{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T01:10:37Z","timestamp":1736125837964,"version":"3.32.0"},"reference-count":73,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T00:00:00Z","timestamp":1656374400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"DRAGON (Data Driven Precision Agriculture Services and Skill Acquisition)"},{"name":"European Union\u2019s Horizon 2020"},{"DOI":"10.13039\/501100004564","name":"Ministry of Education, Science and Technological Development of the Republic of Serbia","doi-asserted-by":"crossref","award":["451-03-68\/2022-14\/200358"],"id":[{"id":"10.13039\/501100004564","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"To create quality decision-making tools that would contribute to transport sustainability, we need to build models relying on accurate, timely, and sufficiently disaggregated data. In spite of today\u2019s ubiquity of big data, practical applications are still limited and have not reached technology readiness. Among them, passively generated telecom data are promising for studying travel-pattern generation. The objective of this study is twofold. First, to demonstrate how telecom data can be fused with other data sources and used to feed up a traffic model. Second, to simulate traffic using an agent-based approach and assess the emission produced by the model\u2019s scenario. Taking Novi Sad as a case study, we simulated the traffic composition at 1-s resolution using the GAMA platform and calculated its emission at 1-h resolution. We used telecom data together with population and GIS data to calculate spatial-temporal movement and imported it to the ABM. Traffic flow was calibrated and validated with data from automatic vehicle counters, while air quality data was used to validate emissions. The results demonstrate the value of using diverse data sets for the creation of decision-making tools. We believe that this study is a positive endeavor toward combining big data and ABM in urban studies.<\/jats:p>","DOI":"10.3390\/ijgi11070366","type":"journal-article","created":{"date-parts":[[2022,6,29]],"date-time":"2022-06-29T03:59:22Z","timestamp":1656475162000},"page":"366","source":"Crossref","is-referenced-by-count":4,"title":["Combining Telecom Data with Heterogeneous Data Sources for Traffic and Emission Assessments\u2014An Agent-Based Approach"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7934-7327","authenticated-orcid":false,"given":"Nastasija","family":"Gruji\u0107","sequence":"first","affiliation":[{"name":"BioSense Institute, University of Novi Sad, 21000 Novi Sad, Serbia"}]},{"given":"Sanja","family":"Brdar","sequence":"additional","affiliation":[{"name":"BioSense Institute, University of Novi Sad, 21000 Novi Sad, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5777-4048","authenticated-orcid":false,"given":"Sjoukje","family":"Osinga","sequence":"additional","affiliation":[{"name":"Information Technology, Wageningen University & Research, 6706 KN Wageningen, The Netherlands"}]},{"given":"Gert Jan","family":"Hofstede","sequence":"additional","affiliation":[{"name":"Information Technology, Wageningen University & Research, 6706 KN Wageningen, The Netherlands"},{"name":"Optentia Research Programme, North-West University, Potchefstroom 2351, South Africa"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2764-0078","authenticated-orcid":false,"given":"Ioannis N.","family":"Athanasiadis","sequence":"additional","affiliation":[{"name":"Geo-Information Science and Remote Sensing Laboratory, Wageningen Data Competence Center, Wageningen University & Research, 6708 PB Wageningen, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4159-0639","authenticated-orcid":false,"given":"Milo\u0161","family":"Pljaki\u0107","sequence":"additional","affiliation":[{"name":"Faculty of Technical Sciences, University of Pri\u0161tina in Kosovska Mitrovica, 38220 Kosovska Mitrovica, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9554-3590","authenticated-orcid":false,"given":"Nikola","family":"Obrenovi\u0107","sequence":"additional","affiliation":[{"name":"BioSense Institute, University of Novi Sad, 21000 Novi Sad, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1698-0800","authenticated-orcid":false,"given":"Miro","family":"Govedarica","sequence":"additional","affiliation":[{"name":"Department for Computing and Control Engineering, Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia"}]},{"given":"Vladimir","family":"Crnojevi\u0107","sequence":"additional","affiliation":[{"name":"BioSense Institute, University of Novi Sad, 21000 Novi Sad, Serbia"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Jain, V., Sharma, A., and Subramanian, L. (2012, January 11\u201312). Road traffic congestion in the developing world. Proceedings of the 2nd ACM Symposium on Computing for Development, Atlanta, GA, USA.","DOI":"10.1145\/2160601.2160616"},{"key":"ref_2","unstructured":"WHO (2021, November 18). World Health Organization\u2014Urban Population Growth, Global Health Observatory. Available online: https:\/\/www.who.int\/."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Khalfan, A., Andrews, G., and Li, H. (2017, January 16\u201318). Real World Driving: Emissions in Highly Congested Traffic. Proceedings of the SAE Powertrain Fuels and Lubricants Meeting 2017, Beijing, China.","DOI":"10.4271\/2017-01-2388"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jclepro.2018.02.113","article-title":"Large scale simulation of CO2 emissions caused by urban car traffic: An agent-based network approach","volume":"183","author":"Hofer","year":"2018","journal-title":"J. Clean. Prod."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.ijtst.2017.05.005","article-title":"Assessing the impacts of deploying a shared self-driving urban mobility system: An agent-based model applied to the city of Lisbon, Portugal","volume":"6","author":"Martinez","year":"2017","journal-title":"Int. J. Transp. Sci. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40649-018-0053-y","article-title":"Including traffic jam avoidance in an agent-based network model","volume":"5","author":"Hofer","year":"2018","journal-title":"Comput. Soc. Netw."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1007\/s11067-013-9204-8","article-title":"Towards high-resolution first-best air pollution tolls","volume":"16","author":"Nagel","year":"2016","journal-title":"Netw. Spat. Econ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1291","DOI":"10.1016\/j.tra.2012.05.006","article-title":"A dynamic cordon pricing scheme combining the macroscopic fundamental diagram and an agent-based traffic model","volume":"46","author":"Zheng","year":"2012","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_9","unstructured":"Willumsen, L. (2021). Use of Big Data in Transport Modelling, OECD\/ITF."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Brdar, S., Novovi\u0107, O., Gruji\u0107, N., Gonz\u00e1lez-V\u00e9lez, H., Truic\u0103, C.O., Benkner, S., Bajrovic, E., and Papadopoulos, A. (2019). Big Data Processing, Analysis and Applications in Mobile Cellular Networks. High-Performance Modelling and Simulation for Big Data Applications, Springer.","DOI":"10.1007\/978-3-030-16272-6_6"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/MPRV.2011.44","article-title":"A tale of one city: Using cellular network data for urban planning","volume":"10","author":"Becker","year":"2011","journal-title":"IEEE Pervasive Comput."},{"key":"ref_12","unstructured":"Arai, A., Witayangkurn, A., Kanasugi, H., Fan, Z., Ohira, W., and Pedro, S. (2020). Building a Data Ecosystem for Using Telecom Data to Inform the COVID-19 Response Efforts, Zenodo."},{"key":"ref_13","unstructured":"Bosetti, P., Poletti, P., Stella, M., Lepri, B., Merler, S., and De Domenico, M. (2019). Reducing measles risk in Turkey through social integration of Syrian refugees. arXiv."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"19342","DOI":"10.1038\/srep19342","article-title":"Unveiling spatial epidemiology of HIV with mobile phone data","volume":"6","author":"Brdar","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"10650","DOI":"10.1038\/srep10650","article-title":"Disease containment strategies based on mobility and information dissemination","volume":"5","author":"Lima","year":"2015","journal-title":"Sci. Rep."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"9796431","DOI":"10.34133\/2021\/9796431","article-title":"Mobile Phone-Based Population Flow Data for the COVID-19 Outbreak in Mainland China","volume":"2021","author":"Lu","year":"2021","journal-title":"Health Data Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"11887","DOI":"10.1073\/pnas.1504964112","article-title":"Impact of human mobility on the emergence of dengue epidemics in Pakistan","volume":"112","author":"Wesolowski","year":"2015","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Novovi\u0107, O., Brdar, S., Mesaro\u0161, M., Crnojevi\u0107, V., and Papadopoulos, A.N. (2020). Uncovering the relationship between human connectivity dynamics and land use. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9030140"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"De Nadai, M., Staiano, J., Larcher, R., Sebe, N., Quercia, D., and Lepri, B. (2016, January 11\u201315). The death and life of great Italian cities: A mobile phone data perspective. Proceedings of the 25th International Conference on World Wide Web, Montreal, QC, Canada.","DOI":"10.1145\/2872427.2883084"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Gruji\u0107, N., Novovi\u0107, O., Brdar, S., Crnojevi\u0107, V., and Govedarica, M. (2019, January 20\u201321). Mobile Phone Data visualization using Python QGIS API. Proceedings of the 2019 18th International Symposium INFOTEH-JAHORINA (INFOTEH), East Sarajevo, Republic of Srpska.","DOI":"10.1109\/INFOTEH.2019.8717767"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1080\/10630732.2014.888904","article-title":"Population mobility dynamics estimated from mobile telephony data","volume":"21","author":"Doyle","year":"2014","journal-title":"J. Urban Technol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"5276","DOI":"10.1038\/srep05276","article-title":"From mobile phone data to the spatial structure of cities","volume":"4","author":"Louail","year":"2014","journal-title":"Sci. Rep."},{"key":"ref_23","unstructured":"Brdar, S., Gruji\u0107, N., Obrenovi\u0107, N., Novovi\u0107, O., Lugonja, P., Mini\u0107, V., Baji\u0107, \u017d., Milovanovi\u0107, M., and Rokvi\u0107, N. (2021). Project-Depopulation Sensing by Integrative Knowledge Discovery from Big Data, Biosense."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Gruji\u0107, N., Brdar, S., Novovi\u0107, O., Govedarica, M., and Crnojevi\u0107, V. (2019, January 26\u201327). Evidence of urban segregation from mobile phone data: A case study of Novi Sad. Proceedings of the 2019 27th Telecommunications Forum (TELFOR), Belgrade, Serbia.","DOI":"10.1109\/TELFOR48224.2019.8971290"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Gruji\u0107, N., Brdar, S., Novovi\u0107, O., Obrenovi\u0107, N., Govedarica, M., and Crnojevi\u0107, V. (2021, January 19\u201330). Biclustering for uncovering spatial-temporal patterns in telecom data. Proceedings of the EGU General Assembly Conference Abstracts, Online.","DOI":"10.5194\/egusphere-egu21-14423"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Pappalardo, L., Pedreschi, D., Smoreda, Z., and Giannotti, F. (November, January 29). Using big data to study the link between human mobility and socio-economic development. Proceedings of the 2015 IEEE International Conference on Big Data (Big Data), Santa Clara, CA, USA.","DOI":"10.1109\/BigData.2015.7363835"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"20160690","DOI":"10.1098\/rsif.2016.0690","article-title":"Mapping poverty using mobile phone and satellite data","volume":"14","author":"Steele","year":"2017","journal-title":"J. R. Soc. Interface"},{"key":"ref_28","unstructured":"Galiana, L., Sakarovitch, B., and Smoreda, Z. (DGINS18, 2018). Understanding socio-spatial segregation in French cities with mobile phone data, DGINS18, unpublished manuscript."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1007\/s10584-016-1753-7","article-title":"Detecting climate adaptation with mobile network data in Bangladesh: Anomalies in communication, mobility and consumption patterns during cyclone Mahasen","volume":"138","author":"Lu","year":"2016","journal-title":"Clim. Chang."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Pastor-Escuredo, D., Morales-Guzm\u00e1n, A., Torres-Fern\u00e1ndez, Y., Bauer, J.M., Wadhwa, A., Castro-Correa, C., Romanoff, L., Lee, J.G., Rutherford, A., and Frias-Martinez, V. (2014, January 10\u201313). Flooding through the lens of mobile phone activity. Proceedings of the IEEE Global Humanitarian Technology Conference (GHTC 2014), San Jose, CA, USA.","DOI":"10.1109\/GHTC.2014.6970293"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Wilson, R., zu Erbach-Schoenberg, E., Albert, M., Power, D., Tudge, S., Gonzalez, M., Guthrie, S., Chamberlain, H., Brooks, C., and Hughes, C. (2016). Rapid and near real-time assessments of population displacement using mobile phone data following disasters: The 2015 Nepal earthquake. PLoS Curr., 8.","DOI":"10.1371\/currents.dis.d073fbece328e4c39087bc086d694b5c"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"J\u00e4rv, O., Ahas, R., Saluveer, E., Derudder, B., and Witlox, F. (2012). Mobile phones in a traffic flow: A geographical perspective to evening rush hour traffic analysis using call detail records. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0049171"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/j.trc.2007.06.003","article-title":"Evaluation of a cellular phone-based system for measurements of traffic speeds and travel times: A case study from Israel","volume":"15","year":"2007","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_34","first-page":"123","article-title":"Use of mobile phone data for analysis of number of train travellers","volume":"8","author":"Bjelland","year":"2018","journal-title":"J. Rail Transp. Plan. Manag."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1016\/j.trc.2015.02.018","article-title":"Origin\u2013destination trips by purpose and time of day inferred from mobile phone data","volume":"58","author":"Alexander","year":"2015","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.deveng.2018.03.002","article-title":"A trip to work: Estimation of origin and destination of commuting patterns in the main metropolitan regions of Haiti using CDR","volume":"3","author":"Zagatti","year":"2018","journal-title":"Dev. Eng."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.trc.2014.01.002","article-title":"Development of origin\u2013destination matrices using mobile phone call data","volume":"40","author":"Iqbal","year":"2014","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_38","first-page":"207","article-title":"Route choice estimation based on cellular signaling data","volume":"9","author":"Tettamanti","year":"2012","journal-title":"Acta Polytech. Hung."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Sakamanee, P., Phithakkitnukoon, S., Smoreda, Z., and Ratti, C. (2020). Methods for inferring route choice of commuting trip from mobile phone network data. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9050306"},{"key":"ref_40","unstructured":"Wang, H., Calabrese, F., Di Lorenzo, G., and Ratti, C. (2008, January 12\u201315). Transportation mode inference from anonymized and aggregated mobile phone call detail records. Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems, Beijing, China."},{"key":"ref_41","unstructured":"Doyle, J., Hung, P., Kelly, D., McLoone, S.F., and Farrell, R. (2011). Utilising Mobile Phone Billing Records for Travel Mode Discovery, Maynooth University."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Wu, H., Liu, L., Yu, Y., Peng, Z., Jiao, H., and Niu, Q. (2019). An agent-based model simulation of human mobility based on mobile phone data: How commuting relates to congestion. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.20944\/preprints201906.0049.v1"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.tra.2018.12.024","article-title":"Mobile phone records to feed activity-based travel demand models: MATSim for studying a cordon toll policy in Barcelona","volume":"121","author":"Bassolas","year":"2019","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"(2018). A Generative Model of Urban Activities from Cellular Data. IEEE Trans. Intell. Transp. Syst., 19, 1682\u20131696.","DOI":"10.1109\/TITS.2017.2695438"},{"key":"ref_45","first-page":"615","article-title":"An agent-based model for real-time bus stop-skipping and holding schemes","volume":"17","author":"Zhang","year":"2021","journal-title":"Transp. A Transp. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.future.2016.02.019","article-title":"Organizational-based model and agent-based simulation for long-term carpooling","volume":"64","author":"Hussain","year":"2016","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.cities.2018.03.018","article-title":"An agent-based modeling approach for sustainable urban planning from land use and public transit perspectives","volume":"81","author":"Motieyan","year":"2018","journal-title":"Cities"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"7280","DOI":"10.1073\/pnas.082080899","article-title":"Agent-based modeling: Methods and techniques for simulating human systems","volume":"99","author":"Bonabeau","year":"2002","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1068\/a3784","article-title":"Agents, cells, and cities: New representational models for simulating multiscale urban dynamics","volume":"37","author":"Batty","year":"2005","journal-title":"Environ. Plan. A"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Crooks, A., Malleson, N., Manley, E., and Heppenstall, A. (2018). Agent-Based Modelling and Geographical Information Systems: A Practical Primer, Sage.","DOI":"10.4135\/9781529793543"},{"key":"ref_51","unstructured":"Heppenstall, A. (2019). Agent-Based Models for Geographical Systems: A Review, University College London."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1007\/s10707-018-00339-6","article-title":"Building, composing and experimenting complex spatial models with the GAMA platform","volume":"23","author":"Taillandier","year":"2019","journal-title":"GeoInformatica"},{"key":"ref_53","unstructured":"(2022, February 03). Handbook on Emission Factors for Road Transport. Available online: https:\/\/www.hbefa.net\/e\/index.html."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1080\/01944369408975590","article-title":"The rational locator: Why travel times have remained stable","volume":"60","author":"Levinson","year":"1994","journal-title":"J. Am. Plan. Assoc."},{"key":"ref_55","first-page":"1","article-title":"Regularities in travel demand: An international perspective","volume":"3","author":"Schafer","year":"2000","journal-title":"J. Transp. Stat."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2883","DOI":"10.1007\/s11116-020-10151-7","article-title":"Mobile phone data in transportation research: Methods for benchmarking against other data sources","volume":"48","author":"Landmark","year":"2021","journal-title":"Transportation"},{"key":"ref_57","unstructured":"Okabe, A., Boots, B., Sugihara, K., and Chiu, S.N. (2000). Concepts and Applications of Voronoi Diagrams, John Wiley & Sons Ltd."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Salgado, M., and Gilbert, N. (2013). Agent based modelling. Handbook of Quantitative Methods for Educational Research, Brill Sense.","DOI":"10.1007\/978-94-6209-404-8_12"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1017\/S0269888913000118","article-title":"A review on agent-based technology for traffic and transportation","volume":"29","author":"Bazzan","year":"2014","journal-title":"Knowl. Eng. Rev."},{"key":"ref_60","unstructured":"Taillandier, P. (2014, January 5\u20136). Traffic simulation with the GAMA platform. Proceedings of the Eighth International Workshop on Agents in Traffic and Transportation, Paris, France."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"020035","DOI":"10.1063\/5.0075719","article-title":"Traffic simulation using agent based modelling","volume":"Volume 2423","author":"Shaharuddin","year":"2021","journal-title":"Proceedings of the AIP Conference Proceedings"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Kickh\u00f6fer, B., H\u00fclsmann, F., Gerike, R., and Nagel, K. (2013). Rising car user costs: Comparing aggregated and geo-spatial impacts on travel demand and air pollutant emissions. Smart Transport Networks, Edward Elgar Publishing.","DOI":"10.4337\/9781782548331.00014"},{"key":"ref_63","unstructured":"(2021, September 21). Novi Sad. Available online: https:\/\/en.wikipedia.org\/wiki\/Novi_Sad."},{"key":"ref_64","unstructured":"(2021, September 21). New Bridge. Available online: https:\/\/www.021.rs\/story\/Novi-Sad\/Vesti\/268583\/Planiranje-novog-mosta-u-Novom-Sadu-Dokument-na-javnom-uvidu-prigovori-do-11-aprila.html."},{"key":"ref_65","unstructured":"(2022, February 01). SEPA\u2014Serbia Environmental Protection Agency, Available online: http:\/\/www.sepa.gov.rs\/."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Ni, D. (2015). Traffic Flow Theory: Characteristics, Experimental Methods, and Numerical Techniques, Butterworth-Heinemann.","DOI":"10.1016\/B978-0-12-804134-5.00003-9"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Plakolb, S., J\u00e4ger, G., Hofer, C., and F\u00fcllsack, M. (2019). Mesoscopic urban-traffic simulation based on mobility behavior to calculate NOx emissions caused by private motorized transport. Atmosphere, 10.","DOI":"10.3390\/atmos10060293"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"03006","DOI":"10.1051\/matecconf\/201815003006","article-title":"Overview of application of traffic simulation model","volume":"Volume 150","author":"Azlan","year":"2018","journal-title":"Proceedings of the MATEC Web of Conferences"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Zhao, B., Kumar, K., Casey, G., and Soga, K. (2019, January 8\u201310). Agent-based model (ABM) for city-scale traffic simulation: A case study on San Francisco. Proceedings of the International Conference on Smart Infrastructure and Construction 2019 (ICSIC) Driving Data-Informed Decision-Making, Cambridge, UK.","DOI":"10.1680\/icsic.64669.203"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1016\/j.ins.2016.07.007","article-title":"Towards felicitous decision making: An overview on challenges and trends of Big Data","volume":"367","author":"Wang","year":"2016","journal-title":"Inf. Sci."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1007\/s13347-017-0279-x","article-title":"Fair, transparent, and accountable algorithmic decision-making processes","volume":"31","author":"Lepri","year":"2018","journal-title":"Philos. Technol."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1016\/j.aap.2005.12.006","article-title":"Spatial analysis of fatal and injury crashes in Pennsylvania","volume":"38","author":"Jovanis","year":"2006","journal-title":"Accid. Anal. Prev."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"1486","DOI":"10.1016\/j.aap.2008.03.009","article-title":"Modelling area-wide count outcomes with spatial correlation and heterogeneity: An analysis of London crash data","volume":"40","author":"Quddus","year":"2008","journal-title":"Accid. Anal. Prev."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/7\/366\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T00:28:52Z","timestamp":1736123332000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/7\/366"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,28]]},"references-count":73,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2022,7]]}},"alternative-id":["ijgi11070366"],"URL":"https:\/\/doi.org\/10.3390\/ijgi11070366","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2022,6,28]]}}}