Evaluating the Effect of Stop Line Visibility on Driver Compliance at Urban Intersections in Jakarta
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Rian Hendris Saputra*
Sutanto Soehodho
Martha Leni Siregar
Urban intersections are critical nodes in city traffic systems, where road marking clarity is vital in guiding driver behavior and reducing violations. In rapidly growing cities such as Jakarta, the degradation of road markings, particularly stop line markings, poses a significant challenge to traffic safety and compliance. This study examines the influence of stop line marking clarity on road user compliance at urban intersections in Jakarta. The research applies a mixed-method approach that integrates field observation, speed profile analysis, Difference-in-Differences (DiD), and multiple linear regression to provide a comprehensive understanding of driver behavior. Two intersections representing different marking conditions, namely clear and faded markings, were selected as study locations. The DiD analysis shows a clear difference in violation behavior, where the intersection with clear markings has a violation rate of 22.0%, while the intersection with faded markings reaches 37.7%, resulting in a difference of 15.6%. The speed profile analysis indicates that vehicles at the intersection with faded markings maintain higher speeds at all observed distances. The largest difference occurs at 20 meters, with a speed gap of 4.74 km/h. This finding suggests that faded markings lead to delayed deceleration, while clear markings encourage earlier and more gradual speed reduction. The multiple linear regression proved that perceived marking clarity has a significant effect on violation behavior with a coefficient of 0.112 and a significance value of 0.029. The model explains 50.4% of the variation in violation behavior. Among the variables, ETLE awareness shows the strongest influence, followed by improved marking perception.
Alimo, P. K., Ma, W., & Wang, L. (2021). A Safety Audit of Seven Signalized Intersections in Ghana Based on Crash Data, Video Observations, and Surveys. 2021 6th International Conference on Transportation Information and Safety (ICTIS), 86–98. https://doi.org/10.1109/ICTIS54573.2021.9798605
Anggia, M. F., Hakim, A., Mardiyono, M., & Solimun, S. (2022). Compliance and Awareness as Mediation Variables on the Influence of Utility and Trust of Electronic Traffic Law Enforcement on the Traffic Habit. WSEAS Transactions on Business and Economics, 19, 421–431. https://doi.org/10.37394/23207.2022.19.38
Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton University Press.
Asmara, T., & Arimuladi, S. U. (2024). Harmonising Justice and Efficiency: Crafting the Future of Electronic Traffic Law Enforcement Systems. Revista Juridica, 2(78), 282–302. https://doi.org/10.26668/revistajur.2316-753X.v2i78.6647
Bosurgi, G., Marra, S., Pellegrino, O., Sollazzo, G., & Villari, M. (2022). Effects of Road Marking Visibility on Vehicles Driving Along Curves: A Preliminary Study in a Simulated Environment. Transportation Research Record, 2676(12), 691–702. https://doi.org/10.1177/03611981221097095
Callaway, B., & Sant’Anna, P. H. C. (2021). Difference-in-Differences with multiple time periods. Journal of Econometrics, 225(2), 200–230. https://doi.org/10.1016/j.jeconom.2020.12.001
Connor, L., Dean, J., McNett, M., Tydings, D. M., Shrout, A., Gorsuch, P. F., Hole, A., Moore, L., Brown, R., Melnyk, B. M., & Gallagher‐Ford, L. (2023). Evidence‐based practice improves patient outcomes and healthcare system return on investment: Findings from a scoping review. Worldviews on Evidence-Based Nursing, 20(1), 6–15. https://doi.org/10.1111/wvn.12621
de Chaisemartin, C., & D’Haultfœuille, X. (2020). Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects. American Economic Review, 110(9), 2964–2996. https://doi.org/10.1257/aer.20181169
Goodman-Bacon, A. (2021). Difference-in-differences with variation in treatment timing. Journal of Econometrics, 225(2), 254–277. https://doi.org/10.1016/j.jeconom.2021.03.014
Hussain, Q., Alhajyaseen, W. K. M., Brijs, K., Pirdavani, A., & Brijs, T. (2020). Innovative countermeasures for red light running prevention at signalized intersections: A driving simulator study. Accident Analysis and Prevention, 134. https://doi.org/10.1016/j.aap.2019.105349
Kučina, I., Kosovec, B., Jezidžić, F., Ferko, M., & Babić, D. (2025). The Influence of Road Marking Visibility on Lateral Vehicle Position and Driving Speed. Acta Polytechnica CTU Proceedings, 52, 69–76. https://doi.org/10.14311/APP.2025.52.0069
Layegh, M., Foomani, M. G., & Alecsandru, C. (2025). Enhancing Safety Measures at Stop-Controlled Intersections: A Study on LED Backlit Signs and Drivers’ Behavior in Montréal, Québec. Urban Science, 9(9), e375. https://doi.org/10.3390/urbansci9090375
Mukherjee, D., Kumar, A., & Dewangan, R. K. (2025). Factors influencing red-light violations behavior by vulnerable road users: A case study from an Indian mid-sized city. Advances in Transportation Studies, 66, 177–194. https://doi.org/10.53136/979122181935912
Mukherjee, D., & Mitra, S. (2020). A comprehensive study on factors influencing pedestrian signal violation behaviour: Experience from Kolkata City, India. Safety Science, 124. https://doi.org/10.1016/j.ssci.2020.104610
Patel, D., Hosseini, P., & Jalayer, M. (2023). A framework for proactive safety evaluation of intersection using surrogate safety measures and non-compliance behavior. Accident Analysis & Prevention, 192, 107264. https://doi.org/10.1016/j.aap.2023.107264
Shepelev, V., Almetova, Z., & Geraskina, O. (2018). Methodology for justification of the place for applying a stop-line to secure safety of completion of travel through a signalled intersection. Transportation Research Procedia, 36, 712–717. https://doi.org/10.1016/j.trpro.2018.12.101
