Effects of real-time warning systems on driving under fog conditions using an empirically supported speed choice modeling framework

Transportation Research Part C: Emerging Technologies

Volumn 86, Issue , 2018, Pages 97-110

  Wu, Yina ^a   Abdel Aty, Mohamed ^a   Park, Juneyoung ^b   Selby, Ryan M ^a  

^a University of Central Florida   (United States)

^b Hanyang University   (South Korea)

Author keywords

Hurdle beta regression model; Random parameter; Real time fog warning system; Reduced visibility conditions; Speed adjustment

Indexed keywords

FOG; HIERARCHICAL SYSTEMS; RANDOM PROCESSES; REAL TIME SYSTEMS; REGRESSION ANALYSIS; SPEED; VISIBILITY;

CONDITION; HURDLE BETA REGRESSION MODEL; RANDOM PARAMETERS; REAL- TIME; REAL-TIME FOG WARNING SYSTEM; REDUCED VISIBILITY; REDUCED VISIBILITY CONDITION; REGRESSION MODELLING; SPEED ADJUSTMENT; VISIBILITY CONDITIONS;

RISK PERCEPTION;

EMPIRICAL ANALYSIS; FOG; REAL TIME; REGRESSION ANALYSIS; TRANSPORTATION PLANNING; TRANSPORTATION SYSTEM; TRAVEL BEHAVIOR; VISIBILITY; WARNING SYSTEM;

FLORIDA [UNITED STATES]; UNITED STATES;

EID: 85033581676     PISSN: 0968090X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trc.2017.10.025     Document Type: Article

References (52)

1. Abdel-Aty, M.A., Chen, C.L., Schott, J.R., An assessment of the effect of driver age on traffic accident involvement using log-linear models. Accid. Anal. Prev. 30:6 (1998), 851–861.
2. Abdel-Aty, M., Yan, X., Radwan, E., Wang, X., Using drivers' stop/go decisions in driving simulator to assess rear-end crash risk at signalized intersections. J. Transportation Saf. Security 1:2 (2009), 85–100.
3. Abdel-Aty, M.A., Oloufa, A., Hassan, H., Ahmed, M., Siddiqui, C., Ekram, A., Huang, H., 2010. Developing an early detection system for reduced visibility. University of Central Florida.
4. Ahmed, M.M., Abdel-Aty, M., Lee, J., Yu, R., Real-time assessment of fog-related crashes using airport weather data: A feasibility analysis. Accid. Anal. Prev. 72 (2014), 309–317.
5. Al-Ghamdi, A.S., Experimental evaluation of fog warning system. Accid. Anal. Prev. 39:6 (2007), 1065–1072.
6. Anastasopoulos, P.C., Mannering, F.L., An empirical assessment of fixed and random parameter logit models using crash-and non-crash-specific injury data. Accid. Anal. Prev. 43:3 (2011), 1140–1147.
7. Barua, S., EI-Basyouny, K., Islam, M.T., 2016. Multivariate random parameters collision count data models with spatial heterogeneity 9, pp. 1–15.
8. Borowsky, A., Oron-Gilad, T., Parmet, Y., Age and skill differences in classifying hazardous traffic scenes. Transportation Res. Part F: Traffic Psychol. Behav. 12:4 (2009), 277–287.
9. Borowsky, A., Shinar, D., Oron-Gilad, T., Age, skill, and hazard perception in driving. Accid. Anal. Prev. 42:4 (2010), 1240–1249.
10. Boucher, J.P., Santolino, M., Discrete distributions when modeling the disability severity score of motor victims. Accid. Anal. Prev. 42:6 (2010), 2041–2049.
11. Boyle, L.N., Mannering, F., Impact of traveler advisory systems on driving speed: Some new evidence. Transportation Res. Part C: Emerging Technol. 12:1 (2004), 57–72.
12. Brooks, J.O., Crisler, M.C., Klein, N., Goodenough, R., Beeco, R.W., Guirl, C., Tyler, P.J., Hilpert, A., Miller, Y., Grygier, J., Burroughs, B., Speed choice and driving performance in simulated foggy conditions. Accid. Anal. Prev. 43:3 (2011), 698–705.
13. Broughton, K.L., Switzer, F., Scott, D., Car following decisions under three visibility conditions and two speeds tested with a driving simulator. Accid. Anal. Prev. 39:1 (2007), 106–116.
14. Cai, Q., Lee, J., Eluru, N., Abdel-Aty, M., Macro-level pedestrian and bicycle crash analysis: incorporating spatial spillover effects in dual state count models. Accid. Anal. Prev. 93 (2016), 14–22.
15. Cai, Q., Abdel-Aty, M., Lee, J., Eluru, N., Comparative analysis of zonal systems for macro-level crash modeling. J. Saf. Res. 60 (2017), 157–166.
16. Geroliminis, N., Sun, J., Properties of a well-defined macroscopic fundamental diagram for urban traffic. Transportation Res. Part B: Methodol. 45:3 (2011), 605–617.
17. Hassan, H., Abdel-Aty, M.A., Analysis of drivers’ behavior under reduced visibility conditions using a structural equation modeling approach. Transportation Res. Part F: Traffic Psychol. Behav. 14:6 (2011), 614–625.
18. Hamdar, S., Qin, L., Talebpour, A., Weather and road geometry impact on longitudinal driving behavior: Exploratory analysis using an empirically supported acceleration modeling framework. Transportation Res. Part C: Emerging Technol. 67 (2016), 193–213.
19. Haque, M.M., Washington, S., The impact of mobile phone distraction on the braking o young drivers: a hazard-based duration model. Transportation Res. Part C: Emerging Technol. 50 (2015), 13–27.
20. Huang, H., Abdel-Aty, M., Darwiche, A., County-level crash risk analysis in Florida: Bayesian spatial modeling. Transportation Res. Rec.: J. Transportation Res. Board 2148 (2010), 27–37.
21. Kang, J., Ni, R., Andersen, G., Effects of reduced visibility from fog on car-following performance. Transportation Res. Rec.: J. Transportation Res. Board 2069 (2008), 9–15.
22. Lee, J., Abdel-Aty, M., Cai, Q., Intersection crash prediction modeling with macro-level data from various geographic units. Accid. Anal. Prev. 102 (2017), 213–226.
23. Li, X., Yan, X., Wong, S.C., Effects of fog, dirver experience and gender on driving behavior on s-curved road segments. Accid. Anal. Prev. 77 (2015), 91–104.
24. Ma, L., Yan, X., Examining the nonparametric effect of driver's age in rear-end accidents through an additive logistic regression model. Accid. Anal. Prev. 67 (2014), 129–136.
25. Ma, L., Yan, X., Modeling traffic crash rates of road segments through a lognormal hurdle framework with flexible scale parameter. J. Adv. Transportation 49 (2015), 928–940.
26. Ma, L., Yan, X., Wei, C., Wang, J., Modeling the equivalent property damage only crash rate for road segments using the hurdle regression framework. Anal. Methods Accident Res. 11 (2016), 48–61.
27. MacCarley, C.A., Ackles, C., Watts, T., 2006. A study of the response of highway traffic to dynamic fog warning and speed advisory messages, 06–3086. In: Transportation Research Board Annual Meeting.
28. Maneering, F., Shankar, V., Bhat, C., Unobserved heterogeneity and the statistical analysis of highway accident data. Anal. Methods Accident Res. 11 (2016), 1–16.
29. Meaney, C., Moineddin, R., A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design. BMC Med. Res. Methodol., 14(1), 2014, 14.
30. Moeller, M.M., 2013. Methods for analyzing proportions. The University of Texas at Austin. Master's Thesis.
31. Moore, R.l., Cooper, L., 1972. Fog and road traffic. Transport and Road Research Laboratory. TRRL Report LR 446, TRRI., Crowthorne.
32. Mueller, A.S., Trick, L.M., Driving in fog: The effects of driving experience and visibility on speed compensation and hazard avoidance. Accid. Anal. Prev. 48 (2012), 472–479.
33. Mullahy, J., Specification and testing of some modified count data models. J. Econometrics 33:3 (1986), 341–365.
34. Ni, R., Kang, J.J., Andersen, G.J., Age-related declines in car following performance under simulated fog conditions. Accid. Anal. Prev. 42:3 (2010), 818–826.
35. Ospina, R., Ferrari, S.L., A general class of zero-or-one inflated beta regression models. Comput. Stat. Data Anal. 56:6 (2012), 1609–1623.
36. Shi, Q., Abdel-Aty, M., Big data applications in real-time traffic operation and safety monitoring and improvement on urban expressways. Transportation Res. Part C: Emerging Technol. 58 (2015), 380–394.
37. Stamatiadis, N., Deacon, J.A., Quasi-induced exposure: methodology and insight. Accid. Anal. Prev. 29:1 (1997), 37–52.
38. Sumner, R., Baguley, C., Burton, J., 1977. Driving in fog on the m4.
39. Trick, L.M., Lochner, M., Toxopeus, R., Wilson, D., 2009. Manipulating drive characteristics to study the effects of mental load on older and younger drivers. In: Proceedings of the Fifth International Driving Symposium on Human Factors in Driving Assessment, Training, and Vehicle Design, Big Sky, MT.
40. Wu, C.J., Hamada, M.S., 2011. Experiments: Planning, Analysis, and Optimization, vol. 552. John Wiley & Sons.
41. Wu, Y., Abdel-Aty, M., Cai, Q., Lee, J., Park, J., 2017. Rear-end collision risk algorithm under fog conditions based on kinematics analysis. In: Compendium of papers CD-ROM, Transportation Research Board 96th Annual Meeting, Washington, D.C., 2017.
42. Wu, Y., Abdel-Aty, M., Lee, J., Crash risk analysis during fog conditions using real-time traffic data. Accid. Anal. Prev., 2017 In press.
43. Wu, Y., Abdel-Aty, M., Ding, Y., Jia, B., Shi, Q., Yan, X., Comparison of proposed countermeasures for dilemma zone at signalized intersections based on cellular automata simulations. Accid. Anal. Prev., 2017 In press.
44. Van Der Hulst, M., Rothengatter, T., Meijman, T., Strategic adaptations to lack of preview in driving. Transportation Res. Part F: Traffic Psychol. Behav. 1:1 (1998), 59–75.
45. Washington, S.P., Congdon, P., Karlaftis, M.G., Maneering, G., 2005. Bayesian multinomial logit models: exploratory assessment of transportation applications. In: Proceedings of the 84th Transportation Research Board Annual Meeting, Washington, DC.
46. Williams, B., Gibbons, R., Medina, A., Connell, C., 2015. Visibility of a color variable message sign in the fog. In: Transportation Research Board 94th Annual Meeting (No. 15–1840).
47. Xu, P., Huang, H., Dong, N., Wong, S.C., Revisiting crash spatial heterogeneity: a Bayesian spatially varying coefficients approach. Accid. Anal. Prev. 98 (2017), 330–337.
48. Yan, X., Radwan, E., Abdel-Aty, M., Characteristics of rear-end accidents at signalized intersections using multiple logistic regression model. Accid. Anal. Prev. 37:6 (2005), 983–995.
49. Yan, X., Abdel-Aty, M., Radwan, E., Wang, X., Chilakapati, P., Validating a driving simulator using surrogate safety measures. Accid. Anal. Prev. 40:1 (2008), 274–288.
50. Yan, X., Li, X., Liu, Y., Zhao, J., Effects of foggy conditions on drivers’ speed control behaviors at different risk levels. Saf. Sci. 68 (2014), 275–287.
51. Zeng, Q., Wen, H., Huang, H., Abdel-Aty, M., A Bayesian spatial random parameter Tobit model for analyzing crash rates on roadway segments. Accid. Anal. Prev. 100 (2017), 37–43.
52. Zhang, Y., Yan, X., Yang, Z., Discrimination of effects between directional and nondirectional information of auditory warning on driving behavior. Discrete Dyn. Nat. Soc., 2015, 1–7.