Abstract
In the modern world, it is quintessential to enhance the vehicle safety, as defined by automotive industry consortiums. Multiple sensors or sensor-networks are deployed to create Intelligent Transportation Systems (ITS), which comes with advanced technologies to assist the driver’s decision making. These systems aid by providing cognitive information collected by the Electronic Control Unit (ECU) from the sensor-network to the drivers by means of alerting, beeping, and warning or by taking control of the system itself, with very minimal warning time (generally in msec or µsec). ITS help in maintaining the minimum safe distance & speed, assists the driver to change lanes with necessary information on the traffic scenario in adjacent lanes. In coming days/times ahead, the automotive industry is focused towards achieving fully autonomous vehicles (Level-5). For autonomous vehicles to become a reality, the ITS will play a key role, as the major milestones would be to reach high-speed connectivity between the interconnected systems and data processing/transfer between them also becoming more stimulating. With systems becoming complicated in design and implementation, Systems engineering (SE) today can manage and help industries to deploy their ideations, due to the consistent evolution of its methodologies and engineering modelling techniques. This paper focuses on the need of Model-Based Systems Engineering (MBSE) standard practices, integration of modelling and simulations along with other digital enterprise functions to manage the ever growing and evolving systems, and how alignment with it would help automotive Tier-1 Component Suppliers and Original Equipment Manufacturers (OEMs) to manage the mobility needs for the future. The content highlights the essence of utilizing MBSE along with SE practices to minimize project lead time overruns. It outlines the generic information of ITS and a note on ever growing complexity of systems. Additionally, this paper will also touch upon the SE Vision 2025 and key take-aways for the automotive industry.
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Abbreviations
- ADAS:
-
Advanced Driver Assistance Systems
- ASPICE :
-
Automotive Software Process Improvement and Capability dEtermination
- CAN:
-
Controller Area Network
- CM:
-
Configuration Management
- PDM:
-
Product Data Management
- ECU:
-
Electronic Control Unit
- IPO:
-
Input Process Output
- ISO:
-
International Organization for Standardization
- ITS:
-
Intelligent Transportation Systems
- MBSE:
-
Model-Based Systems Engineering
- OEM:
-
Original equipment Manufacturer
- RF:
-
Radio Frequency
- SE:
-
Systems Engineering
- SOI:
-
System of Interest
- SoS:
-
System of Systems
- SysML :
-
Systems Modelling Language
- UML :
-
Unified Modelling Language
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Deshpande, H., Srikumar, V. (2023). Applicability of Systems Engineering for Intelligent Transportation Systems: A Roadmap for Model-Based Approach to Manage Future Mobility Needs. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2022. Lecture Notes in Networks and Systems, vol 544. Springer, Cham. https://doi.org/10.1007/978-3-031-16075-2_41
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