Relevant bibliographies by topics / Traffic matrix

Academic literature on the topic 'Traffic matrix'

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Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Traffic matrix"

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Medina, A., N. Taft, K. Salamatian, S. Bhattacharyya, and C. Diot. "Traffic matrix estimation." ACM SIGCOMM Computer Communication Review 32, no. 4 (October 2002): 161–74. http://dx.doi.org/10.1145/964725.633041.

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Adhikari, Vijay Kumar, Sourabh Jain, and Zhi-Li Zhang. "From traffic matrix to routing matrix." ACM SIGMETRICS Performance Evaluation Review 38, no. 3 (January 3, 2011): 49–54. http://dx.doi.org/10.1145/1925019.1925029.

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Tune, Paul, and Matthew Roughan. "Spatiotemporal Traffic Matrix Synthesis." ACM SIGCOMM Computer Communication Review 45, no. 4 (September 22, 2015): 579–92. http://dx.doi.org/10.1145/2829988.2787471.

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ZHOU, Jing-Jing. "Research on Traffic Matrix Estimation." Journal of Software 18, no. 11 (2007): 2669. http://dx.doi.org/10.1360/jos182669.

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Tune, Paul, and Matthew Roughan. "Maximum entropy traffic matrix synthesis." ACM SIGMETRICS Performance Evaluation Review 42, no. 2 (September 4, 2014): 43–45. http://dx.doi.org/10.1145/2667522.2667536.

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He, Hui, Ming Chang, Xing Wang, Wen Juan Li, Hong Li Zhang, and Hong Mei Ma. "The Quantification of Overlay Network Congestion Based on Compressive Sensing." Advanced Materials Research 268-270 (July 2011): 1564–67. http://dx.doi.org/10.4028/www.scientific.net/amr.268-270.1564.

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To obtain overlay network traffic and delay information between two hosts is important for network management, monitoring, design, planning and assessment. Traffic matrix and delay matrix represent the traffic and delay information between two hosts, so introduce the concept of the overlay network traffic matrix and delay matrix. Compressive sensing theory restores traffic matrix and delay matrix but is not suitable for overlay network. This paper improves compressive sensing algorithm to make it more applicable to overlay network traffic matrix and delay matrix restoration. After calculating the traffic matrix and delay matrix this paper quantifies overlay network congestion, which reflect the current network security situation. The experimental results show the restoration effect of traffic matrix and delay matrix is well and the congestion degree reflects the actual network state.
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Benameur, N., and J. W. Roberts. "Traffic Matrix Inference in IP Networks." Networks and Spatial Economics 4, no. 1 (March 2004): 103–14. http://dx.doi.org/10.1023/b:nets.0000015658.75205.ed.

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Zhou, Huibin, Dafang Zhang, Kun Xie, and Xiaoyang Wang. "Data reconstruction in internet traffic matrix." China Communications 11, no. 7 (July 2014): 1–12. http://dx.doi.org/10.1109/cc.2014.6895380.

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Jiang, Dingde, Xingwei Wang, and Lei Guo. "Mahalanobis distance-based traffic matrix estimation." European Transactions on Telecommunications 21, no. 3 (April 2010): 195–201. http://dx.doi.org/10.1002/ett.1382.

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Soule, Augustin, Kavé Salamatian, Antonio Nucci, and Nina Taft. "Traffic matrix tracking using Kalman filters." ACM SIGMETRICS Performance Evaluation Review 33, no. 3 (December 2005): 24–31. http://dx.doi.org/10.1145/1111572.1111580.

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Dissertations / Theses on the topic "Traffic matrix"

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Wang, Judith. "Wavelet-based traffic matrix modeling." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=96944.

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The traffic matrix is essential for many network management tasks because it provides the amount of traffic that flows between every origin-destination (OD) pair in a network. We focus on two traffic matrix problems: compression and estimation. Traffic matrices contain substantial amounts of data because they are collected at short timescales over long periods. We investigate techniques to compress traffic matrices using wavelet transforms, which allows us to isolate common underlying patterns present within traffic matrix datasets. In addition, it is expensive for network operators to measure traffic matrices directly. We demonstrate a new traffic matrix estimation method that is based on using our compressing transforms and methods for sparse estimation. Our estimation method also relies on inexpensive link-level measurements. We assess the performance of our wavelet-based traffic matrix model by testing it on two traffic matrix datasets.
La matrice de trafic est essentielle pour de nombreuses tâches de gestion de réseau parce qu'elle fourni le volume de trafic qui circule entre chaque paire d'origine et destination (OD) dans un réseau. Nous concentrons sur deux problèmes avec la matrice de trafic: la compression et l'estimation. Les matrices de trafic contiennent de grandes quantités de données parce qu'elles sont recueillies à des délais courts pendant de longues périodes. Nous examinons des techniques pour compresser les matrices de trafic en utilisant les transformées en ondelettes, qui nous permet d'isoler les tendances communes dans les matrices de trafic. En plus, il est coûteux pour les opérateurs de réseau de measurer les matrices de traficdirectement. Nous développons une nouvelle méthode pour estimer la matrice de trafic qui est basée sur les transformées en ondelettes et les méthodes d'estimation rares. Notre méthode d'estimation s'appuie également sur le volume de trafic traversant chaque lien dans un réseau, ce qui est peu coûteux de recueillir. Nous évaluons la performance de notre modèle pour la matrice de trafic en le testant sur deux ensembles de données.
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Eum, Suyong, and suyong@ist osaka-u. ac jp. "Traffic Matrix Estimation in IP Networks." RMIT University. Electrical and Computer Engineering, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080215.155526.

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An Origin-Destination (OD) traffic matrix provides a major input to the design, planning and management of a telecommunications network. Since the Internet is being proposed as the principal delivery mechanism for telecommunications traffic at the present time, and this network is not owned or managed by a single entity, there are significant challenges for network planners and managers needing to determine equipment and topology configurations for the various sections of the Internet that are currently the responsibility of ISPs and traditional telcos. Planning of these sub-networks typically requires a traffic matrix of demands that is then used to infer the flows on the administrator's network. Unfortunately, computation of the traffic matrix from measurements of individual flows is extremely difficult due to the fact that the problem formulation generally leads to the need to solve an under-determined system of equations. Thus, there has been a major effort f rom among researchers to obtain the traffic matrix using various inference techniques. The major contribution of this thesis is the development of inference techniques for traffic matrix estimation problem according to three different approaches, viz: (1) deterministic, (2) statistical, and (3) dynamic approaches. Firstly, for the deterministic approach, the traffic matrix estimation problem is formulated as a nonlinear optimization problem based on the generalized Kruithof approach which uses the Kullback distance to measure the probabilistic distance between two traffic matrices. In addition, an algorithm using the Affine scaling method is developed to solve the constrained optimization problem. Secondly, for the statistical approach, a series of traffic matrices are obtained by applying a standard deterministic approach. The components of these matrices represent estimates of the volumes of flows being exchanged between all pairs of nodes at the respective measurement points and they form a stochastic counting process. Then, a Markovian Arrival Process of order two (MAP-2) is applied to model the counting processes formed from this series of estimated traffic matrices. Thirdly, for the dynamic approach, the dual problem of the multi-commodity flow problem is formulated to obtain a set of link weights. The new weight set enables flows to be rerouted along new paths, which create new constraints to overcome the under-determined nature of traffic matrix estimation. Since a weight change disturbs a network, the impact of weight changes on the network is investigated by using simulation based on the well-known ns2 simulator package. Finally, we introduce two network applications that make use of the deterministic and the statistical approaches to obtain a traffic matrix respectively and also describe a scenario for the use of the dynamic approach.
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Marakov, Dimitri. "Contributions to the traffic matrix problem." Télécom Bretagne, 2007. http://www.theses.fr/2007TELB0058.

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This thesis addresses the traffic matrix estimation problem. Knowledge about the origin-destination (OD) traffic matrix (TM) allows us to solve problems in network engineering; the OD traffic matrix gives us a valuable information about who is communicating with whom in a network, at any given time. Traffic analysis, based on detailed packet or flow level measurements, usually not available throughout a large network due to hardware limitations or/and security reasons. An alternative approach is to use mathematical and statistical techniques for the estimation using the incomplete data accessible via SMNP. In my PhD thesis I describe the traffic data collection and, perform a critical evaluation of existing and novel methods for TM estimation on the real and synthetic data, and test the statistical and non-statistical methods. I discuss the weaknesses and strengths of the various methods, and highlight differences in the results for the simulated traffic and the real one obtained from European and American subnetworks. This research also addresses the variability of Internet traffic in backbone networks is essential for the creation of the better traffic model (vital for the estimation techniques), to better plan and manage existing networks, as well as to design next generation networks. I show the difference between the real traffic in high-bandwidth networks with the classic and most commonly used traffic models, propose a high-bandwidth TM simulation technique which can help with the evaluation of the traffic matrix algorithms in the case when the real TM necessary for the algorithms verification is difficult to obtain.
La matrice de trafic Origine Destination représente le volume de trafic entre chaque source et chaque destination sur un réseau. Elle est utile pour le dimensionnement du réseau, la définition du routage, etc. . . Elle ne peut pas être obtenue directement, mais doit au contraire être estimée, par des méthodes le plus souvent statistiques, partir du volume de trafic agrégé sur chacun des liens du réseau. Les méthodes existantes font des hypothèses réductrices sur les modèles de trafic; le trafic est le plus souvent considéré comme stationnaire et poissonnien. Le sujet de cette thèse est de généraliser les techniques existantes pour des modèles de trafic plus réalistes, et de valider les algorithmes proposés sur du trafic réel dans le cas d'un réseaux local et d' un réseau de cœur, utilisant un simulateur des réseaux large bande, développé dans le cadre du projet
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Gan, Liping. "Optimal traffic counting location for origin-destination matrix estimation /." View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?CIVL%202002%20GAN.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2002.
Includes bibliographical references (leaves 104-106). Also available in electronic version. Access restricted to campus users.
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Timms, Paul Martin. "A Bayesian approach to origin-destination trip matrix estimation." Thesis, University of Leeds, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.257965.

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Kim, Seung-Jun. "Simultaneous calibration of a microscopic traffic simulation model and OD matrix." Texas A&M University, 2006. http://hdl.handle.net/1969.1/4409.

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With the recent widespread deployment of intelligent transportation systems (ITS) in North America there is an abundance of data on traffic systems and thus an opportunity to use these data in the calibration of microscopic traffic simulation models. Even though ITS data have been utilized to some extent in the calibration of microscopic traffic simulation models, efforts have focused on improving the quality of the calibration based on aggregate form of ITS data rather than disaggregate data. In addition, researchers have focused on identifying the parameters associated with car-following and lane-changing behavior models and their impacts on overall calibration performance. Therefore, the estimation of the Origin-Destination (OD) matrix has been considered as a preliminary step rather than as a stage that can be included in the calibration process. This research develops a methodology to calibrate the OD matrix jointly with model behavior parameters using a bi-level calibration framework. The upper level seeks to identify the best model parameters using a genetic algorithm (GA). In this level, a statistically based calibration objective function is introduced to account for disaggregate form of ITS data in the calibration of microscopic traffic simulation models and, thus, accurately replicate dynamics of observed traffic conditions. Specifically, the Kolmogorov-Smirnov test is used to measure the "consistency" between the observed and simulated travel time distributions. The calibration of the OD matrix is performed in the lower level, where observed and simulated travel times are incorporated into the OD estimator for the calibration of the OD matrix. The interdependent relationship between travel time information and the OD matrix is formulated using a Extended Kalman filter (EKF) algorithm, which is selected to quantify the nonlinear dependence of the simulation results (travel time) on the OD matrix. The two test sites are from an urban arterial and a freeway in Houston, Texas. The VISSIM model was used to evaluate the proposed methodologies. It was found that that the accuracy of the calibration can be improved by using disaggregated data and by considering both driver behavior parameters and demand.
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Collins, Jeremy James. "Design of alphanumeric dot matrix displays for use in traffic management." Thesis, University of Southampton, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336147.

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Zeng, Jianfeng. "Time Series Forecasting using Temporal Regularized Matrix Factorization and Its Application to Traffic Speed Datasets." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1617109307510099.

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Peterson, Anders. "The Origin-Destination Matrix Estimation Problem : Analysis and Computations." Doctoral thesis, Norrköping : Dept. of Science and Technology, Linköpings universitet, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8859.

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Komolafe, Olufemi O. "High-speed optical packet switching over arbitrary physical topologies using the Manhattan Street Network." Thesis, University of Strathclyde, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366847.

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Books on the topic "Traffic matrix"

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S, Polibio Santana. Guía evolutiva jurídico procedimental en el ejercicio de la materia de tránsito en la República Dominicana: Lamborghini Murcielago. Santo Domingo, República Dominicana: Talleres de Impresos Jojansel, 2005.

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Medina, Miguel María Muñoz. La potestad sancionadora de la administración en materia de tráfico: Infracciones y sanciones. Madrid: Boletín Oficial del Estado, 1993.

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Sanchez, Felipe Luis Melendez. Consideraciones criminologicas en materia de estupefacientes. Madrid: Dykinson, 1989.

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Villalona, Germán Daniel Miranda. Jurisprudencia dominicana en materia de drogas. Santo Domingo, República Dominicana: Ediciones Jurídicas Trajano Potentini, 2003.

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(Mexico), Distrito Federal. Código civil para el Distrito Federal en materia comun, y para toda la República en materia federal. 2nd ed. México, D.F: Editorial PAC, 1994.

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Republic, Dominican. Ley 241 y sus modificaciones: Materia: responsabilidad penal y civil. [Santo Domingo: s.n.], 2000.

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B, Shanida N. López. Lesiones personales: Mediación y negociación como métodos alternativos de resolución de controversias : aplicados a los procesos penales en materia de tránsito. Panamá: Editorial Cultural Portobelo, 2008.

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B, Shanida N. López. Lesiones personales: Mediación y negociación como métodos alternativos de resolución de controversias : aplicados a los procesos penales en materia de tránsito. Panamá: Editorial Cultural Portobelo, 2008.

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(Mexico), Distrito Federal. Ley sobre justicia en materia de faltas de policía y buen gobierno y su reglamento ; Reglamento de tránsito en el D.F. ; Reglamento de la policía preventiva del D.F. ; Ley de la Caja de Previsión de la policía preventiva del Distrito Federal ; Reglamento de los trib. calificadores del D.F. ; Ley sobre estacionamientos y disposiciones conexas. México: Editorial Porrúa, 1986.

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(Mexico), Distrito Federal. Ley sobre justicia en materia de faltas de policía y buen gobierno y su reglamento ; Reglamento de tránsito del Distrito Federal ; Reglamento de carga del Distrito Federal ; Reglamento de la policía preventiva del Distrito Federal ; Ley de la Caja de Previsión de la policía preventiva del Distrito Federal y su reglamento ; Reglamento de los tribunales calificadores del Distrito Federal ; Ley sobre estacionamientos y disposiciones conexas. 2nd ed. México: Editorial Porrúa, 1989.

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Book chapters on the topic "Traffic matrix"

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Teixeira, Renata, Nick Duffield, Jennifer Rexford, and Matthew Roughan. "Traffic Matrix Reloaded: Impact of Routing Changes." In Lecture Notes in Computer Science, 251–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31966-5_20.

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Tootoonchian, Amin, Monia Ghobadi, and Yashar Ganjali. "OpenTM: Traffic Matrix Estimator for OpenFlow Networks." In Passive and Active Measurement, 201–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12334-4_21.

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Hong, Tang, Fan Tongliang, and Zhao Guogeng. "An Assignment Model on Traffic Matrix Estimation." In Lecture Notes in Computer Science, 295–304. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11881223_36.

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Bianco, Lucio, Giuseppe Confessore, and Pierfrancesco Reverberi. "Traffic Sensor Location and Origin/Destination Matrix Estimation." In Operations Research Proceedings, 527–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-58891-4_83.

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Ásmundsdóttir, Rúna, Yusen Chen, and Henk J. van Zuylen. "Dynamic Origin–Destination Matrix Estimation Using Probe Vehicle Data as A Priori Information." In Traffic Data Collection and its Standardization, 89–108. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-6070-2_7.

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Zhou, Jingjing, Jiahai Yang, Yang Yang, and Guanqun Zhang. "Traffic Matrix Estimation Using Square Root Filtering/Smoothing Algorithm." In Lecture Notes in Computer Science, 519–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88623-5_66.

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Shao, Weijuan, and Man Li. "Urban Railway Network Traffic Prediction with Spatiotemporal Correlations Matrix." In Proceedings of the 2015 International Conference on Electrical and Information Technologies for Rail Transportation, 335–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49370-0_35.

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Shang, Fengjun. "Research on the Traffic Matrix Based on Sampling Model." In Advanced Data Mining and Applications, 533–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73871-8_50.

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Mikians, Jakub, Amogh Dhamdhere, Constantine Dovrolis, Pere Barlet-Ros, and Josep Solé-Pareta. "Towards a Statistical Characterization of the Interdomain Traffic Matrix." In NETWORKING 2012, 111–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30054-7_9.

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Gasnikova, E. V., and T. A. Nagapetyan. "About New Dynamical Interpretations of Entropic Model of Correspondence Matrix Calculation and Nash-Wardrop’s Equilibrium in Beckmann’s Traffic Flow Distribution Model." In Traffic and Granular Flow '11, 465–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39669-4_44.

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Conference papers on the topic "Traffic matrix"

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Medina, A., N. Taft, K. Salamatian, S. Bhattacharyya, and C. Diot. "Traffic matrix estimation." In the 2002 conference. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/633025.633041.

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Tune, Paul, and Matthew Roughan. "Spatiotemporal Traffic Matrix Synthesis." In SIGCOMM '15: ACM SIGCOMM 2015 Conference. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2785956.2787471.

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Tan, Liansheng, and Xiangjun Wang. "On IP Traffic Matrix Estimation." In 2007 16th International Conference on Computer Communications and Networks. IEEE, 2007. http://dx.doi.org/10.1109/icccn.2007.4317886.

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Jia, Ru, Wei Su, and Hongke Zhang. "Traffic Matrix-Based Routing Optimization." In 2015 International Conference on Computer Science and Intelligent Communication. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/csic-15.2015.104.

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Balon, Simon, and Guy Leduc. "Dividing the Traffic Matrix to Approach Optimal Traffic Engineering." In 2006 14th IEEE International Conference on Networks. IEEE, 2006. http://dx.doi.org/10.1109/icon.2006.302619.

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Yang, Qi, Xiaolan Xu, and Wei Wang. "Estimating OD Matrix with Capacity Limited Method." In Second International Conference on Transportation and Traffic Studies (ICTTS ). Reston, VA: American Society of Civil Engineers, 2000. http://dx.doi.org/10.1061/40503(277)70.

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Zhou, Jing-Jing, and xu-dong Zhu. "Multi-scale traffic matrix estimation algorithm." In 2010 Second Pacific-Asia Conference on Circuits,Communications and System (PACCS). IEEE, 2010. http://dx.doi.org/10.1109/paccs.2010.5626989.

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Mesquita, Leonardo A. Jacobina, and Karcius Day R. Assis. "Traffic Matrix Prediction for Optical Networks." In 2019 SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference (IMOC). IEEE, 2019. http://dx.doi.org/10.1109/imoc43827.2019.9317630.

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Tune, Paul, Matthew Roughan, and Chris Wiren. "Hierarchical Traffic Matrices: Axiomatic Foundations to Practical Traffic Matrix Synthesis." In 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2018. http://dx.doi.org/10.23919/apsipa.2018.8659593.

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Shi, Feng, and Maosheng Li. "Recursive Estimation for Origin-Destination Matrix through a Region." In International Conference on Traffic and Transportation Studies (ICTTS) 2002. Reston, VA: American Society of Civil Engineers, 2002. http://dx.doi.org/10.1061/40630(255)81.

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Reports on the topic "Traffic matrix"

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Zhang, Yongping, Wen Cheng, and Xudong Jia. Enhancement of Multimodal Traffic Safety in High-Quality Transit Areas. Mineta Transportation Institute, February 2021. http://dx.doi.org/10.31979/mti.2021.1920.

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Numerous extant studies are dedicated to enhancing the safety of active transportation modes, but very few studies are devoted to safety analysis surrounding transit stations, which serve as an important modal interface for pedestrians and bicyclists. This study bridges the gap by developing joint models based on the multivariate conditionally autoregressive (MCAR) priors with a distance-oriented neighboring weight matrix. For this purpose, transit-station-centered data in Los Angeles County were used for model development. Feature selection relying on both random forest and correlation analyses was employed, which leads to different covariate inputs to each of the two jointed models, resulting in increased model flexibility. Utilizing an Integrated Nested Laplace Approximation (INLA) algorithm and various evaluation criteria, the results demonstrate that models with a correlation effect between pedestrians and bicyclists perform much better than the models without such an effect. The joint models also aid in identifying significant covariates contributing to the safety of each of the two active transportation modes. The research results can furnish transportation professionals with additional insights to create safer access to transit and thus promote active transportation.
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Lippert, David, Marshall Thompson, and Charles Wienrank. Performance of Interstate Rubblization in Illinois. Illinois Center for Transportation, July 2021. http://dx.doi.org/10.36501/0197-9191/21-005.

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In Illinois, hot-mix asphalt overlaid concrete pavements typically exhibit reflective cracking of joints and cracks from the pavement below, resulting in shortened life and maintenance issues. Over the years, various patching, fabric, and crack and seat techniques were attempted with few positive results. This led to more aggressive techniques to eliminate the slab action of the concrete pavement where the pavement would be broken or rubblized into pieces typically less than 12 inches. Since the first rubblizing project in 1990, policy, procedures, and specifications have evolved to the point that rubblization is the mainstream option in dealing with problematic concrete pavements. This report summarizes the performance of several interstate rubblizing projects in Illinois by analyzing available data in Illinois Department of Transportation’s pavement management system. Condition rating survey data allowed the serviceability of these projects to be evaluated by surface mix types and asphalt performance grades. Traffic in the form of 18,000 lb equivalent single axle loads was determined for the projects to evaluate fatigue and rutting as well as compare section performance to the design procedure. The research team reviewed plans, design procedures, and specifications to determine best practices and identify where improvements might be made. Data showed that the use of stone matrix asphalt surface mixtures and mixes using PGXX-28 asphalt binders provides improved performance. Overall, rubblizing has shown good to excellent performance. To provide additional life with improved performance, recommendations include adopting softer asphalt grades, increasing the use of stone matrix asphalt, and improving procedures for protecting culverts.
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Hsueh, Gary, David Czerwinski, Cristian Poliziani, Terris Becker, Alexandre Hughes, Peter Chen, and Melissa Benn. Using BEAM Software to Simulate the Introduction of On-Demand, Automated, and Electric Shuttles for Last Mile Connectivity in Santa Clara County. Mineta Transportation Institute, January 2021. http://dx.doi.org/10.31979/mti.2021.1822.

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Despite growing interest in low-speed automated shuttles, pilot deployments have only just begun in a few places in the U.S., and there is a lack of studies that estimate the impacts of a widespread deployment of automated shuttles designed to supplement existing transit networks. This project estimated the potential impacts of automated shuttles based on a deployment scenario generated for a sample geographic area: Santa Clara County, California. The project identified sample deployment markets within Santa Clara County using a GIS screening exercise; tested the mode share changes of an automated shuttle deployment scenario using BEAM, an open-source beta software developed at the Lawrence Berkeley National Laboratory to run traffic simulations with MATSim; elaborated the model outputs within the R environment; and then estimated the related impacts. The main findings have been that the BEAM software, despite still being in its beta version, was able to model a scenario with the automated shuttle service: this report illustrates the potential of the software and the lessons learned. Regarding transportation aspects, the model estimated automated shuttle use throughout the county, with a higher rate of use in the downtown San José area. The shuttles would be preferred mainly by people who had been using gasoline-powered ride hail vehicles for A-to-B trips or going to the bus stop, as well as walking trips and a few car trips directed to public transport stops. As a result, the shuttles contributed to a small decrease in emissions of air pollutants, provided a competitive solution for short trips, and increased the overall use of the public transport system. The shuttles also presented a solution for short night trips—mainly between midnight and 2 am—when there are not many options for moving between points A and B. The conclusion is that the automated shuttle service is a good solution in certain contexts and can increase public transit ridership overall.
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