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ScienceDirect Transportation Research Procedia 20 (2017) 171 – 179

12th International Conference "Organization and Traffic Safety Management in large cities", SPbOTSIC-2016, 28-30 September 2016, St. Petersburg, Russia

Using 3D-modeling Technologies to Increase Road Safety Michael Eliseev a, Tatyana Tomchinskaya b, Alexandr Lipenkov c*, Alexandr Blinov d Nizhny Novgorod State Technical University n.a. R.E. Alekseev 24, Minina Str., Nizhny Novgorod, Nizhny Novgorod region, 603950, Russia

Abstract This article is dedicated to a technique of 3D modeling traffic network sections and gives an overview of the range of applications of such models to increase road safety. High accuracy models described herein are a detail reproduction of road traffic situations, including road infrastructure elements, surrounding buildings, vegetation and traffic participants. Autodesk software line is used as modeling tools: Maya, AutoCAD Civil 3D, Civil View for 3ds Max Design, InfraWorks 360, Bridge Design for InfraWorks, AutoCAD Map3D. Created models are integrated into the unified system which is intended to increase road safety and called the "Interactive Accident Risk Map" by its creators. This is a software system which solves the problems of collecting and analyzing information on road traffic accidents and feedback from traffic participants. © by Elsevier B.V. This is an open access article under the CC BY-NC-ND license © 2017 2016Published The Authors. Published by Elsevier B.V. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of the 12th International Conference "Organization and Traffic Peer-review under responsibility of the organizing committee of the 12th International Conference “Organization and Traffic Safety Safety Management in large cities". Management in large cities” Keywords: Interactive map, 3D model, road safety, road traffic accident (RTA), GIS, virtual model.

1. Introduction The number of cars on Russian roads is still increasing. Over the last ten years, the number of registered motor vehicles in Russia has increased for more than 65%. At the same time, traffic interchanges are becoming more and more complicated but, in many cases, means of informing traffic participants of the road situation, safety conditions and traffic routes remain unchanged. This article suggests using 3D models as one of the important information distribution means. The article also gives an overview of the range of application of such models to increase road safety. High accuracy models described herein are a detail reproduction of road traffic situations, including road

* Corresponding author. Tel.: +0-000-000-0000 ; fax: +0-000-000-0000 . E-mail address: [email protected] a, [email protected] b, [email protected] c*, [email protected] d

2352-1465 © 2017 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of the 12th International Conference “Organization and Traffic Safety Management in large cities” doi:10.1016/j.trpro.2017.01.045

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Michael Eliseev et al. / Transportation Research Procedia 20 (2017) 171 – 179

infrastructure elements, surrounding buildings and facilities, vegetation and traffic participants. Created models are integrated into a unified system which is intended to increase road safety and which we call the "Interactive Accident Risk Map". This is a software system which solves the problems of collecting and analyzing information on road traffic accidents and feedback from traffic participants. The architecture of the software system is described in publication [Yeliseev et al. (2016)]. Similar systems are actively being developed in many countries, together with their theoretical basis. Publications on this subject are numerous and their full overview is not the objective of this publication. In our opinion, the most interesting publications are [DeLucia and Scopatz (2010)], Graettinger et al. (2005/2001), Harkey (1999), Khan et al. (2009), Miller (2000), Roche (2000)]. As a rule, the main function of such systems is to analyze accident risk and they do not support visualization capability. Moreover, the type of accident risk is ignored when visualizing traffic situations [Paz et al. (2015), Espie et al (2006)]. We suggest a system which has no this deficiency. 2. Road traffic accident 3D-modeling Let us briefly describe technologies used for modeling. When creating a virtual model, it is very important to have a possibility to transfer data between software environments; that is why, the main requirement to software products was their compatibility. In this respect, the Autodesk unified technological line has been chosen: Maya, AutoCAD Civil 3D, Civil View for 3ds Max Design, InfraWorks 360, Bridge Design for InfraWorks, AutoCAD Map3D. Modeling can be divided into several basic steps shown in Fig. 1.

Fig. 1. Basic steps to create informational and training video clips.

Step 1 includes preparing bitmap images which will be used to generate a terrain relief. The digital terrain and environment model shown in Fig. 2 has been created based on the map data available at earthexplorer.usgs.gov. A satellite image is used as a bitmap underlay. Roads, road markings, buildings and the bridge in the area of one of the city squares are created based on the satellite imagery.


Then, AutoCAD Civil 3D software designed for professional terrain and infrastructure modeling is used to detail and edit roads, crossings and traffic interchanges (Fig. 3).

Fig. 2. Automatically built 3D model of terrain relief and traffic situation.

Fig. 3. Creation of complicated traffic interchanges.

Step 3 is detalization in InfraWorks 360. Road markings are made; street railways, bridges etc. are added.

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On the next step, traffic stream is created in Civil View. Vehicles and pedestrians involved in the hazardous situation are animated in Maya (Fig. 4).

Fig. 4. Vehicle animation in Maya.

The following 3D model applications can be defined: 1. driving training; 2. reproduction of potential hazardous situations; 3. virtual passage of traffic infrastructure elements when the operating condition is modified; 4. identification of traffic infrastructure sections where driver’s blinding is possible; 5. high-accuracy description of vehicle movement on a road with complex terrain. Each application is described below in succession. As a rule, along with typical difficulties, such as movement start, maneuvering in a confined space etc., it is especially hard for beginning drivers to pass through the busiest and hazardous traffic infrastructure sections in the city when independent driving starts. Detailed analysis of such sections, demonstration of typical mistakes and correct behavior on the road will allow to avoid potentially hazardous situations and better prepare the student for driving in the city. Let us consider one example.


Several potentially hazardous situations may occur on the crossing of Gagarin Avenue and Beketov Street in the city of Nizhny Novgorod (Fig. 5).

Fig. 5. Traffic diagram on the Gagarin Avenue and Beketov Street crossing.

1. Passage of the crossing from Gagarin Avenue to Beketov Street (direction d2 in Fig. 5) when the green traffic light is already blinking. A collision with a vehicle in the far right or middle traffic lane is possible, providing that the view is limited by the vehicle in the far left lane. 2. Bus drivers often pass the crossing from Gagarin Avenue to Beketov Street (direction d2 in Fig. 5), violating the traffic rules. Turning is permitted from the two left lanes but, in case of traffic congestion, it is difficult for buses to move to the second lane, and bus drivers turn from the third left-hand lane. It is difficult for beginning drivers to maintain the trajectory on this crossing, especially when no markings are present. And when there is such an obstacle as a bus, a potentially hazardous situation occurs.

Fig. 6. Potentially hazardous situation when the vehicle is passing the crossing with the green traffic light blinking.

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Fig. 7. Potentially hazardous situation when the bus driver violates the traffic rules.

3. Passage of the crossing from Beketov Street to Gagarin Avenue (direction d6 in Fig. 5). When making a right turn according to the flashing green arrow, beginning drivers do not always understand that the drivers making the turn have the priority. As a result, a potentially hazardous situation may occur. Each situation described above has been modeled and, for each situation, a training video clip has been created. In this case, the advantages of model application are the following: x possibility to analyze some situations difficult for beginning drivers; x possibility to position the camera anywhere; x possibility to set various parameters of the environment: rain, snow, fog etc. Video clips can also be used when the operating conditions are modified. For example, a new pedestrian crossing signal has been installed on the pedestrian crossing on Komsomolskaya Square in Nizhny Novgorod. It would be useful for both drivers and pedestrians to see a video demonstrating accident which occur in this place, and, in our opinion, this would reduce the number of RTAs of respective types. Fig. 8 shows a fragment of how the model works (Fig. 8)

Fig. 8. Modification of traffic infrastructure: addition of pedestrian crossing signal.

Modeling can be used not only for informative purposes, but also to solve other tasks. For example, 3D models can be used to identify places of possible driver’s blinding in the city. The hazard of sun blinding effect is considered by Pegin, P.A., particularly in [Espie et al. (2006)] where occurrence of this effect is analyzed with account of geographical reference. AutoDesk Map 3D tools allow identifying road sections where blinding is possible. To do so,


it is necessary to make full-sized buildings by "pulling" them up on the vector city map and position a light source in points corresponding to different dates and times. This has been done for one district in Nizhny Novgorod (Fig. 9).

Fig. 9. 3D model of a district in Nizhny Novgorod created in the AutoDesk Map 3D software, video clip fragment demonstrating driver’s blinding.

The last modeling application considered is a high-accuracy description of vehicle movement on a road with complex terrain. Such models can be used to inform traffic participants, to conduct RTA expertise, to model accidents for the purpose of developing safe operating conditions. Creation of such models starts with detailed reproduction of the terrain relief. The figure below shows a fragment of model creation for Nizhny Novgorod: Oksky syezd (Fig. 10). Elevation difference on this road section is 95 meters.

Fig. 10. Reproduction of the terrain relief on Oksky syezd (Nizhny Novgorod).

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The created models are planned to be integrated into the Interactive Accident Risk Map system as follows: 1. hazardous places are displayed when the route is being built; 2. click on the pictograph results in displaying a video clip corresponding to the traffic infrastructure section (Fig. 11).

Fig. 11. Interactive Accident Risk Map site operation. Video clip display mode.

3. Conclusion This overview describes, in our opinion, the basic 3D modeling applications. For each application considered above, a model environment allowing reproduction of any number of traffic situations has been created. 3D modeling is one of the key technologies necessary for creation a unified system which would ensure road safety in a large city. References Alexander, P., Naveen, V., Romesh, K., Hanns de la Fuente-Mella and Luiza, M. (2015). Traffic and Driving Simulator Based on Architecture of Interactive Motion. The Scientific World Journal, 2015: 1–9. De Lucia, B. H. and Scopatz, R.A. (2010). E-Crash: The Model Electronic Crash Data Collection System. Washington: National Highway Traffic Safety Administration. Espie S., Gattuso D., Galante F. (2006). A Hybrid Traffic Model Coupling Macro and Behavioral Micro Simulation. Proceedings of the 85th Annual Meeting Transportation Research Board, USA, Washington. Graettinger, A., Lindly, J.K., and Mistry, G.J. (2005). Display and Analysis of Crash Data. University Transportation Center for Alabama, Tuscaloosa, AL. Graettinger, A.J., McFadden, J., and Rushing, T.W. (2001). Evaluation of Inexpensive Global Positioning System Units to Improve Crash Location Data. Transportation Research Record: Journal of the Transportation Research Board, (1746): 94–101. Harkey, D.L. (1999). Evaluation of Truck Crashes Using a GIS-Based Crash Referencing and Analysis System. Transportation Research Record: Journal of the Transportation Research Board, (1686): 13–21. Khan, G., Santiago-Chaparro, K.R., Qin, X., and Noyce, D.A. (2009). Application and Integration of Lattice Data Analysis, Network KFunctions, and Geographic Information System Software to Study Ice-Related Crashes. Transportation Research Record: Journal of the Transportation Research Board, (2136): 67–76. Miller, J.S. (2000). Geographical Information Systems Unique Analytic Capabilities for the Traffic Safety Community. Transportation Research Record: Journal of the Transportation Research Board, (1734): 21–28. Pegin, P.A., Lopashuk, V.V. (2008). Usage of GPS Survey Results for Taking the Sun Blinding Effect into Account in Highway Designing. Transport construction, (7): 23–24. Roche, J. (2000). Geographic Information Systems-Based Crash Data Analysis and the Benefits to Traffic Safety. MTC Transportation Scholars Conference, Ames, IA, pp. 110–122.

Michael Eliseev et al. / Transportation Research Procedia 20 (2017) 171 – 179 Yeliseev, M.E., Tomchinskaya, T.N., Repnikov, A.A., Blinov, A.S. (2016). Architecture and Standard External Event Reactions of the Interactive Accident Risk Map. Avtotrasnportnoye predpriyatiye, (2): 24–26.

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