The “field of safe travel” revisited: interpreting driving behaviour performance through a holistic approach

References

• Abbink, D. A., & Mulder, M. (2010). Neuromuscular analysis as a guideline in designing shared control. In M. H. Zadeh (Ed.), Advances in haptics (pp. 499–516). InTech. doi:10.5772/8696. Retrieved from http://www.intechopen.com/books/advances-in-haptics/neuromuscular-analysis-as-a-guideline-in-designing-shared-control
   Google Scholar
• Abbink, D. A., Mulder, M., & Boer, E. R. (2012). Haptic shared control: Smoothly shifting control authority? Cognition, Technology & Work, 14, 19–28. doi:10.1007/s10111-011-0192-5
   Web of Science ®Google Scholar
• Abelson, R. P. (1981). Psychological status of the script concept. American Psychologist, 36, 715–729. doi:10.1037/0003-066X.36.7.715
   Web of Science ®Google Scholar
• Armand, A., Filliat, D., & Ibañez-Guzman, J. (2014, June). Ontology-based context awareness for driving assistance systems. 2014 IEEE intelligent vehicles symposium proceedings, pp. 227–233. doi:10.1109/IVS.2014.6856509
   Google Scholar
• Bella, F. (2011). How traffic conditions affect driver behavior in passing manoeuvers. Advances in Transportation Studies, Special Issue, 2011, 113–126.
   Google Scholar
• Ben-Bassat, T., & Shinar, D. (2011). Effect of shoulder width, guardrail and roadway geometry on driver perception and behavior. Accident Analysis and Prevention, 43, 2142–2152. doi:10.1016/j.aap.2011.06.004
   PubMed Web of Science ®Google Scholar
• Brackstone, M., & McDonald, M. (1999). Car following: A historical review. Transportation Research Part F, 2, 181–196. doi:10.1016/S1369-8478(00)00005-X
   Google Scholar
• Brackstone, M., & McDonald, M. (2007). Driver headway: How close is too close on a motorway? Ergonomics, 50, 1183–1195. doi:10.1080/00140130701318665
   PubMed Web of Science ®Google Scholar
• Brackstone, M., Sultan, B., & McDonald, M. (2002). Motorway driver behaviour: Studies on car following. Transportation Research Part F, 5, 31–46. doi:10.1016/S1369-8478(02)00004-9
   Google Scholar
• Brandt, T., Sattel, T., & Böhm, M. (2007, June). Combining haptic human–machine interaction with predictive path planning for lane-keeping and collision avoidance systems. 2007 IEEE intelligent vehicles symposium, pp. 582–587. doi:10.1109/IVS.2007.4290178
   Google Scholar
• Cavallo, V., Mestre, D., & Berthelon, C. (1997). Time-to-collision judgments: Visual and spatio-temporal aspects. In T. Rothengatter & E. C. Vaya (Eds.), Traffic and transport psychology: Theory and application (pp. 97–101). Amsterdam: Pergamon.
   Google Scholar
• Charlton, S. G., Mackie, H. W., Baas, P. H., Hay, K., Menezes, M., & Dixon, C. (2010). Using endemic road features to create self-explaining roads and reduce vehicle speeds. Accident Analysis and Prevention, 42, 1989–1998. doi:10.1016/j.aap.2010.06.006
   PubMed Web of Science ®Google Scholar
• Clarke, D. D., Ward, P. J., & Jones, J. (1998). Overtaking road-accidents: Differences in manoeuvre as a function of driver age. Accident Analysis and Prevention, 30, 455–467. doi:10.1016/S0001-4575(97)00105-X
   PubMed Web of Science ®Google Scholar
• Clarke, D. D., Ward, P. J., & Jones, J. (1999). Processes and countermeasures in overtaking road accidents. Ergonomics, 42, 846–867. doi:10.1080/001401399185333
   Web of Science ®Google Scholar
• DeLucia, P. R. (1991). Pictorial and motion-based information for depth perception. Journal of Experimental Psychology: Human Perception and Performance, 17, 738–748. Retrieved from http://dx.doi.org/10.1037/0096-1523.17.3.738
   PubMed Web of Science ®Google Scholar
• DeLucia, P. R., & Warren, R. (1994). Pictorial and motion-based depth information during active control of self-motion: Size-arrival effects on collision avoidance. Journal of Experimental Psychology: Human Perception and Performance, 20, 783–798. Retrieved from http://dx.doi.org/10.1037/0096-1523.20.4.783
   PubMed Web of Science ®Google Scholar
• Denton, G. G. (1980). The influence of visual pattern on perceived speed. Perception, 9, 393–402. doi:10.1068/p090393
   PubMed Web of Science ®Google Scholar
• De Waard, D., Jessurun, M., Steyvers, F. J. J. M., Regatt, P. T. F., & Brookhuis, K. A. (1995). Effects of road layout and road environment on driving performance, drivers’ physiology and road appreciation. Ergonomics, 38, 1395–1407. doi:10.1080/00140139508925197
   PubMed Web of Science ®Google Scholar
• De Waard, D., Steyvers, F. J. J. M., & Brookhuis, K. A. (2004). How much visual road information is needed to drive safely and comfortably? Safety Science, 42, 639–655. doi:10.1016/j.ssci.2003.09.002
   Web of Science ®Google Scholar
• Domini, F., & Caudec, C. (1999). Perceiving surface slant from deformation of optic flow. Journal of Experimental Psychology: Human Perception and Performance, 25, 426–444. Retrieved from http://dx.doi.org/10.1037/0096-1523.25.2.426
   PubMed Web of Science ®Google Scholar
• Domini, F., & Caudec, C. (2003). 3-D structure perceived from dynamic information: A new theory. Trends in Cognitive Sciences, 7, 444–449. doi:10.1016/j.tics.2003.08.007
   PubMed Web of Science ®Google Scholar
• Eberts, R. E., & MacMillan, A. G. (1985). Misperception of small cars. In R. E. Eberts & C. G. Eberts (Eds.), Trends in ergonomics/human factors II (pp. 33–39). Amsterdam: North-Holland.
   Google Scholar
• Engstrom, J., & Hollnagel, E. (2007). A general conceptual framework for modelling behavioural effects of driver support functions. In P. C. Cacciabue (Ed.), Modelling driver behaviour in automotive environments (pp. 61–84). London: Springer.
   Google Scholar
• Evans, L., & Rothery, R. (1976). The influence of forward vision and target size on apparent inter-vehicular spacing. Transportation Science, 10, 85–101. Retrieved from http://dx.doi.org/10.1287/trsc.10.1.85 doi: 10.1287/trsc.10.1.85
   Google Scholar
• Fajen, B. R., & Warren, W. H. (2000). Go with the flow. Trends in Cognitive Sciences, 4, 369–370. doi:10.1016/S1364-6613(00)01532-1
   PubMed Web of Science ®Google Scholar
• Farah, H. (2013). Modelling drivers’ passing duration and distance in a virtual environment. IATSS Research, 37, 61–67. doi:10.1016/j.iatssr.2013.03.001
   Google Scholar
• Flemisch, F., Heesen, M., Hesse, T., Kelsch, J., Schieben, A., & Beller, J. (2012). Towards a dynamic balance between humans and automation: Authority, ability, responsibility and control in shared and cooperative control situations. Cognition, Technology & Work, 14, 3–18. doi:10.1007/s10111-011-0191-6
   Web of Science ®Google Scholar
• Flemisch, F. O., Bengler, K., Bubb, H., Winner, H., & Bruder, R. (2014). Towards cooperative guidance and control of highly automated vehicles: H-mode and conduct-by-wire. Ergonomics, 57, 343–360. doi:10.1080/001400139.2013.869355 doi: 10.1080/00140139.2013.869355
   PubMed Web of Science ®Google Scholar
• Fodor, J. A., & Pylyshyn, S. W. (1981). How direct is visual perception? Some reflections on Gibson’s “ecological approach”. Cognition, 9, 139–196. doi:10.1016/0010-0277(81)90009-3
   PubMed Web of Science ®Google Scholar
• Forsyth, B. A. C., & MacLean, K. E. (2006). Predictive haptic guidance: Intelligent user assistance for the control of dynamic tasks. IEEE Transactions on Visualization and Computer Graphics, 12, 103–113. doi:10.1109/TVCG.2006.11
   PubMed Web of Science ®Google Scholar
• Frenz, H., Bremmer, F., & Lappe, M. (2003). Discrimination of travel distances from “situated” optic flow. Vision Research, 43, 2173–2183. doi:10.1016/S0042-6989(03)00337-7
   PubMed Web of Science ®Google Scholar
• Gibson, J. J. (1950). The perception of visual world. Oxford: Houghton Mifflin.
   Google Scholar
• Gibson, J. J. (1958). Visually controlled locomotion and visual orientation in animals. British Journal of Psychology, 49, 182–194. doi:10.1111/j.2044-8295.1958.tb00656.x
   PubMed Web of Science ®Google Scholar
• Gibson, J. J. (1979). The ecological approach to visual perception. Boston, MA: Houghton Mifflin.
   Google Scholar
• Gibson, J. J., & Crooks, L. E. (1938). A theoretical field-analysis of automobile-driving. The American Journal of Psychology, 51, 453–471. doi:10.2307/1416145
   Google Scholar
• Godley, S. T., Triggs, T. J., & Fildes, B. N. (2004). Perceptual lane width, wide perceptual road center markings and driving speeds. Ergonomics, 47, 237–256. doi:10.1080/00140130310001629711
   PubMed Web of Science ®Google Scholar
• Godthelp, H. (1988). The limits of path error-neglecting in straight lane driving. Ergonomics, 31, 609–619. doi:10.1080/00140138808966703
   Web of Science ®Google Scholar
• Godthelp, H., Milgram, P., & Blaauw, G. J. (1984). The development of a time-related measure to describe driving strategy. Human Factors, 26, 257–268. doi:10.1177/001872088402600302
   Web of Science ®Google Scholar
• Gray, R., & Regan, D. M. (2005). Perceptual processes used by drivers during overtaking in a driving simulator. Human Factors: The Journal of the Human Factors and Ergonomics Society, 47, 394–417. doi:10.1518/0018720054679443
   PubMed Web of Science ®Google Scholar
• Gregory, R. L. (1998). Eye and brain: The psychology of seeing (5th ed.). Tokyo: Oxford University Press.
   Google Scholar
• Griffiths, P. G., & Gillespie, R. B. (2005). Sharing control between humans and automation using haptic interface: Primary and secondary task performance benefits. Human Factors: The Journal of the Human Factors and Ergonomics Society, 47, 574–590. doi:10.1518/001872005774859944
   PubMed Web of Science ®Google Scholar
• Groeger, J. A. (2000). Understanding driving: Applying cognitive psychology to a complex everyday task. East Sussex: Psychology Press.
   Google Scholar
• Groeger, J. A. (2002). Trafficking in cognition: Applying cognitive psychology to driving. Transportation Research Part F, 5, 235–248. doi:10.1016/S1369-8478(03)00006-8
   Google Scholar
• Harb, R., Radwan, E., Yan, X., & Abdel-Aty, M. (2007). Light truck vehicles (LTVs) contribution to rear-end collisions. Accident Analysis and Prevention, 39, 1026–1036. doi:10.1016/j.aap.2007.01.007
   PubMed Web of Science ®Google Scholar
• Harris, J. M., & Bonas, W. (2002). Optic flow and scene structure do not always contribute to the control of human walking. Vision Research, 42, 1619–1626. doi:10.1016/S0042-6989(02)00066-4
   PubMed Web of Science ®Google Scholar
• Hegeman, G., Brookhuis, K., & Hoogendoorn, S. (2005). Opportunities of advanced driver assistance systems towards overtaking. European Journal of Transportation and Infrastructure Research, 5, 281–294.
   Google Scholar
• Henderson, J. M., & Hollingworth, A. (1998). Eye movements during scene viewing: An overview. In G. Underwood (Ed.), Eye guidance in reading and scene perception (pp. 269–293). Amsterdam: Elsevier.
   Google Scholar
• Hills, B. L. (1980). Vision, visibility, and perception in driving. Perception, 9, 183–216. doi:10.1068/p090183
   PubMed Web of Science ®Google Scholar
• Hohm, A., & Winner, H. (2010, June). Assessment of adequate overtaking margin (AOM) for an overtaking assistance system. 2010 IEEE Intelligent vehicles symposium (IV), pp. 717–722. doi:10.1109/IVS.2010.5548146
   Google Scholar
• Hollnagel, E., & Woods, D. D. (2005). Joint cognitive systems: Foundations of cognitive systems engineering. Boca Raton, FL: CRC Press.
   Google Scholar
• Hollnagel, E., Nåbo, A., & Lau, I. (2003). A systemic model for driver-in-control. Proceedings of the 2nd International driving symposium on human factors in driver assessment, training and vehicle design (pp. 86-91). Iowa City, IA: Public Policy Center, University of Iowa. Retrieved from http://drivingassessment.uiowa.edu/DA2003/pdf/23_Hollnagelformat.pdf
   Google Scholar
• Jacobs, R. A. (2002). What determines visual cue reliability? Trends in Cognitive Sciences, 6, 345–350. doi:10.1016/S1364-6613(02)01948-4
   PubMed Web of Science ®Google Scholar
• Kemeny, A., & Panerai, F. (2003). Evaluating perception in driving simulation experiments. Trends in Cognitive Sciences, 7, 31–37. doi:10.1016/S1364-6613(02)00011-6
   PubMed Web of Science ®Google Scholar
• Kinnear, N., Helman, S., Wallbank, C., & Grayson, G. (2015). An experimental study of factors associated with driver frustration and overtaking intentions. Accident Analysis and Prevention, 79, 221–230. doi:10.1016/j.aap.2015.03.032
   PubMed Web of Science ®Google Scholar
• Klein, G., & Crandall, B. W. (1995). The role of mental simulation in problem solving and decision making. In P. E. Hancock, J. M. Flash, J. E. Caird, & K. J. Vicente (Eds.), Local applications of the ecological approach to human–machine systems (Vol. 2, pp. 324–358). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
   Google Scholar
• Klingelschmitt, S., Damerow, F., & Eggert, J. (2015, June). Managing the complexity of inner-city scenes: An efficient situation hypotheses selection scheme. 2015 IEEE intelligent vehicles symposium (IV), pp. 1232–1239. doi:10.1109/IVS.2015.7225851
   Google Scholar
• Koustanai, A., Boloix, E., van Elslande, P., & Bastien, C. (2008). Formation of expectations while driving: Influence of the possibility and the necessity to anticipate on the ability to identify danger. Transportation Research Part F, 11, 147–157. doi:10.1016/j.trf.2007.09.001
   Google Scholar
• Lee, D. N. (1976). A theory of visual control of braking based on information about time-to-collision. Perception, 5, 437–459. doi:10.1068/p050437
   PubMed Web of Science ®Google Scholar
• Lee, D. N., & Lishman, R. (1977). Visual control of locomotion. Scandinavian Journal of Psychology, 18, 224–230. doi:10.1111/j.1467-9450.1977.tb00281.x
   PubMed Web of Science ®Google Scholar
• Lewis-Evans, B., & Charlton, S. (2006). Explicit and implicit processes in behavioural adaptation to road width. Accident Analysis and Prevention, 38, 610–617. doi:10.1016/j.aap.2005.12.005
   PubMed Web of Science ®Google Scholar
• Liu, S., Wang, J., & Fu, T. (2016). Effects of lane width, lane position and edge shoulder width on driving behavior in underground urban expressways: A driving simulator study. International Journal of Environmental Research and Public Health, 13, 1010. doi:10.3390/ijerph13101010
   Web of Science ®Google Scholar
• Mackie, H. W., Charlton, S. G., Baas, P. H., & Villasenor, P. C. (2013). Road user behaviour changes following a self-explaining roads intervention. Accident Analysis and Prevention, 50, 742–750. doi:10.1016/j.aap.2012.06.026
   PubMed Web of Science ®Google Scholar
• Mars, F., Deroo, M., & Hoc, J. M. (2014). Analysis of human–machine cooperation when driving with different degrees of haptic shared control. IEEE Transactions on Haptics, 7, 324–333. doi:10.1109/TOH.2013.2295095
   PubMed Web of Science ®Google Scholar
• Michon, J. A. (1985). A critical view of driver behaviour models: What do we know, what should we do? In L. Evans & R. C. Schwing (Eds.), Human behaviour and traffic safety (pp. 485–524). New York, NY: Plenum Press.
   Google Scholar
• Morgan, J. F., & Hancock, P. A. (2009). Estimations in driving. In C. Castro (Ed.), Human factors of visual and cognitive performance in driving (pp. 51–62). Boca Raton, FL: CRC Press.
   Google Scholar
• Mulder, M., Abbink, D. A., & Boer, E. R. (2008, October). The effect of haptic guidance on curve negotiation behavior of young, experienced drivers. 2008 IEEE international conference on systems, man and cybernetics (SMC), pp. 804–809. doi:10.1109/ICSMC.2008.4811377
   Google Scholar
• Mulder, M., Abbink, D. A., van Paassen, M. M., & Mulder, M. (2011). Design of a haptic gas pedal for active car-following support. IEEE Transactions on Intelligent Transportation Systems, 12, 268–279. doi:10.1109/TITS.2010.2091407
   Web of Science ®Google Scholar
• Mulder, M., Mulder, M., van Paassen, M. M., & Abbink, D. A. (2008). Haptic gas pedal feedback. Ergonomics, 51, 1710–1720. doi:10.1080/00140130802331583
   PubMed Web of Science ®Google Scholar
• Mulder, M., Pauwelussen, J. J., Van Paassen, M. M., Mulder, M., & Abbink, D. A. (2010). Active deceleration support in car following. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 40, 1271–1284. doi:10.1109/TSMCA.2010.2044998
   Web of Science ®Google Scholar
• Naatanen, R., & Summala, H. (1974). A model for the role of motivational factors in drivers’ decision making. Accident Analysis and Prevention, 6, 243–261. doi:10.1016/0001-4575(74)90003-7
   Google Scholar
• Panerai, F., Droulez, J., Kelada, J.-M., Kemeny, A., Balligand, E., & Favre, B. (2001, September). Speed and safety distance control in truck driving: comparison of simulation and real-world environment. Paper presented at the Driving Simulation Conference (DSC 2001), Sophia-Antipolis, Nice, France. Retrieved from http://experts.renault.com/dsc2001/speed-and-safety.pdf
   Google Scholar
• Papakostopoulos, V., & Marmaras, N. (2008, July). Designing advanced driver assistance systems (ADAS): What kind of analysis is needed? In W. Karwowsky & G. Salvendy (Eds.), AHFE 2008 Conference proceedings: International conference on applied human factors and ergonomics (electronic edition). Las Vegas, NV: USA Publishing.
   Google Scholar
• Papakostopoulos, V., Nathanael, D., Portouli, E., & Marmaras, N. (2015). The effects of changes in traffic scene during overtaking. Accident Analysis and Prevention, 79, 126–132. doi:10.1016/j.aap.2015.02.025
   PubMed Web of Science ®Google Scholar
• Petermeijer, S. M., Abbink, D. A., & de Winter, J. C. (2015). Should drivers be operating within an automation-free bandwidth? Evaluating haptic steering support systems with different levels of authority. Human Factors: The Journal of the Human Factors and Ergonomics Society, 57, 5–20. doi:10.1177/0018720814563602
   PubMed Web of Science ®Google Scholar
• Plant, K. L., & Stanton, N. A. (2013). The explanatory power of schema theory: Theoretical foundations and future applications in ergonomics. Ergonomics, 56, 1–15. doi:10.1080/00140139.2012.736542
   PubMed Web of Science ®Google Scholar
• Pollatschek, M., & Polus, A. (2005). Modelling impatience of drivers in passing maneuvers. In H. S. Mahmassani (Ed.), Transportation and traffic theory: Flow, dynamics and human interaction – Proceedings of the 16th International Symposium on Transportation and Traffic Theory (pp. 267–279). Bingley: Emerald Group.
   Google Scholar
• Ranney, T. A. (1999). Psychological factors that influence car-following and car-following development. Transportation Research Part F, 2, 213–219. doi:10.1016/S1369-8478(00)00010-3
   Google Scholar
• Recarte, M. A., & Nunes, L. M. (1998). Effects of distance and speed on time to arrival estimation in automobile: Two classes of time? In A. G. Gale, I. D. Brown, C. M. Haslegrave, & S. P. Taylor (Eds.), Vision in vehicles (Vol. 6, pp. 63–71). Amsterdam: North-Holland, Elsevier.
   Google Scholar
• Regan, D., & Gray, R. (2000). Visually guided collision avoidance and collision achievement. Trends in Cognitive Sciences, 4, 99–107. doi:10.1016/S1364-6613(99)01442-4
   PubMed Web of Science ®Google Scholar
• Regan, D., & Gray, R. (2001). Hitting what one wants to hit and missing what one wants to miss. Vision Research, 41, 3321–3329. doi:10.1016/S0042-6989(01)00068-2
   PubMed Web of Science ®Google Scholar
• Rock, I. (1984). Perception. New York, NY: Scientific American Library.
   Google Scholar
• Rosey, F., Auberlet, J. M., Moisan, O., & Dupré, G. (2009). Impact of narrower lane width: Comparison between fixed-base simulator and real data. Transportation Research Record: Journal of the Transportation Research Board, 2138, 112–119. doi:10.3141/2138-15
   Web of Science ®Google Scholar
• Rothengatter, T. (1988). Risk and the absence of pleasure: A motivational approach to modelling road user behaviour. Ergonomics, 31, 599–607. doi:10.1080/00140138808966702
   Web of Science ®Google Scholar
• Rushton, S. K., Harris, J. M., Lloyd, M., & Wann, J. P. (1998). Guidance of locomotion on foot uses perceived target location rather than optic flow. Current Biology, 8, 1191–1194. doi:10.1016/S0960-9822(07)00492-7
   PubMed Web of Science ®Google Scholar
• Saad, F. (1996). Driver strategies in car-following situations. In A. G. Gale, I. D. Brown, C. M. Haslegrave, & S. P. Taylor (Eds.), Vision in vehicles (Vol. 5, pp. 61–70). Amsterdam: North-Holland, Elsevier.
   Google Scholar
• Salmon, P. M., Lenne, M. G., Walker, G. H., Stanton, N. A., & Filtness, A. (2014). Exploring schema-driven differences in situation awareness between road users: An on-road study of driver, cyclist and motorcyclist situation awareness. Ergonomics, 57, 191–209. doi:10.1080/00140139.2013.867077
   PubMed Web of Science ®Google Scholar
• Salmon, P. M., Stanton, N. A., & Young, K. L. (2012). Situation awareness on the road: Review, theoretical and methodological issues, and future directions. Theoretical Issues in Ergonomics Science, 13, 472–492. doi:10.1080/1463922X.2010.539289
   Google Scholar
• Sayer, J., Mefford, M. L., & Huang, R. (2003). The effects of lead-vehicle size on driver following behavior: Is ignorance truly bliss? Proceedings of the 2nd International driving symposium on human factors in driver assessment, training and vehicle design (pp. 221–225). Iowa City, IA: Public Policy Center, University of Iowa. Retrieved from http://drivingassessment.uiowa.edu/DA2003/pdf/52_Sayerformat.pdf
   Google Scholar
• Schiff, W., & Arnone, W. (1995). Perceiving and driving: Where parallel roads meet? In P. E. Hancock, J. M. Flash, J. E. Caird, & K. J. Vicente (Eds.), Local applications of the ecological approach to human–machine systems (Vol. 2, pp. 1–35). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
   Google Scholar
• Stanton, N., Salmon, P. M., Walker, G. H., & Jenkins, D. P. (2009). Genotype and phenotype schema and their role in distributed situation awareness in collaborative systems. Theoretical Issues in Ergonomics Science, 10, 43–68. doi:10.1080/14639220802045199
   Google Scholar
• Steyvers, F. J. J. M., & De Waard, D. (2000). Road-edge delineation in rural areas: Effects on driving behaviour. Ergonomics, 43, 223–238. doi:10.1080/001401300184576
   PubMed Web of Science ®Google Scholar
• Summala, H. (1980). How does it change safety margins if overtaking is prohibited: A pilot study. Accident Analysis and Prevention, 12, 95–103. doi:10.1016/0001-4575(80)90047-0
   Web of Science ®Google Scholar
• Summala, H. (2007). Towards understanding motivational and emotional factors in driver behaviour: Comfort through satisficing. In P. C. Cacciabue (Ed.), Modelling driver behaviour in automotive environments (pp. 189–207). London: Springer.
   Google Scholar
• Tharanathan, A. (2012). An examination of overtaking judgments based on limitations in the human perceptual system: Implications for the design of driver-assistance systems. In J. H. L. Hansen, P. Boyraz, K. Takeda, & H. Abut (Eds.), Digital signal processing for in-vehicle systems and safety (pp. 239–252). New York, NY: Springer.
   Google Scholar
• Theeuwes, J., & Godthelp, H. (1995). Self-explaining roads. Safety Science, 19, 217–225. doi:10.1016/0925-7535(94)00022-U
   Web of Science ®Google Scholar
• Tresilian, J. R. (1991). Empirical and theoretical issues in the perception of time to contact. Journal of Experimental Psychology: Human Perception and Performance, 17, 865–876. Retrieved from http://dx.doi.org/10.1037/0096-1523.17.3.865
   PubMed Web of Science ®Google Scholar
• Tresilian, J. R. (1999). Visually timed action: Time-out for “tau”? Trends in Cognitive Sciences, 3, 301–310. doi:10.1016/S1364-6613(99)01352-2
   PubMed Web of Science ®Google Scholar
• Tsoi, K. K., Mulder, M., & Abbink, D. A. (2010, October). Balancing safety and support: Changing lanes with a haptic lane-keeping support system. 2010 IEEE international conference on systems man and cybernetics (SMC), pp. 1236–1243. doi:10.1109/ICSMC.2010.5642414
   Google Scholar
• van der Hulst, M., Meijman, T., & Rothengatter, T. (1999). Anticipation and the adaptive control of safety margins in driving. Ergonomics, 42, 336–345. doi:10.1080/001401399185694
   Web of Science ®Google Scholar
• van Driel, C. J. G., Davidse, R. J., & van Maarseveen, M. F. A. M. (2004). The effects of an edgeline on speed and lateral position: A meta-analysis. Accident Analysis and Prevention, 36, 671–682. doi:10.1016/S0001-4575(03)00090-3
   PubMed Web of Science ®Google Scholar
• van Elslande, P., & Faucher-Alberton, L. (1997). When expectancies become certainties: A potential adverse effect of experience. In T. Rothengatter & E. C. Vaya (Eds.), Traffic and transport psychology: Theory and application (pp. 147–159). Amsterdam: Pergamon.
   Google Scholar
• Walker, G. H., Stanton, N. A., & Chowdhury, I. (2013). Self-explaining roads and situation awareness. Safety Science, 56, 18–28. doi:10.1016/j.ssci.2012.06.018
   Web of Science ®Google Scholar
• Wann, J., & Land, M. (2000). Steering with or without the flow: Is the retrieval of heading necessary? Trends in Cognitive Sciences, 4, 319–324. doi:10.1016/S1364-6613(00)01513-8
   PubMed Web of Science ®Google Scholar
• Wann, J. P. (1996). Anticipating arrival: Is the tau margin a specious theory? Journal of Experimental Psychology: Human Perception and Performance, 22, 1031–1048. Retrieved from http://dx.doi.org/10.1037/0096-1523.22.4.1031
   PubMed Web of Science ®Google Scholar
• Weller, G., Schlag, B., Friedel, T., & Rammin, C. (2008). Behaviourally relevant road categorisation: A step towards self-explaining rural roads. Accident Analysis and Prevention, 40, 1581–1588. doi:10.1016/j.aap.2008.04.009
   PubMed Web of Science ®Google Scholar
• Wickens, C. D., Gordon, S. E., & Liu, Y. (1998). An introduction to human factors engineering. New York, NY: Logman.
   Google Scholar
• de Winter, J. C., & Dodou, D. (2011, October). Preparing drivers for dangerous situations: A critical reflection on continuous shared control. 2011 IEEE international conference on systems, man, and cybernetics (SMC), pp. 1050–1056. doi:10.1109/ICSMC.2011.6083813
   Google Scholar
• Wood, R. M., Harvey, M. A., Young, C. E., Beedie, A., & Wilson, T. (2000). Weighting to go with the flow? Current Biology, 10, R545–R546. doi:10.1016/S0960-9822(00)00606-0
   PubMed Web of Science ®Google Scholar
• Yagar, S., & van Aerde, M. (1983). Geometric and environmental effects on speeds of two-lane highways. Transportation Research Part A, 17, 315–325. doi:10.1016/0191-2607(83)90094-8
   Google Scholar
• Zhao, L., Ichise, R., Yoshikawa, T., Naito, T., Kakinami, T., & Sasaki, Y. (2015, June). Ontology-based decision making on uncontrolled intersections and narrow roads. 2015 IEEE intelligent vehicles symposium (IV), pp. 83–88. doi:10.1109/IVS.2015.7225667
   Google Scholar