15.3.3.4 Lane Changing, Lane-Change, Analysis, Control

Chapter Contents (Back)
Lane Changing. Driver Assistance.

Naranjo, J.E., Gonzalez, C., Garcia, R., de Pedro, T.,
Lane-Change Fuzzy Control in Autonomous Vehicles for the Overtaking Maneuver,
ITS(9), No. 3, September 2008, pp. 438-450.
IEEE DOI 0809
BibRef

Toledo-Moreo, R., Zamora-Izquierdo, M.A.,
IMM-Based Lane-Change Prediction in Highways With Low-Cost GPS/INS,
ITS(10), No. 1, March 2009, pp. 180-185.
IEEE DOI 0903
BibRef

Schubert, R., Schulze, K., Wanielik, G.,
Situation Assessment for Automatic Lane-Change Maneuvers,
ITS(11), No. 3, September 2010, pp. 607-616.
IEEE DOI 1003
BibRef

Xu, G., Liu, L., Ou, Y., Song, Z.,
Dynamic Modeling of Driver Control Strategy of Lane-Change Behavior and Trajectory Planning for Collision Prediction,
ITS(13), No. 3, September 2012, pp. 1138-1155.
IEEE DOI 1209
BibRef

Rahman, M., Chowdhury, M., Xie, Y., He, Y.,
Review of Microscopic Lane-Changing Models and Future Research Opportunities,
ITS(14), No. 4, 2013, pp. 1942-1956.
IEEE DOI 1312
Sardis Award, Survey. Adaptation models. Evaluation of human behaviors, lane changing. BibRef

Lee, H., Jeong, S., Lee, J.,
Robust detection system of illegal lane changes based on tracking of feature points,
IET-ITS(7), No. 1, 2013, pp. 20-27.
DOI Link 1307
BibRef

Hou, Y., Edara, P., Sun, C.,
Modeling Mandatory Lane Changing Using Bayes Classifier and Decision Trees,
ITS(15), No. 2, April 2014, pp. 647-655.
IEEE DOI 1404
Accuracy BibRef

Sivaraman, S., Trivedi, M.M.,
Integrated Lane and Vehicle Detection, Localization, and Tracking: A Synergistic Approach,
ITS(14), No. 2, 2013, pp. 906-917.
IEEE DOI 1307
Image edge detection; Kalman filters; driver assistance; lane departure
See also Vehicle Detection by Independent Parts for Urban Driver Assistance. BibRef

Sivaraman, S.[Sayanan], Trivedi, M.M.[Mohan M.],
Dynamic Probabilistic Drivability Maps for Lane Change and Merge Driver Assistance,
ITS(15), No. 5, October 2014, pp. 2063-2073.
IEEE DOI 1410
data structures BibRef

Satzoda, R.K., Trivedi, M.M.,
Drive Analysis Using Vehicle Dynamics and Vision-Based Lane Semantics,
ITS(16), No. 1, February 2015, pp. 9-18.
IEEE DOI 1502
Computer crashes BibRef

Satzoda, R.K.[Ravi Kumar], Trivedi, M.M.[Mohan M.],
On Enhancing Lane Estimation Using Contextual Cues,
CirSysVideo(25), No. 11, November 2015, pp. 1870-1881.
IEEE DOI 1511
BibRef
Earlier:
On Performance Evaluation Metrics for Lane Estimation,
ICPR14(2625-2630)
IEEE DOI 1412
BibRef
And:
Efficient Lane and Vehicle Detection with Integrated Synergies (ELVIS),
ECVW14(708-713)
IEEE DOI 1409
BibRef
Earlier:
Vision-Based Lane Analysis: Exploration of Issues and Approaches for Embedded Realization,
ECVW13(604-609)
IEEE DOI 1309
Accuracy. embedded system; intelligent driver assistance systems; lane detection. computational efficiency BibRef

Sivaraman, S.[Sayanan], Morris, B.T.[Brendan T.], Trivedi, M.M.[Mohan M.],
Learning multi-lane trajectories using vehicle-based vision,
CVVT11(2070-2076).
IEEE DOI 1201
The other cars. BibRef

McCall, J.C., Trivedi, M.M.,
An integrated, robust approach to lane marking detection and lane tracking,
IVS04(533-537).
IEEE DOI 0411
BibRef

Desiraju, D., Chantem, T., Heaslip, K.,
Minimizing the Disruption of Traffic Flow of Automated Vehicles During Lane Changes,
ITS(16), No. 3, June 2015, pp. 1249-1258.
IEEE DOI 1506
Acceleration BibRef

Knoop, V.L., Buisson, C.,
Calibration and Validation of Probabilistic Discretionary Lane-Change Models,
ITS(16), No. 2, April 2015, pp. 834-843.
IEEE DOI 1504
Calibration BibRef

Dang, R.[Ruina], Wang, J.Q.[Jian-Qiang], Li, S.E., Li, K.Q.[Ke-Qiang],
Coordinated Adaptive Cruise Control System With Lane-Change Assistance,
ITS(16), No. 5, October 2015, pp. 2373-2383.
IEEE DOI 1511
acceleration control BibRef

Yang, D., Zhu, L., Ran, B., Pu, Y., Hui, P.,
Modeling and Analysis of the Lane-Changing Execution in Longitudinal Direction,
ITS(17), No. 10, October 2016, pp. 2984-2992.
IEEE DOI 1610
Acceleration BibRef

Nobukawa, K., Bao, S., LeBlanc, D.J., Zhao, D., Peng, H., Pan, C.S.,
Gap Acceptance During Lane Changes by Large-Truck Drivers: An Image-Based Analysis,
ITS(17), No. 3, March 2016, pp. 772-781.
IEEE DOI 1603
Cameras BibRef

Zhao, H., Wang, C., Lin, Y., Guillemard, F., Geronimi, S., Aioun, F.,
On-Road Vehicle Trajectory Collection and Scene-Based Lane Change Analysis: Part I,
ITS(18), No. 1, January 2017, pp. 192-205.
IEEE DOI 1701
Data models BibRef

Yao, W., Zeng, Q., Lin, Y., Xu, D., Zhao, H., Guillemard, F., Geronimi, S., Aioun, F.,
On-Road Vehicle Trajectory Collection and Scene-Based Lane Change Analysis: Part II,
ITS(18), No. 1, January 2017, pp. 206-220.
IEEE DOI 1701
Analytical models BibRef

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.[Haobin], Shi, K.[Kaijin], 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, Pattern recognition, 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.[Chunguang], 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.[Zhongyin], Su, D.[Donglan], 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


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
Curb Detection, Street Boundaries .


Last update:Jul 28, 2021 at 22:23:09