Application of the AHP Method for Comparative Analysis of Software Systems in Traffic from the Aspect of Traffic Safety


  • Ognjen Pantelić University of Belgrade, Faculty of Organizational Sciences
  • Dalibor Pešić University of Belgrade, Faculty of Transport and Traffic Engineering
  • Milan Vujanić Traffic Safety Group (TSG), Serbia
  • Katarina Švab KPMG Serbia
  • Aleksandar Trifunović University of Belgrade, Faculty of Transport and Traffic Engineering



traffic safety, information systems, intelligent transportation systems, motion, SCATS, SCOOT


It is generally known that traffic safety is influenced by humans, vehicles, and roads. Nowadays, when new technologies have taken over a large part of the traffic industry, the selection of relevant software, whose competition is great, presents a big problem for the decision-maker. Intelligent systems, such as Motion, SCOOT, and SCATS, are used for the implementation of a control strategy in order to manage signals on the traffic network, with the goal of increasing efficiency and traffic safety. These systems operate on the demand-responsive principle and have logic for traffic optimization which represents their main difference along with the optimization subject and method of the system functioning. The research included consideration of mentioned differences, software, and hardware architecture that have a significant impact on the system’s functionality since the detector’s locations themselves depend on the optimization subject. The implementation benefits are considered through the existing world’s projects. Based on the obtained data, the criteria used for the comparative analysis of these three systems were defined, from the aspect of traffic safety.


Federal Highway Administration – FWHA. Intelligent transportation systems technologies. 2021; [Accessed 20th Jan. 2023].

Chen K, Miles C. ITS handbook 2004: Recommendations from the world road association. PIARC; 2004. [Accessed 22th Jan. 2023].

Gordon L, Tighe W. Traffic control systems handbook (2005 edition). Siemens ITS; 2005. [Accessed 22th Jan. 2023].

Vukanović S. Introduction of the ITS into curricula at technical universities. Tehnika-Saobraćaj. 2006;53(5):1-6.

Papageorgiou M, et al. Chapter 11: ITS and traffic management. In: Barnhart C, Laporte G. (eds) Handbooks in Operations Research and Management Science. Vol. 14. 2007. p. 715-774. DOI: 10.1016/S0927-0507(06)14011-6.

Xu H. Decentralized traffic information system design based on inter-vehicle communications. PhD thesis. University of California, Riverside; 2006.

Vukanović S. ITS and traffic management and control: Part II. Tehnika-Saobraćaj. 2010;57(2):19-26.

Stellner F, Vokoun M, Szobi P, Kasa M. Transport policy as a way to strengthen geostrategic position – A review of Vienna as a centre of air and high-speed rail transport in Central Europe. Promet – Traffic&Transportation. 2023;35(3):285-298. DOI: 10.7307/ptt.v35i3.58.

Ryus P, et al. Highway capacity manual 2010. Washington, DC: Transportation Research Board; 2010. [Accessed 22th Jan. 2023].

Jiang P, Poschinger A, Qi Y. MOTION - A developing urban adaptive traffic signal control system. Advanced Materials Research. 2013;779:788-791. DOI: 10.4028/

Mück J. The German approach to adaptive network control. Siemens; 2014. [Accessed 22th Jan. 2023].

Gokulan P. Distributed multi-agent based traffic management system. PhD thesis. University of Madras, National University of Singapore; 2011.

Hebenstreit C, et al. COLOMBO-D2. Policy selection and definition and dynamic policy selection algorithms. EU-Review; 2013. p. 7-156.

McCann B. A review of SCATS operation and deployment in Dublin. JCT Traffic Signal Symposium & Exhibition; 2014. [Accessed 14th Jan. 2023].

Zhao Y, Tian Z. An overview of the usage of adaptive signal control system in the United States of America. Applied Mechanics and Materials. 2012;178:2591-2598. DOI: 10.4028/

Simović S. What causes changes in passenger behavior in South-East Europe during the COVID-19 pandemic?. Sustainability. 2021;13(15):8398. DOI: 10.3390/su13158398.

Friedrich B, Shahin M. Adaptive traffic control in metropolitan areas. Role of Engineering Towards a Better Environment (RETBE’02); 2017. [Accessed 20th Jan. 2023].

Wang Y, Yang X, Liang H, Liu Y. A review of the self-adaptive traffic signal control system based on future traffic environment. Journal of Advanced Transportation. 2018. DOI: 10.1155/2018/1096123.

TRL Software. Urban traffic control (UTC), Powered by SCOOT®7. 2022. [Accessed 20th Jan. 2023].

Levi-Jakšić M, Marinković S, Obradović J. Management of technology and development [Razvoj oblasti i kurikuluma menadžmenta tehnologije]. Belgrade, Serbia: Faculty of Organisational Sciences; 2009: p. 248-280.

Slović Ž. Abdominal injuries in road traffic accidents–an autopsy study. Vojnosanitetski Pregled. 2023:80(03):42. DOI: 10.2298/VSP221118042S.

Čubranić-Dobrodolac M. A bee colony optimization (BCO) and type-2 fuzzy approach to measuring the impact of speed perception on motor vehicle crash involvement. Soft Computing. 2021;26(9):4463-4486. DOI: 10.1007/s00500-021-06516-4.

Steierwald M, Martens S. Sitraffic central - verkehrsrechnersystem urban traffic computer system. Siemens; 2003. [Accessed 20th Jan. 2023].

Leaflet A. SCOOT urban traffic control system. Siemens; 1995. [Accessed 20th Jan. 2023].

Zhaomeng C. Intelligent traffic control central system of Beijing-SCOOT. IEEE; 2010. [Accessed 20th Jan. 2023].

Ireland D, Webb W. Strategic entrepreneurship: Creating competitive advantage through streams of innovation. Business Horizons. 2007;50(1):49-59. DOI: 10.1016/j.bushor.2006.06.002.

Stevanovic A, Dobrota N, Mitrovic N. NCHRP 20-07/Task 414: Benefits of adaptive traffic control deployments—A review of evaluation studies. Washington, DC, USA: NCHRP; 2019. DOI: 10.13140/RG.2.2.33908.30082.

Kergaye C, Stevanovic A, Martin T. An evaluation of SCOOT and SCATS through microsimulation. 10th International Conference on Applications of Advanced Technologies in Transportation, Transportation and Development Institute, Athens, Greece. 2008.

Fellendorf M. Urban traffic management. Encyclopedia of Automotive Engineering; 2014. [Accessed 20th Jan. 2023].

Mück J. The most intelligent answer to congestion and pollution. Munich, Germany: Siemens AG; 2014. [Accessed 20th Jan. 2023].

Xin W, Chang J, Muthuswamy S, Talas M. Midtown in Motion": A new active traffic management methodology and its implementation in New York City. No. 13-4145; 2013. [Accessed 20th Jan. 2023].

Aldridge Traffic Controllers. Intelligent transport systems; 2014. [Accessed 20th Jan. 2023].

Stephanedes J, Kwon E, Chang K, Yao P. Development and application of demand-responsive ramp metering control to improve traffic management in freeway corridors. Iowa State University; 1992. [Accessed 20th Jan. 2023].

Veith E. Adaptive traffic pilot programs. Alpharetta; 2012. [Accessed 20th Jan. 2023].

Junhua W, Boya L, Lanfang Z, Ragland R. Modeling secondary accidents identified by traffic shock waves. Accident Analysis & Prevention. 2016;87:141-147. DOI: 10.1016/j.aap.2015.11.031.

Luo Y. Capturing gender-age thresholds disparities in built environment factors affecting injurious traffic crashes. Travel Behaviour and Society. 2023;30:21-37. DOI: 10.1016/j.tbs.2022.08.003.

Wang J, Xie W, Liu B, Ragland R. Identification of freeway secondary accidents with traffic shock wave detected by loop detectors. Safety Science. 2016;87:195-201. DOI: 10.1016/j.ssci.2016.04.015.

Pešić A. Youth perceptions and attitudes towards road safety in Serbia. Systems. 2022;10(5):191. DOI: 10.3390/systems10050191.




How to Cite

Pantelić, O., Pešić, D., Vujanić, M., Švab, K., & Trifunović, A. (2023). Application of the AHP Method for Comparative Analysis of Software Systems in Traffic from the Aspect of Traffic Safety. Promet - Traffic&Transportation, 35(4), 525–539.