Pei, X., Yang, Z., Wong, W. H., & Wong, S. C. (2023) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc57777.2023.10421906 · Cited by 3

A Multi-Agent Driving-Simulation Approach for Characterizing Hazardous Vehicle Interactions between Autonomous Vehicles and Manual Vehicles

Jung, A., Jo, Y., Oh, C. H., Park, J., & Yun, D. (2024) · Applied Sciences · doi:10.3390/app14041468 · Cited by 3

Worst-Case Response Time of Mixed Vehicles at Complex Intersections

Reddy, R., Almeida, L., Kurunathan, H., Gaitán, M. G., Santos, P. M., & Tovar, E. (2024) · IEEE Open Journal of Intelligent Transportation Systems · doi:10.1109/ojits.2024.3368797 · Cited by 3

L3-AVs Conflict Risk Prediction in Highway Maintenance Areas Using the CatBoost Model and SHAP Method Explanation

Liu, Q., Wang, R., Cai, Y., Xiong, X., & Chen, L. (2025) · Automotive Innovation · doi:10.1007/s42154-024-00319-7 · Cited by 2

Analyzing human-driven vehicles’ following behavior in response to autonomous vehicles under different traffic conditions

Zong, F., Zhao, K., Wu, H., Zhang, H. W., Zeng, M., & Tang, J.-J. (2026) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2026.131267 · Cited by 2

Calibration of car-following models of human driven vehicles interacting with automated vehicles in mixed traffic: a driving simulator experiment

Reddy, N., Hoogendoorn, S. P., & Farah, H. (2026) · Transportmetrica A Transport Science · doi:10.1080/23249935.2026.2629425 · Cited by 2

Behavioral adaptation of human drivers in car-following interactions with automated vehicles

Saljoqi, M., Orsini, F., Rossi, R., & Gastaldi, M. (2026) · Accident Analysis & Prevention · doi:10.1016/j.aap.2026.108514 · Cited by 2

Behavioral adaptation in mixed traffic: the roles of AV penetration rate and human driving style

Chen, H., Ma, Z., & Zhang, Y. (2026) · Accident Analysis & Prevention · doi:10.1016/j.aap.2026.108516 · Cited by 2

Impacts of automated vehicles on human-driving vehicle behaviors on highways: A Literature Review

Wu, J., Qiu, Z., Ding, N., & Zhang, H. (2023) · International Conference on Transportation Information and Safety · doi:10.1109/ictis60134.2023.10243693 · Cited by 2

Examining the Impact of Driving Styles of Automated Vehicles and Human Drivers on Driving Behavior: A Driving Simulator Study

Zhang, Y., Ye, B., Mubbala, D., & Du, N. (2024) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3641308.3685050 · Cited by 2

Optimal Safe Sequencing and Motion Control for Mixed Traffic Roundabouts

Chen, Y., & Cassandras, C. G. (2025) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc57313.2025.11312190 · Cited by 2

基于扩展计划行为理论的驾驶员跟驰意向分析

Xia, L. I., Mengting, G. U. O., ZHANG, X., Chuo, E., & Wei, Z. H. O. U. (2023) · JOURNAL OF SHENZHEN UNIVERSITY SCIENCE AND ENGINEERING · doi:10.3724/sp.j.1249.2023.01118 · Cited by 1

Dynamic Signal Timing Optimization for Left-Turn Maneuvers via V2I and V2V Communication

Herrera, P., Jagdish, A., & Liu, T. (2024) · doi:10.1109/gess63533.2024.10784563 · Cited by 1

Drivers' Perceptions of Front Brake Lights: A Statistical Analysis of Road Safety Benefits

Poliak, M., Frnda, J., Čulík, K., Banse, R., & Kirschbaum, B. (2025) · IET Intelligent Transport Systems · doi:10.1049/itr2.70089 · Cited by 1

Using a new algorithm in Machine learning Approaches to estimate level-of-service in hourly traffic flow data in vehicular ad hoc networks

Turki, A. I., & Hasson, S. T. (2023) · Tikrit Journal of Pure Science · doi:10.25130/tjps.v28i3.1428 · Cited by 1

The Estonian elections of 1992

Fitzmaurice, J. (1993) · Electoral Studies · doi:10.1016/0261-3794(93)90016-d · Cited by 7

Energy and Environmental Implications of Automated Vehicles Under Mixed Autonomy Traffic Environment

Wang, Z., Cheng, Q., Liu, P., Yu, W., Wang, J., & Liu, Z. (2024) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2024.3425532 · Cited by 14

Operational safety of automated and human driving in mixed traffic environments: A perspective of car-following behavior

Li, T., Han, X., Ma, J., Ramos, M. A., & Lee, C. (2021) · Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability · doi:10.1177/1748006x211050696 · Cited by 28

Beyond behavioural change: Investigating alternative explanations for shorter time headways when human drivers follow automated vehicles

Jiao, Y., Li, G., Calvert, S. C., van Cranenburgh, S., & van Lint, H. (2024) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2024.104673 · Cited by 19

Beyond Behaviour Change: Investigating Alternative Explanations for Shorter Time Headways When Human Drivers Follow Automated VehiclesPreprint

Jiao, Y., Li, G., Calvert, S. C., van Cranenburgh, S., & van Lint, H. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4713957