The penetration of ADAS in automotive markets is increasing rapidly. However, their effectiveness and acceptance are significantly influenced by regional driving behaviours and infrastructure. This study explores the interaction between naturalistic driver behaviour in India and the operational characteristics of ADAS systems (FCW, ACC, LCF and BSD) with focus on cars. Using real-world driving data collected from Indian roads, the research aims to highlight the divergence between ADAS design assumptions often based on structured Western traffic environments and the complex, dynamic nature of Indian traffic, characterized by frequent human negotiation, informal road practices, and different vehicle types. The study characterizes multiple driver’s driving pattern through naturalistic driving and ADAS systems behaviour in corresponding situations, notably how they adapt to unstructured Indian scenarios such as lane ambiguity, pedestrian unpredictability, traffic flow unpredictability and

Sankpal, Krishnath Namdev, Magar, Akshay, Khot, Ankush, Kulkarni, Alok, Perez, Marc

A Centralized Framework for Sustaining Safety-Critical Vehicle Systems Through Periodic Servicing

2026-26-0003

1/16/2026

As vehicles are becoming more complex, maintaining the effectiveness of safety critical systems like adaptive cruise control, lane keep assist, electronic breaking and airbag deployment extends far beyond the initial design and manufacturing. In the automotive industry these safety systems must perform reliably over the years under varying environmental conditions. This paper examines the critical role of periodic maintenance in sustaining the long-term safety and functional integrity of these systems throughout the lifecycle. As per the latest data from the Ministry of Road Transport and Highways (MoRTH), in 2022, India reported a total of 4.61 lakh road accidents, resulting in 1.68 lakh fatalities and 4.43 lakh injuries. The number of fatalities could have been reduced by the intervention of periodic services and monitoring the health of safety critical systems. While periodic maintenance has contributed to long term safety of the vehicles, there are a lot of vehicles on the road

HN, Sufiyan Ahmed, Khan, Furqan, Srinivas, Dheeraj

Dynamic Integration of Bilateral and Adaptive Cruise Control for Intuitive Vehicle Behavior and Congestion Mitigations

2026-26-0037

1/16/2026

Bilateral Cruise Control (BCC) is a new concept that has been shown to reduce traffic congestion and enhance fuel/energy efficiency compared to Adaptive Cruise Control (ACC). BCC considers both lead and trailing vehicles to determine the ego vehicle’s acceleration, effectively damping any disturbance down the vehicle string and reducing possibilities for congestion. Despite the advantages demonstrated with BCC, one major limitation is its non-intuitive behavior, which stems from the fact that the BCC reacts not just to the lead vehicle but also to the trailing vehicle’s movement. This paper identifies key issues with BCC control and proposes solutions that retain the benefits of BCC while maintaining intuitive behavior. Specifically, a novel switching strategy is proposed to switch between ACC and BCC control modes by critically analyzing the driving conditions. The proposed system ensures acceptable driving behavior with predictable braking and acceleration, resulting in an intuitive

A, Arya, A, Aishwarya, D, Vishal Mitaran, M, Senthil Vel, Kumar, Vimal

Crowdsourcing Indian Traffic Scenarios for ADAS Development and Testing

2026-26-0046

1/16/2026

In the Indian context, introduction of ADAS can play a positive role in improving road safety by assisting the driver and preventing unsafe driver behaviour. Technologies like Automated Emergency Braking (AEB), Lane Keep System, Adaptive Cruise Control, Driver Drowsiness Detection, Driver Alcohol detection etc., if deployed safely and used in a safe manner can help prevent many of the current road deaths in India. Safe deployment and safe use of such ADAS technologies require the systems to operate without failure within their operational design domains (ODD) and not surprise the drivers with sudden or unpredictable failures, to help develop their trust in the technology. As a result, identifying test scenarios remain a key step in the development of Advanced Driver Assistance Systems (ADAS). This remains a challenge due to the large test space especially for the Indian context due to the unpredictable traffic behaviour and occasional road infrastructure. In this paper, we introduce a

Serry, Hamid, Dodoiu, Tudor, Alakkad, Fadi, Zhang, Xizhe, Khastgir, Siddartha, Jennings, Paul

DRIVING SAFETY FORWARD: How simulation and MODSIM accelerate ADAS innovation

25AUTP12_07

12/1/2025

Simulation has become mission-critical for ADAS development. Model-based systems engineering can integrate modeling and simulation from the start of the design process. Advanced Driver Assistance Systems (ADAS) are transforming vehicle safety, acting as the bridge between conventional driving and full autonomy. From adaptive cruise control to emergency braking and blind-spot detection, these technologies rely on a dense network of radar sensors, antennas, electronic control units and software. What unites them is the need for precise functionality under complex real-world situations. Achieving full reliability requires more than testing on the road; it demands a virtual approach grounded in simulation. Simulation has become mission-critical for ADAS development. As new vehicles integrate dozens of sensors into tightly constrained spaces, even subtle design decisions can affect system performance. Radar solutions, in particular, present unique challenges, especially as vehicle surfaces

Eichler, Jan

Comparative Analysis of Battery Degradation in Hybrid and Electric Vehicles Through Integrated System-Level Simulation

2025-24-0143

9/7/2025

This study presents the development and validation of a numerical model for a hybrid electric vehicle (HEV) and battery electric vehicle (BEV), with a focus on analyzing battery degradation under various driving scenarios and modes. The proposed model integrates a comprehensive vehicle dynamics framework with a detailed battery model to evaluate the impact of different driving conditions on battery performance and longevity. The vehicle model captures the hybrid powertrain's behavior, including energy management strategies, while the battery model incorporates electrochemical dynamics to predict degradation mechanisms such as capacity fade and resistance increase. Two primary driving scenarios are examined: urban driving, characterized by frequent stops, accelerations, and transitions between aggressive and relaxed driving styles, and long-distance highway driving, where cruising speeds and driving patterns vary. The urban scenario emphasizes the effects of stop-and-go traffic and

Martinez, Santiago, Merola, Simona, Irimescu, Adrian, Bibiloni Ipata, Sebastian

Impact of Connected and Automated Vehicles on Longitudinal and Lateral Performance of Heterogeneous Traffic Flow in Shared Autonomy on Two-Lane Highways

2025-01-8098

4/1/2025

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

Evaluating the Impact of Sensor Accuracy on Adaptive Cruise Control Performance: A Simulation Study

2025-01-8063

4/1/2025

Adaptive Cruise Control (ACC) is an advanced driver assistance system designed to manage a vehicle's longitudinal motion. Its effectiveness is critically dependent on the precision of the sensors used. While ACC algorithms are optimized for performance, the overall efficacy of the system is significantly influenced by sensor accuracy and variability. Quantifying the impact of these factors on ACC performance poses a challenge. This paper explores the effects of sensor accuracy on ACC performance through a simulation study that replicates the sensor accuracy and variability observed in realworld vehicles. Additionally, the paper examines potential strategies to mitigate performance fluctuations caused by sensor variability.

Awathe, Arpit, Varunjikar, Tejas, Raut, Abhinandan Vijay, Patel, Darsh

Modular Dynamometer Testing Framework to Evaluate Energy Impacts of Longitudinal Automated Driving Systems

2025-01-8065

4/1/2025

As longitudinal Automated Driving System (ADS) technologies, such as Adaptive Cruise Control (ACC), become more prevalent, robust testing frameworks that encompass both simulation and vehicle-in-the-loop (VIL) methodologies are essential to ensure system reliability, safety, and performance refinement. Although significant research has focused on ACC algorithm development and simulation testing, existing VIL dynamometer testing frameworks are typically tailored to specific vehicle models and sensor simulation tools. These highly customized approaches often fail to account for broader interoperability while overlooking energy consumption as a key performance metric. This paper presents a novel modular framework for ACC dynamometer testing, designed to enhance interoperability across a diverse range of vehicle platforms, simulation tools, and dynamometer facilities with a focus on evaluating impacts of automated longitudinal control on the overall energy consumption of the vehicle. The

Goberville, Nicholas, Hamilton, Kayla, Di Russo, Miriam, Jeong, Jongryeol, Das, Debashis, Ord, David, Misra, Priyashraba, Crain, Trevor

Integration of Safety Standards for a Unified Safety Framework for Automated Vehicles

2025-01-8717

4/1/2025

This paper proposes a structured safety framework tailored for the concept phase of Level 2 and Level 3 automated vehicles, addressing the unique challenges posed by these advanced systems. The framework integrates key principles from ISO 26262 and ISO 21448 to create a safety approach that spans hardware reliability, functional safety, and system performance. Central to the framework is a broad analysis that combines methodologies from System-Theoretic Process Analysis (STPA) and Hazard Analysis and Risk Assessment (HARA). This dual approach enables the identification of potential risks arising from both hardware failures and the intended functionalities of the system. The framework further details a combined specification and design process that aligns the strengths of each standard, ensuring robust sensor architectures and reliable decision-making processes. A case study on Adaptive Cruise Control with Lane Keeping is presented to demonstrate the practical implementation of the

Sari, Ayse Aysu, Soleimani, Morteza

Robust V2X Cruise Control for Class 8 Trucks in the Presence of Traffic Lights

2025-01-8033

4/1/2025

An implementation of a robust predictive cruise control method for class 8 trucks utilizing V2X communication with connected traffic lights is presented in this work. This method accounts for traffic signal phases with the goal of reducing energy consumption when possible while respecting safety concerns. Tightened constraints are created using a robust model predictive control (RMPC) framework in which constraints are modified so that the safety critical requirements are satisfied even in the presence of disturbances, while requiring only the expected bounds of the disturbances to be provided. In particular, variation in the actuator performance under different conditions presents a unique challenge for this application, which the approach applied in this work is well-suited to handle. The errors resulting from lower-level control and actuator performance are accounted for by treating them as bounded and additive disturbances on the states of the model used in the higher level MPC

Ellison, Evan, Ward, Jacob, Brown, Lowell, Bevly, David M.

Feasibility of Road Longitudinal Profiles for Automated Vehicles Based on Vehicle Dynamics

2025-01-7150

3/19/2025

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

Model-Based Vehicle Mass Estimation for Enhanced Adaptive Cruise Control Performance

02-18-02-0009

2/19/2025

This study presents the development and integration of a vehicle mass estimator into the ZF’s Adaptive Cruise Control (ACC) system. The aim is to improve the accuracy of the ACC system’s torque control for achieving desired speed and acceleration. Accurate mass estimation is critical for optimal control performance, particularly in commercial vehicles with variable loads. The incorporation of such mass estimation algorithm into the ACC system leads to significant reductions in the error between requested and measured acceleration during both flat and uphill driving conditions, with or without a preceding vehicle. The article details the estimator’s development, integration, and validation through comprehensive experimental testing. An electric front-wheel drive van was used. The vehicle’s longitudinal dynamics were modeled using D’Alembert’s principle to develop the mass estimation algorithm. This algorithm updates the mass estimate based on specific conditions: zero brake torque, high

Marotta, Raffaele, D’Itri, Valerio, Irilli, Alessandro, Peccolo, Marco

Software Architecture for Autonomous Vehicles using MATLAB Simulink

2025-28-0190

2/7/2025

Autonomous vehicles utilise sensors, control systems and machine learning to independently navigate and operate through their surroundings, offering improved road safety, traffic management and enhanced mobility. This paper details the development, software architecture and simulation of control algorithms for key functionalities in a model that approaches Level 2 autonomy, utilising MATLAB Simulink and IPG CarMaker. The focus is on four critical areas: Autonomous Emergency Braking (AEB), Adaptive Cruise Control (ACC), Lane Detection (LD) and Traffic Object Detection. Also, the integration of low-level PID controllers for precise steering, braking and throttle actuation, ensures smooth and responsive vehicle behaviour. The hardware architecture is built around the Nvidia Jetson Nano and multiple Arduino Nano microcontrollers, each responsible for controlling specific actuators within the drive-by-wire system, which includes the steering, brake and throttle actuators. Communication

Ann Josy, Tessa, Sadique, Anwar, Thomas, Merlin, Manaf T M, Ashik, Vr, Sreeraj

Neural Network-Enhanced Model Predictive Cruise Control for a Heavy Truck with LLM-Assisted Data Collection for Training

2025-01-7033

1/31/2025

Predictive Cruise Control (PCC) is a promising approach for improving fuel efficiency and reducing operational costs in heavy trucks. However, its implementation using conventional Nonlinear Model Predictive Control (NMPC) methods is hindered by computational limitations, often restricting the use of long-horizon slope information. This paper addresses these challenges by proposing a neural network-enhanced slope-adaptive NMPC framework. A Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) architecture is employed to integrate long-horizon slope information and dynamically update control parameters, effectively overcoming computational constraints of traditional NMPC. To further enhance efficiency, an automated simulation scheduling system is developed, leveraging Large Language Models (LLMs) and expert knowledge to optimize parameter tuning and streamline data collection, significantly reducing training overhead. Validation on a high-fidelity simulation platform

Han, Xiao, Song, Kang, Lv, Qing Fang, Zhang, Yi, Xie, Hui

Enhanced Adaptive Cruise Control Strategies Considering Front and Rear Vehicles

10-09-01-0007

1/29/2025

Adaptive cruise control (ACC) systems have increasingly become more robust in adapting to the motion of the preceding vehicle and providing safety and comfort to the driver. But conventional ACC hangs with a concern for rear-end safety in the presence of traffic or aggressive car maneuvers. It often leads to getting dangerously close to the vehicle behind in scenarios where there is less space and time for the rear vehicle to adjust. This research article develops an ACC approach that considers the rear vehicle in addition to the front vehicle, thereby ensuring safety with the rear vehicle without compromising the safety of the front vehicle. Two novel methodologies are devised to enhance the ACC system. The first approach involves utilizing fuzzy logic to associate the inputs with the throttle and brake based on the inference rules within a fuzzy logic controller overseeing both vehicles. The other utilizes a cascaded model predictive control (MPC) system framework that integrates a

Sharma, Vishrut, Sengupta, Somnath, Ghosh, Susenjit

A Reinforcement Learning-Based Parameter Tuning Approach for a Secure Cooperative Adaptive Cruise Control System

12-08-04-0033

1/25/2025

Connected and autonomous vehicles (CAVs) rely on communication channels to improve safety and efficiency. However, this connectivity leaves them vulnerable to potential cyberattacks, such as false data injection (FDI) attacks. We can mitigate the effect of FDI attacks by designing secure control techniques. However, tuning control parameters is essential for the safety and security of such techniques, and there is no systematic approach to achieving that. In this article, our primary focus is on cooperative adaptive cruise control (CACC), a key component of CAVs. We develop a secure CACC by integrating model-based and learning-based approaches to detect and mitigate FDI attacks in real-time. We analyze the stability of the proposed resilient controller through Lyapunov stability analysis, identifying sufficient conditions for its effectiveness. We use these sufficient conditions and develop a reinforcement learning (RL)-based tuning algorithm to adjust the parameter gains of the

Javidi-Niroumand, Farahnaz, Sargolzaei, Arman

Cooperation Dynamics in Multiagent Systems: Modeling Vehicular Cooperation through Game Theory

12-08-03-0026

12/24/2024

Cooperation lies at the core of multiagent systems (MAS) and multiagent reinforcement learning (MARL), where agents must navigate between individual interests and collective benefits. Advanced driver assistance systems (ADAS), like collision avoidance systems and adaptive cruise control, exemplify agents striving to optimize personal and collective outcomes in multiagent environments. The study focuses on strategies aimed at fostering cooperation with the aid of game-theoretic scenarios, particularly the iterated prisoner’s dilemma, where agents aim to optimize personal and group outcomes. Existing cooperative strategies, such as tit-for-tat and win-stay lose-shift, while effective in certain contexts, often struggle with scalability and adaptability in dynamic, large-scale environments. The research investigates these limitations and proposes modifications to align individual gains with collective rewards, addressing real-world dilemmas in distributed systems. By analyzing existing

Nidamanuri, Jaswanth, Sathi, Vaigarai, Shaik, Sabahat

INTEGRATING SENSOR DATA: Selecting an ADAS decision-making process

24AUTP12_01

12/1/2024

Exactly when sensor fusion occurs in ADAS operations, late or early, impacts the entire system. Governments have been studying Advanced Driver Assistance Systems (ADAS) since at least the late 1980s. Europe's Generic Intelligent Driver Support initiative ran from 1989 to 1992 and aimed “to determine the requirements and design standards for a class of intelligent driver support systems which will conform with the information requirements and performance capabilities of the individual drivers.” Automakers have spent the past 30 years rolling out such systems to the buying public. Toyota and Mitsubishi started offering radar-based cruise control to Japanese drivers in the mid-1990s. Mercedes-Benz took the technology global with its Distronic adaptive cruise control in the 1998 S-Class. Cadillac followed that two years later with FLIR-based night vision on the 2000 Deville DTS. And in 2003, Toyota launched an automated parallel parking technology called Intelligent Parking Assist on the

Ramsey, Jonathon

Study on the Test Procedure of Fuel Economy and CO ₂ Emissions for Vehicles with Adaptive Cruise Control System

2024-01-4308

11/5/2024

With advancements in the development of the automated driving technology, vehicles equipped with such technology can be observed widely in market. However, there is a lack of clarity regarding fuel consumption and emission characteristics with automated driving functions. In fact, it cannot be found that any technical papers that have conducted such an evaluation. Therefore, in this study, it was investigated that an evaluation method to understand fuel consumption and emission characteristics by using the adaptive cruise control (ACC) function. The function is one of the automated driving functions which is widely used and corresponds to Level 2 defined by SAE International (Society of Automotive Engineers). In the approach taken for this study, two vehicles were used as the real driving emission test and the preceding vehicle—equipped with a driving robot—was driven accurately to trace the speed pattern defined by the test cycle. The trailing vehicle was driven using the ACC function

Okui, Nobunori

Modelling and Analysis of a Cooperative Adaptive Cruise Control (CACC) Algorithm for Fuel Economy

2024-01-2564

4/9/2024

Connectivity in ground vehicles allows vehicles to share crucial vehicle data, such as vehicle acceleration and speed, with each other. Using sensors such as radars and lidars, on the other hand, the intravehicular distance between a leader vehicle and a host vehicle can be detected. Cooperative Adaptive Cruise Control (CACC) builds upon ground vehicle connectivity and sensor information to form convoys with automated car following. CACC can also be used to improve fuel economy and mobility performance of vehicles in the said convoy. In this paper, a CACC system is presented, where the acceleration of the lead vehicle is used in the calculation of desired vehicle speed. In addition to the smooth car following abilities, the proposed CACC also has the capability to calculate a speed profile for the ego vehicle that is fuel efficient, making it an Ecological CACC (Eco-CACC) model. Simulations were run to model and test the Eco-CACC algorithms with different lead vehicle driving behaviors

Kavas-Torris, Ozgenur, Guvenc, Levent

On-Road Testing to Characterize Speed-Following Behavior in Production Automated Vehicles

2024-01-1963

4/9/2024

A fully instrumented Tesla Model 3 was used to collect thousands of hours of real-world automated driving data, encompassing both Autopilot and Full Self-Driving modes. This comprehensive dataset included vehicle operational parameters from the data busses, capturing details such as powertrain performance, energy consumption, and the control of advanced driver assistance systems (ADAS). Additionally, interactions with the surrounding traffic were recorded using a perception kit developed in-house equipped with LIDAR and a 360-degree camera system. We collected the data as part of a larger program to assess energy-efficient driving behavior of production connected and automated vehicles. One important aspect of characterizing the test vehicle is predicting its car-following behavior. Using both uncontrolled on-road tests and dedicated tests with a lead car performing set speed maneuvers, we tuned conventional adaptive cruise control (ACC) equations to fit the vehicle’s behavior. We

Duoba, Michael, Vellamattathil Baby, Tinu, Pulpeiro Gonzalez, Jorge, HomChaudhuri, Baisravan

A Method for Determining Mileage Accumulation for Robustness Validation of Advanced Driver Assistance Systems (ADAS) Features

2024-01-1977

4/9/2024

Robustness testing of Advanced Driver Assistance Systems (ADAS) features is a crucial step in ensuring the safety and reliability of these systems. ADAS features include technologies like adaptive cruise control, lateral and longitudinal controls, automatic emergency braking, and more. These systems rely on various sensors, cameras, radar, lidar, and software algorithms to function effectively. Robustness testing aims to identify potential vulnerabilities and weaknesses in these systems under different conditions, ensuring they can handle unexpected scenarios and maintain their performance. Mileage accumulation is one of the validation methods for achieving robustness. It involves subjecting the systems to a wide variety of real-world driving conditions and driving scenarios to ensure the reliability, safety, and effectiveness of the ADAS features. Following ISO 21448 (Safety of the intended functionality-SOTIF), known hazardous scenarios can be tested and validated through robustness

Almasri, Hossam, Fan, Hsing-Hua, Mudunuri, Venkateswara Raju

Design, Prototyping, and Implementation of a Vehicle-to-Infrastructure (V2I) System for Eco-Approach and Departure through Connected and Smart Corridors

2024-01-1982

4/9/2024

The advent of Vehicle-to-Everything (V2X) communication has revolutionized the automotive industry, particularly with the rise of Advanced Driver Assistance Systems (ADAS). V2X enables vehicles to communicate not only with each other (V2V) but also with infrastructure (V2I) and pedestrians (V2P), enhancing road safety and efficiency. ADAS, which includes features like adaptive cruise control and automatic intersection navigation, relies on V2X data exchange to make real-time decisions and improve driver assistance capabilities. Over the years, the progress of V2X technology has been marked by standardization efforts, increased deployment, and a growing ecosystem of connected vehicles, paving the way for safer and more efficient automated navigation. The EcoCAR Mobility Challenge was a 4-year student competition among 12 universities across the United States and Canada sponsored by the U.S. Department of Energy, MathWorks, and General Motors, where each team received a 2019 Chevrolet

Chowduri, Suhrit, Midlam-Mohler, Shawn, Singh, Karun Prateek

Expanding the Use of Vehicle Specific Power in Analysis of Platoon Performance

2024-01-2057

4/9/2024

Platooning is a coordinated driving strategy by which following trucks are placed into the wake of leading vehicles. Doing this leads to two primary benefits. First, the vehicles following are shielded from aerodynamic drag by a “pulling” effect. Secondly, by placing vehicles behind the leading truck, the leading vehicles experience a “pushing” effect. The reduction in aerodynamic drag leads to reduced fuel usage and, consequently, reduced greenhouse gas emissions. To maximize these effects, the inter-vehicle distance, or headway, needs to be minimized. In current platooning strategy iterations, Coordinated Adaptive Cruise Control (CACC) is used to maintain close following distances. Many of these strategies utilize the fuel rate signal as a controller cost function parameter. By using fuel rate, current control strategies have limited applicability to non-conventional powertrains. Vehicle Specific Power (VSP) has shown promise as a metric by which the performance of such controllers

Bentley, John, Stegner, Evan, Bevly, David M., Hoffman, Mark

Enhancing Lateral Stability in Adaptive Cruise Control: A Takagi-Sugeno Fuzzy Model-Based Strategy

2024-01-1962

4/9/2024

Adaptive cruise control is one of the key technologies in advanced driver assistance systems. However, improving the performance of autonomous driving systems requires addressing various challenges, such as maintaining the dynamic stability of the vehicle during the cruise process, accurately controlling the distance between the ego vehicle and the preceding vehicle, resisting the effects of nonlinear changes in longitudinal speed on system performance. To overcome these challenges, an adaptive cruise control strategy based on the Takagi-Sugeno fuzzy model with a focus on ensuring vehicle lateral stability is proposed. Firstly, a collaborative control model of adaptive cruise and lateral stability is established with desired acceleration and additional yaw moment as control inputs. Then, considering the effect of the nonlinear change of the longitudinal speed on the performance of the vehicle system. And the input penalty factor of the adaptive cruise control system is designed as a

Yan, Yang, Xin, Yafei, Zheng, Hongyu

An Evaluation of the Bosch Radar-Based Adaptive Cruise Control System on a 2022 Ducati Multistrada V4S

2024-01-2478

4/9/2024

Starting in 2021 Ducati introduced a radar based adaptive cruise control (ACC) developed by Bosch. It utilizes a single radar unit on the front of the motorcycle to detect the presence of vehicles ahead, as well as the separation distance. The system is not an automatic emergency braking (AEB) system but does have similar features. The Ducati ACC system does have limitations, some of which are explored in the subject research. Initial testing was conducted to document the engine braking in each gear. Following initial testing, several tests were performed at high closing speeds of over 100 kph. It was determined that at a closing speed of approximately 100 kph the ACC system would not react to a moving vehicle ahead. Additionally, the system will not react to a stopped vehicle or a “swerve-around” stopped vehicle that suddenly appears. Another series of tests were performed while actively following a vehicle at various speeds, with the front vehicle suddenly slowing to a stop and

Fatzinger, Edward C., Gonzaga, William

Employing a Model of Computation for Testing and Verifying the Security of Connected and Autonomous Vehicles

12-07-03-0020

3/5/2024

Testing and verifying the security of connected and autonomous vehicles (CAVs) under cyber-physical attacks is a critical challenge for ensuring their safety and reliability. Proposed in this article is a novel testing framework based on a model of computation that generates scenarios and attacks in a closed-loop manner, while measuring the safety of the unit under testing (UUT), using a verification vector. The framework was applied for testing the performance of two cooperative adaptive cruise control (CACC) controllers under false data injection (FDI) attacks. Serving as the baseline controller is one of a traditional design, while the proposed controller uses a resilient design that combines a model and learning-based algorithm to detect and mitigate FDI attacks in real-time. The simulation results show that the resilient controller outperforms the traditional controller in terms of maintaining a safe distance, staying below the speed limit, and the accuracy of the FDI estimation.

Alnaser, Ala Jamil, Holland, James, Sargolzaei, Arman

Letter from the Focus Issue Editors

14-13-01-0001

2/2/2024

Letter from the Focus Issue Editors

Song, Ziyou, Feng, Shuo, Wu, Guoyuan, Li, Zhaojian

Implementation of Predictive Adaptive Cruise Control Strategy Based on ADAS Map

2023-01-7111

12/31/2023

Heavy vehicles are major fuel consumers in road transportation, and the traditional way to reduce fuel consumption is to reduce weight, resistance, improve mechanical transmission efficiency, and improve engine thermal efficiency. However, European heavy-duty truck companies took the lead in realizing predictive cruise control (PCC) technology on the basis of cruise through intelligent network technology, based on ADAS maps, and achieved good fuel saving effects. In this paper, by studying the fuel consumption characteristics of trucks, designing the dynamic parameters of the load and whole vehicle, the predictive adaptive cruise control (PACC) technology is realized based on the predictive cruise strategy, and the statistics of fuel saving rate under different cruise ratio conditions are analyzed through the big data platform.

Qian, Guoping, Lu, Zhenghua, Tian, Juntao, Liu, Lianfang, Xi, Chong, Zhou, Xiaoying

An Energy-Efficient Merge-Aware Cruise Control Method for Connected Electric Vehicles

14-13-01-0010

12/28/2023

This article presents a merge-aware cruise control method that incorporates vehicle-to-vehicle (V2V) information and aims at improving the energy efficiency of vehicles and reducing speed disruptions of merging traffic during highway merges. During the events of highway merges, the gap between the ego and the preceding vehicle reduces drastically, which can result in sudden braking of the ego vehicle and thus reduction of its energy efficiency. We propose a rather simple cruise control algorithm to eliminate such sudden variations in the gap and velocity with respect to the preceding vehicle during highway merges, thus reducing the large accelerations and braking during such events and thereby improving energy efficiency. The proposed algorithm incorporates future traffic information and has computational requirements similar to adaptive cruise control methods, hence it is real-time applicable. Data used in this article are taken from on-road experiments using a 2020 Tesla Model 3

Vellamattathil Baby, Tinu, HomChaudhuri , Baisravan

Closet In-Path Vehicle Detection and Recognition Algorithm Based on Camera and Millimeter-Wave Radar Fusion

12-07-02-0010

10/11/2023

The closet in-path vehicle (CIPV) is recognized relying on the detection results for road lane lines in most current ACC system, which may not work well in the poor conditions, for example, unclear road lane lines, low light level, bad weather, and so on. To solve this problem, the article proposes a sensor fusion-based CIPV recognition algorithm independent of road lane lines. First, a robust Kalman filter based on the global coordinate system is designed to fuse the millimeter-wave radar and camera targets. The fusion algorithm can dynamically adjust the covariance matrix of sensor observations to avoid the influence of anomalous observations on the fusion results. Stable detection of targets by the fusion algorithm is the basis of the CIPV recognition algorithm. Then, the CIPV recognition algorithm generates virtual lane lines using the motion parameters of self-vehicle or the driving trajectory of vehicle target and develops a mode switch strategy for virtual lane lines generation

Yang, Yifei, Zhao, Zhiguo, Yu, Qin, Deng, Yunhong, Li, Wenchang

Vinfast needs to slow down

23AUTP09_11

9/1/2023

Startups are famous for moving quickly. Vinfast may want to slow things down. It was only 2019 when the Vietnamese company built its first cars, rebodied versions of gasoline BMWs that became hits in its home market. Vinfast speedily developed four electric SUVs, including the inaugural VF8 that SAE Media drove in southern California. At the same time, a cargo ship docked near San Francisco, carrying nearly 2,000 VF8s for customers in California and Canada. The next day, Vinfast announced plans to go public via a SPAC merger. And Vinfast recently broke ground on a $4 billion factory in North Carolina, targeting 150,000 units of annual capacity and more than 7,000 jobs.

Ulrich, Lawrence

Battery Electric Vehicle Control Strategy for String Stability Based on Deep Reinforcement Learning in V2V Driving

2023-24-0173

8/28/2023

This works presents a Reinforcement Learning (RL) agent to implement a Cooperative Adaptive Cruise Control (CACC) system that simultaneously enhances energy efficiency and comfort, while also ensuring string stability. CACC systems are a new generation of ACC which systems rely on the communication of the so-called ego-vehicle with other vehicles and infrastructure using V2V and/or V2X connectivity. This enables the availability of robust information about the environment thanks to the exchange of information, rather than their estimation or enabling some redundancy of data. CACC systems have the potential to overcome one typical issue that arises with regular ACC, that is the lack of string stability. String stability is the ability of the ACC of a vehicle to avoid unnecessary fluctuations in speed that can cause traffic jams, dampening these oscillations along the vehicle string rather than amplifying them. In this work, a real-time ACC for a Battery Electric Vehicle, based on a Deep

Borneo, Angelo, Miretti, Federico, Acquarone, Matteo, Misul, Daniela

Using Distributed Autonomous Adaptive Cruise Control Vehicles to Mitigate Congestion in a Two-Lane Traffic Flow

2023-01-5055

8/22/2023

Steady advances in autonomous vehicle development are expected to lead to improved traffic flow in terms of string stability compared with that for human-driven vehicles. Fluctuation in intervehicle distances among a group of vehicles without string stability is amplified as it propagates upstream (rearward), which may cause traffic congestion. Since it will take a few decades for autonomous vehicles to replace all human-driven vehicles, it is important to tackle the problem of traffic congestion in a mixed flow of human-driven and autonomous vehicles. Communication technologies such as fifth-generation mobile communication systems, which are improving rapidly, enable vehicle-to-vehicle communication with a sufficiently small delay. We previously reported a strategy based on vehicle-to-vehicle communication for avoiding traffic congestion by using leader–follower control, which is a distributed autonomous control strategy. However, it was designed and evaluated for single-lane traffic

Kurishige, Masahiko

A Review of Dynamic State Estimation for the Neighborhood System of Connected Vehicles

10-07-03-0023

7/28/2023

Precise vehicle state and the surrounding traffic information are essential for decision-making and dynamic control of intelligent connected vehicles. Tremendous research efforts have been devoted to developing state estimation techniques. This work investigates the research progress in this field over recent years. To be able to describe the state of multiple traffic elements uniformly, the concept of a vehicle neighborhood system is proposed to describe the system composed of vehicles and their surrounding traffic elements and to distinguish it from the traditional macroscopic traffic research field. In this work, the vehicle neighborhood system consists of three main traffic elements: the host vehicle, the preceding vehicle, and the road. Therefore, a review of state estimation methods for the vehicle neighborhood system is presented around the three traffic objects mentioned earlier. This article performs a comprehensive analysis of these approaches and depicts their strengths and

Wang, Yan, Wei, Henglai, Yang, Lie, Hu, Binbin, Lv, Chen

Evaluation of Longitudinal ADAS Functions for Fuel Economy Improvement of Class 8 Long Haul Trucks

2023-01-0217

4/11/2023

Fuel economy improvement of Class 8 long-haul trucks has been a constant topic of discussion in the commercial vehicle industry due to the significant potential it offers in reducing GHG emissions and operational costs. Among the different vehicle categories in on-road transportation, Class 8 long-haul trucks are a significant contributor to overall GHG emissions. Furthermore, with the upcoming 2027 GHG emission and low-NOx regulations, advanced powertrain technologies will be needed to meet these stringent standards. Connectivity-based powertrain optimization is one such technology that many fleets are adopting to achieve significant fuel savings at a relatively lower technology cost. With advancements in vehicle connectivity technologies for onboard computing and sensing, the full potential of connected vehicles in reducing fuel consumption can be realized through V2X (Vehicle-to-Everything) communication. Upcoming road grade, traffic lights and lead vehicle speeds can be utilized to

Paul, Sumit, Goyal, Vasu, Joshi, Satyum, Franke, Michael, Tomazic, Dean, Zeman, Jonathan

Comparing the Performance of Different Heavy Duty Platooning Control Strategies

2023-01-0895

4/11/2023

Platooning is a promising technology which can mitigate greenhouse gas impacts and reduce transportation energy consumption. Platooning is a coordinated driving strategy where trucks align themselves in order to realize aerodynamic benefits to reduce required motive force. The aerodynamic benefit is seen as either a “pull” effect experienced by the following vehicles or a “push” effect experienced by the leader. The energy savings magnitude increases nonlinearly as headway (following distance) is reduced [1]. In efforts to maximize energy savings, cooperative adaptive cruise control (CACC) is utilized to maintain relatively short headways. However, when platooning is attempted in the real world, small transient accelerations caused by imperfect control result in observed energy savings being less than expected values. This study analyzes the performance of a recently developed nonlinear model predictive control (NMPC) platooning strategy over challenging terrain. The NMPC strategy is

Bentley, John William, Snitzer, Philip, Stegner, Evan, Bevly, David M., Hoffman, Mark

New Controller Evaluation Techniques for Autonomously Driven Heavy-Duty Convoys

2023-01-0688

4/11/2023

Platooning vehicles present novel pathways to saving fuel during transportation. With the rise of autonomous solutions, platooning becomes an increasingly apparent sector requiring the application of this new technology. Platooning vehicles travel together intending to reduce aerodynamic resistance during operation. Drafting allows following vehicles to increase fuel economy and save money on refueling, whether that be at the pump or at a charging station. However, autonomous solutions are still in infancy, and controller evaluation is an exciting challenge proposed to researchers. This work brings forth a new application of an emissions quantification metric called vehicle-specific power (VSP). Rather than utilize its emissions investigative benefits, the present work applies VSP to heterogeneous Class 8 Heavy-Duty truck platoons as a means of evaluating the efficacy of Cooperative Adaptive Cruise Control (CACC). VSP creates a bridge between types of passenger vehicles to compare

Snitzer, Philip, Stegner, Evan, Bentley, John, Bevly, David M., Hoffman, Mark

Drive-Thru Climate Tunnel: A Proposed Method to Study ADAS Performance in Adverse Weather

2023-01-0827

4/11/2023

The advancement of Advanced Driver Assistance System (ADAS) technologies offers tremendous benefits. ADAS features such as emergency braking, blind-spot monitoring, lane departure warning, adaptive cruise control, etc., are promising to lower on-road accident rates and severity. With a common goal for the automotive industry to achieve higher levels of autonomy, maintaining ADAS sensor performance and reliability is the core to ensuring adequate ADAS functionality. Currently, the challenges faced by ADAS sensors include performance degradation in adverse weather conditions and a lack of controlled evaluation methods. Outdoor testing encounters repeatability issues, while indoor testing with a stationary vehicle lacks realistic conditions. This study proposes a hybrid method to combine the advantages of both outdoor and indoor testing approaches in a Drive-thru Climate Tunnel (DCT). The proposed DCT features a test section that is isolated from the surrounding environment and allows a

Pao, Wing Yi, Li, Long, Agelin-Chaab, Martin, Komar, John

Research on Cooperative Adaptive Cruise Control (CACC) Based on Fuzzy PID Algorithm

2023-01-0682

4/11/2023

For cooperative adaptive cruise control (CACC) system, a robust following control algorithm based on fuzzy PID principle is adopted in this paper. Firstly, a nonlinear vehicle dynamics model considering the lag of driving force and acceleration constraints was established. Then, with the vehicle’s control hierarchic, the upper controller takes the relative speed between vehicles and the spacing error as inputs to output the following vehicle's target acceleration, while the lower controller takes the target acceleration as inputs and the throttle opening and brake master cylinder pressure as outputs. For the setting of target spacing, this paper additionally considers the relative speed between vehicles and the acceleration of the front vehicle. Through testing, compared with the traditional variable safety distance model, the average distance reduces by 5.43% when leading vehicle is accelerating, while increases by 2.74% in deceleration. For the fixed-speed cruise mode, a set of logic

Zhu, Mingyang, Tan, Gangfeng

Utilizing Speed Information Forecast in Energy Optimization of an Electric Vehicle with Adaptive Cruise Controller

2023-01-0685

4/11/2023

The efficiency in energy consumption of an electric vehicle (EV) has significant value to both vehicle manufacturers and vehicle owners. Such efficiency will directly impact the cost of energy and vehicle range while relieving the stringent requirements on the DC motor and battery specs. Nowadays, with the development of advanced driver assistance systems (ADAS), such as adaptive cruise control (ACC) or cooperative adaptive cruise control (CACC), drivers enjoy a much safer driving experience. ADAS capabilities in sensory, computing and communication can be leveraged in EVs for the purpose of optimizing energy consumption. This paper introduces an energy-optimized ACC platform, which utilizes a forecast of the speed profile of the host vehicle in a short (few seconds) horizon. Such speed information can be available through ADAS or similar systems. This paper focuses on optimization in longitudinal tracks. We consider ten different drive-cycles in several driving scenarios, such as

Shahram, Shahriar, Pourmohammadi Fallah, Yaser

Testing of Heavy Truck Advanced Driver Assistance Systems and Crash Mitigation Systems

2023-01-0010

4/11/2023

Modern heavy vehicles may be equipped with an Advanced Driver Assistance System (ADAS) designed to increase highway safety. Depending on the vehicle or manufacturer, these systems may detect objects in a driver’s blind spot, provide an alert when the ADAS determines that the vehicle is leaving its lane of travel without the use of a turn signal, or notify the driver when certain road signs are detected. ADASs also include adaptive cruise control, which adjusts the vehicle’s set cruise speed to maintain a safe following distance when a slower vehicle is detected ahead of the truck. In addition, the ADAS may have a Collision Mitigation System (CMS) component that is designed to help drivers respond to roadway situations and reduce the severity of crashes. CMSs typically use radar or a combination of radar and optical technologies to detect objects such as vehicles or pedestrians in the vehicle’s path. If the CMS determines that a collision event is likely, interventions such as audible

Austin, Timothy, Grimes, Wesley, Cheek, Timothy, Plant, David, Steiner, John, Higgins, Bradley, Lombardi, Kristina, DiSogra, Matthew, Wilcoxson, Gregory

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