15.3.3.3.1 Lane Changing, Lane-Change, Analysis, Control

Nilsson, J., Brännström, M., Coelingh, E., Fredriksson, J.,
Lane Change Maneuvers for Automated Vehicles,
ITS(18), No. 5, May 2017, pp. 1087-1096.
IEEE DOI 1705
Planning, Prediction algorithms, Real-time systems, Road transportation, Safety, Trajectory, Vehicles, Autonomous driving, automated driving, lane change, model predictive control, trajectory, planning BibRef

Tao, P.[Peng], Zhi-Wei, G.[Guan], Rong-Hui, Z.[Zhang], Ling, H.[Huang], Hong-Guo, X.[Xu], Hong-Fei, L.[Liu],
Bifurcation of lane change on highway for large bus,
IET-ITS(11), No. 8, October 2017, pp. 475-484.
DOI Link 1710
BibRef

Nilsson, P., Laine, L., Jacobson, B.,
A Simulator Study Comparing Characteristics of Manual and Automated Driving During Lane Changes of Long Combination Vehicles,
ITS(18), No. 9, September 2017, pp. 2514-2524.
IEEE DOI 1709
braking, motion control, optimisation, road traffic control, driver acceptance, driver behavior, driver model control, lane changes, lane-change maneuvers, long combination vehicles, manual driving, moving-base truck driving simulator, safety-critical lane-change scenario, steering behavior, Automated highway vehicle, driving simulator, heavy-duty vehicle, BibRef

Lee, S.[Seolyoung], Oh, C.[Cheol], Hong, S.[Sungmin],
Exploring lane change safety issues for manually driven vehicles in vehicle platooning environments,
IET-ITS(12), No. 9, November 2018, pp. 1142-1147.
DOI Link 1810
BibRef

Guo, J.H.[Jing-Hua], Luo, Y.[Yugong], Li, K.Q.A.[Ke-Qi-Ang],
Adaptive non-linear trajectory tracking control for lane change of autonomous four-wheel independently drive electric vehicles,
IET-ITS(12), No. 7, September 2018, pp. 712-720.
DOI Link 1808
BibRef

Jiang, H.B.[Hao-Bin], Shi, K.J.[Kai-Jin], Cai, J.Y.[Jun-Yu], Chen, L.[Long],
Trajectory planning and optimisation method for intelligent vehicle lane changing emergently,
IET-ITS(12), No. 10, December 2018, pp. 1336-1344.
DOI Link 1812
BibRef

Muslim, H., Itoh, M.,
Effects of Human Understanding of Automation Abilities on Driver Performance and Acceptance of Lane Change Collision Avoidance Systems,
ITS(20), No. 6, June 2019, pp. 2014-2024.
IEEE DOI 1906
Vehicles, Automation, Wheels, Collision avoidance, Hazards, Accidents, Driver assistance systems, automation, control, system design BibRef

Li, X., Wang, W., Roetting, M.,
Estimating Driver's Lane-Change Intent Considering Driving Style and Contextual Traffic,
ITS(20), No. 9, September 2019, pp. 3258-3271.
IEEE DOI 1909
Vehicles, Labeling, Estimation, Lead, Bayes methods, Gaussian mixture model, Lane-change intent estimation, driving style BibRef

Yang, S., Wang, W., Lu, C., Gong, J., Xi, J.,
A Time-Efficient Approach for Decision-Making Style Recognition in Lane-Changing Behavior,
HMS(49), No. 6, December 2019, pp. 579-588.
IEEE DOI 1912
Nearest neighbor methods, Decision making, Clustering algorithms, Morphology, Support vector machines, Accuracy, mathematical morphology BibRef

Cao, P.[Peng], Xu, Z.D.[Zhan-Dong], Fan, Q.C.[Qiao-Chu], Liu, X.B.[Xiao-Bo],
Analysing driving efficiency of mandatory lane change decision for autonomous vehicles,
IET-ITS(13), No. 3, March 2019, pp. 506-514.
DOI Link 1903
BibRef

Deng, Q., Wang, J., Hillebrand, K., Benjamin, C.R., Söffker, D.,
Prediction Performance of Lane Changing Behaviors: A Study of Combining Environmental and Eye-Tracking Data in a Driving Simulator,
ITS(21), No. 8, August 2020, pp. 3561-3570.
IEEE DOI 2008
Hidden Markov models, Vehicles, Support vector machines, Radio frequency, Predictive models, Machine learning, and advanced driver assistance systems BibRef

Nie, Z.G.[Zhi-Gen], Li, Z.L.[Zhong-Liang], Wang, W.Q.[Wan-Qiong], Zhao, W.Q.A.[Wei-Qi-Ang], Lian, Y.F.[Yu-Feng], Outbib, R.[Rachid],
Gain-scheduling control of dynamic lateral lane change for automated and connected vehicles based on the multipoint preview,
IET-ITS(14), No. 10, October 2020, pp. 1338-1349.
DOI Link 2009
BibRef

Zheng, Y., Ran, B., Qu, X., Zhang, J., Lin, Y.,
Cooperative Lane Changing Strategies to Improve Traffic Operation and Safety Nearby Freeway Off-Ramps in a Connected and Automated Vehicles Environment,
ITS(21), No. 11, November 2020, pp. 4605-4614.
IEEE DOI 2011
Road transportation, Safety, Merging, Acceleration, Oscillators, Automobiles, Freeway off-ramps, collision risk BibRef

Zheng, Y.[Yuan], Ding, W.T.[Wan-Ting], Ran, B.[Bin], Qu, X.[Xu], Zhang, Y.[Yu],
Coordinated decisions of discretionary lane change between connected and automated vehicles on freeways: a game theory-based lane change strategy,
IET-ITS(14), No. 13, 15 December 2020, pp. 1864-1870.
DOI Link 2102
BibRef

Jin, H.[Hao], Duan, C.G.[Chun-Guang], Liu, Y.[Yang], Lu, P.P.[Ping-Ping],
Gauss mixture hidden Markov model to characterise and model discretionary lane-change behaviours for autonomous vehicles,
IET-ITS(14), No. 5, May 2020, pp. 401-411.
DOI Link 2005
BibRef

Ma, Y.L.[Yan-Li], Yin, B.Q.[Bi-Qing], Jiang, X.C.[Xian-Cai], Du, J.[Jankun], Chan, C.Y.[Ching-Yao],
Psychological and environmental factors affecting driver's frequent lane-changing behaviour: a national sample of drivers in China,
IET-ITS(14), No. 8, August 2020, pp. 825-833.
DOI Link 2007
BibRef

Zhou, X.C.[Xiao-Chuan], Kuang, D.[Dengming], Zhao, W.[Wanzhong], Xu, C.[Can], Feng, J.[Jian], Wang, C.Y.[Chun-Yan],
Lane-changing decision method based Nash Q-learning with considering the interaction of surrounding vehicles,
IET-ITS(14), No. 14, 27 December 2020, pp. 2064-2072.
DOI Link 2103
BibRef

Liu, X.[Xiao], Liang, J.[Jun], Zhang, H.[Hua],
Dynamic motion planner with trajectory optimisation for automated highway lane-changing driving,
IET-ITS(14), No. 14, 27 December 2020, pp. 2133-2140.
DOI Link 2103
BibRef

Lu, C., Hu, F., Cao, D., Gong, J., Xing, Y., Li, Z.,
Transfer Learning for Driver Model Adaptation in Lane-Changing Scenarios Using Manifold Alignment,
ITS(21), No. 8, August 2020, pp. 3281-3293.
IEEE DOI 2008
Adaptation models, Vehicles, Data models, Manifolds, Principal component analysis, Dimensionality reduction, Wheels, local Procrustes analysis BibRef

Chen, Q.Y.[Qing-Yun], Zhao, W.Z.[Wan-Zhong], Xu, C.[Can], Wang, C.Y.[Chun-Yan], Li, L.[Lin], Dai, S.J.[Shi-Juan],
An Improved IOHMM-Based Stochastic Driver Lane-Changing Model,
HMS(51), No. 3, June 2021, pp. 211-220.
IEEE DOI 2106
Hidden Markov models, Vehicles, Data models, Wheels, Trajectory, Probability distribution, Predictive models, stochastic model BibRef

Li, X.Y.[Xian-Yu], Guo, Z.Y.[Zhong-Yin], Su, D.L.[Dong-Lan], Liu, Q.[Qiang],
Time-dependent lane change trajectory optimisation considering comfort and efficiency for lateral collision avoidance,
IET-ITS(15), No. 5, 2021, pp. 595-605.
DOI Link 2106
BibRef

Zhang, B.[Bo], Zhang, J.W.[Jian-Wei], Liu, Y.[Yang], Guo, K.[Konghui], Ding, H.T.[Hai-Tao],
Planning flexible and smooth paths for lane-changing manoeuvres of autonomous vehicles,
IET-ITS(15), No. 2, 2021, pp. 200-212.
DOI Link 2106
BibRef

Hu, Z.Y.[Zhan-Yi], Yang, Z.[Zeyu], Huang, J.[Jin], Zhong, Z.H.[Zhi-Hua],
Safety guaranteed longitudinal motion control for connected and autonomous vehicles in a lane-changing scenario,
IET-ITS(15), No. 2, 2021, pp. 344-358.
DOI Link 2106
BibRef

Zhao, C.[Can], Li, Z.H.[Zhi-Heng], Li, L.[Li], Wu, X.B.[Xiang-Bin], Wang, F.Y.[Fei-Yue],
A negotiation-based right-of-way assignment strategy to ensure traffic safety and efficiency in lane changes,
IET-ITS(15), No. 11, 2021, pp. 1345-1358.
DOI Link 2110
BibRef

Zhu, B.[Bing], Han, J.[Jiayi], Zhao, J.[Jian], Wang, H.[Huaji],
Combined Hierarchical Learning Framework for Personalized Automatic Lane-Changing,
ITS(22), No. 10, October 2021, pp. 6275-6285.
IEEE DOI 2110
Vehicles, Artificial neural networks, Safety, Logic gates, Learning systems, Trajectory, Wheels, safety field BibRef

Ji, A.[Ang], Levinson, D.[David],
Estimating the Social Gap With a Game Theory Model of Lane Changing,
ITS(22), No. 10, October 2021, pp. 6320-6329.
IEEE DOI 2110
Games, Vehicle crash testing, Game theory, Mathematical model, Safety, Automobiles, Discretionary lane changing, game theory, social dilemma BibRef

Nie, G.M.[Guang-Ming], Xie, B.[Bo], Lu, H.Q.[Hui-Qiu], Tian, Y.[Yantao],
A cooperative lane change approach for heterogeneous platoons under different communication topologies,
IET-ITS(16), No. 1, 2022, pp. 53-70.
DOI Link 2112
BibRef

Gim, S.[Suhyeon], Lee, S.[Sukhan], Adouane, L.[Lounis],
Safe and Efficient Lane Change Maneuver for Obstacle Avoidance Inspired From Human Driving Pattern,
ITS(23), No. 3, March 2022, pp. 2155-2169.
IEEE DOI 2203
Collision avoidance, Vehicles, Roads, Boundary conditions, Turning, Wheels, Trajectory, Continuous curvature path, passenger comfort BibRef

Zhang, H.J.[Hong-Jia], Guo, Y.[Yingshi], Wang, C.[Chang], Fu, R.[Rui],
Stacking-based ensemble learning method for the recognition of the preceding vehicle lane-changing manoeuvre: A naturalistic driving study on the highway,
IET-ITS(16), No. 4, 2022, pp. 489-503.
DOI Link 2203
BibRef

Mahajan, V.[Vishal], Katrakazas, C.[Christos], Antoniou, C.[Constantinos],
Crash Risk Estimation Due to Lane Changing: A Data-Driven Approach Using Naturalistic Data,
ITS(23), No. 4, April 2022, pp. 3756-3765.
IEEE DOI 2204
Accidents, Vehicles, Estimation, Safety, Automobiles, Vehicle dynamics, Real-time systems, Crash risk, lane changing, naturalistic data BibRef

Chen, R.[Rui], Cassandras, C.G.[Christos G.], Tahmasbi-Sarvestani, A.[Amin], Saigusa, S.[Shigenobu], Mahjoub, H.N.[Hossein Nourkhiz], Al-Nadawi, Y.K.[Yasir Khudhair],
Cooperative Time and Energy-Optimal Lane Change Maneuvers for Connected Automated Vehicles,
ITS(23), No. 4, April 2022, pp. 3445-3460.
IEEE DOI 2204
Optimal control, Trajectory, Safety, Minimization, Acceleration, Transportation, Research and development, Autonomous vehicles, optimal control BibRef

Wang, G.[Guan], Hu, J.M.[Jian-Ming], Li, Z.H.[Zhi-Heng], Li, L.[Li],
Harmonious Lane Changing via Deep Reinforcement Learning,
ITS(23), No. 5, May 2022, pp. 4642-4650.
IEEE DOI 2205
Reinforcement learning, Vehicle-to-everything, Space vehicles, Sensors, Roads, Mathematical model, Delays, Lane changing, deep learning BibRef

Fan, J.[Jiayu], Liang, J.[Jun], Tula, A.K.[Anjan K.],
A lane changing time point and path tracking framework for autonomous ground vehicle,
IET-ITS(16), No. 7, 2022, pp. 860-874.
DOI Link 2206
BibRef

Mehr, G.[Goodarz], Eskandarian, A.[Azim],
Estimating the Probability That a Vehicle Reaches a Near-Term Goal State Using Multiple Lane Changes,
ITS(23), No. 6, June 2022, pp. 5326-5337.
IEEE DOI 2206
Predictive models, Autonomous vehicles, Roads, Random variables, Mathematical model, Vehicles, Navigation, Lane change, autonomous vehicles BibRef

Song, R.[Ruitao], Li, B.[Bin],
Surrounding Vehicles' Lane Change Maneuver Prediction and Detection for Intelligent Vehicles: A Comprehensive Review,
ITS(23), No. 7, July 2022, pp. 6046-6062.
IEEE DOI 2207
Intelligent vehicles, Autonomous vehicles, Safety, Sensors, Hidden Markov models, Accidents, Predictive models, driver intention BibRef

Zhang, C.Y.[Cheng-Yuan], Zhu, J.C.[Jia-Cheng], Wang, W.[Wenshuo], Xi, J.Q.[Jun-Qiang],
Spatiotemporal Learning of Multivehicle Interaction Patterns in Lane-Change Scenarios,
ITS(23), No. 7, July 2022, pp. 6446-6459.
IEEE DOI 2207
Hidden Markov models, Bayes methods, Space vehicles, Vehicle dynamics, Spatiotemporal phenomena, Autonomous vehicles, Bayesian nonparametrics BibRef

Griesbach, K.[Karoline], Beggiato, M.[Matthias], Hoffmann, K.H.[Karl Heinz],
Lane Change Prediction With an Echo State Network and Recurrent Neural Network in the Urban Area,
ITS(23), No. 7, July 2022, pp. 6473-6479.
IEEE DOI 2207
Reservoirs, Neurons, Input variables, Vehicles, Urban areas, Recurrent neural networks, Roads, Echo state network, urban area BibRef

Cong, S.[Sensen], Wang, W.[Wensa], Liang, J.[Jun], Chen, L.[Long], Cai, Y.F.[Ying-Feng],
An Automatic Vehicle Avoidance Control Model for Dangerous Lane-Changing Behavior,
ITS(23), No. 7, July 2022, pp. 8477-8487.
IEEE DOI 2207
Hidden Markov models, Collision avoidance, Neural networks, Predictive models, Trajectory, Wheels, Stability criteria, back propagation neural network BibRef

Liu, Y.G.[Yong-Gang], Zhou, B.[Bobo], Wang, X.[Xiao], Li, L.[Liang], Cheng, S.[Shuo], Chen, Z.[Zheng], Li, G.[Guang], Zhang, L.[Lu],
Dynamic Lane-Changing Trajectory Planning for Autonomous Vehicles Based on Discrete Global Trajectory,
ITS(23), No. 7, July 2022, pp. 8513-8527.
IEEE DOI 2207
Trajectory, Vehicle dynamics, Planning, Autonomous vehicles, Trajectory planning, Safety, Roads, Autonomous vehicle, discrete global trajectory BibRef

Mehr, G.[Goodarz], Eskandarian, A.[Azim],
Sentinel: An Onboard Lane Change Advisory System for Intelligent Vehicles to Reduce Traffic Delay During Freeway Incidents,
ITS(23), No. 7, July 2022, pp. 8906-8917.
IEEE DOI 2207
Traffic control, Predictive models, Roads, Delays, Intelligent vehicles, Accidents, Data models, Freeway incident, traffic simulation BibRef

Chen, B.[Baiming], Chen, X.[Xiang], Wu, Q.[Qiong], Li, L.[Liang],
Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios,
ITS(23), No. 8, August 2022, pp. 10333-10342.
IEEE DOI 2208
Autonomous vehicles, Accidents, Databases, Reinforcement learning, Training, Testing, Safety, Autonomous vehicle, vehicle evaluation, unsupervised learning BibRef

Sharma, S.[Salil], Papamichail, I.[Ioannis], Nadi, A.[Ali], van Lint, H.[Hans], Tavasszy, L.[Lóránt], Snelder, M.[Maaike],
A Multi-Class Lane-Changing Advisory System for Freeway Merging Sections Using Cooperative ITS,
ITS(23), No. 9, September 2022, pp. 15121-15132.
IEEE DOI 2209
Merging, Traffic control, Microscopy, Intelligent transportation systems, cooperative intelligent transportation system BibRef

Chen, Y.Y.[Yao-Yu], Li, G.F.[Guo-Fa], Li, S.[Shen], Wang, W.J.[Wen-Jun], Li, S.B.E.[Sheng-Bo Eben], Cheng, B.[Bo],
Exploring Behavioral Patterns of Lane Change Maneuvers for Human-Like Autonomous Driving,
ITS(23), No. 9, September 2022, pp. 14322-14335.
IEEE DOI 2209
Vehicles, Hidden Markov models, Data models, Bayes methods, Data mining, Autonomous vehicles, Analytical models, Bayesian methods BibRef

Li, S.[Shurong], Wei, C.[Chong], Wang, Y.[Ying],
Combining Decision Making and Trajectory Planning for Lane Changing Using Deep Reinforcement Learning,
ITS(23), No. 9, September 2022, pp. 16110-16136.
IEEE DOI 2209
Decision making, Trajectory planning, Trajectory, Vehicles, Reinforcement learning, Planning, Safety, Decision making, safety action set technique BibRef

Daoud, M.A.[Mohamed A.], Mehrez, M.W.[Mohamed W.], Rayside, D.[Derek], Melek, W.W.[William W.],
Simultaneous Feasible Local Planning and Path-Following Control for Autonomous Driving,
ITS(23), No. 9, September 2022, pp. 16358-16370.
IEEE DOI 2209
Planning, Roads, Vehicle dynamics, Task analysis, Tires, Predictive models, Decision making, Model predictive control, double-lane change BibRef

Wang, Y.[Ying], Wei, C.[Chong], Li, S.[Shurong],
QPNet: Lane-changing trajectory planning combining quadratic programming and neural network under the convex optimization framework,
IET-ITS(16), No. 11, 2022, pp. 1578-1599.
DOI Link 2210
BibRef

Yuan, T.C.[Tian-Chen], Alasiri, F.[Faisal], Ioannou, P.A.[Petros A.],
Selection of the Speed Command Distance for Improved Performance of a Rule-Based VSL and Lane Change Control,
ITS(23), No. 10, October 2022, pp. 19348-19357.
IEEE DOI 2210
Uncertainty, Microscopy, Traffic control, Safety, Analytical models, Throughput, Roads, Integrated traffic control, VSL zone distance BibRef

Scheel, O.[Oliver], Nagaraja, N.S.[Naveen Shankar], Schwarz, L.[Loren], Navab, N.[Nassir], Tombari, F.[Federico],
Recurrent Models for Lane Change Prediction and Situation Assessment,
ITS(23), No. 10, October 2022, pp. 17284-17300.
IEEE DOI 2210
Task analysis, Predictive models, Autonomous vehicles, Planning, Data models, Vehicles, Trajectory, Artificial intelligence, prediction methods BibRef

Zhang, Y.[Yi], Shi, X.[Xiupeng], Zhang, S.[Sheng], Abraham, A.[Anuj],
A XGBoost-Based Lane Change Prediction on Time Series Data Using Feature Engineering for Autopilot Vehicles,
ITS(23), No. 10, October 2022, pp. 19187-19200.
IEEE DOI 2210
Feature extraction, Trajectory, Vehicle dynamics, Support vector machines, Vehicles, Prediction algorithms, feature selection BibRef

Hwang, S.[Seulbin], Lee, K.[Kibeom], Jeon, H.[Hyeongseok], Kum, D.[Dongsuk],
Autonomous Vehicle Cut-In Algorithm for Lane-Merging Scenarios via Policy-Based Reinforcement Learning Nested Within Finite-State Machine,
ITS(23), No. 10, October 2022, pp. 17594-17606.
IEEE DOI 2210
Safety, Reinforcement learning, Autonomous vehicles, Vehicles, Decision making, Automata, Stochastic processes, finite-state machine BibRef

Chen, R.[Ruishuang], Yang, Z.[Zaiyue],
A Cooperative Merging Strategy for Connected and Automated Vehicles Based on Game Theory With Transferable Utility,
ITS(23), No. 10, October 2022, pp. 19213-19223.
IEEE DOI 2210
Merging, Games, Roads, Game theory, Fuels, Optimal control, Trajectory, Connected and automated vehicles (CAVs), optimal control BibRef

Hu, J.C.[Jin-Chao], Li, X.[Xu], Cen, Y.Q.[Yan-Qing], Xu, Q.M.[Qi-Min], Zhu, X.F.[Xue-Fen], Hu, W.M.[Wei-Ming],
A Roadside Decision-Making Methodology Based on Deep Reinforcement Learning to Simultaneously Improve the Safety and Efficiency of Merging Zone,
ITS(23), No. 10, October 2022, pp. 18620-18631.
IEEE DOI 2210
Decision making, Merging, Safety, Vehicle dynamics, Reinforcement learning, Roads, Hidden Markov models, merging zone BibRef

Chen, N.[Na], van Arem, B.[Bart], Wang, M.[Meng],
Hierarchical Optimal Maneuver Planning and Trajectory Control at On-Ramps With Multiple Mainstream Lanes,
ITS(23), No. 10, October 2022, pp. 18889-18902.
IEEE DOI 2210
Merging, Trajectory, Predictive models, Vehicle-to-everything, Vehicle dynamics, Road transportation, Predictive control, multiple lanes BibRef

Wu, P.[Peng], Xu, L.[Ling], d'Ariano, A.[Andrea], Zhao, Y.X.[Yong-Xiang], Chu, C.B.[Cheng-Bin],
Novel Formulations and Improved Differential Evolution Algorithm for Optimal Lane Reservation With Task Merging,
ITS(23), No. 11, November 2022, pp. 21329-21344.
IEEE DOI 2212
Task analysis, Roads, Transportation, Merging, Costs, Games, Uncertainty, Lane reservation, task merging, integer linear programming, differential evolution algorithm BibRef

Peng, J.K.[Jian-Kun], Zhang, S.[Siyu], Zhou, Y.[Yang], Li, Z.B.[Zhi-Bin],
An Integrated Model for Autonomous Speed and Lane Change Decision-Making Based on Deep Reinforcement Learning,
ITS(23), No. 11, November 2022, pp. 21848-21860.
IEEE DOI 2212
Decision making, Task analysis, Automobiles, Safety, Behavioral sciences, Predictive models, Reinforcement learning, trajectory reconstruction BibRef

Li, Y.[Yang], Li, L.[Linbo], Ni, D.H.[Dai-Heng], Wang, W.X.[Wen-Xuan],
Automatic Lane-Changing Trajectory Planning: From Self-Optimum to Local-Optimum,
ITS(23), No. 11, November 2022, pp. 21004-21014.
IEEE DOI 2212
Trajectory, Trajectory planning, Safety, Smoothing methods, Planning, Liquid crystal displays, Behavioral sciences, HighD dataset BibRef

Zhang, L.[Lin], Li, B.[Bin], Hao, Y.[Yi], Hu, H.Q.[Hao-Qi], Hu, Y.F.[Yun-Feng], Huang, Y.J.[Yan-Jun], Chen, H.[Hong],
A Novel Simultaneous Planning and Control Scheme of Automated Lane Change on Slippery Roads,
ITS(23), No. 11, November 2022, pp. 20696-20706.
IEEE DOI 2212
Roads, Tires, Planning, Wheels, Trajectory, Predictive models, Heuristic algorithms, Automated lane change scheme, model predictive control BibRef

Elsayed, M.A.[Marwa A.], Wrana, M.[Michael], Jiang, L.S.[Long-Sheng], Chen, D.[Dong], Li, Z.J.[Zhao-Jian], Wang, Y.[Yue],
Risk Representation, Perception, and Propensity in an Integrated Human Lane-Change Decision Model,
ITS(23), No. 12, December 2022, pp. 23474-23487.
IEEE DOI 2212
Vehicles, Hidden Markov models, Liquid crystal displays, Behavioral sciences, Decision making, Cognition, traffic simulation BibRef

Li, Z.N.[Zhen-Ni], Huang, X.H.[Xing-Hui], Mu, T.[Tong], Wang, J.[Jiao],
Attention-Based Lane Change and Crash Risk Prediction Model in Highways,
ITS(23), No. 12, December 2022, pp. 22909-22922.
IEEE DOI 2212
Behavioral sciences, Predictive models, Hidden Markov models, Accidents, Decision trees, Trajectory, Safety, LSTM BibRef

Siddiqi, M.R.[Muhammad Rehan], Milani, S.[Sina], Jazar, R.N.[Reza N.], Marzbani, H.[Hormoz],
Motion Sickness Mitigating Algorithms and Control Strategy for Autonomous Vehicles,
ITS(24), No. 1, January 2023, pp. 304-315.
IEEE DOI 2301
Mathematical models, Splines (mathematics), Surface topography, Surface reconstruction, Motion sickness, Autonomous vehicles, lane change maneuver BibRef

Zhang, J.W.[Jia-Wei], Chang, C.[Cheng], Zeng, X.L.[Xian-Lin], Li, L.[Li],
Multi-Agent DRL-Based Lane Change With Right-of-Way Collaboration Awareness,
ITS(24), No. 1, January 2023, pp. 854-869.
IEEE DOI 2301
Behavioral sciences, Safety, Collaboration, Planning, Vehicles, Trajectory, Reinforcement learning, Automated vehicle, lane change, driving intention BibRef

He, J.[Jia], Qu, J.[Jie], Zhang, J.[Jian], He, Z.B.[Zheng-Bing],
The Impact of a Single Discretionary Lane Change on Surrounding Traffic: An Analytic Investigation,
ITS(24), No. 1, January 2023, pp. 554-563.
IEEE DOI 2301
Trajectory, Roads, Behavioral sciences, Safety, Space vehicles, Decision making, Time factors, Traffic flow, lane change impact, traffic condition BibRef

Zhang, Y.[Yifan], Xu, Q.[Qian], Wang, J.P.[Jian-Ping], Wu, K.[Kui], Zheng, Z.[Zuduo], Lu, K.[Kejie],
A Learning-Based Discretionary Lane-Change Decision-Making Model With Driving Style Awareness,
ITS(24), No. 1, January 2023, pp. 68-78.
IEEE DOI 2301
Decision making, Mathematical models, Vehicles, Human factors, Analytical models, Computational modeling, Predictive models, autonomous driving BibRef

Sheng, Z.[Zihao], Liu, L.[Lin], Xue, S.[Shibei], Zhao, D.Z.[De-Zong], Jiang, M.[Min], Li, D.[Dewei],
A Cooperation-Aware Lane Change Method for Automated Vehicles,
ITS(24), No. 3, March 2023, pp. 3236-3251.
IEEE DOI 2303
Trajectory, Decision making, Trajectory planning, Safety, Planning, Roads, Prediction algorithms, Decision making, motion planning, automated vehicles BibRef

He, X.K.[Xiang-Kun], Lou, B.C.[Bai-Chuan], Yang, H.[Haohan], Lv, C.[Chen],
Robust Decision Making for Autonomous Vehicles at Highway On-Ramps: A Constrained Adversarial Reinforcement Learning Approach,
ITS(24), No. 4, April 2023, pp. 4103-4113.
IEEE DOI 2304
Autonomous vehicles, Decision making, Merging, Road transportation, Markov processes, Games, Uncertainty, Autonomous vehicle, adversarial attack BibRef

Schuurmans, M.[Mathijs], Katriniok, A.[Alexander], Meissen, C.[Christopher], Tseng, H.E.[H. Eric], Patrinos, P.[Panagiotis],
Safe, learning-based MPC for highway driving under lane-change uncertainty: A distributionally robust approach,
AI(320), 2023, pp. 103920.
Elsevier DOI 2306
Model predictive control, Risk measures, Distributionally robust optimization, Automated driving, Path planning BibRef

Gao, K.[Kai], Li, X.[Xunhao], Chen, B.[Bin], Hu, L.[Lin], Liu, J.[Jian], Du, R.H.[Rong-Hua], Li, Y.[Yongfu],
Dual Transformer Based Prediction for Lane Change Intentions and Trajectories in Mixed Traffic Environment,
ITS(24), No. 6, June 2023, pp. 6203-6216.
IEEE DOI 2306
Trajectory, Predictive models, Feature extraction, Autonomous vehicles, Transformers, Adaptation models, highD BibRef

Zhang, Y.[Yue], Zou, Y.J.[Ya-Jie], Selpi, Zhang, Y.L.[Yun-Long], Wu, L.T.[Ling-Tao],
Spatiotemporal Interaction Pattern Recognition and Risk Evolution Analysis During Lane Changes,
ITS(24), No. 6, June 2023, pp. 6663-6673.
IEEE DOI 2306
Hidden Markov models, Behavioral sciences, Autonomous vehicles, Semantics, Safety, Vehicle dynamics, Spatiotemporal phenomena, driving primitive BibRef

Ali, Y.[Yasir], Haque, M.M.[Md. Mazharul], Zheng, Z.[Zuduo],
Assessing a Connected Environment's Safety Impact During Mandatory Lane-Changing: A Block Maxima Approach,
ITS(24), No. 6, June 2023, pp. 6639-6649.
IEEE DOI 2306
Computer crashes, Safety, Accidents, Data models, Roads, Australia, Trajectory, Connected environment, extreme value theory, safety BibRef

Duan, X.[Xuting], Sun, C.[Chen], Tian, D.X.[Da-Xin], Zhou, J.[Jianshan], Cao, D.[Dongpu],
Cooperative Lane-Change Motion Planning for Connected and Automated Vehicle Platoons in Multi-Lane Scenarios,
ITS(24), No. 7, July 2023, pp. 7073-7091.
IEEE DOI 2307
Planning, Task analysis, Trajectory, Optimal control, Numerical models, Computational modeling, Autonomous vehicles, platoons BibRef

Liu, R.[Rui], Zhao, X.[Xuan], Zhu, X.C.[Xi-Chan], Ma, J.[Jian],
A Human-Like Shared Driving Strategy in Lane-Changing Scenario Using Cooperative LPV/MPC,
ITS(24), No. 9, September 2023, pp. 9915-9928.
IEEE DOI 2310
BibRef

Donà, R.[Riccardo], Mattas, K.[Konstantinos], Ciuffo, B.[Biagio],
Towards Bi-Dimensional driver models for automated driving system safety requirements: Validation of a kinematic model for evasive lane-change maneuvers,
IET-ITS(17), No. 9, 2023, pp. 1784-1798.
DOI Link 2310
automated driving and intelligent vehicles, optimal control, transport modeling and microsimulation, vehicle dynamics BibRef

Chen, S.[Songge], Chen, Y.[Yong], Pan, C.W.[Cheng-Wei], Ali, I.[Ikram], Pan, J.T.[Jun-Tao], He, W.[Wen],
Distributed Adaptive Platoon Secure Control on Unmanned Vehicles System for Lane Change Under Compound Attacks,
ITS(24), No. 11, November 2023, pp. 12637-12647.
IEEE DOI 2311
BibRef

Cui, M.Y.[Ming-Yang], Liu, J.X.[Jin-Xin], Zheng, H.T.[Hao-Tian], Xu, Q.[Qing], Wang, J.[Jiangqiang], Geng, L.[Lu], Sekiguchi, T.[Takaaki],
Passing-yielding intention estimation during lane change conflict: A semantic-based Bayesian inference method,
IET-ITS(17), No. 11, 2023, pp. 2285-2299.
DOI Link 2311
automated driving and intelligent vehicles, driver cognition, drivers, cyclists and pedestrians modelling BibRef

Kim, Y.J.[Yong-Ju], Ka, D.[Dongju], Lee, C.[Chungwon],
Lane-changing control with balancing lane flow at freeway merge bottlenecks in a connected vehicle environment: Application of a PID controller,
IET-ITS(17), No. 11, 2023, pp. 2313-2332.
DOI Link 2311
balancing lane flow, capacity drop, connected vehicle, lane-changing control, merge bottleneck, proportional-integral-derivative feedback controller BibRef

Xia, M.[Ming], Lin, J.J.[Jun-Jie], Ying, L.H.[Ling-Hao], Sun, J.[Jian], Chi, K.[Kaikai], Gao, K.[Kun], Yu, K.P.[Ke-Ping],
Toward Sustainable Transportation: Robust Lane-Change Monitoring With a Single Back View Cabin Camera,
ITS(24), No. 12, December 2023, pp. 15414-15424.
IEEE DOI 2312
BibRef

Zhang, H.J.[Hong-Jia], Gao, S.[Song], Guo, Y.[Yingshi],
Driver Lane-Changing Intention Recognition Based on Stacking Ensemble Learning in the Connected Environment: A Driving Simulator Study,
ITS(25), No. 2, February 2024, pp. 1503-1518.
IEEE DOI 2402
Vehicles, Ensemble learning, Human-machine systems, Stacking, Magnetic heads, Behavioral sciences, Accidents, co-driving BibRef

Zhang, J.Q.[Jin-Qi], Yan, M.[Maode], Zuo, L.[Lei],
Deep Q-network based multi-layer safety lane changing strategy for vehicle platoon,
IET-ITS(18), No. 4, 2024, pp. 645-656.
DOI Link 2404
decision making, learning (artificial intelligence), intelligent transportation systems, vehicle routing BibRef

Fan, J.[Jiayu], Zhan, Y.[Yinxiao], Liang, J.[Jun],
A hierarchical control strategy for reliable lane changes considering optimal path and lane-changing time point,
IET-ITS(18), No. 4, 2024, pp. 657-671.
DOI Link 2404
automated driving and intelligent vehicles, path planning, vehicle dynamics and control BibRef

Lu, Y.[Yun], Su, R.[Rong], Huang, L.[Lingying], Yao, J.[Jiarong], Hu, Z.J.[Zhi-Jian],
Modeling Driver Decision Behavior of the Cut-In Process,
ITS(25), No. 5, May 2024, pp. 4133-4144.
IEEE DOI 2405
Vehicles, Behavioral sciences, Hidden Markov models, Predictive models, Process control, Vehicle dynamics, model predictive control BibRef

Jokhio, S.[Sarang], Olleja, P.[Pierluigi], Bärgman, J.[Jonas], Yan, F.[Fei], Baumann, M.[Martin],
Analysis of Time-to-Lane-Change-Initiation Using Realistic Driving Data,
ITS(25), No. 5, May 2024, pp. 4620-4633.
IEEE DOI 2405
Vehicles, Roads, Regulation, Europe, Analytical models, Trajectory, Radar, Lane change, time-to-lane-change-initiation, autonomous vehicles BibRef

Li, Y.[Ye], Liu, F.[Fei], Xing, L.[Lu], Yuan, C.[Chen], Wu, D.[Dan],
A Deep Learning Framework to Explore Influences of Data Noises on Lane-Changing Intention Prediction,
ITS(25), No. 7, July 2024, pp. 6514-6526.
IEEE DOI 2407
Predictive models, Hidden Markov models, Trajectory, Deep learning, Data models, Kinematics, Feature extraction, Lane-changing, driving intention BibRef

Xu, J.B.[Jing-Bin], Qian, C.[Chen], Han, S.[Shu], Guo, F.[Feng],
Detecting Critical Mismatched Driver Visual Attention During Lane Change: An Embedding Kernel Algorithm,
ITS(25), No. 7, July 2024, pp. 7070-7080.
IEEE DOI 2407
Vehicles, Behavioral sciences, Visualization, Safety, Accidents, Kernel, Measurement, Driver visual behavior, driving safety, distraction BibRef

Ding, C.[Cao], Ho, I.W.H.[Ivan Wang-Hei], Chung, E.[Edward], Fan, T.T.[Ting-Ting],
V2X and Deep Reinforcement Learning-Aided Mobility-Aware Lane Changing for Emergency Vehicle Preemption in Connected Autonomous Transport Systems,
ITS(25), No. 7, July 2024, pp. 7281-7293.
IEEE DOI 2407
Vehicle-to-everything, Quality of service, Safety, Delays, Data models, Peer-to-peer computing, Numerical models, V2X, emergency vehicle preemption BibRef

Zhang, Q.Y.[Qing-Yu], Langari, R.[Reza], Tseng, H.E.[H. Eric], Mohan, S.[Shankar], Szwabowski, S.[Steven], Filev, D.[Dimitar],
Stackelberg Differential Lane Change Game Based on MPC and Inverse MPC,
ITS(25), No. 8, August 2024, pp. 8473-8485.
IEEE DOI 2408
Games, Differential games, TV, Hidden Markov models, Cost function, Vehicles, Predictive models, Autonomous vehicles, motion planning, game theory BibRef

Zhang, H.J.[Hong-Jia], Wu, F.[Fuwei], Guo, D.[Dong], Gao, S.[Song],
What are the Differences in Driver Lane-Changing Intention Models Recognition Performance Between Connected and Non-Connected Environments,
ITS(25), No. 9, September 2024, pp. 10896-10911.
IEEE DOI 2409
Vehicles, Safety, Pressing, Vehicle dynamics, Transformers, Roads, Data models, Connected environment, non-connected environment, co-driving BibRef

Huang, P.[Ping], Ding, H.T.[Hai-Tao], Sun, Z.J.[Zhen-Jia], Chen, H.[Hong],
A Game-Based Hierarchical Model for Mandatory Lane Change of Autonomous Vehicles,
ITS(25), No. 9, September 2024, pp. 11256-11268.
IEEE DOI 2409
Games, Decision making, Vehicles, Vehicle dynamics, Safety, Adaptation models, Road transportation, relative driving style (RDS) BibRef

Hu, J.C.[Jin-Chao], Li, X.[Xu], Hu, W.M.[Wei-Ming], Xu, Q.[Qimin], Kong, D.[Dong],
A Cooperative Control Methodology Considering Dynamic Interaction for Multiple Connected and Automated Vehicles in the Merging Zone,
ITS(25), No. 9, September 2024, pp. 12669-12681.
IEEE DOI 2409
Vehicle dynamics, Merging, Decision making, Deep reinforcement learning, Safety, Topology BibRef

Yoon, Y.[Youngmin], Kim, C.H.[Chang-Hee], Lee, H.[Heeseong], Seo, D.[Dabin], Yi, K.[Kyongsu],
Spatio-Temporal Corridor-Based Motion Planning of Lane Change Maneuver for Autonomous Driving in Multi-Vehicle Traffic,
ITS(25), No. 10, October 2024, pp. 13163-13183.
IEEE DOI 2410
Planning, Trajectory, Decision making, Autonomous vehicles, Optimization, Vehicle dynamics, Safety, Autonomous vehicle, model predictive control (MPC) BibRef

Zhu, C.F.[Chang-Feng], An, C.[Chun], He, R.[Runtian], Zhang, C.[Chao], Cheng, L.[Linna],
Prediction of the vehicle lane-changing distance in an urban inter-tunnel weaving section based on wavelet transform and dual-channel neural network,
IET-ITS(18), No. 11, 2024, pp. 2078-2096.
DOI Link 2411
Influence Factor Analysis, Urban Inter-tunnel Weaving Section, Vehicle Lane-changing Distance, WT-DCNN BibRef

Gupta, A.[Akshay], Choudhary, P.[Pushpa], Parida, M.[Manoranjan],
Analyzing Lane Change Execution Behavior on Expressway Using an Instrumented Vehicle: A Random Effect Accelerated Failure Time Approach,
ITS(25), No. 11, November 2024, pp. 18038-18048.
IEEE DOI 2411
Vehicles, Instruments, Data collection, Laser radar, Accuracy, Lead, Cameras, Lane-changing, driving behaviour, expressway, LiDAR BibRef

Liang, K.[Kai], Wang, J.[Jun], Bhalerao, A.[Abhir],
Lane Change Classification and Prediction with Action Recognition Networks,
AVVision22(617-632).
Springer DOI 2304
BibRef

Xiang, X.[Xiang],
Bootstrapping Autonomous Lane Changes with Self-supervised Augmented Runs,
SelfLearnDrive22(118-130).
Springer DOI 2304
BibRef

Saboune, J.[Jamal], Arezoomand, M.[Mehdi], Martel, L.[Luc], Laganiere, R.[Robert],
A Visual Blindspot Monitoring System for Safe Lane Changes,
CIAP11(II: 1-10).
Springer DOI 1109
BibRef

Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Road Markings, Marking Detection .

Last update:Nov 26, 2024 at 16:40:19