Browse Topic: Automated vehicles

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Applying Real World Traffic Data on Machine Learning Methods for Graph Based Cooperation Strategies of Automated Vehicles2025-01-0286To be published on 07/02/2025
With the increasing distribution of smart mobility systems, automated & connected vehicles are more and more interacting with each other and with smart infrastructure using V2X-communication. Hereby, the vehicles' position, driving dynamics data, or driving intention are exchanged. Previous research has explored graph-based cooperation strategies for automated vehicles in mixed traffic environments based on current V2X-communication standards. Thereby, the focus is set on cooperation optimization and maneuver negotiation. These strategies can be implemented through both centralized and decentralized computational approaches and are conflict-free by design. To enhance these previously established cooperation models, real-world traffic data is used to derive vehicle trajectories, providing a more accurate representation of actual traffic scenarios in order to enhance the practical application of the described methodology. Additionally, machine learning algorithms are employed to train
Flormann, Maximilian, Meyer, Felix, Henze, Roman
Technical Paper
Data-Driven Analysis of Vehicle Lateral Control in the Country Road Domain2025-01-0268To be published on 07/02/2025
The optimization and further development of automated driving functions offer significant potential for reducing the driver's workload and increasing road safety. Among these functions, vehicle lateral control plays a critical role, especially with regard to its acceptance by end customers. Significant development efforts are required to ensure the effectiveness and reliability of this aspect in real-world conditions. This work focuses on analyzing vehicle lateral control using extensive measurement data collected from a dedicated vehicle fleet at the Institute of Automotive Engineering at the Technical University of Braunschweig. Equipped with state-of-the-art measurement technology, the fleet has driven several hundred thousand kilometers, allowing for the collection of detailed information on vehicle trajectories under various driving conditions. These measurements have been classified into different driving environment domains - namely city, country road, and highway - with
Iatropoulos, Jannes, Panzer, Anna, Arntz, Martin, Prueggler, Adrian, Henze, Roman
Technical Paper
A Modular Framework for Lateral Movement Modeling2025-01-0269To be published on 07/02/2025
The lateral movement of vehicles within their lane determines occurring occlusions, and thus decides on the range of visions of vehicle sensors used by automated driving functions and the objects detected by down-stream algorithms. As simulations play an integral role in the validation of automated driving functions, their ability to realistically model the lateral movement is crucial. However, currently applied methods such as microscopic traffic simulations and the scenario-based approach making use of maneuver-based scenario descriptions simplify or neglect the lateral movement of vehicles. For that reason, a two-level stochastic model has been introduced in earlier work. It consists of a Markov model for the systematic coarse movement and a noise model for the residual fine movement. In follow-up publications, several advancements for both model components have been presented. These follow a modular structure, thus, can be flexibly combined. This paper for the first time gives an
Neis, Nicole, Beyerer, Jürgen
Technical Paper
Conception and Experience of Non-driving Related Activities in Semi-autonomous Vehicles2025-01-0260To be published on 07/02/2025
While semi-autonomous driving (SAE level 3 & 4) is already partially a reality, the driver still needs to take over driving upon notice. Hence, the cockpit cannot be designed freely to accommodate spaces for non-driving related activities. In the following Use Case, a mobile workplace is created by integrating a translucent acrylic glass pane into the cockpit and introducing joystick steering of the car. By using the technology Virtual Desktop 1, which is a software layer, any desktop application can be represented freely transformable on arbitrary physical and virtual surfaces. Thus, a complete Windows environment can be distributed across all curved and flat surfaces of an interior. The concept is further enhanced by a voice-driven generative AI which helps to summarize documents. A physical and a virtual demonstrator are created to experience and assess the mobile workspace, the well-being of the driver, influences, and psychological aspects. The physical demonstrator is a 1:1
Beutenmüller, Frank, Reining, Nine, Rosenstiel, Reto, Schmidt, Maximilian, Layer, Selina, Bues, Matthias, Mendonca, Daisy
Technical Paper
A Systematic Literature Review on Safety of the Intended Functionality for Automated Driving Systems2025-01-5030To be published on 04/28/2025
In the automobile industry, ensuring the safety of automated vehicles equipped with the automated driving system (ADS) is becoming a significant focus due to the increasing development and deployment of automated driving. Automated driving depends on sensing both the external and internal environments of a vehicle, utilizing perception sensors and algorithms, and electrical/electronic (E/E) systems for situational awareness and response. ISO 21448 is the standard for Safety of the Intended Functionality (SOTIF) that aims to ensure that the ADS operate safely within their intended functionality. SOTIF focuses on preventing or mitigating potential hazards that may arise from the limitations or failures of the ADS, including hazards due to insufficiencies of specification, or performance insufficiencies, as well as foreseeable misuse of the intended functionality. However, the challenge lies in ensuring the safety of vehicles despite the limited availability of extensive and systematic
Patel, Milin, Jung, Rolf, Khatun, Marzana
Technical Paper
Adapting the Technology Readiness Level (TRL) Framework to Automated Vehicle Development2025-01-867104/01/2025
Abstract The technological advancements in the automotive industry have seen a significant leap with the introduction of automated driving system (ADS)-equipped Vehicles (AVs), with potential for enhanced safety, efficiency, and mobility. As the development of an AV transitions from the stages of conceptual design to deployment, assessing the maturity of the technology through a structured framework is crucial. This paper proposes the adaptation of the Technology Readiness Level (TRL) framework originally developed by NASA (and adopted widely in a variety of industries) to the AV industry to provide a consistent, understandable, and transparent method to describe an AV product’s stage of development. The TRL framework is mated to the existing safety case framework (SCF) developed in the Automated Vehicle – Test and Evaluation Process (AV-TEP) Mission, a collaboration between Science Foundation Arizona and Arizona State University. The claim that the AV is ready to transition from one
Swaminathan, Sunder, Wishart, Jeffrey, Zhao, Junfeng, Russo, Brendan, Rahimi, Shujauddin
Technical Paper
Tube-MPC Based Path Tracking for I Vehicle Considering Data-Driven Stable Region and External Disturbances2025-01-826204/01/2025
Path tracking is a key function of intelligent vehicles, which is the basis for the development and realization of advanced autonomous driving. However, the imprecision of the control model and external disturbances such as wind and sudden road conditions will affect the path tracking effect and even lead to accidents. This paper proposes an intelligent vehicle path tracking strategy based on Tube-MPC and data-driven stable region to enhance vehicle stability and path tracking performance in the presence of external interference. Using BP-NN combined with the state-of-the-art energy valley optimization algorithm, the five eigenvalues of the stable region of the vehicle β−β̇ phase plane are obtained, which are used as constraints for the Tube-MPC controller and converted into quadratic forms for easy calculation. In the calculation of Tube invariant sets, reachable sets are used instead of robust positive invariant sets to reduce the calculation. Simulation results demonstrates that the
Zhang, Haosen, Li, Yihang, Wu, Guangqiang
Technical Paper
The Model Predictive Control of Dual-Chamber Active Air Suspension Based on Road Preview2025-01-878904/01/2025
Adverse weather conditions such as rain and snow, as well as heavy load transportation, can cause varying degrees of damage to road surfaces, and untimely road maintenance often results in potholes. Perception sensors equipped on intelligent vehicles can identify road surface conditions in advance, allowing each wheel’s suspension to actively adjust based on the road information. This paper presents an active suspension control strategy based on road preview information, utilizing a newly designed dual-chamber active air suspension system. It addresses the issue of point cloud stratification caused by vehicle body vibrations in onboard LiDAR data. The point cloud is processed through segmentation, filtering, and registration to extract real-time road roughness information, which serves as preview information for the suspension control system. The MPC algorithm is applied to actively adjust the nonlinear stiffness and damping of the suspension’s dual-chamber air springs, enhancing
Dong, Fuxin, Shen, Yanhua, Wang, Kaidi, Liu, Zuyang, Qian, Shuo
Technical Paper
Integrated Multimodal System for Real-Time Driver Fatigue Detection and Cognitive Load Assessment2025-01-807604/01/2025
As human drivers' roles diminish with higher levels of driving automation (SAE L2-L4), understanding driver engagement and fatigue is crucial for improving safety. We developed an integrated hardware and software system to analyze driver interaction with automated vehicles, with a particular focus on cognitive load and fatigue assessment. The system includes three submodules; namely the Driver Behavior Measurement (DBM), Vehicle Dynamics Measurement (VDM), and the Driver Physiological Measurement (DPM). The DBM module uses electro-optical (EO) and infrared (IR) camera to track a number of facial features such as eye aspect ratio (EAR), mouth aspect ratio (MAR), pupil circularity (PUC), and mouth to eye aspect ratio (MOE). Although determining these metrics from images of the driver’s face in conditions such as low light or with sunglasses is challenging, the paper showed that fusion of EO and IR image analysis produces robust performance. The VDM module utilizes an Inertial Measurement
Jirjees, Abdullah, Rahman, Taufiq, Farhani, Ghazal, Singh, Daniel, Charlebois, Dominique
Technical Paper
On-Road Investigation of Energy Saving Opportunity for Autonomous Light-Duty Vehicles through Automated Vehicle-Following in Safe Distance Scenarios2025-01-802904/01/2025
Reducing aerodynamic drag through Vehicle-Following is one of the energy reduction methods for connected and automated vehicles with advanced perception systems. This paper presents the results of an investigation aimed at assessing energy reduction in light-duty vehicles through on-road tests of reducing the aerodynamic drag by Vehicle-Following. This study provides insights into the effects of lateral positioning in addition to intervehicle distance and vehicle speed, and the profile of the lead vehicle. A series of tests were conducted to analyze the impact of these factors, conducted under realistic driving conditions. The research encompasses various light-duty vehicle models and configurations, with advanced instrumentation and data collection techniques employed to quantify energy-saving potential. The study featured two sets of L4 capable light duty vehicles, including the Stellantis Pacifica PHEV minivan and Stellantis RAM Truck, examined in various lead and following vehicle
Poovalappil, Aman, Robare, Andrew, Schexnaydre, Logan, Santhosh, Pruthwiraj, Bahramgiri, Mojtaba, Bos, Jeremy P., Chen, Bo, Naber, Jeffrey, Robinette, Darrell
Technical Paper
Controllability and Driving Automation2025-01-867904/01/2025
A key challenge for manufacturers of automotive systems, hardware components and software products with no contribution to driving automation is the stringent requirements imposed on elements while being integrated into vehicles with driving automation. The result is increased development cost and low reusability. For such elements or components with no contribution to driving automation, their functions and failure modes remain unchanged when comparing vehicle integration with and without driving automation. The influence of driving automation is not accounted for in the current approach of classifying risk while conducting a Hazard Analysis and Risk Assessment (HARA). Functional safety standards for on-road vehicles rely on human intervention as a parameter to classify risk. Since current safety standards for on-road vehicles are not inclusive of driving automation concepts, classification of risk, based on existing definitions of parameters such as controllability, leads to
Shah, Mihir, Ibarra, Ireri
Technical Paper
Safe Cooperative Control Framework for Highway On-Ramp Merging2025-01-802404/01/2025
The development of connected and automated vehicles (CAVs) is rapidly increasing in the next generation and the automotive industry is dedicated to enhancing the safety and efficiency of CAVs. A cooperative control strategy helps CAVs to collaborate and share information among the neighboring CAVs, improving efficiency, optimizing traffic flow, and enhancing safety. This research proposes a safe cooperative control framework for CAVs designed for highway merging applications. In the urban transportation system, highway merging scenarios are high-risk collision zone, and the CAVs on the main and merging lanes should collaborate to avoid potential accidents. In the proposed framework, the on-ramp CAVs merge at 40 mph within the same and opposite directions to the main lane CAVs. The proposed framework includes the consensus controller, safety filter, and quadratic programming (QP) optimization method. The consensus controller incorporates the communication between CAVs and designs the
Chang, PeiYu, Bhatti, Sidra, Javed, Nur Uddin, Ahmed, Qadeer
Technical Paper
Eco-Approach and Departure Algorithm for Connected and Automated PHEVs: Simulation and in-Vehicle Results2025-01-838404/01/2025
Plug-in Hybrid Electric Vehicles (PHEVs) combine the benefits of electric propulsion and storage with the extended range of conventional internal combustion engines to reduce fuel consumption and greenhouse gas emissions. However, optimizing the efficiency of PHEVs in real-world driving conditions remains a challenge due to the uncertainties of environmental and driving conditions. Connectivity and automation technologies can offer a unique opportunity to enhance the efficiency of PHEVs by enabling real-time interaction with surrounding vehicles and infrastructure. By leveraging these technologies, significant reductions in energy consumption for PHEVs can be achieved. However, most existing works primarily rely on simulation-based analyses to evaluate energy savings offered by connected and automated PHEVs. This study advances the understanding of the energy-saving potential of connected and automated PHEVs by incorporating experimental validation alongside simulation-based analyses
Kibalama, Dennis, Ozkan, Mehmet Fatih, Stockar, Stephanie, Canova, Marcello, Rizzoni, Giorgio
Technical Paper
Reproduction of Real-World Scenarios in CARLA: An Extension of CARLA Functionality2025-01-805904/01/2025
Reproducing driving scenarios involving near-collisions and collisions in a simulator can be useful in the development and testing of autonomous vehicles, as it provides a safe environment to explore detailed vehicular behavior during these critical events. CARLA, an open-source driving simulator, has been widely used for reproducing driving scenarios. CARLA allows for both manual control and traffic manager control (the module that controls vehicles in autopilot manner in the simulation). However, current versions of CARLA are limited to setting the start and destination points for vehicles that are controlled by traffic manager, and are unable to replay precise waypoint paths that are collected from real-world collision and near-collision scenarios, due to the fact that the collision-free pathfinding modules are built into the system. This paper presents an extension to CARLA’s source code, enabling the replay of exact vehicle trajectories, irrespective of safety implications
Ai, Yan, Adhikari, Bikram, Park, Chung-Kyu, Kan, Cing-Dao, Wijesekera, Duminda
Technical Paper
Machine Learning-Based Lane Detection and Lateral Offset Estimation Model for Vehicle Following Applications2025-01-802004/01/2025
Precisely understanding the driving environment and determining the vehicle’s accurate position is crucial for a safe automated maneuver. vehicle following systems that offer higher energy efficiency by precisely following a lead vehicle, the relative position of the ego vehicle to lane center is a key measure to a safe automated speed and steering control. This article presents a novel Enhanced Lane Detection technique with centimeter-level accuracy in estimating the vehicle offset from the lane center using the front-facing camera. Leveraging state-of-the-art computer vision models, the Enhanced Lane Detection technique utilizes YOLOv8 image segmentation, trained on a diverse world driving scenarios dataset, to detect the driving lane. To measure the vehicle lateral offset, our model introduces a novel calibration method using nine reference markers aligned with the vehicle perspective and converts the lane offset from image coordinates to world measurements. This design minimizes
Karuppiah Loganathan, Nirmal Raja, Poovalappil, Aman, Naber, Jeffrey, Robinette, Darrell, Bahramgiri, Mojtaba
Technical Paper
A Model for the Design of Automated Vehicle Event Data Recorders2025-01-867804/01/2025
When vehicle accidents occur, investigators rely on event data recorders for accident investigations. However current event data recorders do not support accident investigation involving automated or self-driving vehicles when there is state information that needs to be recorded, for example ADS modes, changes in the ODD that the vehicle operates under, and the various states of vehicle features such as intelligent cruise control, automated lane changes, autonomous emergency braking, and others. In this paper, we propose a model to design new types of event data recorders that supports accident investigations involving automated vehicles when there is state information to be recorded. The model is generic enough to be adapted to any automation level and any set of automated vehicle functional features. The model has been instantiated to a specific ADAS system.
Pimentel, Juan
Technical Paper
Leveraging the Automated Mobility Partnership (AMP) to Support the Evaluation of Safety of the Intended Functionality (SOTIF) in Automated Driving Systems2025-01-867404/01/2025
The Automated Mobility Partnership (AMP) is a consortium of industry and academic stakeholders dedicated to advancing Automated Driving Systems (ADS) through a comprehensive suite of tools, datasets, and methodologies. The AMP portal integrates events from over 35 million miles of naturalistic driving data including thousands of annotated crashes and near-crashes and a decade of U.S. police-reported crash data curated by the Virginia Tech Transportation Institute. The portal enables data discovery, visualization, processing, and analysis through secured web access. This paper briefly describes the AMP portal and examines its utility in developing and evaluating the safety of ADS using standardized processes. For the examination, we provide examples based on generic automated driving functions, guided by the Safety of the Intended Functionality (SOTIF) framework. The results show that AMP is instrumental in identifying recorded real-world cases in which the hazardous behavior of a
Antona-Makoshi, Jacobo, Williams, Vicki, Ali, Gibran, Sullivan, Kaye, Terranova, Paolo, Kefauver, Kevin, Hatchett, Alex
Technical Paper
The Effect of Directional Tactile Guidance on Takeover Performance in Level 3 Automated Driving2025-01-804904/01/2025
Automated driving is an important development direction of the current automotive industry. Level 3 automated driving allows the driver to perform non-driving related tasks (NDRTs) during automated driving, however, once the operating conditions exceed the designed operating domain, the driver is still required to take over. Therefore, it is important to rationally design takeover requests (TORs) in Level 3 conditional automated driving. This paper investigates the effect of directional tactile guidance on driver takeover performance in emergency obstacle avoidance scenarios during the transfer of control from automated driving mode to manual driving. 18 participants drove a Level 3 conditional automated driving vehicle in a driving simulator on a two-way four-lane urban road, performed a takeover, and avoided obstacles while performing non-driving related tasks. The driver's takeover performance during the takeover process was measured and subjective driver evaluation data was
Liang, Xinying, Liang, Yunhan, Ma, Xiaoyuan, Wang, Luyao, Chen, Guoying, Hu, Hongyu
Technical Paper
Energy-Efficient Maneuvering of Connected and Automated Vehicles: NEXTCAR Phase II Results2025-01-838504/01/2025
Onboard sensing and Vehicle-to-Everything (V2X) connectivity enhance a vehicle's situational awareness beyond direct line-of-sight scenarios. A team led by Southwest Research Institute (SwRI) demonstrated 20% energy savings by leveraging these information streams on a 2017 Prius Prime as part of the first phase of the ARPA-E-funded NEXTCAR program. Combining this technology with automation can improve vehicle safety and enhance energy efficiency further. In the second phase, SwRI demonstrated 30% energy savings over the baseline. This paper summarizes the efforts to achieve 30% savings on a 2021 Honda Clarity PHEV. The vehicle was outfitted with the SwRI Ranger automated driving suite for perception and localization. Model-based control schemes with selective interrupt and control (SIC) were used to override stock vehicle controls and actuate the accelerator, brake, and electric power steering system, enabling drive-by-wire and steer-by-wire functionalities. Key algorithms contributing
Bhagdikar, Piyush, Gankov, Stanislav, Sarlashkar, Jayant, Hotz, Scott, Rajakumar Deshpande, Shreshta, Rengarajan, Sankar, Adsule, Kartik, Drallmeier, Joseph, D'Souza, Daniel, Alden, Joshua, Bhattacharjya, Shuvodeep
Technical Paper
Assessing the Energy Consumption Impact of Intelligent Driving Technologies on Electric Vehicles: A Comprehensive Review2025-01-859804/01/2025
With the continuous advancement of artificial intelligence technology, the automation level of electric vehicles (EVs) is rapidly increasing. Despite the improvements in travel efficiency, safety, and convenience brought about by automation, cutting-edge intelligent technologies also pose the potential of increased energy consumption, such as the computational power required by advanced algorithms and the energy usage of high-precision equipment, leading to higher overall energy consumption for connected or autonomous electric vehicles (CAEVs). To assess the impact of intelligent technologies on AEVs, this study innovatively provides a comprehensive evaluation of the impact of intelligent technologies on CAEV energy consumption from both positive and negative perspectives. After reviewing 59 relevant studies, the findings highlight energy savings achieved through Vehicle-to-Infrastructure and Vehicle-to-Vehicle cooperation as positive effects, while increased energy consumption from
Liu, Tianyi, Qi, Hao, Ou, Shiqi (Shawn)
Technical Paper
Impact of Connected and Automated Vehicles on Longitudinal and Lateral Performance of Heterogeneous Traffic Flow in Shared Autonomy on Two-Lane Highways2025-01-809804/01/2025
Intelligent transportation systems and connected and automated vehicles (CAVs) are advancing rapidly, though not yet fully widespread. Consequently, traditional human-driven vehicles (HDVs), CAVs, and human-driven connected and automated vehicles (HD-CAVs) will coexist on roads for the foreseeable future. Simultaneously, car-following behaviors in equilibrium and discretionary lane-changing behaviors make up the most common highway operations, which seriously affect traffic stability, efficiency and safety. Therefore, it’s necessary to analyze the impact of CAV technologies on both longitudinal and lateral performance of heterogeneous traffic flow. This paper extends longitudinal car-following models based on the intelligent driver model and lateral lane-changing models using the quintic polynomial curve to account for different vehicle types, considering human factors and cooperative adaptive cruise control. Then, this paper incorporates CAV penetration rates, shared autonomy rates
Wang, Tianyi, Guo, Qiyuan, He, Chong, Li, Hao, Xu, Yiming, Wang, Yangyang, Jiao, Junfeng
Technical Paper
Developing a Safety Management System for the Automated Vehicle Industry2025-01-867304/01/2025
Safety Management Systems (SMSs) have been used in many safety-critical industries and are now being developed and deployed in the automated driving system (ADS)-equipped vehicle (AV) sector. Industries with decades of SMS deployment have established frameworks tailored to their specific context. Several frameworks for an AV industry SMS have been proposed or are currently under development. These frameworks borrow heavily from the aviation industry although the AV and aviation industries differ in many significant ways. In this context, there is a need to review the approach to develop an SMS that is tailored to the AV industry, building on generalized lessons learned from other safety-sensitive industries. A harmonized AV-industry SMS framework would establish a single set of SMS practices to address management of broad safety risks in an integrated manner and advance the establishment of a more mature regulatory framework. This paper outlines a proposed SMS framework for the AV
Wichner, David, Wishart, Jeffrey, Sergent, Jason, Swaminathan, Sunder
Technical Paper
Dynamic Driving Task Assessment Scores for Scenarios Navigated by an OEM ADS-Equipped Vehicle2025-01-867204/01/2025
One of the major issues facing the automated driving system (ADS)-equipped vehicle (AV) industry is how to evaluate the performance of an AV as it navigates a given scenario. The development and validation of a sound, consistent, and transparent dynamic driving task (DDT) assessment (DA) methodology is a key component of the safety case framework (SCF) of the Automated Vehicle – Test and Evaluation Process (AV-TEP) Mission, a collaboration between Science Foundation Arizona and Arizona State University. The DA methodology was presented in earlier work and includes the DA metrics from the recently published SAE J3237 Recommended Practice. This work extends and implements the methodology with an AV developed by OEM May Mobility in four diverse, real-world scenarios: (1) an oncoming vehicle entering the AV’s lane, (2) vulnerable road user (VRU) crossing in front of the AV’s path, (3) a vehicle executing a three-point turn encroaches into the AV’s path, and (4) the AV exhibiting aggressive
Wishart, Jeffrey, Rahimi, Shujauddin, Swaminathan, Sunder, Zhao, Junfeng, Frantz, Matt, Singh, Satvir, Como, Steven Gerard
Technical Paper
Objective and Subjective Evaluation of the Interaction of Automated Vehicles and Human Drivers in Take-Over Scenarios2025-01-804804/01/2025
The research activity aims at defining specific Operational Design Domains (ODDs) representative of Italian traffic environments. The paper focuses on the human-machine interaction in Automated Driving (AD), with a focus on take-over scenarios. The study, part of the European/Italian project “Interaction of Humans with Level 4 AVs in an Italian Environment - HL4IT”, describes suitable methods to investigate the effect of the Take-Over Request (TOR) on the human driver’s psychophysiological response. The DriSMI dynamic driving simulator at Politecnico di Milano has been used to analyse three different take-over situations. Participants are required to regain control of the vehicle, after a take-over request, and to navigate through a urban, suburban and highway scenario. The psychophysiological characterization of the drivers, through psychological questionnaires and physiological measures, allows for analyzing human factors in automated vehicles interactions and for contributing to
Gobbi, Massimiliano, Boscaro, Linda, De Guglielmo, Veronica, Fossati, Andrea, Galbiati, Andrea, Mastinu, Leda, Ponti, Marco, Mastinu, Gianpiero, Previati, Giorgio, Sabbioni, Edoardo, Signorini, Maria Gabriella, Somma, Antonella, Subitoni, Luca, Uccello, Lorenzo
Technical Paper
Data Driven Quantitative Evaluation of Safety Controllability for Automated Vehicle2025-01-828104/01/2025
With the development of automated vehicle (AV), it is essential to ensure their safety even in the presence of system faults or function inefficiency. Safety controllability refers to the ability to manage and control the vehicle, ensuring that it remains safe even in the presence of faults with unexpected conditions. This study proposed a data driven method to evaluate quantitatively safety controllability for AVs. Safety analysis is conducted to identify the potential hazard events. Taking system function and architecture into consideration, the failure modes of the vehicle hazards are identified with hazardous driving situation. Based on the identified failure modes, fault injection tests are conducted with critical scenarios. According to the vehicle dynamic performance, the improved analytic hierarchy process (AHP) can be explored to quantitatively evaluate the safety controllability based on fault injection test results. In particular, this study focuses on the case study to
Ye, Xiaoming, Yang, Yanding, Li, Lingyang, Zhang, Yaguo, Wang, Yongliang
Technical Paper
Incorporating the Scenario-Based Framework Underpinned by Operational Design Domain (ODD) for Automated Driving Stack (ADS) Evaluation2025-01-806704/01/2025
The rapid development of open-source Automated Driving System (ADS) stacks has created a pressing need for clear guidance on their evaluation and selection for specific use cases. This paper introduces a scenario-based evaluation framework combined with a modular simulation framework, offering a scalable methodology for assessing and benchmarking ADS solutions, including but not limited to off-the-shelf designs. The study highlights the lack of clear Operational Design Domain (ODD) descriptions in such systems. Without a common understanding, users must rely on subjective assumptions, which hinders the process of accurate system selection. To address this gap, the study proposes adopting a standardised ISO 34503 ODD description format within the ADS stacks. The application of the proposed framework is showcased through a case study evaluating two open-source systems, Autoware and Apollo. By first defining the assumed system’s ODD, then selecting a relevant scenario, and establishing
Chodowiec, Emil, Zhang, Xizhe, Mitchell, Joe, Baker, Peter, Khastgir, Siddartha, Jennings, Paul
Technical Paper
Portable Track-Based Connected Intersection Testing System for Connected and Automated Vehicles2025-01-806204/01/2025
Connected and automated vehicle (CAV) technology is a rapidly growing area of research as more automakers strive towards safer and greener roads through its adoption. The addition of sensor suites and vehicle-to-everything (V2X) connectivity gives CAVs an edge on predicting lead vehicle and connected intersection states, allowing them to adjust trajectory and make more fuel-efficient decisions. Optimizing the energy consumption of longitudinal control strategies is a key area of research in the CAV field as a mechanism to reduce the overall energy consumption of vehicles on the road. One such CAV feature is autonomous intersection navigation (AIN) with eco-approach and departure through signalized intersections using vehicle-to-infrastructure (V2I) connectivity. Much existing work on AIN has been tested using model-in-loop (MIL) simulation due to being safer and more accessible than on-vehicle options. To fully validate the functionality and performance of the feature, additional
Hamilton, Kayla, Misra, Priyashraba, Ord, David, Goberville, Nick, Crain, Trevor, Marwadi, Shreekant
Technical Paper
Improving Vehicle Localization Confidence under Different Road Geometries2025-01-804304/01/2025
A significant challenge to the scalability of automated driving systems is the potential unavailability of GPS information for localization. To address this issue, a methodology using a static 2D map of road and lane geometry and vehicle on board sensors data is proposed to ensure reliable localization and navigation for automated vehicles in GPS-denied situations. In this study, a dead reckoning system based on vehicle kinematics is implemented by using onboard sensor data from the vehicle's Controller Area Network (CAN). However, the kinematic dead reckoning estimate has error accumulation, the drift in the dead reckoning position estimate is eliminated by using an arc-length based map matching approach. This innovative approach was tested and validated at various safety-critical intersection scenarios, including four-way intersection, roundabout, slip-lane intersection, and curved road. This approach ensures the continuous and reliable localization of automated vehicles, thereby
Javed, Nur Uddin, Singh, Yuvraj, Tan, Shengzhe, Ahmed, Qadeer
Technical Paper
Vehicle–Vehicle Collaborative Control Strategy for Dedicated Lanes of Connected Vehicles12-08-02-001203/28/2025
To alleviate the problem of reduced traffic efficiency caused by the mixed flow of heterogeneous vehicles, including autonomous and human-driven vehicles, this article proposes a vehicle-to-vehicle collaborative control strategy for a dedicated lane in a connected and automated vehicle system. First, the dedicated lane’s operating efficiency and formation performance are described. Then, the characteristics of connected vehicle formations are determined, and a control strategy for heterogeneous vehicle formations was developed. Subsequently, an interactive strategy was established for queueing under the coordination of connected human-driven and autonomous vehicles, and the queue formation, merging, and splitting processes are divided according to the cooperative interaction strategy. Finally, the proposed lane management and formation strategies are verified using the SUMO+Veins simulation software. The simulation results show that the dedicated lane for connected vehicles can
Zhang, Xiqiao, Cui, Leqi, Yang, Longhai, Wang, Gang
Journal Article
System Configuration and Validation of Hybrid-Based Six Degrees of Freedom Motion Platform for Vehicle Dynamic Testing2025-01-502103/27/2025
Scenario-based testing has become one of the important elements to evaluate the performance of automated vehicle systems before deploying on actual road. There are several approaches that can be used to conduct scenario-based testing via simulation approach. One of the important aspects in scenario-based safety testing is the driver-in-the-loop (DiL) simulation where it involves integration of hardware and human interaction. Therefore, motion platform-based vehicle driving simulators are commonly used for the DiL simulation for scenario-based testing. Generally, a high degree of freedom driving simulator is used for scenario-based testing such as 6 degrees of freedom (DoF) to achieve high accuracy to represent an actual vehicle response. Moreover, most of the motion platforms are designed using hexapod configuration, which also contributes to 6-DoF. However, this type of design requires large space to conduct the testing because the field of motion (FoM) is high in three axes and high
Kleolee, KahOnn, Aparow, Vimal Rau, Cheok, Jun Hong, de Boer, Niels, Jamaluddin, Hishamuddin
Technical Paper
Improving Safety of Autonomous Vehicles: A Verifiable Method for Graceful Degradation of Decision and Control Responsibilities12-08-02-002103/24/2025
Developing safe and reliable autonomous vehicles is crucial for addressing contemporary mobility challenges. While the goal of autonomous vehicle development is full autonomy, up to SAE Level 4 and beyond, human intervention remains necessary in critical or unfamiliar driving scenarios. This article introduces a method for gracefully degrading system functionality and seamlessly transferring decision-making and control between the autonomous system and a remote safety operator when needed. This transfer is enabled by an onboard dependability cage, which continuously monitors the vehicle’s performance during its operation. The cage communicates with a remote command control center, allowing for remote supervision and intervention by a safety driver. We assess this methodology in both lab and test field settings in a case study of last-mile parcel delivery logistics and discuss the insights and results obtained from these evaluations.
Aniculaesei, Adina, Aslam, Iqra, Zhang, Meng, Buragohain, Abhishek, Vorwald, Andreas, Rausch, Andreas
Journal Article
Feasibility of Road Longitudinal Profiles for Automated Vehicles Based on Vehicle Dynamics2025-01-715003/19/2025
With the development and maturity of new generation digital technologies such as artificial intelligence, Internet of Things, and 5G mobile communication, their integration with physical products is becoming increasingly seamless. Automobiles serve as a prime example in this regard. In recent years, automated vehicle (AV) technologies have emerged as a prominent focal point, witnessing an escalating acceptance in the market and a growing number of self-driving vehicles on the roads, existing roads are primarily designed for traditional human-driven vehicles (HVs). Due to the differences in perception between automated systems and human drivers, it is essential to assess AVs' feasibility to current road infrastructure. This paper analyzes the safety and comfort of automated vehicles equipped with adaptive cruise control systems (ACC-AVs) on longitudinal road profiles from the perspective of vehicle dynamics. Firstly, a co-simulation platform integrating PreScan, CarSim, and Simulink
Li, Zezhou, Cai, Mingmao, Gu, Tianqi, Yu, Bin
Technical Paper
Research on Automatic Emergency Braking Pedestrian System Considering Road Adhesion Coefficient10-09-03-002203/08/2025
To further optimize the automatic emergency braking for pedestrian (AEB-P) control algorithm, this study proposes an AEB-P hierarchical control strategy considering road adhesion coefficient. First, the extended Kalman filter is used to estimate the road adhesion coefficient, and the recursive least square method is used to predict the pedestrian trajectory. Then, a safety distance model considering the influence factor of road adhesion coefficient is proposed to adapt to different road conditions. Finally, the desired deceleration is converted into the desired pressure and desired current to the requirements of the electric power-assisted braking system. The strategy is verified through the hardware-in-the-loop (HIL) platform; the simulation results show that the control algorithm proposed in this article can effectively avoid collision in typical scenarios, the safe distance of parking is between 0.61 m and 2.34 m, and the stop speed is in the range of 1.85 km/h–27.64 km/h.
Wang, Zijun, Wang, Liang, Ma, Liang, Sun, Yong, Li, Chenghao, Yang, Xinglong
Journal Article
Power over Coaxial: a simplified path to advanced vehicle systems25AUTP03_0703/01/2025
As automotive technology advances, modern vehicles increasingly rely on complex electronics such as cameras, sensors, radar and lidar. These components are critical for advanced driver-assistance systems (ADAS) and automated driving. With the growing complexity of these systems, automotive manufacturers face challenges in efficiently transmitting both power and data while minimizing weight and system complexity. Power over Coaxial (PoC) technology offers a solution by allowing the transmission of power and data over a single coaxial cable, significantly simplifying vehicle design. With the integration of more electronic systems, especially those required for ADAS and autonomous driving, the demand for power and high-speed data transmission in vehicles has surged. Modern cars now use multiple cameras and sensors, and as vehicle systems continue to evolve, the number of electronic components is expected to increase. This shift places significant demands on the transmission of both data
Thurman, Travis
Magazine Article
Toward a Methodology for Safety—Performance Trade-Off Analysis for Connected Automated Vehicles Supported by a Smart Infrastructure12-08-02-002002/24/2025
Introducing connectivity and collaboration promises to address some of the safety challenges for automated vehicles (AVs), especially in scenarios where occlusions and rule-violating road users pose safety risks and challenges in reconciling performance and safety. This requires establishing new collaborative systems with connected vehicles, off-board perception systems, and a communication network. However, adding connectivity and information sharing not only requires infrastructure investments but also an improved understanding of the design space, the involved trade-offs and new failure modes. We set out to improve the understanding of the relationships between the constituents of a collaborative system to investigate design parameters influencing safety properties and their performance trade-offs. To this end we propose a methodology comprising models, analysis methods, and a software tool for design space exploration regarding the potential for safety enhancements and requirements
Fornaro, Gianfilippo, Törngren, Martin, Gaspar Sánchez, José Manuel
Journal Article
Ecological Driving for Connected and Automated Vehicles Considering Driver Acceptance at Signalized Intersection in a Mixed Traffic Flow2025-01-712302/21/2025
This work aims to design an ecological driving strategy for connected and automated vehicles (CAVs) at an isolated signalized intersection in a mixed traffic flow of CAVs and human-driven vehicles (HVs). Actually, from existing experiments and theories, we can obtain that stochasticity of HVs plays a nontrivial role in traffic flow, including the drivers’ driving personality style and the interaction between HV and CAV. To consider the uncertainty of HVs, we propose driver acceptance to describe the interaction between HV and CAV with the increase of CAV market penetration rate (MPR). Then, to estimate the arrival time of CAV accurately, we propose an improved LWR method integrating the vehicle to V2X data and detector data. The problem is formulated as a multi-objective optimization model and solved by NSGA-II. Our study indicates that multi-objective performance benefits depend on inflow rate, the MPR, and the drivers’ acceptance towards CAVs. The results show that traffic efficiency
Wang, Xiaoliang, Ma, Shufang, Yu, Qin, Song, Wen, Peng, Hongrui, Hu, Yiming
Technical Paper
A Car-following Model Considering Acceleration of Multiple Vehicles for Mixed Traffic Flow2025-01-719502/21/2025
The practice of vehicle platooning for managing mixed traffic can greatly enhance safety on the roads, augment overall traffic flow, and boost fuel efficiency, garnering considerable focus in transportation. Existing research on vehicle platoon control of mixed traffic has primarily focused on using the state information of the leading or head vehicle as control input for following vehicles without accounting for the driving variability of Human-driven Vehicles (HDVs), which does not conform to the driving conditions of vehicles in reality. Inspired by this, this paper presents a car-following model for Connected and Automated Vehicles (CAVs) that utilizes communication with multiple preceding vehicles in mixed traffic. The study further investigates the impact of parameters such as the speed and acceleration of preceding vehicles on the car-following behavior of CAVs, as well as the overall effect of different CAV penetration rates on mixed traffic flow. Firstly, a mixed-vehicle
Peng, Fuke, Huang, Xin
Technical Paper
A Distributed Control Strategy for Highway Merge Zone Based on Virtual Rotation2025-01-720002/21/2025
The merging problem in the highway merge zone has been a research focus in the field of transportation for a long time. The rise of Connected and Automated Vehicles (CAVs) provides the potential to improve traffic flow efficiency, alleviate congestion and handle safety issues. However, existing two-dimensional merging strategies are facing challenges such as high computational complexity and the inevitable traffic oscillations during merging, which hinder the stability of traffic flow and fail to meet the dynamic requirements of merging control. To address these issues, this study proposes a distributed control strategy for CAVs in highway merge scenarios. Firstly, a virtual rotation method is designed to transform the merging problem of two different lanes into a car-following problem of a virtual platoon, and a virtual leader vehicle is introduced, to reduce computational complexity and determine vehicle sequencing. Based on this method, a Spring Cooperative Merging System (SCMS) is
Liu, Yandan, Qu, Xu
Technical Paper
Leveraging Triggering Conditions for Efficient Scenario-Based Testing of Automated Vehicles12-08-04-003502/19/2025
Scenario-based testing has become a central approach of safety verification and validation (V&V) of automated driving. The standard ISO 21448: Safety of the intended functionality (SOTIF) [1] proposes triggering conditions (e.g., an occluded traffic sign) as a new aspect to be considered to organize scenario-based testing. In this contribution, we discuss the requirements and the strategy of testing triggering conditions in an iterative, SOTIF-oriented V&V process. Accordingly, we illustrate a method for generating test scenarios for evaluating potential triggering conditions. We apply the proposed method in a two-fold case study: We demonstrate how to derive test scenarios and test these with a virtual automated driving system in simulation. We provide an analysis of the testing result to show how triggering condition-based testing facilitates spotting the weakness of the system. Besides, we exhibit the applicability of the method based on multiple triggering conditions and nominal
Zhu, Zhijing, Philipp, Robin, Howar, Falk
Journal Article
Optimum Scheduling of a Multi-Machine FMS with Alternative Routing Using Crow Search Algorithm2025-28-017902/07/2025
This article addresses the machines and automated guided vehicles (AGVs) concurrent scheduling with alternative machines in a multi-machine flexible manufacturing system (FMS) in order to provide the best optimum sequences for the minimization of makespan (MKSN).The assignment of AGVs and related trips, such as the dead headed trip and loaded trip times of AGVs to jb-ons, as well as the decision to select machines for job-operations (jb-ons) and the sequencing of jb-ons on the machines, make this problem extremely difficult to solve. This paper offers a mixed integer nonlinear programming (MINLP) formulation for modeling the problem, as well as the crow search algorithm (CSA) to solve the problem. For verification, a manufacturing company's industrial problem is employed. The findings indicate that CSA performs better than the existing techniques, and that the utilization of alternative machines for the operations can bring the MKSN and cost down.
Mareddy, Padma Lalitha, Reddy K, Ajaya, Katta, Lakshmi Narasimhamu, Siva Rami Reddy, Narapureddy
Technical Paper
Intelligent Vehicle Trajectory Tracking Control Based on Variable Universe Fuzzy Rule Speed Planning and Piecewise Preview Model Prediction02-18-01-000602/06/2025
Intelligent vehicles can utilize a variety of sensors, computing, and control technologies to autonomously perceive the environment and make decisions to achieve safe, efficient, and automated driving. If the speed planning of intelligent vehicles ignores the vehicle dynamics state, it leads to unreasonable planning speed and is not conducive to improving the accuracy of trajectory tracking control. Meanwhile, trajectory tracking usually does not consider the road and speed information beyond the prediction horizon, resulting in poor tracking precision that is not conducive to improving driving comfort. To solve these problems, this study proposes a new longitudinal speed planning method based on variable universe fuzzy rules and designs the piecewise preview model predictive control (PPMPC) to realize the vehicle trajectory tracking. First, the three-degrees-of-freedom vehicle dynamics model and trajectory tracking model are established and verified. Then, the variable universe fuzzy
Zhang, Jie, Teng, Shipeng, Gao, Jianjie, Zhou, Xingxing, Zhou, Junchao
Journal Article
Data-Driven Performance Evaluation of Machine Learning for Velocity Estimation Based on Scan Artifacts from LiDAR Sensors12-08-04-003201/21/2025
Light detection and ranging (LiDAR) sensors are increasingly applied to automated driving vehicles. Microelectromechanical systems are an established technology for making LiDAR sensors cost-effective and mechanically robust for automotive applications. These sensors scan their environment using a pulsed laser to record a point cloud. The scanning process leads in the point cloud to a distortion of objects with a relative velocity to the sensor. The consecutive generation and processing of points offers the opportunity to enrich the measured object data from the LiDAR sensors with velocity information by extracting information with the help of machine learning, without the need for object tracking. Turning it into a so-called 4D-LiDAR. This allows object detection, object tracking, and sensor data fusion based on LiDAR sensor data to be optimized. Moreover, this affects all overlying levels of autonomous driving functions or advanced driver assistance systems. However, since such
Haas, Lukas, Haider, Arsalan, Kastner, Ludwig, Kuba, Matthias, Zeh, Thomas, Jakobi, Martin, Koch, Alexander Walter
Journal Article
Research on the Intelligent Vehicle Trajectory Tracking Control Based on Optimal Preview Distance02-18-01-000501/03/2025
Accurate and responsive trajectory tracking is a critical challenge in intelligent vehicle control system. To improve the adaptability and real-time performance of intelligent vehicle trajectory tracking controllers, we propose a genetic algorithm adaptive preview (GAAP) scheme that offline optimizes the preview distance based on vehicle speed and reference path curvature. The goal is to obtain the optimal preview distance that balances tracking accuracy, stability, and real-time performance. By establishing a relationship between optimal preview distance, speed, and curvature, we enhance real-time performance through online table checking during trajectory tracking. Our trajectory tracking error model takes into account not only position errors but also heading errors. A feedback–feedforward trajectory tracking controller is then designed to achieve rapid responses without compromising robustness. Simulation tests conducted under straight circular arc condition and double lane change
Cheng, Kehan, Zhang, Huanhuan, Hu, Shengli, Ning, Qianjia
Journal Article
Low-Level Data Fusion between Camera and Automotive RADAR for Vehicle and Pedestrian Detection Using nuScenes Database2024-36-006412/20/2024
Autonomous driving technology has indeed become a focal point of research globally, with significant efforts directed towards enhancing its key components: environment perception, vehicle localization, path planning, and motion control. These components work together to enable autonomous vehicles to navigate complex environments safely and efficiently. Among these components, environment perception stands out as critical, as it involves the robust, real-time detection of targets on the road. This process relies heavily on the integration of various sensors, making data fusion an indispensable tool in the early stages of automation. Sensor fusion between the camera and RADAR (Radio Detection and Ranging) has advantages because they are complementary sensors, where fusion combines the high lateral resolution from the vision system with the robustness in the face of adverse weather conditions and light invulnerability of RADAR, as well as having a lower production cost compared to the
Cury, Hachid Habib, Teixeira, Evandro Leonardo Silva, Silva, Rafael Rodrigues
Technical Paper
Trajectory Planning and Tracking Control for Single Lane Changing with Different Driving Styles of Intelligent Vehicles Based on Seventh-Degree Polynomial12-08-03-002812/14/2024
Single lane changing is one of the typical scenarios in vehicle driving. Planning an appropriate lane change trajectory is crucial in autonomous and semi-autonomous vehicle research. Existing polynomial trajectory planning mostly uses cubic or quintic polynomials, neglecting the lateral jerk constraints during lane changes. This study uses seventh-degree polynomials for lane change trajectory planning by considering the vehicle lateral jerk constraints. Simulation results show that the utilization of the seventh-degree method results in a 41% reduction in jerk compared to the fifth-degree polynomial. Furthermore, this study also proposes lane change trajectory schemes that can cater to different driving styles (e.g., safety, efficiency, comfort, and balanced performance). Depending on the driving style, the planned lane change trajectory ensures that the vehicle achieves optimal performance in one or more aspects during the lane change process. For example, with the trajectory that
Lai, Fei, Huang, Chaoqun
Journal Article
Unified Multi-Modal Multi-Agent Cooperative Perception Framework for Intelligent Transportation Systems2024-01-702812/13/2024
Cooperative perception has attracted wide attention given its capability to leverage shared information across connected automated vehicles (CAVs) and smart infrastructure to address the occlusion and sensing range limitation issues. To date, existing research is mainly focused on prototyping cooperative perception using only one type of sensor such as LiDAR and camera. In such cases, the performance of cooperative perception is constrained by individual sensor limitations. To exploit the multi-modality of sensors to further improve distant object detection accuracy, in this paper, we propose a unified multi-modal multi-agent cooperative perception framework that integrates camera and LiDAR data to enhance perception performance in intelligent transportation systems. By leveraging the complementary strengths of LiDAR and camera sensors, our framework utilizes the geometry information from LiDAR and the semantic information from cameras to achieve an accurate cooperative perception
Meng, Zonglin, Xia, Xin, Zheng, Zhaoliang, Gao, Letian, Liu, Wei, Zhu, Jiaqi, Ma, Jiaqi
Technical Paper
Realistic Trajectory Generation using Dynamic Deduction for Stochastic Microscopic Traffic Flow Model2024-01-704512/13/2024
The application trend of automated driving is gaining significant concern, making it increasingly crucial to validate automated driving within the stochastic simulated traffic flow environment from both time and cost perspectives. The stochastic traffic flow model attempts to encapsulate the variability inherent in traffic conditions through a stochastic process. This approach is particularly important as it accounts for the unpredictable nature of traffic, which is often not fully captured by traditional deterministic testing scenarios. However, while stochastic traffic flow models have made strides in simulating the behavior of traffic participants, there remains a significant oversight in the simulation of vehicles’ driving trajectories, leading to unrealistic portrayals of their behaviors. The trajectories of vehicles are a critical component in the overall behavior of traffic flow, and their accurate representation is essential for the simulation to reflect real-world driving
Gao, Yibo, Cao, Peng, Yang, Aixi
Technical Paper
Road Friction Coefficient Estimation based on Nonlinear Tire Force Observer for Distributed Driven Electric Vehicles2024-01-704912/13/2024
Road friction coefficient is an important characteristic parameter of the interaction force between road surface and tire, which plays a crucial role in vehicle dynamics control. At present, it is difficult to measure the road friction coefficient directly. Therefore, it is a challenge to estimate the road adhesion coefficient accurately and reliably. Considering that tire force is an important reflection of road adhesion coefficient, a road adhesion coefficient estimation method based on nonlinear tire force observation is proposed in this paper. First, based on the nonlinear Dugoff tire model, the nonlinear observer of tire longitudinal force is established. Then a 7-degree-of-freedom (DOF) nonlinear vehicle model is established, and the noise adaptive square root cubature kalman filter (ASRCKF) method is used to estimate the lateral force of the front and rear wheels. Finally, based on the ASRCKF algorithm, combined with the longitudinal force and lateral force information, the all
Zhang, Xiaoting, Zhao, Qi, Wu, Dongmei, Liu, Xing, Fang, Jiameng, Fu, Yuanyi, Wei, Jian
Technical Paper
Research on the Duties of Remote safety Inspector for Autonomous Commercial Vehicles2024-01-704012/13/2024
At present, autonomous commercial vehicles can automatically complete all transport services under limited conditions. Compared with traditional vehicles, autonomous vehicles have the characteristics of high electronic level and multiple control subjects. Remote driving safety inspector is an important guarantee for the safety application of unmanned vehicles at this stage. Whether the intelligent vehicle equipped with the driver or the safety inspector is an obvious feature to reflect the intelligence of the vehicle, a basis for the division of responsibilities, and an important factor to affect the commercial application of intelligent vehicles. Nowadays, the responsibility of remote safety inspector domestic and abroad is not clear. This paper analyzes the traditional vehicle to execute the whole transportation process task list. Combined with the current autonomous vehicle technical level, remote control technical level and other development level, the research put forward three
Wenliang, Li, Huajian, Li, Wei, Zhou
Technical Paper
Redundant Brake Boost Control Strategy of Integrated Electro-hydraulic Braking System2024-01-703812/13/2024
The traditional braking system has been unable to meet the redundant safety requirements of the intelligent vehicle for the braking system. At the same time, under the change of electrification and intelligence, the braking system needs to have the functions of braking boost, braking energy recovery, braking redundancy and so on. Therefore, it is necessary to study the redundant braking boost control of the integrated electro-hydraulic braking system. Based on the brake boost failure problem of the integrated electro-hydraulic brake system, this paper proposes a redundant brake boost control strategy based on the Integrated Brake Control system plus the Redundant Brake Unit configuration, which mainly includes fault diagnosis of Integrated Brake Control brake boost failure, recognition of driver braking intention based on pedal force, pressure control strategy of Integrated Brake Control brake boost and pressure control strategy of Redundant Brake Unit brake boost. The designed control
Dexing, Lao, Luping, Yan, Qinghai, Sui, Long, Cao, Shang, Gao, Zhigang, Chen, Mingxing, Ren, Zhicheng, Chen
Technical Paper
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