THE RELATIONSHIP BETWEEN SPEED DIFFERENTIAL AND TIME TO COLLISION OF MALAYSIAN EXPRESSWAYS
DOI:
https://doi.org/10.55766/sujst-2023-01-e01613Keywords:
Lane-changing, TTC, speed differential, instrumented vehicle, risk indicatorAbstract
Lane change (LC) manoeuvre has been recognized as an important aspect of driving behavior that significantly impacts traffic operation and management. Incorrect LC execution, particularly incorrect gap distance selection before the LC movement, can lead to traffic accidents, most often in the form of a rear-end, sideswipe, or angled collision. This paper investigates the relationship between time to collision and the speed differential between the leading and following vehicles when lane change occurs. Using an instrumented vehicle method, data was gathered along a typical length of the Kuala Lumpur-Seremban expressway. A VBox (Video Velocity Box) is an on-board data collection device that is used to videotape traffic incidents on the road, was installed in a passenger car. In a three-day period, a total of 175 instances of lane changing were documented. Following gap distance was used to calibrate the VBox equipment as a measure of efficiency. A simple linear regression was conducted between time to collision (TTC) and speed differential. It was found that 60% and 75% of drivers have TTC fewer than 5 sec and 10 sec, separately, with 6.10 sec average TTC. The time to collision (TTC) has a negative linear relationship with speed differential (R2 = 84.47%). The finding shows that the higher the speed differential between vehicles, the lower the TTC value, which indicates a higher probability of collisions. It can be concluded that the speed differential between the test car and following vehicles is affecting the TTC, which is to be utilised as a risk indicator throughout lane-changing operation.
References
Ataelmanan, H., Puan, O.C., and Hassan, S.A. (2021a). Empirical evaluation of lane changing following gap distance on expressway. In: IOP Conference Series: Materials Science and Engineering, IOP Conf. Ser.: Mater. Sci. Eng., 1144: 012077. https://doi.org/10.1088/1757-899X/1144/1/012077
Ataelmanan, H., Puan, O.C., Hassan, S.A., and Azhari, S.A. (2021b). Calibration and validation of lane changing following gap distance in VISSIM. Ser I O P Conf Sci Mater. 1153(Regional Conference in Civil Engineering & Sustainable Development Goals in Higher Education Institutions (RCCE SDG 2020) 23rd-25th January 2021, Johor, Malaysia).
Bascunana, J.L. (1997). Analysis of lane change collision avoidance. Syst Iss ITS, p. 1-13.
Brackstone, M. (2010). Examination of the use of fuzzy sets to describe relative speed perception. Ergon 2000, 43(4):528-42. https://doi.org/10.1080/001401300184396
Hayward, J.C. (1972). Near miss determination through use of a scale of danger. 0PERATION Maint Transp Facil., p. 1-34.
Horst, R.V.D. (1991). Time-to-collision as a cue for decision-making in braking. Vis Veh., p. 19-26.
Horst, R.V.D. and Hogema, J. (1993). Time-to-collision and collision avoidance systems. Proc 6th Work Int [Internet].
Hou, J., List, G.F., and Guo, X. (2014). New algorithms for computing the time-to-collision in freeway traffic simulation models. Comput. Intell. Neurosci., 2014:761047. https://doi.org/10.1155/2014/761047
Hydén, C. (1987). The development of a method for traffic safety evaluation: The swedish traffic conflicts technique. Bull Lund Inst Technol Dep., 70:57p.
Ibrahim, M.N. (2015). Modelling of percent time spent following using spatial measurment approach for two lane highway. [PhD thesis]. UTM, (December), 41p.
Jula, H., Kosmatopoulos, E.B., and Ioannou, P.A. (2000). Collision avoidance analysis for lane changing and merging. IEEE Trans Veh Technol., 49(6):2,295-2,308. https://doi.org/10.1109/25.901899
Laureshyn, A., Svensson, Å., and Hydén, C. (2010). Evaluation of traffic safety, based on micro-level behavioural data: Theoretical framework and first implementation. Accid. Anal. Prev., 42(6):1,637-1,646. https://doi.org/10.1016/j.aap.2010.03.021
Li, M., Li, Z., Xu, C., and Liu, T. 2020; Short-term prediction of safety and operation impacts of lane changes in oscillations with empirical vehicle trajectories. Accid. Anal. Prev., 135:105345. https://doi.org/10.1016/j.aap.2019.105345
Lv, W., Song, W.G., Liu, X.D., and Ma, J. (2013). A microscopic lane changing process model for multilane traffic. Phys A Stat Mech its Appl. 392(5):1,142-1,152. https://doi.org/10.1088/1475-7516/2012/11/012
McLeod, R.W. and Ross, H.E. (1983). Optic-flow and cognitive factors in time-to-collision estimates. Perception, 12(4):417-423. https://doi.org/10.1068/p120417
Möbus, C. (2017). Driver modeling and simulation of lane change situations. PhD Thesis Günzbg Ger., 239p.
Moridpour, S., Rose, G., Sarvi, M., and Mazloumi, E. (2012). Influence of the surrounding traffic characteristics on lane changing decision of heavy vehicle drivers. Road. Transp. Res., 21(3):19-33.
Naranjo, J.E., González, C., García, R., De Pedro, T. (2008). Lane-change fuzzy control in autonomous vehicles for the overtaking maneuver. IEEE Trans. Intell. Transp. Syst., 9(3):438-450. https://doi.org/10.1109/TITS.2008.922880
Nobukawa, K., Bao, S., LeBlanc, D.J., Zhao, D., and Peng, H. (2016). Gap acceptance during lane changes by large truck driver an image based analysis. IEEE Trans. Intell. Transp. Syst., 17(3):772-781. https://doi.org/10.1109/TITS.2015.2482821
Peng, J., Guo, Y., Fu, R., Yuan, W., and Wang, C. (2015). Multi-parameter prediction of drivers' lane-changing behaviour with neural network model. Appl. Ergon., 50:207-217. https://doi.org/10.1016/j.apergo.2015.03.017
Saffarzadeh, M., Nadimi, N., Naseralavi, S., and Mamdoohi, A.R. (2013). A general formulation for time-to-collision safety indicator. In: Proceedings of the Institution of Civil Engineers-Transport, p. 294-304. https://doi.org/10.1680/tran.11.00031
Schwarz, C. (2014). On computing time-to-collision for automation scenarios. Transp. Res. Part F Traffic. Psychol. Behav.,
https://doi.org/10.1016/j.trf.2014.06.015
Sen, B., Smith, J.D., and Najm, W.G. (2003). Analysis of lane change crashes. Final Rep DOT Hs 809 702, p. 1-49.
Shawky, M. (2020). Factors affecting lane change crashes. IATSS Res. 44(2):155-161. https://doi.org/10.1016/j.iatssr.2019.12.002
Smith, D.L, Najm, W.G., and Glassco, R.A. (2002). Feasibility of driver judgment as basis for a crash avoidance database. Trans. Res. Rec., 1784(1):9-16. https://doi.org/10.3141/1784-02
St-aubin, P. and Candidate, P.D. (2014). Comparison of various time-to-collision prediction and aggregation methods for surrogate safety analysis. Transp. Res. Board. 94th Annu. Meet., 1(514):20.
Suh, J., Chae, H., and Yi, K. (2018). Stochastic model-predictive control for lane change decision of automated driving vehicles. IEEE Trans. Veh. Technol., 67(6):4,771-4,782. https://doi.org/10.1109/TVT.2018.2804891
Svensson, Å. (1998). A method for analysing the traffic process in a safety perspective. Dept. traffic. Plan. Eng., 145p.
Talmadge, S., Dixon, D., and Quon, B. (1997). Development of performance specifications for collision avoidance systems for lane change crashes. task 6 interim report: testbed systems design and associated facilities. Interim Rep Dev Perform Specif. (May).
Toledo, T. and Farah, H. (2011). Alternative definitions of passing critical gaps. Transp. Res. Rec.: J. Transp. Res. Board., 2260:76-82. https://doi.org/10.3141/2260-09
Toledo, T., Koutsopoulos, H.N., and Ben-Akiva, M.E. (2003). Modeling integrated lane-changing behavior. Transp Res Rec J Transp Res Board. 1857(1):30-38. https://doi.org/10.3141/1857-04
Vogel, K. (2003). A comparison of headway and time to collision as safety indicators. Accid. Anal. Prev., 35(3):427-433. https://doi.org/10.1016/S0001-4575(02)00022-2
Wali, B., Khattak, A.J., and Karnowski, T. (2020). The relationship between driving volatility in time to collision and crash-injury severity in a naturalistic driving environment. Anal. Met. Accid. Res., 28:100136. https://doi.org/10.1016/j.amar.2020.100136
Weber, L. (2017). Driver modeling and simulation of lane change situations: influence of different rear view mirror types on gap acceptance behavior, [PhD thesis]. Universität Oldenburg, 239p.
Winsum, W.V., Waard, D.D., and Brookhuis, K.A. (1999). Lane change manoeuvres and safety margins. Transp. Res. Part F., 2(3):139-149. https://doi.org/10.1016/S1369-8478(99)00011-X
Xu, C. and Qu, Z.W. (2014). Empirical analysis on time to collision at urban expressway. Appl. Mech. Mater., 505-506:1,127-1,132. https://doi.org/10.4028/www.scientific.
net/AMM.505-506.1127
Yang, M., Wang, X., and Quddus, M. (2019). Examining lane change gap acceptance, duration and impact using naturalistic driving data. Transp. Res. Part C., 104(April):317-331. https://doi.org/10.1016/j.trc.2019.05.
Zhao, D., Lam, H., Peng, H., Bao, S., LeBlanc, D.J., Nobukawa, K., Pan, C.S. (2017). Accelerated evaluation of automated vehicles safety in lane-change scenarios based on importance sampling techniques. IEEE Trans. Intell. Transp. Syst., 18(3):595-607. https://doi.org/10.1109/
TITS.2016.2582208
Zhou, H. and Itoh, M. (2016). How does a driver perceive risk when making decision of lane-changing?, IFAC-PapersOnLine, 49(19):60-65. https://doi.org/10.1016/
j.ifacol.2016.10.462
