Sight distances at unsignalized intersections: a comparison of guidelines and requirements for human drivers and autonomous vehicles

Zsofia Magyari; Csaba Koren; Mariusz Kieć; Attila Borsos

doi:10.5604/01.3001.0014.9553

Authors

Zsofia Magyari Department of Transport Infrastructure and Water Resources Engineering, University of Gyor, Gyor Author https://orcid.org/0000-0002-1975-035X
Csaba Koren Department of Transport Infrastructure and Water Resources Engineering, University of Gyor, Gyor Author https://orcid.org/0000-0002-1034-0557
Mariusz Kieć Department of Roads, Railways and Traffic Engineering, Cracow University of Technology, Cracow Author https://orcid.org/0000-0001-9193-7269
Attila Borsos Department of Transport Infrastructure and Water Resources Engineering, University of Gyor, Gyor Author https://orcid.org/0000-0003-4029-0818

DOI:

https://doi.org/10.5604/01.3001.0014.9553

Keywords:

intersection, sight distance, autonomous vehicle, speed, gap acceptance

Abstract

Many traffic accidents are caused by unforeseen and unexpected events in a site that was hidden from the driver's eyes. Road design parameters determining required visibility are based on relationships formulated decades ago. It is worth reviewing them from time to time in the light of technological developments. In this paper, sight distances for stopping and crossing situations are studied in relation to the assumed visual abilities of autonomous vehicles. Current sight distance requirements at unsignalized intersections are based among others on speeds on the major road and on accepted gaps by human drivers entering or crossing from the minor road. Since these requirements vary from country to country, regulations and sight terms of a few selected countries are compared in this study. From the comparison it is remarkable that although the two concepts, i.e. gap acceptance on the minor road and stopping on the major road have different back-grounds, but their outcome in terms of required sight distances are similar. Both distances are depending on speed on the major road: gap sight distances show a linear, while stopping sight distances a parabolic function. In general, European SSD values are quite similar to each other. However, the US and Australian guidelines based on gap acceptance criteria recommend higher sight distances. Human capabilities and limitations are considered in sight field requirements. Autonomous vehicles survey their environment with sensors which are different from the human vision in terms of identifying objects, estimating distances or speeds of other vehicles. This paper compares current sight field requirements based on conventional vehicles and those required for autonomous vehicles. Visibility requirements were defined by three vision indicators: distance, angle of view and resolution abilities of autonomous cars and human drivers. These indicators were calculated separately for autonomous vehicles and human drivers for various speeds on the main road and for intersections with 90° and 60° angles. It was shown that the required sight distances are 10 to 40 meters shorter for autonomous vehicles than for conventional ones.

References

AASHTO, 2018. A Policy on Geometric De-sign of Highways and Streets (The Green Book). American Association of State Highway and Transportation Officials.

AUSTROADS, 2017. Guide to Road Design Part 4A: Unsignalised and Signalised Intersections.

BASSAN, S., 2018. Empirical modeling of the relationship between decision sight distance and stopping sight distance based on AASHTO. Archives of Transport, 48(4), 7-25. DOI: 10.5604/01.3001.0012.8362.

BHAGAVATHULA, R., et al., 2019. Effect of Intersection Lighting Design on Drivers’ Perceived Visibility and Glare. Transportation Research Record Journal of the Transportation Research Board Volume: 2673(2), 799-810. DOI: 10.1177/0361198119827928.

BRILON, W., TROUTBECK, R., TRACZ, M., 1997. Review of International Practices Used to Evaluate Un-signalized Intersections. Transportation Research Circular 468. Transportation Research Board.

BRYCHT, N., 2020. Analysis of road safety in the context of horizontal visibility within intersections – field studies. QPI 2020, 2(1), 150-157. DOI: 10.2478/czoto-2020-0018.

CAMERON, O., 2017. An Introduction to LIDAR: The Key Self-Driving Car Sensor. Online: https://news.voyage.auto/an-introduction-to-lidar-the-key-self-driving-car-sensor-a7e405590cff.

DIXIT V.V., CHAND S., NAIR D.J., 2016. Autonomous Vehicles: Disengagements, Accidents and Reaction Times. PLoS ONE, 11(12), e0168054. DOI: 10.1371/journal.pone.0168054.

DUDA, K., SIERPIŃSKI, G., 2019. Traffic organisation problems at non-signalised intersections – case studies of visibility distance and ‘give way’ and ‘stop’ road signs. Scientific Journal of Silesian University of Technology. Series Transport, 102, 41-52. DOI: 10.20858/sjsutst.2019.102.3.

EISENKOPF, A., et al., 2017. Automatisiertes Fahren im Straßenverkeh.r Herausforderungen für die zukünftige Verkehrspolitik Wissenschaftlicher Beirat beim Bundesminister für Verkehr und digitale Infrastruktur. Gutachten Des Wissenschaftlichen Beirats Beim Bundesminister Für Verkehr Und Digitale Infrastruktur, Berlin.

FARAH, H., ERKENS, S., ALKIM, T., VAN AREM, B., 2018. Infrastructure for Automated and Connected Driving: State of the Art and Future Research Directions. In: G. Meyer and S. Beiker (eds.), Road Vehicle Automation 4, Lecture Notes in Mobility. © Springer International Publishing AG. DOI: 10.1007/978-3-319-60934-8_16.

HRS, 2004. Design of at-grade intersections e-UT 03.03.21. Hungarian Road Society. Budapest, 37.

GONZÁLEZ-GÓMEZ, K., CASTRO, M., 2019. Evaluating Pedestrians’ Safety on Urban Intersections: A Visibility Analysis. Sustainability, 11, 6630. DOI: 10.3390/su11236630.

GUZEK, M., LOZIA, Z., ZDANOWICZ, P., JURECKI, R.S., STANCZYK, T.L., PIENIAZEK, W., 2012. Assessment of driver's reaction times in diverisified research environments. Archives of Transport, 24(2), 149-164. DOI: 10.2478/v10174-012-0010-8.

FAMBRO, D.B., FITZPATRICK, K., KOPPA, R., 1997. Determination of stopping sight distance. NCHRP Report 400. Transportation Research Board, Washington, DC.

FGSV, 2012. Richtlinien für die Anlage von Landstraßen RAL, (Guidelines for the Design of Highways). Forschungsgesellschaft für Straßen und Verkehrswesen, Köln, 136.

HARWOOD, D.W., FANBRO, D.B., FISHBURN, B., JOUBERT, H., LAMM, R., PSARIANOS, B., 1998. International sight distance design practices. Transportation Research Circular, 32, 1-23.

HESSAI, 2019. Pandar64 Mechanical LiDAR. Online: http://www.hesaitech.com/en/autonomous_driving.html?param=64.

HIGHWAYS ENGLAND, 2020/1. Road Lay-out Design. CD 109. Highway link design (formerly TD 9/93, TD 70/08). Revision 1. March 2020.

HIGHWAYS ENGLAND, 2020/2. CD 116 Geometric design of roundabouts Revision 2. April 2020.

HIGHWAYS ENGLAND, 2020/3. CD 123. Geometric design of at-grade priority and signal-controlled junctions. Revision 1. Jan 2020.

JUNG, J., OLSEN, M.J., HURWITZ, D.S., KASHANI, A.G., BUKER, K., 2018. 3D virtual intersection sight distance analysis using lidar data. Transportation Research Part C: Emerging Technologies, 86, 563-579. DOI: 10.1016/j.trc.2017.12.004.

LU, Q., TETTAMANTI, T., HÖRCHER, D., VARGA, I., 2019. The impact of autonomous vehicles on urban traffic network capacity: an experimental analysis by microscopic traffic simulation. Transportation Letters, 12(8), 540-549. DOI: 10.1080/19427867.2019.1662561.

LYTRIVIS, PAPANIKOLAOUA, E., AMDITISA, A., DIRNWÖBERB, M., FROETSCHERB, A., PROTZMANNC, R., ROMD, W., KERSCHBAUMER. A., 2018. Advances in Road Infrastructure, both Physical and Digital, for Mixed Vehicle Traffic Flows. In: Proceedings of 7th Transport Research Arena TRA 2018, Vienna, Austria.

NARKSRI, P., TAKEUCHI, E., NINOMIYA, Y., TAKEDA, K., 2021. Deadlock-Free Planner for Occluded Intersections Using Estimated Visibility of Hidden Vehicles. Electronics, 10, 411. https://doi.org/10.3390/ electron-ics10040411.

NEMCHINOV, D., MARTIYAHINBA, D., MIKHAILOV, A., KOSTSOV, A., NEMCHINOVB, M., 2020. Research of accepted head-ways and visibility conditions on intersections. Transportation Research Procedia, 45, 13–20. DOI: 10.1016/j.trpro.2020.02.057.

NOMURA, T., HIROTA, M., SATO, J., 2021. Evaluation of the Driver Visibility Affecting the Occurrence of Crossing Accidents. International Journal of Intelligent Transportation Systems Research DOI: 10.1007/s13177-020-00249-8.

NZTA, 2012. Traffic control devices manual. Part 9. Level crossings. Second edition, 1(2), 84. New Zealand Transport Agency.

SALWAN, A., M. EASA, S.M., RAJU, N., ARKATKAR, S., 2021. Intersection Sight Distance Characteristics of Turbo Roundabouts. Designs 5, 16. DOI: 10.3390/designs5010016.

SCHERMERS, G., BROEREN, P.T.W., 2015. Representative parameter values study. Deliverable D6.1. CEDR European Sight distances in perspective (EUSight). Amersfoort, Netherlands.

SCHOETTLE, B., 2017. Sensor fusion: A comparison of sensing capabilities of human drivers and highly automated vehicles. Ann Arbor: University of Michigan.

STRAUSS, M., CARNAHAN, J., 2009. Distance Estimation Error in a Roadway Setting. Police Journal, 8(3), 247-264. DOI: 10.1350/pojo.2009.82.3.458.

THAKUR, S., SUBHADIT, B., 2019. Assessment of pedestrian-vehicle interaction on urban roads: a critical review. Archives of Transport, 51(3), 49-63. DOI: https://doi.org/10.5604/01.3001.0013.6162.

WANG, P., SONG, G., LIANG, L., SHUO, C., HAILAN, Z., 2020. Research on driving behavior decision making system of autonomous driving vehicle based on benefit evaluation model. Archives of Transport, 53(1), 21-36. DOI: 10.5604/01.3001.0014.1740.

WEBER, R., PETEGEM, J.H., VAN SCHERMERS, G., HOGEMA, J., STUIVER, A., BROEREN, P., STERLING, T., RUIJS, P., 2016. Final report. Deliverable D8.1. CEDR European Sight distances in perspective (EU-Sight), Amersfoort, Netherlands.