Iteris,
2007.
Lane departure systems.
WWW Link.
Vendor, Driver Assistance.
Lee, J.W.[Joon Woong],
A Machine Vision System for Lane-Departure Detection,
CVIU(86), No. 1, April 2002, pp. 52-78.
DOI Link
0211
BibRef
Lee, J.W.[Joon Woong],
Yi, U.K.[Un Kun],
A lane-departure identification based on LBPE, Hough transform, and
linear regression,
CVIU(99), No. 3, September 2005, pp. 359-383.
Elsevier DOI
0508
BibRef
Jung, C.R.[Cláudio Rosito],
Kelber, C.R.[Christian Roberto],
Lane following and lane departure using a linear-parabolic model,
IVC(23), No. 13, 29 November 2005, pp. 1192-1202.
Elsevier DOI
0512
BibRef
Earlier:
A lane departure warning system based on a linear-parabolic lane model,
IVS04(891-895).
IEEE DOI
0411
BibRef
Zhang, J.,
Ioannou, P.A.,
Longitudinal control of heavy trucks in mixed traffic:
Environmental and fuel economy considerations,
ITS(7), No. 1, March 2006, pp. 92-104.
IEEE DOI
0604
BibRef
Lin, H.Y.[Huei-Yung],
Lin, J.H.[Jen-Hung],
A Visual Positioning System for Vehicle or Mobile Robot Navigation,
IEICE(E89-D), No. 7, July 2006, pp. 2109-2116.
DOI Link
0607
BibRef
McCall, J.C.,
Trivedi, M.M.,
Video-based lane estimation and tracking for driver assistance:
Survey, system, and evaluation,
ITS(7), No. 1, March 2006, pp. 20-37.
IEEE DOI
0604
Survey, Driver Assistance.
BibRef
Mammar, S.,
Glaser, S.,
Netto, M.,
Time to Line Crossing for Lane Departure Avoidance:
A Theoretical Study and an Experimental Setting,
ITS(7), No. 2, June 2006, pp. 226-241.
IEEE DOI
0606
BibRef
Minoiu Enache, N.,
Mammar, S.,
Netto, M.,
Lusetti, B.,
Driver Steering Assistance for Lane-Departure Avoidance Based on Hybrid
Automata and Composite Lyapunov Function,
ITS(11), No. 1, March 2010, pp. 28-39.
IEEE DOI
1003
BibRef
Angkititrakul, P.,
Terashima, R.,
Wakita, T.,
On the Use of Stochastic Driver Behavior Model in Lane Departure
Warning,
ITS(12), No. 1, March 2011, pp. 174-183.
IEEE DOI
1103
BibRef
Mohapatra, A.G.[Ambarish G.],
Computer Vision Based Smart Lane Departure Warning System for
Vehicle Dynamics Control,
Sensors(132), No. 9, September 2011, pp. 122-135:
HTML Version.
BibRef
1109
Cualain, D.O.,
Hughes, C.,
Glavin, M.,
Jones, E.,
Automotive standards-grade lane departure warning system,
IET-ITS(6), No. 1, 2012, pp. 44-57.
DOI Link
1204
BibRef
Cualain, D.O.,
Glavin, M.,
Jones, E.,
Multiple-camera lane departure warning system for the automotive
environment,
IET-ITS(6), No. 2, 2012, pp. 223-234.
DOI Link
1209
BibRef
Kullack, A.,
Ehrenpfordt, I.,
Lemmer, K.,
Eggert, F.,
Reflektas: lane departure prevention system based on behavioural
control,
IET-ITS(2), No. 4, 2008, pp. 285-293.
DOI Link
1204
BibRef
Clanton, J.M.,
Bevly, D.M.,
Hodel, A.S.,
A Low-Cost Solution for an Integrated Multisensor Lane Departure
Warning System,
ITS(10), No. 1, March 2009, pp. 47-59.
IEEE DOI
0903
BibRef
Marzotto, R.[Roberto],
Zoratti, P.[Paul],
Bagni, D.[Daniele],
Colombari, A.[Andrea],
Murino, V.[Vittorio],
A real-time versatile roadway path extraction and tracking on an FPGA
platform,
CVIU(114), No. 11, November 2010, pp. 1164-1179.
Elsevier DOI
1011
Lane detection; Lane tracking; Road modeling; Lane departure warning;
FPGA processing; Embedded Automotive
BibRef
Ali, M.,
Falcone, P.,
Olsson, C.,
Sjoberg, J.,
Predictive Prevention of Loss of Vehicle Control for Roadway Departure
Avoidance,
ITS(14), No. 1, March 2013, pp. 56-68.
IEEE DOI
1303
BibRef
Wang, J.,
Zhang, L.,
Zhang, D.,
Li, K.,
An Adaptive Longitudinal Driving Assistance System Based on Driver
Characteristics,
ITS(14), No. 1, March 2013, pp. 1-12.
IEEE DOI
1303
BibRef
Eum, S.,
Jung, H.G.,
Enhancing Light Blob Detection for Intelligent Headlight
Control Using Lane Detection,
ITS(14), No. 2, 2013, pp. 1003-1011.
IEEE DOI
1307
Intelligent headlight control (IHC); lane detection
BibRef
Thomaidis, G.,
Kotsiourou, C.,
Grubb, G.,
Lytrivis, P.,
Karaseitanidis, G.,
Amditis, A.,
Multi-sensor tracking and lane estimation in highly automated vehicles,
IET-ITS(7), No. 1, 2013, pp. 160-169.
DOI Link
1307
BibRef
An, X.J.[Xiang-Jing],
Shang, E.[Erke],
Song, J.Z.[Jin-Ze],
Li, J.[Jian],
He, H.[Hangen],
Real-time lane departure warning system based on a single FPGA,
JIVP(2013), No. 1, 2013, pp. 38.
DOI Link
1307
BibRef
Yoo, H.,
Yang, U.,
Sohn, K.,
Gradient-Enhancing Conversion for Illumination-Robust Lane Detection,
ITS(14), No. 3, 2013, pp. 1083-1094.
IEEE DOI
1309
Gradient-enhancing conversion
BibRef
Yenikaya, S.[Sibel],
Yenikaya, G.[Gökhan],
Düven, E.[Ekrem],
Keeping the vehicle on the road:
A survey on on-road lane detection systems,
Surveys(46), No. 1, October 2013, pp. Article No 2.
DOI Link
1311
Survey, Lane Detection. The development of wireless sensor networks, such as researchers
Advanced Driver Assistance Systems (ADAS) requires the ability to
analyze the road scene just like a human does.
BibRef
Rose, C.,
Britt, J.,
Allen, J.,
Bevly, D.,
An Integrated Vehicle Navigation System Utilizing Lane-Detection and
Lateral Position Estimation Systems in Difficult Environments for GPS,
ITS(15), No. 6, December 2014, pp. 2615-2629.
IEEE DOI
1412
Global Positioning System
BibRef
Schakel, W.J.,
van Arem, B.,
Improving Traffic Flow Efficiency by In-Car Advice on Lane, Speed,
and Headway,
ITS(15), No. 4, August 2014, pp. 1597-1606.
IEEE DOI
1410
automobiles
BibRef
Topfer, D.,
Spehr, J.,
Effertz, J.,
Stiller, C.,
Efficient Road Scene Understanding for Intelligent Vehicles Using
Compositional Hierarchical Models,
ITS(16), No. 1, February 2015, pp. 441-451.
IEEE DOI
1502
Feature extraction
BibRef
Gaikwad, V.,
Lokhande, S.,
Lane Departure Identification for Advanced Driver Assistance,
ITS(16), No. 2, April 2015, pp. 910-918.
IEEE DOI
1504
Image color analysis
BibRef
Brown, A.A.,
Brennan, S.N.,
Lateral Vehicle State and Environment Estimation Using Temporally
Previewed Mapped Lane Features,
ITS(16), No. 3, June 2015, pp. 1601-1608.
IEEE DOI
1506
Accuracy
BibRef
Chen, C.F.[Chang-Fang],
Jia, Y.M.[Ying-Min],
Shu, M.L.[Ming-Lei],
Wang, Y.L.[Ying-Long],
Hierarchical Adaptive Path-Tracking Control for Autonomous Vehicles,
ITS(16), No. 5, October 2015, pp. 2900-2912.
IEEE DOI
1511
Lyapunov methods
BibRef
Dias, J.E.A.,
Pereira, G.A.S.,
Palhares, R.M.,
Longitudinal Model Identification and Velocity Control of an
Autonomous Car,
ITS(16), No. 2, April 2015, pp. 776-786.
IEEE DOI
1504
Computational modeling
BibRef
Qi, G.Q.[Ge-Qi],
Du, Y.M.[Yi-Man],
Wu, J.P.[Jian-Ping],
Xu, M.[Ming],
Leveraging longitudinal driving behaviour data with data mining
techniques for driving style analysis,
IET-ITS(9), No. 8, 2015, pp. 792-801.
DOI Link
1511
behavioural sciences computing
BibRef
Jo, K.,
Jo, Y.,
Suhr, J.K.,
Jung, H.G.,
Sunwoo, M.,
Precise Localization of an Autonomous Car Based on Probabilistic
Noise Models of Road Surface Marker Features Using Multiple Cameras,
ITS(16), No. 6, December 2015, pp. 3377-3392.
IEEE DOI
1512
Autonomous automobiles
BibRef
Tagne, G.,
Talj, R.,
Charara, A.,
Design and Comparison of Robust Nonlinear Controllers for the Lateral
Dynamics of Intelligent Vehicles,
ITS(17), No. 3, March 2016, pp. 796-809.
IEEE DOI
1603
Intelligent vehicles
BibRef
Saito, Y.[Yuichi],
Itoh, M.[Makoto],
Inagaki, T.[Toshiyuki],
Driver Assistance System With a Dual Control Scheme: Effectiveness of
Identifying Driver Drowsiness and Preventing Lane Departure Accidents,
HMS(46), No. 5, October 2016, pp. 660-671.
IEEE DOI
1610
control engineering computing
BibRef
Saito, Y.[Yuichi],
Itoh, M.[Makoto],
Inagaki, T.[Toshiyuki],
Bringing a Vehicle to a Controlled Stop: Effectiveness of a
Dual-Control Scheme for Identifying Driver Drowsiness and Preventing
Lane Departures Under Partial Driving Automation Requiring
Hands-on-Wheel,
HMS(52), No. 1, February 2022, pp. 74-86.
IEEE DOI
2201
Vehicles, Automation, Eyelids, Wheels, Control systems, Torque, Fatigue,
Driver monitoring, driving safety, dual control,
partial driving automation
BibRef
Li, C.,
Dai, B.,
Wang, R.,
Fang, Y.,
Yuan, X.,
Wu, T.,
Multi-lane detection based on omnidirectional camera using
anisotropic steerable filters,
IET-ITS(10), No. 5, 2016, pp. 298-307.
DOI Link
1608
cameras
BibRef
Wang, J.,
Zhang, G.,
Wang, R.,
Schnelle, S.C.,
Wang, J.,
A Gain-Scheduling Driver Assistance Trajectory-Following Algorithm
Considering Different Driver Steering Characteristics,
ITS(18), No. 5, May 2017, pp. 1097-1108.
IEEE DOI
1705
Delays, Robustness, Tires, Trajectory, Uncertainty, Vehicles,
Trajectory following, driver's characteristics, gain scheduling,
robust control, shared, control
BibRef
Clausen, P.[Philipp],
Gilliéron, P.Y.[Pierre-Yves],
Perakis, H.[Harris],
Gikas, V.,
Spyropoulou, I.[Ioanna],
Assessment of positioning accuracy of vehicle trajectories for
different road applications,
IET-ITS(11), No. 3, April 2017, pp. 113-125.
DOI Link
1705
BibRef
Narote, S.P.[Sandipann P.],
Bhujbal, P.N.[Pradnya N.],
Narote, A.S.[Abbhilasha S.],
Dhane, D.M.[Dhiraj M.],
A review of recent advances in lane detection and departure warning
system,
PR(73), No. 1, 2018, pp. 216-234.
Elsevier DOI
1709
Edge, detection
BibRef
Li, R.M.[Rui-Min],
Ye, Z.[Zhen],
Li, B.[Bin],
Zhan, X.Y.[Xian-Yuan],
Simulation of hard shoulder running combined with queue warning during
traffic accident with CTM model,
IET-ITS(11), No. 9, November 2017, pp. 553-560.
DOI Link
1710
BibRef
Zhang, K.[Kai],
Liu, S.J.[Shao-Jun],
Dong, Y.H.[Yu-Han],
Wang, D.S.[Dao-Shun],
Zhang, Y.[Yi],
Miao, L.X.[Li-Xin],
Vehicle positioning system with multi-hypothesis map matching and
robust feedback,
IET-ITS(11), No. 10, December 2017, pp. 649-658.
DOI Link
1711
BibRef
Atia, M.M.,
Hilal, A.R.,
Stellings, C.,
Hartwell, E.,
Toonstra, J.,
Miners, W.B.,
Basir, O.A.,
A Low-Cost Lane-Determination System Using GNSS/IMU Fusion and
HMM-Based Multistage Map Matching,
ITS(18), No. 11, November 2017, pp. 3027-3037.
IEEE DOI
1711
Global Positioning System, Hidden Markov models, Kalman filters,
Roads, Sensor fusion, GPS, Lane-determination, MEMS IMU,
extended Kalman filter, hidden Markov models.
BibRef
Kim, S.[Shinwook],
Chang, T.G.[Tae-Gyu],
Neuromorphic Hardware Accelerated Lane Detection System,
IEICE(E100-D), No. 12, December 2017, pp. 2871-2875.
WWW Link.
1712
BibRef
Li, S.E.,
Gao, F.,
Li, K.,
Wang, L.,
You, K.,
Cao, D.,
Robust Longitudinal Control of Multi-Vehicle Systems:
A Distributed H-Infinity Method,
ITS(19), No. 9, September 2018, pp. 2779-2788.
IEEE DOI
1809
Vehicle dynamics, Uncertainty, Topology, Control systems, Robustness,
Stability analysis, Mathematical model, Automated vehicle,
string stability
BibRef
Manoharan, K.[Kodeeswari],
Daniel, P.[Philemon],
Survey on various lane and driver detection techniques based on image
processing for hilly terrain,
IET-IPR(12), No. 9, September 2018, pp. 1511-1520.
DOI Link
1809
Survey, Lane Detection.
Survey, Driver Monitoring.
BibRef
Guo, H.,
Yin, Z.,
Cao, D.,
Chen, H.,
Lv, C.,
A Review of Estimation for Vehicle Tire-Road Interactions Toward
Automated Driving,
SMCS(49), No. 1, January 2019, pp. 14-30.
IEEE DOI
1901
Estimation, Roads, Tires, Vehicle dynamics, Force, Automation, Friction,
Automated driving, extended Kalman filter (EKF),
vehicle dynamics model
BibRef
Sentouh, C.[Chouki],
Nguyen, A.T.[Anh-Tu],
Rath, J.J.[Jagat Jyoti],
Floris, J.[Jérôme],
Popieul, J.C.[Jean-Christophe],
Human-machine shared control for vehicle lane keeping systems:
A Lyapunov-based approach,
IET-ITS(13), No. 1, January 2019, pp. 63-71.
DOI Link
1901
BibRef
Wu, C.,
Wang, L.,
Wang, K.,
Ultra-Low Complexity Block-Based Lane Detection and Departure Warning
System,
CirSysVideo(29), No. 2, February 2019, pp. 582-593.
IEEE DOI
1902
Image color analysis, Roads, Feature extraction,
Image edge detection, Transforms, Automobiles, Complexity theory,
lane departure warning (LDW)
BibRef
Andrade, D.C.,
Bueno, F.,
Franco, F.R.,
Silva, R.A.,
Neme, J.H.Z.,
Margraf, E.,
Omoto, W.T.,
Farinelli, F.A.,
Tusset, A.M.,
Okida, S.,
Santos, M.M.D.,
Ventura, A.,
Carvalho, S.,
Amaral, R.d.S.,
A Novel Strategy for Road Lane Detection and Tracking Based on a
Vehicle's Forward Monocular Camera,
ITS(20), No. 4, April 2019, pp. 1497-1507.
IEEE DOI
1904
Cameras, Roads, Feature extraction, Vehicles, Sensor fusion,
Interpolation, Driver assistance systems, image processing,
monocular camera
BibRef
Li, J.,
Gao, J.,
Zhang, H.,
Qiu, T.Z.,
RSE-Assisted Lane-Level Positioning Method for a Connected Vehicle
Environment,
ITS(20), No. 7, July 2019, pp. 2644-2656.
IEEE DOI
1907
Global Positioning System, Roads, Urban areas,
Global navigation satellite system, Bayes methods,
vehicle-to-infrastructure communication
BibRef
Tian, D.,
Wu, G.,
Hao, P.,
Boriboonsomsin, K.,
Barth, M.J.,
Connected Vehicle-Based Lane Selection Assistance Application,
ITS(20), No. 7, July 2019, pp. 2630-2643.
IEEE DOI
1907
Predictive models, Vehicles, Hidden Markov models, Roads,
Traffic control, Markov processes, Safety, Connected vehicles,
spatial-temporal discretization
BibRef
Lee, K.,
Li, S.E.,
Kum, D.,
Synthesis of Robust Lane Keeping Systems: Impact of Controller and
Design Parameters on System Performance,
ITS(20), No. 8, August 2019, pp. 3129-3141.
IEEE DOI
1908
Stability criteria, Roads, Tires, Robustness, Mathematical model,
Asymptotic stability, Autonomous vehicle,
tracking performance
BibRef
Rabiee, R.,
Zhong, X.,
Yan, Y.,
Tay, W.P.,
LaIF: A Lane-Level Self-Positioning Scheme for Vehicles in
GNSS-Denied Environments,
ITS(20), No. 8, August 2019, pp. 2944-2961.
IEEE DOI
1908
Radar tracking, Atmospheric measurements, Particle measurements,
Global navigation satellite system, Acceleration,
inertial navigation systems
BibRef
Tran, D.,
Du, J.,
Sheng, W.,
Osipychev, D.,
Sun, Y.,
Bai, H.,
A Human-Vehicle Collaborative Driving Framework for Driver Assistance,
ITS(20), No. 9, September 2019, pp. 3470-3485.
IEEE DOI
1909
Collaboration, Risk analysis, Autonomous vehicles, Accidents, Robots,
Assisted driving, collaborative control, driver monitoring, autonomous driving
BibRef
Ito, Y.,
Kamal, M.A.S.,
Yoshimura, T.,
Azuma, S.,
Coordination of Connected Vehicles on Merging Roads Using
Pseudo-Perturbation-Based Broadcast Control,
ITS(20), No. 9, September 2019, pp. 3496-3512.
IEEE DOI
1909
Merging, Roads, Linear programming, Unicast, Indium tin oxide,
Broadcast control, broadcast communication, merging roads,
partially connected vehicle environment
BibRef
Küçükmanisa, A.[Ayhan],
Tarim, G.[Gökhan],
Urhan, O.[Oguzhan],
Real-time illumination and shadow invariant lane detection on mobile
platform,
RealTimeIP(16), No. 5, October 2019, pp. 1781-1794.
WWW Link.
1911
BibRef
Liu, J.Y.[Jing-Yi],
Learning full-reference quality-guided discriminative gradient cues
for lane detection based on neural networks,
JVCIR(65), 2019, pp. 102675.
Elsevier DOI
1912
Lane detection, Full-reference IQA, CNN, RNN
BibRef
Hongbo, W.[Wang],
Li, C.[Chen],
Weihua, Z.[Zhang],
Lane-keeping control based on an improved artificial potential method
and coordination of steering/braking systems,
IET-ITS(13), No. 12, December 2019, pp. 1832-1842.
DOI Link
1912
BibRef
Chen, Y.X.[Yu-Xuan],
Chen, W.G.[Wei-Gang],
Wang, X.[Xun],
Yu, R.[Runyi],
Tian, Y.[Yan],
Learning-based method for lane detection using regionlet representation,
IET-ITS(13), No. 12, December 2019, pp. 1745-1753.
DOI Link
1912
BibRef
Bian, Y.,
Ding, J.,
Hu, M.,
Xu, Q.,
Wang, J.,
Li, K.,
An Advanced Lane-Keeping Assistance System With Switchable Assistance
Modes,
ITS(21), No. 1, January 2020, pp. 385-396.
IEEE DOI
2001
Vehicles, Automation, Switches, Roads, Decision making, Safety,
Predictive control, Lane-keeping assistance system (LKAS),
learning-based model predictive control (LBMPC)
BibRef
Wang, H.R.[Hui-Ran],
Wang, Q.D.[Qi-Dong],
Chen, W.[Wuwei],
Tan, D.[Dongkui],
Zhao, L.F.[Lin-Feng],
Multi-mode human-machine cooperative control for lane departure
prevention based on steering assistance and differential braking,
IET-ITS(14), No. 6, June 2020, pp. 578-588.
DOI Link
2005
BibRef
Ko, B.J.[Byung-Jin],
Ryu, S.[Seunghan],
Park, B.B.[Byungkyu Brian],
Son, S.H.[Sang Hyuk],
Speed harmonisation and merge control using connected automated
vehicles on a highway lane closure: a reinforcement learning approach,
IET-ITS(14), No. 8, August 2020, pp. 947-957.
DOI Link
2007
BibRef
Liu, W.[Wei],
Xiong, L.[Lu],
Xia, X.[Xin],
Lu, Y.S.[Yi-Shi],
Gao, L.[Letian],
Song, S.H.[Shun-Hui],
Vision-aided intelligent vehicle sideslip angle estimation based on a
dynamic model,
IET-ITS(14), No. 10, October 2020, pp. 1183-1189.
DOI Link
2009
BibRef
Li, B.[Bin],
Zhang, J.W.[Jian-Wei],
Zhang, C.[Ce],
Pan, W.[Wei],
Cai, S.[Shuo],
Liu, Y.[Yang],
Li, H.[He],
Lane-keeping system design considering driver's nervousness via scene
analysis,
IET-ITS(14), No. 10, October 2020, pp. 1171-1182.
DOI Link
2009
BibRef
Wang, C.,
Sun, Q.,
Guo, Y.,
Fu, R.,
Yuan, W.,
Improving the User Acceptability of Advanced Driver Assistance
Systems Based on Different Driving Styles: A Case Study of Lane
Change Warning Systems,
ITS(21), No. 10, October 2020, pp. 4196-4208.
IEEE DOI
2010
Vehicles, Cognition, Standards, Acceleration,
Advanced driver assistance systems, risk cognition
BibRef
An, Q.[Quan],
Cheng, S.[Shuo],
Li, L.[Liang],
Peng, H.[Haonan],
Novel dual-layer-oriented strategy for fully automated vehicles'
lane-keeping system,
IET-ITS(14), No. 13, 15 December 2020, pp. 1778-1787.
DOI Link
2102
BibRef
Kim, H.,
Park, J.,
Min, K.,
Huh, K.,
Anomaly Monitoring Framework in Lane Detection With a Generative
Adversarial Network,
ITS(22), No. 3, March 2021, pp. 1603-1615.
IEEE DOI
2103
Anomaly detection, Monitoring, Generative adversarial networks,
Training, Robustness, Detection algorithms,
lane abnormality monitoring
BibRef
Qu, T.[Ting],
Zhao, J.[Junwu],
Gao, H.H.[Hui-Hua],
Cai, K.Y.[Kun-Yang],
Chen, H.[Hong],
Xu, F.[Fang],
Multi-mode switching-based model predictive control approach for
longitudinal autonomous driving with acceleration estimation,
IET-ITS(14), No. 14, 27 December 2020, pp. 2102-2112.
DOI Link
2103
BibRef
Olofsson, B.[Björn],
Nielsen, L.[Lars],
Using Crash Databases to Predict Effectiveness of New Autonomous
Vehicle Maneuvers for Lane-Departure Injury Reduction,
ITS(22), No. 6, June 2021, pp. 3479-3490.
IEEE DOI
2106
Accidents, Databases, Injuries, Safety, Optimization, Roads,
Vehicle crash testing, Risk analysis, active safety,
vehicle-braking strategies
BibRef
Lee, S.[Soomok],
Choi, J.[Jinwoo],
Seo, S.W.[Seung-Woo],
Ego-lane index-aware vehicular localisation using the DeepRoad
Network for urban environments,
IET-ITS(15), No. 3, 2021, pp. 371-386.
DOI Link
2106
BibRef
Chen, J.[Jin],
Sun, D.H.[Di-Hua],
Zhao, M.[Min],
Li, Y.[Yang],
Liu, Z.C.[Zhong-Cheng],
A New Lane Keeping Method Based on Human-Simulated Intelligent
Control,
ITS(23), No. 7, July 2022, pp. 7058-7069.
IEEE DOI
2207
Vehicles, Task analysis, Control systems, Feedforward systems,
Computational modeling, Roads, Wheels,
human vehicle co-piloting
BibRef
Dahl, J.[John],
Rodrigues-de Campos, G.[Gabriel],
Fredriksson, J.[Jonas],
Performance and Efficiency Analysis of a Linear Learning-Based
Prediction Model Used for Unintended Lane-Departure Detection,
ITS(23), No. 7, July 2022, pp. 9115-9125.
IEEE DOI
2207
Predictive models, Computational modeling, Time series analysis,
Kinematics, Data models, Analytical models, Benchmark testing,
active safety systems
BibRef
Li, W.F.[Wen-Feng],
Xie, Z.C.[Zheng-Chao],
Zhao, J.[Jing],
Gao, J.[Jinwu],
Hu, Y.F.[Yun-Feng],
Wong, P.K.[Pak Kin],
Human-Machine Shared Steering Control for Vehicle Lane Keeping
Systems via a Fuzzy Observer-Based Event-Triggered Method,
ITS(23), No. 8, August 2022, pp. 13731-13744.
IEEE DOI
2208
Vehicles, Man-machine systems, Vehicle dynamics, Tires, Automation,
Control design, Bandwidth, Vehicle system dynamics,
event-triggered communication
BibRef
Wu, W.[Wei],
Liu, Y.[Yang],
Liu, W.[Wei],
Zhang, F.[Fangni],
Dixit, V.[Vinayak],
Waller, S.T.[S. Travis],
Autonomous Intersection Management for Connected and Automated Vehicles:
A Lane-Based Method,
ITS(23), No. 9, September 2022, pp. 15091-15106.
IEEE DOI
2209
Delays, Autonomous vehicles, Resource management,
Intelligent transportation systems, Servers, Numerical analysis,
sliding time window
BibRef
Quan, Y.S.[Ying Shuai],
Kim, J.S.[Jin Sung],
Chung, C.C.[Chung Choo],
Linear Parameter Varying Models-Based Gain-Scheduling Control for
Lane Keeping System With Parameter Reduction,
ITS(23), No. 11, November 2022, pp. 20746-20756.
IEEE DOI
2212
Vehicle dynamics, Tires, Roads, Artificial neural networks,
Processor scheduling, Dynamics, Mathematical models,
gain-scheduling control
BibRef
Ustunel, E.[Eser],
Masazade, E.[Engin],
Iterative Range and Road Parameters Estimation Using Monocular Camera
on Highways,
ITS(24), No. 1, January 2023, pp. 139-151.
IEEE DOI
2301
For lane-keeping and adaptive cruise control.
Roads, Cameras, Estimation, Iterative methods, Numerical models,
Kalman filters, Road parameters estimation, 3D road modeling, optimization
BibRef
Guo, L.X.[Long-Xiang],
Jia, Y.[Yunyi],
Bilateral Adaptation of Longitudinal Control of Automated Vehicles
and Human Drivers,
ITS(24), No. 5, May 2023, pp. 5663-5671.
IEEE DOI
2305
Adaptation models, Vehicles, Behavioral sciences, Cost function,
Safety, Predictive models, Costs, Human driving behaviors, prediction
BibRef
Kim, H.[Hunmin],
Wan, W.B.[Wen-Bin],
Hovakimyan, N.[Naira],
Sha, L.[Lui],
Voulgaris, P.[Petros],
Robust vehicle lane keeping control with networked proactive
adaptation,
AI(325), 2023, pp. 104020.
Elsevier DOI
2312
Connected vehicles, Robust control under uncertainty, Vehicle control
BibRef
Liu, S.[Shen],
Müller, S.[Steffen],
Reliability of Deep Neural Networks for an End-to-End Imitation
Learning-Based Lane Keeping,
ITS(24), No. 12, December 2023, pp. 13768-13786.
IEEE DOI
2312
BibRef
Guo, X.[Xiye],
Liu, K.[Kai],
Meng, Z.J.[Zhi-Jun],
Li, X.Y.[Xiao-Yu],
Yang, J.[Jun],
Pseudolite-Based Lane-Level Vehicle Positioning in Highway Tunnel,
ITS(25), No. 2, February 2024, pp. 1612-1624.
IEEE DOI
2402
Base stations, Synchronization, Receivers,
Global navigation satellite system, Phase measurement, Clocks,
vehicle positioning
BibRef
Wang, T.S.[Tian-Shi],
Lu, H.[Huapu],
Sun, Z.Y.[Zhi-Yuan],
Wang, J.Y.[Jian-Yu],
Lane changing and keeping as mediating variables to investigate the
impact of driving habits on efficiency:
An EWM-GRA and CB-SEM approach with trajectory data,
IET-ITS(18), No. 2, 2024, pp. 230-243.
DOI Link
2402
CB-SEM, driving habits, efficiency, EWM-GRA, lane-change, NGSIM
BibRef
Li, F.B.[Fan-Biao],
Wu, Z.[Zheng],
Pal, N.R.[Nikhil R.],
Yang, C.H.[Chun-Hua],
Peng, H.[Hao],
Kaynak, O.[Okyay],
Huang, T.W.[Ting-Wen],
Lane-Keeping Control of Automatic Steering Systems via Adaptive Fuzzy
Sliding-Mode Approach,
SMCS(54), No. 3, March 2024, pp. 1683-1693.
IEEE DOI
2402
Steering systems, Task analysis, Tires, Uncertainty,
Velocity measurement, Vehicle dynamics, Torque,
sliding-mode control (SMC)
BibRef
Chang, X.H.[Xiao-Heng],
Liu, X.M.[Xi-Ming],
Hou, L.W.[Li-Wei],
Qi, J.H.[Jing-Han],
Quantized Fuzzy Feedback Control for Electric Vehicle Lateral
Dynamics,
SMCS(54), No. 4, April 2024, pp. 2331-2341.
IEEE DOI
2403
Vehicle dynamics, Quantization (signal), Feedback control,
Nonlinear dynamical systems, Mathematical models, Linear systems,
T-S fuzzy systems
BibRef
Xing, C.[Chao],
Zhu, Y.[Yueying],
Wang, J.Y.[Jia-Ying],
Wang, W.[Wei],
Vertical-Longitudinal Comprehensive Control for Vehicle With In-Wheel
Motors Considering Energy Recovery and Vibration Mitigation,
ITS(25), No. 7, July 2024, pp. 6730-6740.
IEEE DOI
2407
Reluctance motors, Vibrations, Automobiles, Force,
Suspensions (mechanical systems), Vehicle dynamics, Torque, active suspension
BibRef
Zhao, J.[Jing],
Qiu, Z.[Zengyu],
Hu, H.Q.[Hui-Qin],
Sun, S.L.[Shi-Liang],
HWLane: HW-Transformer for Lane Detection,
ITS(25), No. 8, August 2024, pp. 9321-9331.
IEEE DOI Code:
WWW Link.
2408
BibRef
Getahun, T.[Tesfamichael],
Karimoddini, A.[Ali],
An Integrated Vision-Based Perception and Control for Lane Keeping of
Autonomous Vehicles,
ITS(25), No. 8, August 2024, pp. 9001-9015.
IEEE DOI
2408
Roads, Lane detection, Automobiles, Sensors, Predictive models,
Global Positioning System, Cameras, Black Lane detection,
autonomous vehicles
BibRef
Zhang, Y.J.[Yu-Jun],
Zhu, L.[Lei],
Feng, W.[Wei],
Fu, H.Z.[Hua-Zhu],
Wang, M.Q.[Ming-Qian],
Li, Q.X.[Qing-Xia],
Li, C.[Cheng],
Wang, S.[Song],
VIL-100: A New Dataset and A Baseline Model for Video Instance Lane
Detection,
ICCV21(15661-15670)
IEEE DOI
2203
Dataset, Lane Detection. Performance evaluation, Codes, Lane detection, Annotations,
Object segmentation, Streaming media,
grouping and shape
BibRef
Liu, L.[Lizhe],
Chen, X.[Xiaohao],
Zhu, S.[Siyu],
Tan, P.[Ping],
CondLaneNet: a Top-to-down Lane Detection Framework Based on
Conditional Convolution,
ICCV21(3753-3762)
IEEE DOI
2203
Codes, Lane detection, Convolution, Shape, Pipelines,
Benchmark testing, Detection and localization in 2D and 3D,
Vision for robotics and autonomous vehicles
BibRef
Peng, F.C.[Feng-Chao],
Wang, C.[Chao],
Liu, J.Z.[Jian-Zhuang],
Yang, Z.[Zhen],
Active Learning for Lane Detection: A Knowledge Distillation Approach,
ICCV21(15132-15141)
IEEE DOI
2203
Measurement, Learning systems, Uncertainty, Lane detection,
Redundancy, Object detection,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Lee, M.[Minhyeok],
Lee, J.[Junhyeop],
Lee, D.[Dogyoon],
Kim, W.[Woojin],
Hwang, S.[Sangwon],
Lee, S.Y.[Sang-Youn],
Robust Lane Detection via Expanded Self Attention,
WACV22(1949-1958)
IEEE DOI
2202
Deep learning, Visualization, Lane detection, Roads,
Lighting, Benchmark testing, Segmentation,
Grouping and Shape Scene Understanding
BibRef
Tabelini, L.[Lucas],
Berriel, R.[Rodrigo],
Paixão, T.M.[Thiago M.],
Badue, C.[Claudine],
de Souza, A.F.[Alberto F.],
Oliveira-Santos, T.[Thiago],
Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection,
CVPR21(294-302)
IEEE DOI
2111
Codes, Lane detection, Computational modeling,
Aggregates, Detectors, Feature extraction
BibRef
Sun, J.,
Kim, S.,
Lee, S.,
Kim, Y.,
Ko, S.,
Reverse and Boundary Attention Network for Road Segmentation,
CVRSUAD19(876-885)
IEEE DOI
2004
driver information systems, image segmentation,
learning (artificial intelligence), neural nets,
traffic scene understanding
BibRef
van Gansbeke, W.,
de Brabandere, B.,
Neven, D.,
Proesmans, M.,
Van Gool, L.J.,
End-to-end Lane Detection through Differentiable Least-Squares
Fitting,
CVRSUAD19(905-913)
IEEE DOI
2004
backpropagation, edge detection,
feature extraction, image segmentation,
Autonomous Driving
BibRef
Hou, Y.,
Ma, Z.,
Liu, C.,
Loy, C.C.,
Learning Lightweight Lane Detection CNNs by Self Attention
Distillation,
ICCV19(1013-1021)
IEEE DOI
2004
convolutional neural nets, learning (artificial intelligence),
object detection, lightweight lane detection CNNs,
Message passing
BibRef
Roy, P.R.[Pankaj Raj],
Bilodeau, G.A.[Guillaume-Alexandre],
Road User Abnormal Trajectory Detection Using a Deep Autoencoder,
ISVC18(748-757).
Springer DOI
1811
BibRef
Irshad, A.,
Khan, A.A.,
Yunus, I.,
Shafait, F.,
Real-Time Lane Departure Warning System on a Lower Resource Platform,
DICTA17(1-8)
IEEE DOI
1804
alarm systems, image resolution, mobile computing,
object detection, object tracking, road accidents, road safety,
Shape
BibRef
Kim, J.,
Park, C.,
End-To-End Ego Lane Estimation Based on Sequential Transfer Learning
for Self-Driving Cars,
CVVT17(1194-1202)
IEEE DOI
1709
Convolution, Feature extraction, Image edge detection,
Image segmentation, Machine learning, Roads, Training
BibRef
Zhu, S.L.[Shu-Liang],
Wang, J.Q.[Jian-Qiang],
Yu, T.[Tao],
Wang, J.[Jiao],
A method of lane detection and tracking for expressway based on
RANSAC,
ICIVC17(62-66)
IEEE DOI
1708
Advanced driver assistance systems, Automobiles, Cameras, Fitting,
Image edge detection, Roads, Lane detection, RANSAC, local otsu,
window, scanning
BibRef
Ahmed, S.,
Rahiman, W.,
Robustness analysis of lane keeping system for autonomous ground
vehicle,
IVPR17(1-5)
IEEE DOI
1704
Friction
BibRef
Gurghian, A.,
Koduri, T.,
Bailur, S.V.,
Carey, K.J.,
Murali, V.N.,
DeepLanes: End-To-End Lane Position Estimation Using Deep Neural
Networks,
CVVT16(38-45)
IEEE DOI
1612
BibRef
Alkhorshid, Y.[Yasamin],
Aryafar, K.[Kamelia],
Wanielik, G.[Gerd],
Shokoufandeh, A.[Ali],
Camera-Based Lane Marking Detection for ADAS and Autonomous Driving,
ICIAR15(514-519).
Springer DOI
1507
BibRef
Chandakkar, P.S.[Parag S.],
Wang, Y.L.[Yi-Lin],
Li, B.X.[Bao-Xin],
Improving Vision-Based Self-Positioning in Intelligent Transportation
Systems via Integrated Lane and Vehicle Detection,
WACV15(404-411)
IEEE DOI
1503
Feature extraction
BibRef
Chandakkar, P.S.[Parag S.],
Venkatesan, R.[Ragav],
Li, B.X.[Bao-Xin],
Video-Based Self-positioning for Intelligent Transportation Systems
Applications,
ISVC14(I: 718-729).
Springer DOI
1501
BibRef
Al-Sarraf, A.[Ali],
Shin, B.S.[Bok-Suk],
Xu, Z.[Zezhong],
Klette, R.[Reinhard],
Ground Truth and Performance Evaluation of Lane Border Detection,
ICCVG14(66-74).
Springer DOI
1410
BibRef
Matveev, A.S.[Alexey S.],
Hoy, M.C.[Michael C.],
Savkin, A.V.[Andrey V.],
Boundary tracking by a wheeled robot with rigidly mounted sensors,
ICARCV12(148-153).
IEEE DOI
1304
BibRef
Borkar, A.[Amol],
Hayes, M.[Monson],
Smith, M.T.[Mark T.],
A New Multi-camera Approach for Lane Departure Warning,
ACIVS11(58-69).
Springer DOI
1108
BibRef
Leng, Y.C.[Yu-Chi],
Chen, C.L.[Chieh-Li],
Vision-based lane departure detection system in urban traffic scenes,
ICARCV10(1875-1880).
IEEE DOI
1109
BibRef
Morris, J.,
Haeusler, R.,
Jiang, R.[Ruyi],
Jawed, K.,
Kalarot, R.,
Khan, T.,
Khan, W.,
Manoharan, S.,
Morales, S.,
Vaudrey, T.,
Wiest, J.,
Klette, R.,
Current work in the ENPEDA project,
IVCNZ09(130-135).
IEEE DOI
0911
Environment perception and driver assistance.
Lane departure warning, blind spot supervision.
BibRef
Liu, J.F.[Jing-Fu],
Su, Y.F.[Yi-Feng],
Ko, M.K.[Ming-Kuan],
Yu, P.N.[Pen-Ning],
Development of a Vision-Based Driver Assistance System with Lane
Departure Warning and Forward Collision Warning Functions,
DICTA08(480-485).
IEEE DOI
0812
BibRef
Fritz, H.,
Gern, A.,
Schiemenz, H.,
Bonnet, C.,
CHAUFFEUR Assistant: a driver assistance system for commercial vehicles
based on fusion of advanced ACC and lane keeping,
IVS04(495-500).
IEEE DOI
0411
BibRef
Ishida, S.,
Gayko, J.E.,
Development, evaluation and introduction of a lane keeping assistance
system,
IVS04(943-944).
IEEE DOI
0411
BibRef
Chen, M.,
Jochem, T.M.[Todd M.],
Pomerleau, D.A.[Dean A.],
AURORA: a vision-based roadway departure warning system,
IROS95(I: 243-248).
IEEE DOI
9508
BibRef
Pomerleau, D.A.[Dean A.],
Jochem, T.M.[Todd M.],
A Rapidly Adapting Machine Vision System for Automated Vehicle Steering,
DARPA97(345-356).
BibRef
9700
Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Lateral Control for Vehicles .