Browse Topic: Communication protocols

Items (1,011)
This paper presents the development of a speed controller for e-bikes, designed as part of an energy-adaptive assistance system. The controller provides riders with appropriate support along planned routes, based on the available battery capacity. The control concept is intended for integration into existing commercial e-bikes without requiring extensive modifications to the drive system. Therefore, the rider remains part of the control loop, adjusting the support mode according to instructions from the controller. The speed controller is implemented as a rule-based state machine, enabling comprehensible design and parameterization. Since the rider must manually switch between support modes while riding, the control logic incorporates hysteresis and dead times to ensure stability, prevent oscillations, and avoid frequent mode switching. The user interface is a smartphone application that issues visual and audio instructions for switching support modes. An initial, system-independent version that relied on GPS-based speed measurement was found to be insufficiently accurate for the control task. Furthermore, it was found that detection of the pedaling state was essential for proper operation. To address these issues, a Bluetooth-based hardware adapter was developed to access relevant signals from the e-bike’s CAN bus communication system. These include pedal power, cadence and speed, which are made accessible through reverse engineering of the CAN bus. The proposed concept is evaluated in a chassis dynamometer study with 13 participants on two test profiles: a synthetic gradient profile for assessing control stability and a realistic elevation profile for dynamic evaluation. Additional measurements taken with one of the test riders at different speeds demonstrate the system’s reliability and its potential to improve the energy efficiency. The results show that, with approximately the same power brought in by the rider, only 27% more electrical energy is required to increase the average speed by 45%.
Rauch, YannickSimmann, GabrielSchneider, ManuelGoss, ChristianKriesten, Reiner
This SAE Information Report SAE J2836/6 establishes use cases for communication between plug-in electric vehicles and the EVSE for wireless energy transfer as specified in SAE J2954. It addresses the requirements for communications between the on-board charging system and the wireless EV supply equipment (WEVSE) in support of detection of the WEVSE, the charging process, and monitoring of the charging process. Since the communication to the charging infrastructure and the power grid for smart charging will also be communicated by the WEVSE to the EV over the wireless interface, these requirements are also covered. However, the processes and procedures are expected to be identical to those specified for V2G communications specified in SAE J2836/1. Where relevant, the specification notes interactions that may be required between the vehicle and vehicle operator, but does not formally specify them. Similarly, communications between the on-board charging sub-system and the on-board vehicle electronics is not formally specified in this document. This document will be published as a set of steps. The intent of step 1 was to record as much information on “what we think works” and publish. The intent of step 2 is to provide refinement and missing pieces to step 1, with a an eye to early testing. This version is step 2, with the aim of providing a communication protocol for home chargers.
Hybrid - EV Committee
This Surface Vehicle & Aerospace Recommended Practice offers best practices and a methodology by which IVHM functionality relating to components and subsystems should be integrated into vehicle or platform level applications. The intent of the document is to provide practitioners with a structured methodology for specifying, characterizing and exposing the inherent IVHM functionality of a component or subsystem using a common functional reference model, i.e., through the exchange of design-time data and the application of standard vehicle data communications interfaces. This document includes best practices and guidance related to the specification of the information that must be exchanged between the functional layers in the IVHM system or between lower-level components/subsystems and the higher-level control system to enable health monitoring and tracking of system degradation severity. The intent is to provide an IVHM system that can robustly report the degradation of a given component before it reaches the point where it goes outside its operational performance envelope by providing sufficient advance notice to deal with the issue. This document does not specify or address how each layer in the IVHM system produces or uses the data available for exchange.
HM-1 Integrated Vehicle Health Management Committee
SAE J1979-2 describes the communication between the vehicle’s OBD systems and test equipment required by OBD regulations. OBD regulations require passenger cars and light-, medium-, and heavy-duty trucks to support a minimum set of diagnostic information to external (off-board) “generic” test equipment.
Vehicle E E System Diagnostic Standards Committee
SAE J1978-1 specifies a complementary set of functions to be provided by an OBD-II scan tool. These functions provide complete, efficient, and safe access to all regulated OBD (on-board diagnostic) services on any vehicle which complies to SAE J1979. The content of this document is intended to satisfy the requirements of an OBD-II scan tool as required by current U.S. OBD regulations. This document specifies: A means of establishing communications between an OBD-equipped vehicle and an OBD-II scan tool. A set of diagnostic services to be provided by an OBD-II scan tool in order to exercise the services defined in SAE J1979. In addition, SAE J1978-1 covers first generation protocol functionality defined in SAE J1979 plus automatic protocol determination for all SAE J1979/J1979-2/J1979-3 application content. The presentation of the SAE J1978 document family, where SAE J1978-1 covers first generation protocol functionality defined in SAE J1979 and protocol determination for SAE J1979, SAE J1979-2, and SAE J1979-3, and SAE J1978-2 covers second generation protocol functionality defined in SAE J1979-2. The SAE J1978 document family does not preclude the inclusion of additional capabilities or functions in an OBD-II scan tool. However, it is the responsibility of the OBD-II scan tool designer to ensure that no such capability or function can adversely affect either an OBD-equipped vehicle, which may be connected to the OBD-II scan tool, or to the OBD-II scan tool itself.
Vehicle E E System Diagnostic Standards Committee
Automotive Original Equipment Manufacturers (OEMs) closely guard information about their products due to the significant investment in vehicle research and development. However, advancing automotive innovation often requires insights from existing systems to improve safety, efficiency, and performance. The Controller Area Network (CAN) bus remains the industry standard for communication between electronic control units (ECUs), yet CAN message specifications are typically proprietary and undocumented. This paper presents a case study involving the reverse engineering of CAN messages from a 2024 Toyota Grand Highlander powertrain. By capturing and analyzing communication between a diagnostics tester and the vehicle’s ECUs and replicating the communication, substituting A CANcase and software in place of a diagnostics tester, we were able to reverse engineer the vehicle’s CAN bus, demonstrating a practical methodology for decoding and interpreting CAN traffic without prior access to proprietary data. The approach highlights both general principles and OEM-specific variations in message structure and encoding. The goal of this work is to support researchers and engineers in developing their own reverse engineering workflows. It illustrates that while the foundational techniques are consistent, adapting to vehicle-specific implementations is essential. The paper aims to provide a replicable process and to encourage further exploration in the field of automotive CAN analysis.
Bolarinwa, EmmanuelPeters, Diane
Electric vehicles (EVs) rely extensively on sensor feedback for safe and efficient powertrain operation. However, this dependency introduces cyber-physical vulnerabilities, especially when sensor signals are maliciously manipulated. This paper presents a simulation-based investigation into sensor-level cyberattacks on a mid-sized EV powertrain model developed in MATLAB/Simulink. The study quantifies mechanical consequences and evaluates mitigation strategies to enhance system resilience. Four representative attack scenarios were simulated. Speed sensor spoofing led the controller to misinterpret vehicle velocity, causing a 41% overshoot beyond the 50 km/h setpoint. False data injection into torque/current sensors triggered an unintended torque surge of approximately 20%, resulting in inverter current saturation within 2 seconds. Battery temperature spoofing delayed thermal protection, allowing a deviation of 1.5 °C/min beyond safe operating limits. A hybrid attack combining frozen speed feedback with a forced 100% throttle input caused runaway acceleration and actuator saturation lasting over 10 seconds. These scenarios demonstrate how localized sensor attacks can propagate through control loops, destabilizing vehicle dynamics. To counter these threats, we implemented signal plausibility checks, observer-based anomaly detection, and fail-safe torque limiting. These measures collectively reduced overshoot by more than 50% in spoofing cases. Beyond simulation, we propose a multi-layered defense framework incorporating cross-sensor validation, statistical and machine learning-based anomaly detection, guided by ISO/SAE 21434 cybersecurity engineering principles, signal-level defenses, and conservative fallback controls. By linking cyber intrusions to tangible mechanical instabilities and validating countermeasures through simulation, this work offers actionable insights for engineers developing robust and secure EV powertrains. It underscores the necessity of integrating mgechanical and cybersecurity disciplines to ensure the safety and reliability of future electric mobility systems.
Tariq, UsamaSahandabadi, SaherehDianat, Ali
Cooperative Driving Automation (CDA) has emerged as an active research area in recent years, categorized into four classes of operations with varying levels of cooperation as defined in the SAE J3216 standard. Among these, Class C CDA, referred to as Agreement-Seeking Cooperation (ASC), has received limited attention in literature. Unlike Cooperative Adaptive Cruise Control (CACC), which typically engages when lead vehicles are identified as cooperative and disagree under manual override or safety-critical conditions, ASC requires agents to exchange messages interactively to reach consensus on a proposed plan and its implementation. This necessitates more sophisticated communication and control designs, which in turn influences customized ASC efficiency. Previous work has examined, through simulation, the impact of three key parameters on ASC system performance: CDA message transmission frequency, Packet Drop Ratio (PDR), and Cooperation Duration Length (CDL). In this paper, we extend that investigation by conducting Hardware-in-the-Loop (HIL) experiments in a scenario-based simulation environment, integrating the ASC controller with vehicle-to-vehicle (V2V) communication enabled by PC5-based Cellular Vehicle-to-Everything (C-V2X) radios. Using HIL test data, we derived a simple analytical model based on Pascal Distribution to predict the Cooperative Ratio (CR), which is a key index defined by cooperative time over the total scenario time. The model explores the fundamental mechanism of how transmission frequency, total trip time, instance CDA engagement probability and CDL collaboratively impact Cooperative Ratio. The validation of the model with experimental data reports the relative error is less than 5% for scenarios with CDA message transmission frequency higher than 5 HZ. Furthermore, because the model is independent of specific control logic assumptions, it provides a practical tool for guiding the design of ASC communication protocols and control strategies.
Zhan, LuDi Russo, MiriamDas, DebashisStutenberg, KevinMisra, PriyashJeong, JongryeolHyeon, Eunjeong
Distributed battery management systems (BMS) are critical for scaling electric vehicle packs to hundreds of cells, but reliable high-speed communication between modules remains a challenge. Daisy-chained SPI and CAN FD are widely deployed today, while Ethernet is being evaluated for next-generation systems that require higher bandwidth, synchronization, and diagnostics. This paper examines the signal integrity (SI) challenges facing distributed BMS communication, including skew, jitter, crosstalk, and electromagnetic interference (EMI) across PCB traces and wiring harnesses. HyperLynx and SPICE-based simulations are combined with experimental results on a 192-cell test platform to quantify the impact of layout constraints, impedance mismatches, and harness parasitic. Results show that poor SI design can reduce signal margins by more than 18 dB, leading to data corruption and diagnostic failures. Results show poor SI design can reduce signal margins by 18 dB, causing data errors. Measured BER is ≤1×10-12, jitter decreases up to 30%, and Ethernet latency stays below 120 ns under worst-case EMI. Additional testing confirmed SPI and Ethernet maintain stable communication across 192-cell BMS platform. Co-design strategies for PCB routing, termination, and shielding are proposed, achieving up to 30% reduction in jitter and error rates under worst-case EMI conditions. By addressing both current SPI-based systems and future Ethernet implementations, this paper provides practical guidelines for engineers developing distributed BMS architectures that meet ISO 26262 functional safety while enabling scalable and reliable next-generation EV platforms.
Abdul Karim, Abdul Salam
Electrification is rapidly entering all vehicle classes, including light- and heavy-duty trucks designed for heavy towing capabilities. Still, the quantitative impact of towing on battery-electric vehicle (BEV) energy use and range remains under-characterized. We conducted controlled towing tests with a Ford F-150 Lightning using two trailers of different sizes and varying payloads to isolate aerodynamic and mass effects and to span the full range of towable payloads within the vehicle’s rated capacity. The vehicle was instrumented at the CAN bus level, capturing motor power, torque, speed, and related internal signals from different control modules. On-road testing consisted of repeated back-and-forth passes on level, straight road segments at set speeds focusing on highway operation, where aerodynamic drag is stronger and real-world towing use cases occur. From these data, we extracted road load equations and dynamometer coefficients for each trailer combination, then reproduced equivalent conditions on a four-wheel drive chassis dynamometer across several standard cycles. Results were consistent across runs, showing a significant increase in the vehicle’s overall energy consumption and a corresponding range penalty. Additional impacts on vehicle systems due to towing, including thermal management of the motors and battery, were quantified. Dynamometer tests of varying characteristics (highway, urban, steady state speeds and accelerations) allow isolation of specific behaviors in functions like regenerative braking operation and torque-split strategy. Dynamometer results aligned with on-road measurements, enabling repeatable laboratory evaluation of towing scenarios. These findings provide a validated methodology and dataset to quantify towing impacts on BEVs, inform range prediction and route planning, support labeling and consumer guidance, and characterize sustained, high load real world operation of vehicle components.
Timermans Ladero, Inigo
Towing imposes substantial efficiency penalties on both battery-electric vehicles (BEVs) and internal combustion engine (ICE) vehicles, reducing range by 30-50%. This paper presents a proof-of-concept embedded control architecture for distributed trailer propulsion that actively regulates drawbar force to reduce towing loads. Unlike proprietary e-trailer systems requiring specialized hardware, the proposed implementation demonstrates feasibility using commercial off-the-shelf (COTS) components and open-source software. The distributed architecture employs dual Raspberry Pi 4B single-board computers communicating via ROS 2 at 20 Hz. The trailer-mounted controller executes a Simulink-generated control node coordinating load cell acquisition (HX711 ADC), motor CAN bus telemetry, and throttle commands to a 5 kW BLDC traction motor powered by a 5 kWh LiFePO4 battery pack. A vehicle-mounted controller logs OBD-II/CAN validation data. The control pipeline implements cascaded EWMA/Hampel digital filtering with intentional phase lag for hitch-force regulation. The system was validated through on-road testing with an ICE towing vehicle pulling a 1,000-lb trailer over standardized 2.1 km segments following SAE J1321 Type II procedures. Preliminary trials demonstrated stable control performance with drawbar force regulation with no oscillatory behavior. Fuel consumption measurements showed promising improvements (9.4% lower fuel consumption in assisted vs. baseline conditions), though limited sample size precludes definitive causal claims. The primary contribution is establishing technical feasibility of cost-effective COTS implementation (USD 5,000 hardware cost) for trailer propulsion control, providing a foundation for expanded validation studies and commercial deployment pathways.
Joshi, GauravAdelman, IanLiu, JunDonnaway, Ruthie
Off-road vehicles are typically powered by diesel engines, sized to cover the highest peak loads in their dutycycles. Such applications can be designed with downsized engines, using hybridization to supplement engine power with electrical power for short periods. However, many applications are low-volume and specialized, making it impractical to deploy heavy engineering resources to optimize each one. For this reason, manufacturers tend to produce maid-of-all-work vehicles to cover every situation. This paper demonstrates the benefits of custom hybridization for specialist applications, and addresses the lack of accessible software tools for evaluating such opportunities. Analysis is applied with a fast, low-cost, Concept-based software tool named “ePOP Concept”, suited to original equipment manufacturers (OEMs) who seek to provide custom low-volume vehicles. It allows many different powertrain architectures to be evaluated rapidly at the product planning stage, and can be quickly set up and used by non-specialists in simulation. Agricultural load cases are analyzed, showing the benefits of adding hybridization through electric motors and stored energy, supplementing engine power for demand peaks to enable engine downsizing. Use cases for four Fendt diesel tractors were taken from a dataset generated by Götz et al, at the agricultural facilities of the Technical University of Munich, which has been made publicly available by the authors to address the absence of standard load cycle data for the analysis of tractor electrification. The results show benefits for a customizable hybridization architecture to accommodate specific use cases, and the benefits of quick, accessible analysis methods for small engineering teams, to support early product decisions and what-if analyses.
De Salis, RupertFons, Daniel
SAE J1939-75 defines the set of data parameters (SPs) and messages (PGs) for information predominantly associated with monitoring and control generators and driven equipment in electric power generation and industrial applications. The data parameters (SPs) and messages (PGs) previously published within this document are published in SAE J1939DA. Applications using the SAE J1939-75 document must refer to SAE J1939DA for the SAE J1939 parameters and messages for monitoring and controlling the power units, e.g., engines and turbines, that power the generators and driven industrial equipment.
Truck and Bus Control and Communications Network Committee
This top-level document provides a general overview of the SAE J1939 network and describes the subordinate document structure. This document includes definitions of terms and abbreviations which are used among the various SAE J1939 subordinate documents.
Truck and Bus Control and Communications Network Committee
J1939 Enhanced DBCJ1939DBC_2026033/10/2026
The SAE J1939 Enhanced DBC file contains decoding rules for converting raw J1939 data to 'physical values' (Mph, %, etc.). This file lets you easily decode data from heavy duty vehicles (trucks, buses, tractors, etc.). This DBC file download includes: The SAE J1939 Enhanced DBC file with Includes 2,400+ Parameter Group Numbers (PGNs) and 16,000+ Suspect Parameter Numbers (SPNs), derived from the J1939 Digital Annex (DA) released in March 2026. One legal license (1 user, 1 PC) matching the DA license DECODE J1939: Convert J1939 data in wide range of software/API tools Combines the J1939DBC and J1939-73DBC files into a single resource REVIEW FIRST: Use our CAN ID converter to check if your PGNs are covered CROWD INPUT: Benefit from free corrections based on large user base SAVE HOURS: Avoid manually constructing the DBC file from scratch Improved Accuracy & Reliability A fully standardized DBC file ensures precise signal decoding, eliminating errors and ensuring reliable data interpretation. Interoperability Seamlessly compatible with many different software stacks, enabling frictionless adoption and significantly expanding market reach. Partnership with Vector Informatik GmbH Works seamlessly with Vector’s free software (CANdb++), used by over 90% of the industry, with free download link provided on SAEI’s J1939DBC file landing page. What is a DBC file? A DBC file is a standardized method for storing the "rules" on how to interpret raw CAN bus data. It contains details on what 'signals' (e.g. RPM, Vehicle Speed, …) are contained within which 'messages' (i.e. CAN IDs). In the J1939 standard, messages are referred to as Parameter Group Numbers (PGN) and signals as Suspect Parameter Numbers (SPN). Further, a DBC file includes names, descriptions, positions, and lengths of the signals - as well as how to offset & scale them.
Modern vehicles require sophisticated, secure communication systems to handle the growing complexity of automotive technology. As in-vehicle networks become more integrated with external wireless services, they face increasing cybersecurity vulnerabilities. This paper introduces a specialized Proxy based security architecture designed specifically for Internet Protocol (IP) based communication within vehicles. The framework utilizes proxy servers as security gatekeepers that mediate data exchanges between Electronic Control Units (ECUs) and outside networks. At its foundation, this architecture implements comprehensive traffic management capabilities including filtering, validation, and encryption to ensure only legitimate data traverses the vehicle's internal systems. By embedding proxies within the automotive middleware layer, the framework enables advanced protective measures such as intrusion detection systems, granular access controls, and protected over-the-air (OTA) update channels. This strategy enhances both data security and system isolation, creating protective boundaries between critical vehicle operations and potential external attacks. The architecture particularly excels in supporting Vehicle-to-Everything (V2X) connectivity, facilitating seamless information exchange between vehicles, roadside infrastructure, and pedestrians. This capability is essential for enhancing roadway safety, optimizing traffic flow, and supporting autonomous driving technologies. The system incorporates dedicated proxy modules for specialized protocols including Trivial File Transfer Protocol (TFTP), Diagnostic Over Internet Protocol (Doip), and Message Queuing Telemetry Transport (MQTT), each fulfilling specific functions in vehicle diagnostics, software updates, and telemetry data management. Performance evaluations will measure latency and throughput metrics to validate the architecture's efficiency and reliability. The framework's modular design aims to provide scalability and adaptability to accommodate both technological advancements and emerging security challenges. The proxy-based security framework presented offers a holistic and forward-looking approach to safeguarding in-vehicle networks. It provides automotive manufacturers with the tools to develop connected vehicles that combine intelligence and efficiency with robust protection against diverse cybersecurity threats.
M, ArvindPraneetha, Appana DurgaRemalli, Ravi Teja
The paper presents the design and implementation of an AI-enabled smart timer-based power control and energy monitoring solution for household appliances. The proposed system integrates real-time sensing of electrical device parameters with cloud artificial intelligence for predictive analytics and automatic control. Continuous measurement of voltage, current and power consumption of the connected appliances are performed for analysis of the usage patterns. The appliance operation is completely automated by choosing between the best option which is the user-defined schedule or the load shifted schedule recommended by AI. The AI recommendation depends on peak demand of the day and the current load requirement thereby aiding approximate smoothening of daily load curve and improving load factor. The data collected is transmitted to the cloud for real-time and historical data collection, for prediction of consumption patterns, anomaly detection, and clustering appliances according to their operational behavior. A machine learning model trained on an energy dataset enhances decision-making by predicting overload conditions and distributing the load throughout the day. A mobile interface provides live monitoring, cost estimation, scheduling, and control. The modular design allows the proposed solution to be scalable by adding an additional appliance. The experimental evaluation provided evidence of the system’s ability to predict an overload condition, and its capacity to shift loads to off-peak hours thereby providing energy savings of 20-30%, based on usage patterns. By integrating IoT monitoring, cloud analytics, and AI-enabled automation the proposed system overcomes the limitations of standard metering, and high-cost proprietary solutions. Overall, it offers a scalable, cost-effective, and intelligent approach to appliance-level energy management, fostering sustainable energy practices and reducing operating costs.
D, AnithaD, SuchitraJain, UtsavMaity, SouvikDinda, Atish
This study presents the design and implementation of an advanced IoT-enabled, cloud-integrated smart parking system, engineered to address the critical challenges of urban parking management and next-generation mobility. The proposed architecture utilizes a distributed network of ultrasonic and infrared occupancy sensors, each interfaced with a NodeMCU ESP8266 microcontroller, to enable precise, real-time monitoring of individual parking spaces. Sensor data is transmitted via secure MQTT protocol to a centralized cloud platform (AWS IoT Core), where it is aggregated, timestamped, and stored in a NoSQL database for scalable, low-latency access. A key innovation of this system is the integration of artificial intelligence (AI)-based space optimization algorithms, leveraging historical occupancy patterns and predictive analytics (using LSTM neural networks) to dynamically allocate parking spaces and forecast demand. The cloud platform exposes RESTful APIs, facilitating seamless interoperability with user-facing mobile and web applications. These interfaces provide end-users with real-time visualization of parking availability, intelligent navigation to optimal spaces, and digital payment integration, thereby minimizing search time and enhancing user convenience. From an administrative perspective, the system delivers comprehensive analytics dashboards, including heatmaps of space utilization, anomaly detection for unauthorized parking, and predictive maintenance alerts for sensor nodes. Field trials conducted across a multi-level parking facility demonstrated a 32% reduction in average vehicle search time and a 21% improvement in space utilization efficiency compared to conventional systems. The end-to-end solution adheres to robust cybersecurity standards (TLS 1.2 encryption, role-based access control) and is designed for modular scalability, supporting integration with smart city infrastructure and electric vehicle charging stations. This research establishes a scalable, intelligent framework for urban parking management, contributing significantly to reduced congestion, optimized resource allocation, and enhanced urban mobility.
Deepan Kumar, SadhasivamS, BalakrishnanDhayaneethi, SivajiBoobalan, SaravananAbdul Rahim, Mohamed ArshadS, ManikandanR, JamunaL, Rishi Kannan
As electric trucks become more central to modern logistics, the need for smarter, more adaptive route planning is growing rapidly. This paper presents a key navigation feature for analyzing and recalibrating such optimized routes in real time. Integrating map features into the navigation mode improves user experience by offering real-time navigation and dynamic route adjustments based on traffic updates, road closures, vehicle coordinates and deviation in expected energy consumption. This study compares the performance of Server sent events (SSE), web sockets, and Application programming interface (API) polling methodologies, focusing on metrics such as data transmission efficiency, latency, resource utilization, scalability, and reliability. Our results demonstrate the advantages and limitations of each method, providing insights into their suitability for real-time route optimization in electric truck logistics. The results highlight the potential of SSE in achieving efficient and timely data updates, contributing to more effective route planning and resource management. Additionally, we discuss how API Polling, Web sockets, and SSE each make sense in different scenarios when creating a navigation system (drive mode), considering factors such as the frequency of updates, network conditions, and system architecture. This research underscores the importance of choosing the right communication protocol and integrating advanced map features to enhance the performance and reliability of logistics systems.
Bhandari, MehulKaur, PrabhjotDadoo, VishalMahendrakar, ShrinidhiRamanaiah, Rachala
State Transport Units (STUs) are increasingly using electric buses (EVs) as a result of India's quick shift to sustainable mobility. Although there are many operational and environmental benefits to this development, like lower fuel prices, fewer greenhouse gas emissions, and quieter urban transportation, there are also serious cybersecurity dangers. The attack surface for potential cyber threats is expanded by the integration of connected technologies, such as cloud-based fleet management, real-time monitoring, and vehicle telematics. Although these systems make fleet operations smarter and more efficient, they are intrinsically susceptible to remote manipulation, data breaches, and unwanted access. This study looks on cybersecurity flaws unique to connected passenger electric vehicles (EVs) that run on India's public transit system. Electric vehicle supply equipment (EVSE), telematics control units (TCUs), over-the-air (OTA) update systems, and in-car networks (such as the Controller Area Network or CAN bus) are important areas of interest. Potential interruptions to vehicle functionality and passenger safety are examined in relation to common attack techniques such spoofing, data injection, denial-of-service (DoS), and remote code execution. In comparison to international standards like ISO/SAE 21434 and UNECE rules R155/R156, the report also assesses regulatory and compliance deficiencies in India. It lists the operational difficulties that Indian STUs encounter, including as antiquated infrastructure, a deficiency in cybersecurity knowledge, and a lack of established protocols. The paper suggests a plan for installing a Cybersecurity Management System (CSMS) in STU-operated EV fleets in order to reduce these threats. Strong incident response mechanisms, focused training initiatives, and the creation of cybersecurity standards tailored to India are among the recommendations. Implementing these measures will enhance the resilience of electric vehicle infrastructure against emerging cyber risks. Furthermore, collaboration between government agencies, industry stakeholders, and academic institutions is emphasized to ensure a comprehensive cybersecurity framework.
Mokhare, Devendra Ashok
The rapid expansion of electric vehicle (EV) charging infrastructure introduces complex cybersecurity challenges across hardware, software, network, and cloud layers. This review paper synthesizes existing research, standards, and documented incidents to identify critical vulnerabilities and propose layered mitigation strategies. We present a structured threat taxonomy based on the STRIDE model, enriched with real-world attack vectors and mapped to mitigation controls. Our analysis spans physical tampering, insecure firmware updates, protocol-level flaws in OCPP and ISO 15118, and cloud misconfigurations. While prior studies often focus on isolated domains, this work unifies fragmented insights into a cohesive framework. We highlight gaps in current literature, such as inconsistent adoption of secure protocols and limited validation of EVSE identity formats. By aligning threats with industry standards (SAE J3061, NIST CSF, IEC 62443) and scoring risks using CVSS v3.1, we offer a practical roadmap for manufacturers, operators, and policymakers. The paper concludes with recommendations for future research, including experimental validation, blockchain-based audit trails, and AI-driven anomaly detection.
Aggarwal, AkshitGupta, SaurabhSirohi, KapilArisetty, VenkateshChatterjee, Avik
The proliferation of wireless charging technology in electric vehicles (EVs) introduces novel cybersecurity challenges that require comprehensive threat analysis and resilient design strategies. This paper presents a proactive framework for assessing and mitigating cybersecurity risks in wireless charger Electronic Control Units (ECUs), addressing the unique vulnerabilities inherent in electromagnetic power transfer systems. Through systematic threat modeling, vulnerability assessment, and the development of defense-in-depth strategies, this research establishes design principles for creating robust wireless charging ecosystems resistant to cyber threats. The proposed framework integrates hardware security modules, encrypted communication protocols, and adaptive threat detection mechanisms to ensure operational integrity while maintaining charging efficiency. Experimental validation demonstrates the effectiveness of the proposed security measures in preventing unauthorized access, data manipulation, and service disruption attacks while preserving system performance.
Uthaman, SreekumarMulay, Abhijit BGadekar, Pundlik
The invention tackles the main drawback of traditional electric vehicle charge ports which use Vehicle Control Unit (VCU) communication intensively and tend to have separate actuators to fulfill the locking function and requirements. These existing systems do not only limit autonomous operation of the charging lid in ignition-off condition but they also add mechanical complexity and packaging space, as well. To overcome these limitations, this research work introduces a Smart Charge Port Housing (CPH), which combines a rotary actuator with an onboard microcontroller and single shaft self-locking device, which allows intelligent and autonomous control of the flaps without relying on vehicle wide control networks. The actuator can remember the last position that the charging lid was in so it can be operated even while the VCU is in the inactive state. The integrated self-locking functionality is achieved by using a specially designed hinge shaft that allows a certain free play for rotation of the shaft at a specific angular range allowing the lock-unlocking functionality to be performed without any extra actuators. Various use cases supported by the system are manual close, auto-close with anti-pinch detection and LIN-based communication (only during the ignition on and VCU active states), IP69 sealing, laser-welded joints. Improved waterproofing features allow the charging bowl to handle the unfavorable environmental conditions. This solution provides a considerable upgrade in user experience, security, and design integration of modern EV cars because of the blend of mechanical reliability and intelligence incorporated in the control architecture. The architecture is scalable, space-efficient and can be used on next generation of electric vehicle platforms requiring both a functional and aesthetic step change in the user accessible charging systems.
Mohunta, SanjayKhadake, Sagar
Electric vehicle (EV) transmissions play a vital role in powering EVs by channeling energy from the electric motor to the wheels. Recently, the focus has shifted to multi-speed transmissions in the EV sector due to their potential to improve efficiency and performance. By utilizing various gear ratios, these transmissions enable the motor to function within its most efficient range across different speeds. Most of these transmissions need electric control unit (ECU) with software for optimal functionality and smoother gear shifting. These controllers incorporate controller area network (CAN) communication protocol to operate along with other ECUs. Thus validation of these transmissions is a challenge as they are clutch less, motor has to be controlled for speed matching and have electro mechanical systems replacing conventional systems for operation. This paper proposes a methodology to validate multispeed EV transmissions on a test bench. The validation setup consists of electric motor at the input of a two speed EV transmission and inertia at the output of the transmission to simulate vehicle along with control unit flashed with vehicle level software. Scripts based on C-language and panels are developed which use CAN database (dbc) file of the vehicle to communicate between electric motor, transmission and vehicle control unit. Using the panels the user either controls the gear shift actuation manually or automate the gear shifting process as per vehicle operating conditions for evaluating the gear shift process. Using the mentioned methodology various vehicle scenarios can be simulated and validated on test bench at early stages, thus providing important feedback in development stage for software refinement for optimal operation of the motor and transmission actuator during gear shift process. The developed scripts can be modified to match for other vehicle configurations.
Thambala, PrashanthPatel, HiralSoor, Debasis
With the rapid adoption of electric vehicles (EVs), ensuring the reliability, safety, and cost-effectiveness of power electronic subsystems such as onboard chargers, DC-DC converters, and vehicle control units (VCUs) has become a critical engineering focus. These components require thorough validation using precise calibration and communication protocols. This paper presents the development and implementation of an optimized software stack for the Universal Measurement and Calibration Protocol (XCP), aimed at real-time validation of VCUs using next-generation communication methods such as CAN, CAN-FD, and Ethernet. The stack facilitates read/write access to the ECU’s internal memory in runtime, enabling efficient diagnostics, calibration, and parameter tuning without hardware modifications. It is designed to be modular, platform-independent, and compatible with microcontrollers across different EV platforms. By utilizing the ASAM-compliant protocol architecture, the proposed system significantly reduces dependency on expensive proprietary tools, offering a cost-effective alternative for the Indian EV industry.
Uthaman, Sreekumar
This paper presents a comprehensive testing framework and safety evaluation for Vehicle-to-Vehicle (V2V) charging systems, incorporating advanced theoretical modeling and experimental validation of a modern, integrated 3-in-1 combo unit (PDU, DCDC, OBC). The proliferation of electric vehicles has necessitated the development of resilient and flexible charging solutions, with V2V technology emerging as a critical decentralized infrastructure component. This study establishes a rigorous mathematical framework for power flow analysis, develops novel safety protocols based on IEC 61508 and ISO 26262 functional safety standards, and presents comprehensive experimental validation across 47 test scenarios. The framework encompasses five primary test categories: functional performance validation, power conversion efficiency optimization, electromagnetic compatibility (EMC) assessment, thermal management evaluation, and comprehensive fault-injection testing including Byzantine fault scenarios. Through systematic experimental validation using advanced power electronics simulation and hardware-in-the-loop (HIL) testing, we demonstrate 98.2% power conversion efficiency, sub-50ms fault detection response times, and compliance with automotive safety integrity level ASIL-D requirements. Our results establish the theoretical foundations and practical validation methodologies essential for next-generation V2V charging infrastructure deployment.
Uthaman, SreekumarMulay, Abhijit BNikam, Sandip B.
This comprehensive research presents an in-depth analysis of communication protocols essential for implementing fast charging systems in India's rapidly expanding electric two-wheeler and three-wheeler market. As India witnesses unprecedented growth in electric mobility, with two-wheelers representing over 95% of current EV sales, the establishment of standardized, secure, and efficient charging protocols becomes paramount for widespread adoption. This study examines the current landscape of AC charging methodologies, evaluates the technical and economic feasibility of DC fast charging implementation, and provides detailed comparative analysis of existing international standards including IS 17017-25, IS 17017-31, ChaoJi, and CCS 2.0. The research concludes with strategic recommendations for developing cyber-secure, cost-effective charging infrastructure specifically tailored to meet India's unique market requirements and operational constraints.
Uthaman, SreekumarMulay, Abhijit B
The automotive industry is undergoing a transformational shift with the addition of Virtual ECU in the development of software and validation. The Level 3 Virtual ECU concept will lead to the transformation in the SDLC process, as early detection of defects will have a significant impact on cost and effort reduction. This paper explains the application of a Level 3 virtual ECU which can enable to perform testing in initial period considering the Shift Left Strategy, which will significantly reduce development time. This paper demonstrates various development and validation strategies of virtual ECU and how it can impact project timeline.
Bhopi, AmeySengar, Bhan
Effective communication is the key for bringing harmony - be it the communication between humans and humans, or communication between machine and machine. Today’s car is a sophisticated gadget, equipped with the best of technologies running using millions of lines of codes of software. The effective use of these technologies involve communication between car to car and car to infrastructure using Dedicated Short-Range Communication (DSRC), C-V2X (Cellular Vehicle-to-Everything). It is pertinent that any communication using the internet needs to be digitally secure and that the systems are designed to mitigate the perceived threats. The methods used for ensuring cyber safety of automobiles need to be verified before the end product is put to use. Automotive Industry Standards AIS-189 and AIS-190 have been formulated to provide a harmonized verification framework. Both the vehicle manufacturer and the test agency need to equip themselves with necessary skills and tools to ensure compliance as per the laid down norms. With the ever-increasing use of software to run vehicles, the regulatory requirements would need to be constantly updated by reviewing the future threats involved and probable measures to mitigate them. The paper presents an overview of these important elements of cyber security regulations viz., applicable standards and approval procedure and means for a constant update of the two.
Nayak, PratikTandon, VikramBadusha, AkbarDesai, ManojSathianesan, Rejin
The exponential growth of connected and autonomous vehicles has significantly escalated cybersecurity threats, compelling automotive Original Equipment Manufacturers (OEMs) to adopt robust and structured Cybersecurity Incident Response (CSIR) capabilities. Current automotive cybersecurity regulations, such as AIS 189 in India and UNECE WP.29 globally, mandate precise frameworks for proactive threat detection, timely response, and comprehensive incident documentation. This research presents an innovative, comprehensive CSIR framework specifically tailored to integrate seamlessly into OEM cybersecurity management processes. Leveraging a combination of real-time monitoring systems, structured threat categorization methodologies, and integrated escalation and communication protocols, the proposed CSIR framework ensures efficient incident handling aligned with stringent regulatory compliance. The framework encompasses advanced methodologies including Vehicle Security Operations Center (VSOC) integration for continuous monitoring, standardized incident classification based on severity and potential impact, and well-defined communication channels with national Computer Emergency Response Teams (CERTs) and regulatory authorities. By integrating this framework, OEMs can significantly elevate their cybersecurity resilience, strengthen stakeholder confidence, and effectively meet evolving global cybersecurity regulatory demands.
Chaudhary lng, VikashDesai, ManojChatterjee, AvikChatterjee lng, Avik
Tire wear progression is a nonlinear and multi-factor degradation phenomenon that directly influences vehicle safety, handling stability, braking performance, rolling resistance, and fleet operational cost. Global accident investigations indicate that accelerated or undetected tread depletion contributes to nearly 30% of highway tire blowouts, highlighting the limitations of conventional wear indicators such as physical tread wear bars, mileage-based service intervals, and periodic manual inspections. These manual and threshold-based approaches fail to capture dynamic driving loads, compound ageing, pressure imbalance effects, or platform-specific wear behaviours, thereby preventing timely intervention in real-world conditions. This work presents an Indirect Tire Wear Health Monitoring System that employs an advanced Machine Learning + Transfer learning architecture to infer tread wear level and Remaining Useful Life (RUL) without relying on any tire-mounted sensors. The system ingests CAN bus telemetry signals (e.g., wheel torque, longitudinal/lateral accelerations, brake pressure, speed distribution, steering dynamics, thermal exposure) and converts them into high-resolution wear state estimations through a multi-stage feature learning pipeline. A transfer-learning layer enables model domain adaptation across tire brands, rubber compounds, rim sizes, inflation pressure ranges, and axle-loading variations — reducing retraining cost and ensuring cross-platform. The pipeline supports both cloud analytics workloads (fleet health dashboards, risk scoring, and advisory scheduling) and real-time embedded inference on in-vehicle microcontrollers for predictive safety intervention. On-road validation experiments demonstrate that the proposed model maintains high correlation to ground truth tread depth measurements, delivering per-tire wear estimation, non-linear RUL curves (in km and %), progressive wear trend modelling, and dynamic replacement advisory logic. The proposed architecture therefore establishes a scalable, sensor-less predictive maintenance framework suitable for OEM, Tier-1, and fleet-operations deployment.
Imteyaz, ShahmaIqbal, Shoaib
The rapid evolution of intelligent transportation systems has made drivers’ attentiveness and adherence to safety protocols more critical than ever. Traditional monitoring solutions often lack the adaptability to detect subtle behavioral changes in real time. This paper presents an advanced AI-powered Driver Monitoring System designed to continuously assess driver behavior, fatigue, distractions, and emotional state across various driving conditions. By providing real-time alerts and insights to vehicle owners, fleet operators, and safety personnel, the system significantly enhances road safety. The system integrates lightweight AI/ML algorithms, image processing techniques, perception models, and rule-based engines to deliver a comprehensive monitoring solution for multiple transportation modes, including automotive, rail, aerospace, and off-highway vehicles. Optimized for edge devices, the models ensure real-time processing with minimal computational overhead. Alerts are communicated through web and mobile platforms, supplemented by audio-visual cues for prompt user responses. Data from multi-camera setups, auditory sensors, and vehicle CAN bus inputs are processed by a real-time analytics engine that detects abnormal behaviors and safety violations, improving situational awareness and enabling timely interventions. For both individual drivers and fleet managers, the platform serves as an intelligence hub that boosts situational awareness, operational efficiency, and safety compliance. Drivers receive real-time feedback on their behavior, allowing them to make proactive adjustments and reduce risks. Fleet managers can leverage cloud-based connectivity to access predictive analytics, real-time monitoring, and detailed historical behavior data. This enables the identification of unsafe driving patterns, enforcement of safety protocols, and optimization of fleet performance. The system also simplifies regulatory reporting and auditing processes, ensuring compliance with safety standards. By continuously monitoring driver behavior, managers can foster a culture of safety and performance while improving overall fleet operations.
Chikhale, ShraddhaSing, SandipHivarkar, UmeshMardhekar, Amogh
The rapid evolution of in-vehicle electronic systems toward zonal based architectures introduces a new layer of complexity in automotive diagnostics. Traditional architectures, built on Controller Area Network (CAN) and Local Interconnect Network (LIN) protocols, operate on a uniform Real-Time Operating System (RTOS), enabling simplified and consistent diagnostic workflows across Electronic Control Units (ECUs). However, next-generation platforms must accommodate diverse communication protocols (e.g., CAN, LIN, DoIP, SOME/IP) and heterogeneous operating systems (e.g., RTOS, Linux, QNX), resulting in fragmented and inflexible diagnostic processes. This paper presents a Diagnostic controller that addresses these challenges by enabling unified, scalable, and adaptive diagnostic capabilities across modern vehicle platforms. The proposed system consolidates protocol handling at the application level, abstracts diagnostic complexities, and allows cross-platform communication through hypervisor-based services. Diagnostic configurations are decoupled from static software builds and delivered dynamically as configuration files, supporting real-time adaptability to software updates and Over-The-Air (OTA) changes. This architecture also facilitates seamless interoperability across operating systems and enables service-based diagnostics in line with the industry’s move toward software-defined vehicles. The result is a robust, future-ready diagnostic solution optimized for high software variability, platform heterogeneity, and increasing system complexity in modern automotive ecosystems.
Mukherjee, SoumyadeepRaman, Kothanda
The Vehicle software is moving towards software-centric architectures and hence software-defined vehicles. With this transition, there is a need to handle various challenges posed during development and validation. Some of the challenges include unavailability of hardware limiting the evaluation of various hardware options, board bring-up and hence leading to delays in software development targeted for the hardware, eventually leading to delayed validation cycles. To overcome the above challenges, we present in this whitepaper a virtual ECU (vECU) framework integrated with a CI/CD pipeline. A Virtual ECU (Electronic Control Unit) is a software-based emulation of a physical ECU. The adoption of virtual ECUs empowers development teams to commence software development prior to the availability of physical hardware. Multiple tools are available to demonstrate virtual ECUs, for example, QEMU, Synopsys, QNX Cabin, etc. vECU setup, when paired with a CI/CD pipeline, allows continuous integration, rapid iterations, and improved testing coverage. The integrated framework for virtual ECU and CI/CD thereby Significantly expedites the entire software lifecycle, enabling early-stage software development and validation. This research paper presents a vECU framework developed using QEMU as the virtualization tool to simulate NXP high-performance compute platforms. Instead of directly emulating hardware, custom Yocto-based images for GoldBox and i.MX8 were run on QEMU to replicate Body, Gateway, and Cluster functionalities. For CI/CD integration, Gerrit, Jenkins, and Azure DevOps were used to enable automated builds, reviews, and validation workflows. To establish communication, CAN and Ethernet protocols were utilized. Specifically, vSomeIP was used over Ethernet to enable service-oriented communication. Integration of this framework into the SDV workflow has shown significant improvements in early development and validation.
Singh, JyotsanaShaikh, ArshiyaMane, RahulBurangi, Piyush
The efficient tracking and management of goods within light commercial vehicles (LCVs) is crucial for various industries, particularly craftsmen and parcel delivery services. This article explores the integration of artificial intelligence (AI) and sensor technologies to enhance item tracking and optimize logistical operations in LCVs. Two technological approaches are examined: a Bluetooth-based tracking system and a camera-based parcel identification framework. The Bluetooth-based solution is designed primarily for craftsmen. It employs Bluetooth tags, vehicle connectivity gateways (VCGs), and a centralized server to provide real-time inventory monitoring and prevent tool misplacement. The camera-based system is aimed at parcel carriers. It utilizes AI-driven object detection and pose estimation to localize and identify parcels within the vehicle. Experimental evaluations show that Bluetooth tracking ensures reliability in tool management and the AI-based vision system holds promise for future scalability in parcel logistics. The findings underscore the need for adaptive tracking methodologies to improve efficiency, reduce operational costs, and support the digital transformation of commercial vehicle ecosystems.
Aslandere, TurgayLens, MathijsKirchhof, Jörg ChristianRobberechts, PieterGrein, MarcelMeert, WannesVandewalle, PatrickDavis, JesseRumpe, BernhardGoedemé, Toon
The acquisition of sensor data is essential for the operation and validation of the SAE vehicle. This system must be capable of converting analog data into digital form and communicating with the sensors. To this end, printed circuit boards (PCBs) were designed and manufactured, incorporating electromagnetic interference mitigation solutions through various analog filters, in order to ensure the integrity of the acquired signals. Data conversion and communication were implemented using a microprocessor from the STM32 family, with efficient transmission of the processed data carried out via the CAN protocol.
David, Mateus PadilhaAndrade, Fernanda Matsumoto LimaSousa Oliveira, IvanCarvalho, Luis Pedro FeioGuerreiro, Joel FilipeRibeiro, Rodrigo EustaquioSantos Neto, Pedro José
The advancement of electric mobility has driven the development of technologies aimed at enabling smart, secure, and interoperable electric vehicle (EV) charging. In this context, this paper presents a technical and market analysis of the Vehicle-to-Grid (V2G) and Plug & Charge (PnC) functionalities, focusing on their architectures, applicable technical standards, communication protocols, levels of commercial maturity, and emerging applications. The discussion begins with a review of the main national and international standards relevant to charging infrastructure, with emphasis on IEC 61851, IEC 62196, and ISO 15118 series, which address the technical requirements of equipment, connectors, and vehicle-to-grid communication. The operation of V2G is then discussed as a technology that enables bidirectional energy flow between the EV and the power grid, with a focus on topological configurations, pilot project applications, and regulatory and economic challenges that currently limit its large-scale adoption. In parallel, Plug & Charge solutions based on ISO 15118 are presented, which enable automatic authentication and billing directly through vehicle-charger communication, eliminating the need for user interaction via cards or apps. Market analysis identifies commercially available V2G- and PnC-compatible EV models, charging stations, backend systems, and roaming platforms such as Hubject and Digital Charging Solutions (DCS). The findings show that while V2G is still in a validation phase with limited deployments, Plug & Charge is already undergoing broader commercial adoption. This study provides technical and strategic insights to support national research and development initiatives, outlining the main technical requirements, standards, and regulatory challenges for the effective implementation of these technologies in the Brazilian electric mobility ecosystem.
Marques, Felipe L. R.Arioli, Vitor T.Bernardo, RodrigoNakandakare, Cleber A.Pizzini, Luiz R.Nicola, Eduardo V.
Commercial vehicle operation faces challenges from driver distraction associated with traditional Human-Machine Interfaces (HMIs) and inconsistent network connectivity, particularly in long-haul scenarios. This paper addresses these issues through the development and presentation of an embedded, offline AI-powered voice assistant. The system is designed to reduce driver distraction and enhance operational efficiency by enabling hands-free control of vehicle functions and access to critical information, irrespective of internet availability. The technical approach involves a three-tier architecture comprising an Android-based In-Vehicle Infotainment (IVI) unit for primary user interaction and voice processing, an Android mobile device acting as a communication bridge and processing hub, and a proprietary OBD-II dongle for CAN bus interfacing. Offline speech recognition is achieved using embedded wake word detection and speech-to-intent engines. A user-centered design methodology, informed by a field study with 25 professional truck drivers in Brazil, guided the prioritization of system functionalities. Key findings from this study highlighted strong driver interest in voice interaction for vehicle status monitoring (e.g., fluid levels, fault alerts) and control of essential systems (e.g., lighting, cabin environment). The implemented prototype successfully integrates these prioritized features, demonstrating the viability of offline voice control. Preliminary observations indicate robust wake word and intent recognition accuracy (≥97% based on vendor benchmarks) and acceptable system responsiveness (400-700 ms latency) under typical cabin noise conditions. This work establishes a foundation for safer, more intuitive HMIs in software-defined commercial vehicles, emphasizing the importance of offline capabilities for reliable operation.
De Oliveira Nelson, RafaelDe Almeida, Lucas GomesArantes Levenhagen, Ivan
SAE J1978-2 specifies a complementary set of functions to be provided by an OBD-II scan tool. These functions provide complete, efficient access to all regulated OBD services on any vehicle that is compliant with SAE J1979-2 and SAE J1979-3. The content of this document is intended to satisfy the requirements of an OBD-II scan tool as required by current U.S. OBD regulations. This document specifies: A means of establishing communications between an OBD-equipped vehicle and an OBD-II scan tool. A set of diagnostic services to be provided by an OBD-II scan tool in order to exercise the services defined in SAE J1979-2 and SAE J1979-3. In addition, SAE J1978-1 covers first generation protocol functionality defined in SAE J1979 plus automatic protocol determination for all SAE J1979/J1979-2/J1979-3 application content. The presentation of the SAE J1978 document family, where SAE J1978-2 covers second generation protocol functionality defined in SAE J1979-2 and SAE J1979-3, and SAE J1978-1 covers first generation protocol functionality defined in SAE J1979 and protocol determination for SAE J1979, SAE J1979-2, and SAE J1979-3. The SAE J1978 document family does not preclude the inclusion of additional capabilities or functions in an OBD-II scan tool. However, it is the responsibility of the OBD-II scan tool designer to ensure that no such capability or function can adversely affect either an OBD-equipped vehicle, which may be connected to the OBD-II scan tool, or an OBD-II scan tool itself.
Vehicle E E System Diagnostic Standards Committee
This article entails the design, manufacturing, application, testing, and analysis/discussion of a controller area network (CAN)–based vehicle safety system that detects vehicle failure such as brake failure, gear failure, tire blowouts, and other failures that can be monitored using digital or analogue sensors. The aim and objectives are to implement a real-life tire blowout on an Iveco S-Way Euro III and design a system that sends out CAN-based messages using J1939 protocol to the Iveco S-Way Euro III to downshift the gears, retarders, activate the limp mode braking system, activate the hooter, and activate the hazards. The system is split into five sections: (1) detection and activation, (2) gear control system, (3) retarder control system, (4) braking control system, and (5) hooter and hazard control system; while analyzing the: acceleration in the lateral, longitudinal, and vertical acceleration (g) vs. time (s), vehicle speed (km/h), rate of deflation (s), and the steering torque (Nm). The findings show that pressure (bar) vs. time (ms) indicates that the rate of deflation without the countermeasures took 1.053 s longer, wheel speed (mph) vs. time (s) indicates that the testing without countermeasures took 3.9800 s longer to reach 0 km/h, steering torque (Nm) vs. time (ms) indicates that the testing without countermeasures had a maximum value that was 0.1179 Nm higher than the testing with countermeasures, longitudinal acceleration (g) vs time (s) indicates that the testing without countermeasures has more sporadic values, lateral acceleration (g) vs time (s) indicated the testing with countermeasures has a 0.132 g higher lateral acceleration, and vertical acceleration (g) vs time (s) indicated that both tests (with and without countermeasures) have almost the same maximum vertical acceleration when the tire blowout occurred with the test without countermeasures having a 0.02 g higher vertical acceleration than the testing with countermeasures.
Rampath, AmaanStopforth, RiaanProctor-Parker, Craig
Minimum Requirements to Support Traffic Signal Priority and Preemption™ SET FileJ2945/BS_202511 (Current)11/20/2025
Included in this set are the SAE J2945/B Standard which specifies the over-the-air (OTA) interface between connected vehicles (CVs) and connected intersections (CIs) to support traffic signal priority and preemption (TSPP) applications. It specifies the use of updated revisions of the SAE J2735 Signal Request Message (SRM) and Signal Status Message (SSM) and the use of a Wireless Access in Vehicular Environments (WAVE) Service Advertisement (WSA) to advertise support for TSPP at a CI. Included are a concept of operations, requirements, design, and the Abstract Syntax Notation One (ASN.1) message format, data frame, and data element definitions. Also included is the Abstract Syntax Notation One (ASN.1) file precisely defines the structure of the data used to implement applications conformant to the SAE J2945/B Standard. Using this ASN.1 specification, a compiler tool can be used to produce encodings to enable applications to easily encode and decode the Signal Request Message (SRM) and Signal Status Message (SSM) messages, along with the Wireless Access in Vehicular Environments (WAVE) Service Advertisement (WSA) application data, defined in SAE J2945/B defined in SAE J2945/B. Included in the ASN.1 file is the complete SAE J2735 ASN.1 along with the updates to the ASN.1 for the SRM and SSM defined in SAE J2945/B.
Connected Transportation Interoperability Committee
This article suggests a validation methodology for autonomous driving. The goal is to validate front camera sensors in advanced driver-assist systems (ADAS) based on virtually generated scenarios. The outcome is the CARLA-based hardware-in-the-loop (HIL) simulation environment (CHASE). It allows the rapid prototyping and validation of the ADAS software. We tested this general approach on a specific experimental application/setup for a vehicle front camera sensor. The setup results were then proven to be comparable to real-world sensor performance. The CARLA simulation environment was used in tandem with a vehicle CAN bus interface. This introduced a significantly improved realism to user-defined test scenarios and their results. The approach benefits from almost unlimited variability of traffic scenarios and the cost-efficient generation of massive testing data.
Cardozo, Shawn MosesHlavác, Václav
This document describes the functional safety (FuSa) assurance data to be included when communicating safety-related A_PDUs using either the Multi-PG service or the FD Transport service within an SAE J1939-22 protocol stack. It specifies the following: The parameters that make up the FuSa assurance information The behavioral requirements when producing and consuming FuSa assurance information The technical requirements for different FuSa profiles intended to meet different application requirements The trailer formats for the different FuSa profiles that can be incorporated into Multi-PG and FD Transport services This document does not specify the assignment of a FuSa profile to any values of the TOS and TF fields when using the Multi-PG service, or to any value of the AD TYPE field when using the FD Transport service; instead, SAE J1939-22, or an OEM in the manufacturer-specific ranges of these fields, specifies the assignments for these fields.
Truck and Bus Control and Communications Network Committee
This document provides the technical requirements for implementing the SAE J1939 Functional Safety Communication Protocol in a manner determined suitable for meeting industry applicable functional safety standards.
Truck and Bus Control and Communications Network Committee
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