Dynamic Vehicular Traffic Load: Definition and Quantification
Main Article Content
Keywords
vehicular traffic load quantification, cloud service, vehicular communication, vehicular traffic
Abstract
In this paper, we introduce a method that quantifies the amount of traffic over time by the help of a cloud calculation service and vehicular communication. Furthermore, the approach is applicable also in vehicular traffic simulations, which are widely used in research to demonstrate the effects of proposed solutions to traffic problems. As unused road segments strongly influence the overall traffic load (i.e. used vs full road capacity), we propose a methodology that dynamically calculates the load over time and considers whether specific parts of the road network are used. We introduce two possibilities to filter out distortion of the created statistics due to variation in usage over time. Our novel approach is both simple but widely configurable to fit individual needs. The approach is proven by simulations and application of the load calculation in combination with an intelligent route optimization approach by comparing the optimization gain with the calculated traffic load.
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References
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Blazek, T., Backfrieder, C., Mecklenbräuker, C. F., Ostermayer, G. (2017). Improving Communication Reliability in Intelligent Transport Systems through Cooperative Driving. Proceedings of the 10th IFIP Wireless and Mobile Networking Conference, 1-6, Valencia, Spain.
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Mandziuk, J., Swiechovski, M. (2016). Simulation-based approach to Vehicle Routing Problem with Traffic Jams. Proceedings of IEEE Symposium Series on Computational Intelligence, 1-8, Athens, Greece.
Nafi, N., Khan, R., Khan, J., Gregory M. (2014). A Predictive Road Traffic Management System based on Vehicular Ad-hoc Network. Proceedings of the International Telecommunication Networks and Applications Conference, 135-140, Melbourne, Australia.
Nebbou, T., Fouchal, H., Lehsaini, M. (2017). Metrics for Vehicle Density in Urban Environment. Proceedings of the 2017 IEEE Global Communications Conference, 1–6, Singapore.
Ni, D. (2015). Traffic Flow Theory: Characteristics, Experimental Methods, and Numerical Techniques. Butterworth-Heinemann.
Pan, J., Khan, M., Sandu Popa, I., Zeitouni, K., Borcea, C. (2012). Proactive Vehicle Re-routing Strategies for Congestion Avoidance. Proceedings of the 8th IEEE International Conference on Distributed Computing in Sensor Systems, 265–272, Hangzhou, China.
Stevanovic, A., Stevanovic, J., Zhang, K., Batterman, S. (2009). Optimizing Traffic Control to Reduce Fuel Consumption and Vehicular Emissions: Integrated Approach with VISSIM, CMEM, and VISGAOST. Transportation Research Record: Journal of the Transportation Research Board, 2128, 105–113.
Szeto, W. Y., Jiang, Y., Wang, D. Z. W., Sumalee, A. (2015). A Sustainable Road Network Design Problem with Land Use Transportation Interaction Over Time. Networks and Spatial Economics, 15(3), 791–822.
Treiber, M., Kesting, A. (2013). Traffic Flow Dynamics. Berlin, Heidelberg. Springer.
Zhang, B., Ma, M., Liu, C., Shu, Y. (2017). Delay Guaranteed MDP Scheduling Scheme for HCCA based on 802.11p Protocol in V2R Environments. International Journal of Communication Systems, 30(15), 1-12.
Zhou, X., Tanvir, S., Lei, H., Taylor, J., Liu, B., Rouphail, N. M., Frey, H. C. (2015). Integrating a Simplified Emission Estimation Model and Mesoscopic Dynamic Traffic Simulator to Efficiently Evaluate Emission Impacts of Traffic Management Strategies. Transportation Research Part D: Transport and Environment, 37, 123–136.
Abbas, T., Sjöberg, K., Karedal, J., Tufvesson, F. (2015). A Measurement Based Shadow Fading Model for Vehicle-to-Vehicle Network Simulations. International Journal of Antennas and Propagation, 2015, 1-12. DOI: 10.1155/2015/190607
An, X., Hou, Q., Li, N., Zhai, S. (2013). Assessment of Human Exposure Level to PM10 in China. Atmospheric Environment, 70, 376–386.
Athol, P. (1965). Interdependence of Certain Operational Characteristics within a Moving Traffic Stream. Highway Research Record, 72, 58–87.
Aw, A., Rascle, M. (2000). Resurrection of “Second Order” Models of Traffic Flow. SIAM Journal on Applied Mathematics, 60(3), 916–938.
Backfrieder, C., Ostermayer, G., Mecklenbräuker, C. F. (2014). TraffSim – A Traffic Simulator for Investigations of Congestion Minimization through Dynamic Vehicle Rerouting. International Journal of Simulation – Systems, Science and Technology, 15(4), 38–47.
Backfrieder, C., Ostermayer, G., Mecklenbräuker, C. F. (2017). Increased Traffic Flow through Node-based Bottleneck Prediction and V2X Communication. IEEE Transactions on Intelligent Transportation Systems, 18(2), 349–363.
Backfrieder, C., Lindorfer, M., Mecklenbräuker, C. F., Ostermayer, G. (2018). Robustness of Intelligent Vehicular Rerouting towards Non-ideal Communication Delay. Proceedings of the Future of Information and Communication Conference, 143-164, Singapore.
Behrisch, M., Bieker, L., Erdmann, J., Krajzewicz, D. (2011). SUMO - Simulation of Urban MObility - an Overview. Proceedings of the 3rd International Conference on Advances in System Simulation, 55–60, Barcelona, Spain.
Blazek, T., Backfrieder, C., Mecklenbräuker, C. F., Ostermayer, G. (2017). Improving Communication Reliability in Intelligent Transport Systems through Cooperative Driving. Proceedings of the 10th IFIP Wireless and Mobile Networking Conference, 1-6, Valencia, Spain.
Boskovich, S., Barth, M. (2013). Vehicular network Rerouting Autonomy with a V2V, I2V, and V2I Communication Matrix Classification. Proceedings of the 16th International IEEE Conference on Intelligent Transportation Systems, 172-177, The Hague, Netherlands.
Cassidy, M., Coifman, B. (1997). Relation among Average Speed, Flow, and Density and Analogous Relation between Density and Occupancy. Transportation Research Record: Journal of the Transportation Research Board, 1591, 1–6.
Cappiello, A., Chabini, I., Nam, E. K., Lue, A., Zeid, M. A. (2002). A Statistical Model of Vehicle Emissions and Fuel Consumption. Proceedings of the 5th IEEE International Conference on Intelligent Transportation Systems, 801–809, Singapore.
Chan, K. Y., Dillon, T., Chang, E. (2013). An Intelligent Particle Swarm Optimization for Short-term Traffic Flow Forecasting Using on-road Sensor Systems. IEEE Transactions on Industrial Electronics, 60 (10), 4714–4725.
Chen, A., Subprasom, K., Ji, Z. (2006). A Simulation-based Multi-objective Genetic Algorithm (SMOGA) Procedure for BOT Network Design Problem. Optimization and Engineering, 7(3), 225–247.
Elbery, A., Rakha, H., Elnainay, M., Drira, W., Filali, F. (2015). Eco-Routing Using V2I Communication: System Evaluation. Proceedings of the 18th IEEE International Conference on Intelligent Transportation Systems, 71–76, Las Palmas, Spain.
Gazis, D. C., Edie, L. C. (1968). Traffic Flow Theory. Proceedings of the IEEE, 56(4), 458–471.
Greenshields, B. D. (1935). A Study of Traffic Capacity. Highway Research Board, 14, 448-477.
Hoogendoorn, S. P., Bovy, P. H. (2001). State-of-the-art of vehicular traffic flow modelling. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 215, 283-303.
Horvitz, E. J., Apacible, J., Sarin, R, Liao, L. (2009). Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service. arXiv:1207.1352 [physics], 2012. [Online]. Available: http://arxiv.org/abs/1207.1352
Jing, B., Wu, L., Mao, H., Gong, S., He, J., Zou, C., Song, G., Li, X., Wu, Z. (2016). Development of a Vehicle Emission Inventory with High Temporal Spatial Resolution based on NRT Traffic Data and its Impact on Air Pollution in Beijing Part 1: Development and Evaluation of Vehicle Emission Inventory. Atmospheric Chemistry and Physics, 16(5), 3161–3170.
Kumar, R., Chhabra, S. (2016). Efficient Routing in Vehicular Ad-hoc Networks Using Firefly Optimization. Proceedings of the 2016 International Conference on Inventive Computation Technologies, 1–6, Coimbatore, India.
Lighthill, M. J., Whitham, G. B. (1955). On Kinematic Waves. I. Flood Movement in Long Rivers. Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences, 281–316.
Lindorfer, M., Mecklenbräuker, C. F., Ostermayer, G. (2017). Modeling the Imperfect Driver: Incorporating Human Factors in a Microscopic Traffic Model. IEEE Transactions on Intelligent Transportation Systems, 19(9), 2856–2870.
Mandziuk, J., Swiechovski, M. (2016). Simulation-based approach to Vehicle Routing Problem with Traffic Jams. Proceedings of IEEE Symposium Series on Computational Intelligence, 1-8, Athens, Greece.
Nafi, N., Khan, R., Khan, J., Gregory M. (2014). A Predictive Road Traffic Management System based on Vehicular Ad-hoc Network. Proceedings of the International Telecommunication Networks and Applications Conference, 135-140, Melbourne, Australia.
Nebbou, T., Fouchal, H., Lehsaini, M. (2017). Metrics for Vehicle Density in Urban Environment. Proceedings of the 2017 IEEE Global Communications Conference, 1–6, Singapore.
Ni, D. (2015). Traffic Flow Theory: Characteristics, Experimental Methods, and Numerical Techniques. Butterworth-Heinemann.
Pan, J., Khan, M., Sandu Popa, I., Zeitouni, K., Borcea, C. (2012). Proactive Vehicle Re-routing Strategies for Congestion Avoidance. Proceedings of the 8th IEEE International Conference on Distributed Computing in Sensor Systems, 265–272, Hangzhou, China.
Stevanovic, A., Stevanovic, J., Zhang, K., Batterman, S. (2009). Optimizing Traffic Control to Reduce Fuel Consumption and Vehicular Emissions: Integrated Approach with VISSIM, CMEM, and VISGAOST. Transportation Research Record: Journal of the Transportation Research Board, 2128, 105–113.
Szeto, W. Y., Jiang, Y., Wang, D. Z. W., Sumalee, A. (2015). A Sustainable Road Network Design Problem with Land Use Transportation Interaction Over Time. Networks and Spatial Economics, 15(3), 791–822.
Treiber, M., Kesting, A. (2013). Traffic Flow Dynamics. Berlin, Heidelberg. Springer.
Zhang, B., Ma, M., Liu, C., Shu, Y. (2017). Delay Guaranteed MDP Scheduling Scheme for HCCA based on 802.11p Protocol in V2R Environments. International Journal of Communication Systems, 30(15), 1-12.
Zhou, X., Tanvir, S., Lei, H., Taylor, J., Liu, B., Rouphail, N. M., Frey, H. C. (2015). Integrating a Simplified Emission Estimation Model and Mesoscopic Dynamic Traffic Simulator to Efficiently Evaluate Emission Impacts of Traffic Management Strategies. Transportation Research Part D: Transport and Environment, 37, 123–136.
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Published
Jun 30, 2019
Article Details
How to Cite
Ostermayer, G., Backfrieder, C., & Lindorfer, M. (2019). Dynamic Vehicular Traffic Load: Definition and Quantification. Journal of Telecommunications and the Digital Economy, 7(2), 74–91. https://doi.org/10.18080/jtde.v7n2.191
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Telecommunications
Copyright Telecommunications Association Inc.
