This paper proposes a novel algorithm for decision-making on autonomous lane change manoeuvre in vehicles. The proposed approach defines a number of constraints, based on the vehicle’s dynamics and environmental conditions, which must be satisfied for a safe and comfortable lane change manoeuvre. Inclusion of the lateral position of other vehicles on the road and the tyre-road friction are the main advantages of the proposed algorithm. To develop the lane change manoeuvre decision-making algorithm, first, the equations for the lateral movement of the vehicle in terms of manoeuvre time are produced. Then, the critical manoeuvring time is calculated on the basis of the constraints. Finally, the decision is made on the feasibility of carrying out the manoeuvre by comparing the critical times. Numerous simulations, taking into account the tyre-road friction and vehicles’ inertia and velocity, are conducted to compute the
critical times and a model named TUG-LCA is presented based on the corresponding results.
Mathew TV. Lane Changing Models. In: Transportation Systems Engineering. 2014; p. 15.1-15.12.
Djenouri D, Soualhi W, Nekka E. VANET’s Mobility Models and Overtaking: An Overview. 3rd International Conference on Information and Communication Technologies: From Theory to Applications (ICTTA). 2008; p. 1-6.
Wang J, Chai R, Wu G. Changing Lane Probability Estimating
Model Based on Neural Network. 26th Chinese Control and Decision Conference (CCDC). 2014; p. 3915-3920.
Gipps PG. A Model for the Structure of Lane-changing Decisions. Transportation Research Part B: Methodological.
;20(5):403-414. doi: 10.1016/0191-2615(86)90012-3
Hetrick S. Examination of Driver Lane Change Behavior and the Potential Effectiveness of Warning Onset Rules for Lane Change or “Side” Crash Avoidance Systems [Master Thesis]. Virginia Polytechnic Institute & State University; 1997.
Penghui L, Mengxia H, Wenhui Z, Xiaoqing X, Yibing L.
Steering Behavior during Overtaking on Freeways. Proceedings
of the 5th International Conference on Computing for Geospatial Research and Application; 2014 Aug 4-6; Washington DC; 2014. p. 117-118.
Lee HK, Barlovic R, Schreckenberg M, Kim D. Mechanical
Restriction Versus Human Overreaction Triggering Congested Traffic States. Physical Review Letters. 2004;92(23):1-4. doi: 10.1103/PhysRev-Lett.92.238702.
Habel L, Schreckenberg M. Asymmetric Lane Change Rules for a Microscopic Highway Traffic Model. Proceedings of the 11th International Conference on Cellular Automata for Research and Industry (ACRI); 2014 Sep 22-25; Krakow, Poland; Springer International Publishing; 2014. p. 620-629.
Ghaffari A, Khodayari A, Arvin S, Alimardani F. Lane Change Trajectory Model Considering the Driver Effects Based on MANFIS. International Journal of Automotive Engineering. 2012;2(4):261-275.
Song X, Cao H, Huang J. Vehicle Path Planning in Various Driving Situations Based on the Elastic Band Theory for Highway Collision Avoidance. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 2013; p. 1706-1722.
Yoon J. Path Planning and Sensor Knowledge Store for Unmanned Ground Vehicles in Urban Area Evaluated by Multiple Ladars [PhD thesis]. University of Florida; 2011.
El-Hajjaji A, Ouladsine M. Modeling Human Vehicle Driving by Fuzzy Logic for Standardized ISO Double Lane Change Maneuver. 10th IEEE International Workshop on Robot and Human Interactive Communication. 2001; p. 499-503.
Nilsson J, Sjoberg J. Strategic Decision Making for Automated Driving on Two-lane, One Way Roads Using Model Predictive Control. IEEE Intelligent Vehicles Symposium (IV). 2013; p. 1253-1258.
Zhang S, Deng W, Zhao Q, Sun H, Litkouhi B. Dynamic
Trajectory Planning for Vehicle Autonomous Driving. IEEE International Conference on Systems, Man, and Cybernetics (SMC). 2013; p. 4161-4166.
Toledo T, Zohar D. Modeling Duration of Lane Changes. Transportation Research Record: Journal of the Transportation Research Board. 2007; p. 71-78. doi: http://dx.doi.org/10.3141/1999-08.
Xiaorui W, Hongxu Y. A Lane Change Model with the Consideration of Car Following Behavior. Procedia - Social and Behavioral Sciences. 2013;96:2354-2361. doi:10.1016/j.sbspro.2013.08.264.
Shamir T. How Should an Autonomous Vehicle Overtake a Slower Moving Vehicle: Design and Analysis of an Optimal Trajectory. IEEE Transactions on Automatic Control. 2004;49(4):607-610. doi: 10.1109/TAC.2004.825632.
Hult R, Sadeghi Tabar R. Path Planning for Highly Automated Vehicles [Master Thesis]. Chalmers University of Technology, Gothenburg, Sweden; 2013.
Ahmed KI. Modeling Drivers’ Acceleration and Lane Changing Behavior [PhD thesis]. Massachusetts Institute of Technology; 1999.
Keller CG, Dang T, Fritz H, Joos A, Rabe C, Gavrila DM. Active Pedestrian Safety by Automatic Braking and Evasive Steering. IEEE Transactions on Intelligent Transportation Systems. 2011;12(4):1292-1304. doi: 10.1109/TITS.2011.2158424.
Jula H, Kosmatopoulos EB, Ioannou PA. Collision Avoidance Analysis for lane Changing and Merging. IEEE Transactions on Vehicular Technology. 2000;49(6):2295-2308. doi: 10.1109/25.901899.
Chen YL, Wang CA. Vehicle Safety Distance Warning System: A Novel Algorithm for Vehicle Safety Distance Calculating Between Moving Cars. IEEE 65th Vehicular Technology Conference (VTC). 2007; p. 2570-2574.
Feng G, Wang W, Feng J, Tan H, Li F. Modelling and Simulation for Safe Following Distance Based on Vehicle Braking Process. IEEE 7th International Conference on e-Business Engineering (ICEBE). 2010; p. 385-388.
Wu Y, Xie J, Du L, Hou Z. Analysis on Traffic Safety Distance of Considering the Deceleration of the Current Vehicle. Second International Conference on Intelligent Computation Technology and Automation (ICICTA). 2009; p. 491-494.
Chen YL, Wang SC, Wang CA. Study on Vehicle Safety Distance Warning System. IEEE International Conference on Industrial Technology (ICIT). 2008; p. 1-6.
Salvucci DD, Liu A. The Time Course of a Lane Change: Driver Control and Eye-movement Behavior. Transportation Research Part F: Traffic Psychology and Behavior. 2002;5(2):123-132.
Lee G. Modeling Gap Acceptance at Freeway Merges [Master Thesis]. Massachusetts Institute of Technology; 2006.
Thiemann C, Treiber M, Kesting A. Estimating Acceleration and Lane-changing Dynamics Based on NGSIM Trajectory Data. 87th Transportation Research Board Annual Meeting; 2008.
Gurupackiam S, Lee JS. Empirical Study of Accepted Gap and Lane Change Duration within Arterial Traffic under Recurrent and Non-recurrent Congestion. International Journal for Traffic and Transport Engineering. 2012;2(4):306-322. doi: 10.7708/ijtte.
Cao X, Young W, Sarvi M. Exploring Duration of Lane Change Execution. Australasian Transport Research Forum; 2013.
Caywood WC, Donnelly HL, Rubinstein N. Guideline for Ride-quality Specifications Based on Transpo ‘72 Test Data. Johns Hopkins University Applied Physics Laboratory, Washington. 1977. Tech. Rep: 00168889.
Samiee S, Azadi S, Kazemi S, Hatamian Haghighi AH, Ashouri MR. The Effect of Torque Feedback Exerted to Driver’s Hands on Vehicle Handling - A Hardware-in-the-loop Approach. Systems Science & Control Engineering. 2015;3(1):129-141. doi: 10.1080/21642583.2014.996918.
Jazar RN. Vehicle Dynamics: Theory and Applications. New York, USA: Springer; 2008.
Lex C, Eichberger A, Hirschberg W. Methods to Estimate the Tire Road Friction for Advanced Driver Assistance Systems. ATZ Worldwide. 2011;113(12):56-61.
Albers A, Düser T. Implementation of a Vehicle-in-the-Loop Development and Validation Platform. FISITA World Automotive Congress; 2010.
Anonymous “CarMaker User’s Guide”. IPG Automotive GmbH, Vol. 4; 2012.
Ziegler S, Höpler R. Extending the IPG CarMaker by FMI Compliant Units. 8th International Modelica Conference. 2011; p. 779-784.
Huber F, Hickel G, Hammann K, Leonhard V, Schmidt E, Schik W, Tschritter P, Weilacher V, Wurster U. IPG CarMaker Pro, vol. 4.0.3; 2012.
Martinus M, Deicke M, Folie M. Virtual Test Driving Hardware-Independent Integration of Series Software. ATZ Elektronik. 2013;8(5):16-21.
Schwab S, Leichsenring T, Zofka MR, Baer T. Consistent Test Method for Assistance Systems. ATZ Worldwide. 2014;116(9):38-43. doi: 10.1007/s38311-014-0216-x.
Anonymous. The New Car Assessment Program Electronic Stability Control System Testing. U.S. Department of Transportation, National Highway Traffic Safety Administration; 2013.
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