innovative development of intelligent transport systems based on biocybernetical vehicle control systems

Available online at www.sciencedirect.com ScienceDirect Transportation Research Procedia 20 (2017) 326 – 333 12th International Conference "Organization and Traffic Safety Management in large cities", SPbOTSIC-2016, 28-30 September 2016, St Petersburg, Russia Innovative Development of Intelligent Transport Systems Based on Biocybernetical Vehicle Control Systems Sergei Korjagin a, Pavel Klachek b* Institute of Transport and Technical Services, Baltic Federal University of Immanuel Kant, 14A A Nevskogo Str., Kaliningrad, 236038, Russia Abstract In recent years rapid development of unmanned vehicles enables to set a task of creating prospective intelligent transportation systems (ITS) based on unconventional, hybrid approaches enabling to combine macro traffic control (T) at road and transport conditions with fine adjustment at the micro-level of physiological and intellectual actions and decisions taken by the driver The work presents grounds for creating a biocybernetical management system as an innovative development of unmanned cars to ensure traffic safety It examines a uniquely designed architecture of the biocybernetical management system together with hardware and software architecture and the structure of the unmanned car system based on it © Published by by Elsevier B.V.B.V This is an open access article under the CC BY-NC-ND license © 2017 2016The TheAuthors Authors Published Elsevier (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: intelligent transportation system; traffic safety; intelligent transport security system; biocybernetical management paradigm; unmanned vehicle Introduction The fundamental document defining development priorities of the transport complex, main objectives, tasks of its development and ways of their achievement is “Transport Strategy of the Russian Federation for the Period until 2030” In the Transport Strategy revision special attention is paid to introduction of modern systems, technologies and management methods The main task for the Russian Federation transport complex is application of modern * Corresponding author Tel.: +0-000-000-0000 ; fax: +0-000-000-0000 E-mail address: SKoryagin@kantiana.rua, pklachek@mail.rub* 2352-1465 © 2017 The Authors 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.2017.01.038 Sergei Korjagin and Pavel Klachek / Transportation Research Procedia 20 (2017) 326 – 333 327 intelligent transportation systems uniting a complex of modern and innovative technologies of modeling, real time management as well as communication technologies Modern ITS enable to exercise traffic management effectively by means of control and optimization of road and transport conditions preventing in such a way a great number of critical (conflict situations) and road traffic accidents (RTA) related to them On the other hand, as the extensive investigations of recent years showed, the vast majority of road traffic accidents (50–70%) happen not as a result of critical situations but because of wrong actions of the driver, which means such factors as reaction time, correctness of the decisions taken by the driver and driving skills are the basis for the majority of the reasons for RTA One of the most important manifestations of psychophysiological qualities of drivers in terms of traffic safety is reaction time and correctness of the taken decisions The information comes to the driver at a speed of 109–1011 bits per second At the same time the driver can apprehend and process only 16 bits per second The work [Klachek and Korjagin (2015)] presents statistics of mistakes made by the driver in various situations of driving a vehicle Classification of RTA by functions: the driver doesn’t apprehend the situation on the road — 49%; wrong assessment of the situation by the driver and taking the wrong decision — 41%; other mistakes — 10% Classification by factors: Direct mistakes: attention distraction — 36%; danger underestimation — 30%; timidity in behavioral patterns and dangerous habits — 25%; faulty forecast of behavior of other road users — 18%; wrong assessment of the conditions— 12%; underestimation of the own faulty behavior — 11%; conscious illegal own behavior — 8% Indirect mistakes: mistakes while forecasting the traffic conditions — 36%; hurry — 35%; mood — 17%; insufficient knowledge of skills of vehicle driving — 16%; temporary deterioration in the functional state because of psychological conditions — 16%; inaction — 5; unsatisfactory technical condition of the vehicle — 4% So, a large amount of information or its quick changes often prevent apprehending and processing it promptly and exactly, and consequently, to elaborate a correct solution The driver must carry out a large number of actions for driving, the part of which turns out to be faulty due lack of time for information processing and insufficient experience in driving In recent years rapid development of unmanned vehicles, Cooperative-Intelligent Transportation Systems technologies enables to set a task of creating prospective ITS based on unconventional, hybrid approaches enabling to combine macro traffic control at road and transport conditions with fine adjustment at the micro-level of physiological and intellectual actions and decisions taken by the driver Main text 2.1 Intelligent Transport Security System The intelligent transportation system is intended for effective management of traffic streams, increase in traffic capacity of the street and road network, traffic jams prevention, reduction of delays in traffic flow, improvement of traffic safety, informing the road users about the emerging road and transport situation and options of the optimal traffic route, ensuring uninterrupted flow of the land urban passenger transport [Klachek and Korjagin (2015)] Ensuring traffic safety remains the most important direction of ITS functional development The studies of the Russian and European experience [Klachek and Korjagin (2015)].] show that application of ITS enables to reduce RTA level by 30 percent Undoubtedly, despite so good results further development of ITS in this direction is required, also on the basis of interdisciplinary approaches The work [Klachek et al (2015), Klachek and Korjagin (2015)].] presents a biocybernetical traffic management paradigm based on ITS This paradigm is intended to combine macro traffic control at road and transport conditions with fine adjustment at the micro-level of physiological and intellectual actions and decisions taken by the driver (Fig 1) An innovative component of ITS development based on biocybernetical management paradigm [Klachek et al (2015), Klachek and Korjagin (2015)].] is application of the intelligent transport security system (ITSS) in its structure (Fig 2) 328 Sergei Korjagin and Pavel Klachek / Transportation Research Procedia 20 (2017) 326 – 333 Fig Innovative ITS development based on the intelligent transport security system Fig Highly intelligent environment-system ITSS Sergei Korjagin and Pavel Klachek / Transportation Research Procedia 20 (2017) 326 – 333 The intelligent transport security system [Klachek and Korjagin (2015)] being harmonious development of the modern Cooperative-Intelligent Transportation Systems, unmanned cars, intelligent transport infrastructures and vehicles biocybernetical management systems presents highly intelligent environment-system of traffic control enabling: x to make decisions on the road quickly, taking into account fairly large number of quickly changing conditions; x to take into account the experience of reaction to unforeseen situations on the road, for example, sudden appearance of a child or a bicyclist on the carriageway; x to carry out highly intelligent vehicle driving in various modes (autonomous, manual, biocybernetical and so on); x to implement a high level of reactions automation and effective management under conditions of daily traffic; x to carry out anticipatory actions when autopiloting to optimize traffic stream, improve comfort and road safety and so on 2.2 Fundamentals of Biocybernetical Management The central task of biocybernetical management paradigm [Klachek, (2015), Klachek, Kolesnikov et al (2011), Klachek and Korjagin (2008), Klachek and Korjagin (2011), Klachek and Korjagin (2015)] consists in coordinating the biological management chain consisting (generally manual or foot control) of the following links: eye → nervous canal → motor cortical center → nervous canal → muscle → extremity → executive element → object; with the cybernetical one consisting of the following links: sensor system → CAN system → central processing unit (artificial intelligence system) → biocybernetical management system → executive element → object Fig presents the architecture of the biocybernetical management system [Klachek et al (2015), Klachek, Kolesnikov aet al (2011), Klachek and Korjagin (2008), Klachek and Korjagin (2011), Klachek and Korjagin (2015), Kraynov et al (2011)] 329 330 Sergei Korjagin and Pavel Klachek / Transportation Research Procedia 20 (2017) 326 – 333 Fig Architecture of the biocybernetical management system Fig presents unique hardware and software architecture and structure of the unmanned car system based on biocybernetical management paradigm [Kraynov et al (2011)] Sergei Korjagin and Pavel Klachek / Transportation Research Procedia 20 (2017) 326 – 333 Fig Hardware and software architecture of the unmanned car based on biocybernetical management system Using a number of innovative, author’s approaches, methods and technologies such as: advanced “Bicycle” car model; search of optimal ways on the basis of the latest achievements in the field of Dubins curves; advanced RRT (Rapidly Exploring Random Tree) method for modes with unstable dynamics; modeling on the basis of prediction; technologies for creating hybrid, adaptive intelligent systems [Klachek et al (2015), Klachek, Kolesnikov et al (2011), Klachek and Korjagin (2008), Klachek and Korjagin (2011), Klachek and Korjagin (2015), Belikova et al (2013), Belikova et al (2014), Pyatikop et al (2013), Klachek et al (2011), Kraynov et al (2011)]; general-purpose power controllers (GPC) of new generation [Klachek et al (2015), Klachek, Kolesnikov et al (2011), Klachek and 331 332 Sergei Korjagin and Pavel Klachek / Transportation Research Procedia 20 (2017) 326 – 333 Korjagin (2015)]; as well as the latest achievements in the field of bionics, biometric systems, electrostimulation and so on — the proposed hardware and software platform enables to make decisions on the road quickly, taking into account fairly large number of quickly changing conditions, to take into account the experience of reaction to unforeseen situations on the road, for example, sudden appearance of a child or a bicyclist on the carriageway, to carry out highly intelligent vehicle driving in various modes (autonomous, manual, biocybernetical and so on), to implement a high level of reactions automation and effective management under conditions of daily traffic, to carry out anticipatory actions when autopiloting to optimize traffic stream, improve comfort and road safety and so on Conclusion In conclusion it should be mentioned that the innovative approach proposed in this article is capable of transforming the existing transportation system radically having turned it into a highly intelligent environment It will not only bring mortality and injury rate on roads to nothing but will also increase social mobility, improve environmental situation; it will also give impulse to development of new services in different fields Moreover, a new type of cars constructed on the basis of the proposed biocybernetical management paradigm can bury a traditional concept of the car (Fig 5) and open new unprecedented opportunities and directions Fig Concept of the car of the future of Nissan Company, the car is created of “organic synthetic materials” created of the fast-growing genetically modified ivy being processed by nanorobots, with mental management system based on the distributed artificial intelligence Moreover, the proposed approach and application solutions can become harmonious ITS development not only in the field of ensuring traffic safety but also become a basis for development of the unified environment for solution of the problems of transport infrastructure management ensuring essential improvement of characteristics of the traffic management in the urbanized territory Application of such systems will enable to raise the traffic management level: to improve characteristics of the street and road network, to improve location of the traffic management facilities, to optimize the process of traffic control on all traffic phases reducing transport delays, improving traffic safety References Belikova, A O., Klachek, P M., Korjagin, S I et al (2013) Tool environment for creation of intelligent centers of strategic modeling and “AITC” transport infrastructures management Certificate of state registration of software (Russian Federation) No 2013660959; application No 2013618962, as of October 08, 2013; state registration date in the software register: November 25, 2013 (in Russian) Belikova, A O., Minkova, E S., Korjagin, S I., Klachek, P M (2014) Bases of mathematical modeling of transport processes by the method of rank analysis and multivariable quasi-real data cubes [Osnovy matematicheskogo modelirovanija transportnyh processov metodom rangovogo analiza i mnogomernyh kvazireal'nyh kubov dannyh] Transport and Service collection of research papers, issue Functioning of stable urban transportation systems Kaliningrad: Publishing house of the Baltic Federal University of Immanuel Kant, pp 31–45 (in Russian) Klachek, P M., Korjagin, S I (2008) Systems of information processing and motor transport control [Sistemy obrabotki informacii i upravlenija na avtomobil'nom transporte] Kaliningrad: Publishing house of the Russian State University of Immanuel Kant (in Russian) Sergei Korjagin and Pavel Klachek / Transportation Research Procedia 20 (2017) 326 – 333 Klachek, P M., Korjagin, S I (2011) Mathematical bases of artificial intelligence [Matematicheskie osnovy iskusstvennogo intellekta] Kaliningrad: Publishing house of the Federal State Educational Institution of Higher Professional Education “Kaliningrad State Technical University” (in Russian) Klachek, P M., Korjagin, S I (2015) Applied calculation methods, models and algorithms used during traffic arrangement and management [Prikladnye raschetnye metody, modeli i algoritmy, primenjaemye pri organizacii i upravlenii dorozhnym dvizheniem] Monograph, 2nd edition, revised and enlarged Kaliningrad: Publishing house of the Baltic Federal University of Immanuel Kant (in Russian) Klachek, P M., Korjagin, S I., Kolesnikov, A V., Minkova, E S (2011) Hybrid adaptive intelligent systems Part 1: Theory and development technology [Gibridnye adaptivnye intellektual'nye sistemy Chast' 1: Teorija i tehnologija razrabotki] Kaliningrad: Publishing house of the Baltic Federal University of Immanuel Kant (in Russian) Klachek, P M., Korjagin, S I., Lizorkina, O A (2015) Intelligent system engineering [Intellektual'naja sistemotehnika] Kaliningrad: Publishing house of the Baltic Federal University of Immanuel Kant (in Russian) Klachek, P M., Korjagin, S I., Minkova, E S (2011) Technological platform as a tool of the regional innovative development of the economy of Russia [Tehnologicheskaja platforma kak instrument regional'nogo innovacionnogo razvitija jekonomiki Rossii] Saint Petersburg State Polytechnic University Journal, series “Economics, (4): 160–170 (in Russian) Kraynov, P N., Korjagin, S I., Klachek, P M (2011) Traffic arrangement and management based on interaction between cars [Organizacija i upravlenie dorozhnym dvizheniem na osnove mezh avtomobil'nogo vzaimodejstvija] “Technical and technological problems of service” [Tehniko-tehnologicheskie problemy servisa] Scientific and technical journal of the Saint Petersburg State University of Service and Economics, 1(16): 95–101 (in Russian) Pyatikop, A D., Klachek, P M., Korjagin, S I (2013) Tool environment for creation of intelligent production systems at the enterprises of “AIS-SC” car service Certificate of state registration of software (Russian Federation) No 2013617394; application No 2013613959, May 13, 2013; state registration date in the software register: August 13, 2013 (in Russian) 333 ... recent years rapid development of unmanned vehicles, Cooperative -Intelligent Transportation Systems technologies enables to set a task of creating prospective ITS based on unconventional, hybrid approaches... statistics of mistakes made by the driver in various situations of driving a vehicle Classification of RTA by functions: the driver doesn’t apprehend the situation on the road — 49%; wrong assessment of. .. majority of the reasons for RTA One of the most important manifestations of psychophysiological qualities of drivers in terms of traffic safety is reaction time and correctness of the taken decisions