OPEN ACCESS
Collisions between vehicles leaving the road and unforgiving roadside objects such as trees, poles, road signs, etc. constitute a major road safety issue. On the Austrian road network, approximately 7.500 injury crashes occur every year due to run-off-road (ROR) manoeuvres (i.e. 20% of all injury crashes on public roads), contributing 35% to fatalities and 25% to serious injuries. Vehicle restraint systems (VRS) such as guardrails, concrete barriers, terminals or crash attenuators play a decisive role in mitigating the consequences of ROR crashes. Unfortunately, most national road administrations (NRA) do not have a centralized data management, while geo-referenced information on VRS and their safety-related attributes are also not available as digitized data. Researchers from the AIT have developed a novel approach to investigate, classify and evaluate VRS by means of image data processing, towards providing a comprehensive VRS inventory. The information obtained can be used for benefit-cost-analyses, road safety inspections and the evaluation of the effectiveness of different vehicle restraint systems.
Asset management, database, decision tree, geographical information system, inventory control, run-off-road crashes, traffic safety, vehicle restraint system.
[1] Thomson, R., Fagerlind, H., Martinez, A.V., Amengual, A., Naing, C.L., Lanner, G., Dupre, G., Bisson, O., Garcia, J., Lopez, F., Hallemann, B., Wink, W., Hoschopf, H., Valtonen, J., Gosse, U., Kelkka, M., Ridder, S.d., Hill, J., & Van der Horst, R., RISER –Roadside Infrastructure for Safer European Roads, Deliverable D06 – European Best Practice for Roadside Design: Guidelines for Roadside Infrastructure on New and Existing Roads, 2006.
[2] Tomasch, E., Sinz, W., Hoschopf, H., Gobald, M., Steffan, H., Nadler, B., Nadler, F., Strnad, B. & Schneider, F., Required length of guardrails before hazards. In Accident Analysis and Prevention, 43(6), pp. 2112–2120, 2011. https://doi.org/10.1016/j.aap.2011.05.034
[3] Stefan, C., Stütz, R., Tomasch, E., Luttenberger, P. & Klein, C., A risk-based methodology to assess run-off-road crashes on Austrian motorways – the RISKANT project. In International Journal of Safety and Security Engineering, 6(2), pp. 351–361, 2016.https://doi.org/10.2495/safe-v6-n2-351-361
[4] ASFINAG Service GmbH, Road Safety Programme 2020, Download-Link:https://www.asfinag.at/media/2970/asfinag_vsb2020_english_einseiter_web_100526.pdf,
(accessed 16 May 2019).
[5] OECD/International Transport Forum (ITF), Towards Zero – Ambitious Road Safety Targets and the Safe System Approach, Publisher: Joint Transport Research Centre, Download: https://www.itf-oecd.org/sites/default/files/docs/08towardszeroe.pdf, 2008 (accessed 03 May 2019).
[6] EN 1317-2, Road Restraint Systems – Part 2: Performance Classes, Impact Test Acceptance Criteria and Test Methods for Safety Barriers Including Vehicle Parapets, 2011.
[7] Austrian Standards Institute, Passive Safety of Support Structures for Road Equipment –Requirements and Test Methods, EN 12767, 2011.
[8] American Association of State Highway and Transport Officials (AASHTO), Manual for Assessing Safety Hardware, 2009.
[9] Conference of European Directors of Roads (CEDR), CEDR Transnational road research programme, call 2019 (safety: use of vehicle restraint systems), SAVeRS –Defining the Different Parameters Which Can Influence the Need and Selection of VRS,Deliverable D1.1, https://www.cedr.eu/strategic-plan-tasks/research/cedr-call-2012/call-2012-safety/savers-project-results/, September 2014 (accessed 22 May 2019).
[10] Conference of European Directors of Roads (CEDR), Forgiving Roadside Design Guide, November 2012. Download-Link:https://www.cedr.eu/download/Publications/2013/T10_Forgiving_roadsides.pdf
[11] Austrian Research Association for Roads, Railways and Transport (FSV), RVS 05.02.31– Vehicle Restraint Systems, Requirements and Installation, October 2011.
[12] Conference of European Directors of Roads (CEDR), CEDR Transnational Road Research Programme, Call 2019 (Safety: Use of Vehicle Restraint Systems), SAVeRS –Guideline for the Selection of the Most Appropriate Roadside Vehicle Restraint System, Deliverable D3. 1 July 2015.
[13] Cho, J. & Humenberger, M., Fast patchmatch stereo matching using cross-scale cost fusion for automotive applications. IEEE Intelligent Vehicles Symposium, IV 2015, Seoul, South Korea, IEEE, pp. 802–807, 2015.
[14] Zinner, C. & Humenberger, M., Distributed real-time stereo matching on smart cameras,Fourth ACM/IEEE International Conference on Distributed Smart Cameras, Atlanta, GA, USA - August 31–September 4, 2010, ACM, pp. 182–189, 2010.
[15] Fang, L., Yang, B., Chen, C. & Fu, H., Extraction 3d road boundaries from mobile laser scanning point clouds, 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, ICSDM, pp. 162–165, 2015.
[16] Golovinskiy, A., Kim, V.G. & Funkhouser, T.A., Shape-Based recognition of 3d point clouds in urban environments, IEEE 12th International Conference on Computer Vision, pp. 2154–2161, 2009.
[17] Golparvar-Fard, M., Balali V. & de la Garza J.M., Segmentation and recognition of highway assets using image-based 3d point clouds and semantic texton forests. Journal of Computing in Civil Engineering, 29(1), p. 04014023, 2012. https://doi.org/10.1061/(asce)cp.1943-5487.0000283
[18] Shotton, J., Johnson, M. & Cipolla, R., Semantic texton forests for image categorization and segmentation. IEEE Conference on Computer Vision and Pattern Recognition,pp. 1–8, 2008. https://doi.org/10.1109/cvpr.2008.4587503
[19] Verma, B., Zhang, L. & Stockwell, D.R.B., Roadside Video Data Analysis: Deep Learning- Deep Learning, Springer, p. 711, 2017.
[20] Neuhold, G., Ollmann, T., Bulò, S.R. & Kontschieder, P., The mapillary vistas dataset for semantic understanding of street scenes. IEEE International Conference on Computer Vision, ICCV, pp. 5000–5009, 2017.
[21] Ordóñez, C., Cabo, C. & Sanz-Ablanedo, E., Automatic detection and classification of pole-like objects for urban cartography using mobile laser scanning data. Sensors,17(7), p. 1465, 2017. https://doi.org/10.3390/s17071465