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This book contains 63 papers covering the past 11 years (1996-2006) of research on the progress and challenges in the design of Adaptive Cruise Control (ACC) systems and components. Introduced in the automotive market in 1995, ACC takes advantage of the functions of several existing electronic control units and adds a sensor for measuring distance, relative speed, and lateral position of potential target vehicles using laser optics or millimeter waves.

Subjects covered include:

- ACC sensors overview
- Hybrid ACC systems
- Interactive cruise control
- Predictive safety systems
- Brake actuation
- ACC radar sensors
- Vision sensors
- Miscellaneous ACC sensors

The book also includes editor Ronald K. Jurgen's introduction ("Adaptive Cruise Control: Still Evolving") and a concluding chapter on the current state of ACC and what can be expected in the future.


Motorcars engineering --- remmen --- radars --- ACC (adaptive cruise control) --- veiligheid (autotechnologie) --- hybridevoertuigen --- auto's --- sensoren

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Hybrid drives and the operation of hybrid vehicles are characteristic of contemporary automotive technology. Together with the electronic driver assistant systems, hybrid technology is of the greatest importance and both cannot be ignored by today’s car drivers. This technical reference book provides the reader with a firsthand comprehensive description of significant components of automotive technology. All texts are complemented by numerous detailed illustrations. Contents History of the automobile.- History of the Diesel engine.- Areas of use for Diesel engines.- Basic principles of the Diesel engine.- Basic principles of Diesel fuel-injection.- Basic principles of the gasoline engine.- Inductive ignition system.- Transmissions for motor vehicles.- Motor vehicle safety.- Basic principles of vehicle dynamics.- Car braking systems.- Vehicle electrical systems.- Overview of electrical and electronic systems in the vehicle.- Control of gasoline engines.- Control of Diesel engines.- Lighting technology.- Electronic stability program.- Adaptive cruise control.- Occupant-protection systems.- Hybrid drives.- Operation of hybrid vehicles.- Regenerative braking system.- Service technology. The target groups Motor-vehicle technicians in education and vocational training Master-mechanics and technicians in garage-workshops Teachers and lecturers in vocational schools Students at universities and technical colleges And all those interested in automotive engineering About the Bosch Group Bosch is the world´s largest independent supplier of parts and equipment for motor vehicles. Innovations by Bosch have shaped the development of the automobile. Bosch´s dominant technological role in many fields is demonstrated by the fact that it has the most patent applications in automotive engineering in Germany, to the European Patent Office and in the USA.

Applied physical engineering --- Motorcars engineering --- Transport engineering --- remmen --- ontsteking (autotechnologie) --- ACC (adaptive cruise control) --- hybridevoertuigen --- motorrijtuigen --- elektronica --- machines --- ingenieurswetenschappen --- auto's --- dieselmotoren

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This fundamental work explains in detail systems for active safety and driver assistance, considering both their structure and their function. These include the well-known standard systems such as Anti-lock braking system (ABS), Electronic Stability Control (ESC) or Adaptive Cruise Control (ACC). But it includes also new systems for protecting collisions protection, for changing the lane, or for convenient parking. The book aims at giving a complete picture focusing on the entire system. First, it describes the components which are necessary for assistance systems, such as sensors, actuators, mechatronic subsystems, and control elements. Then, it explains key features for the user-friendly design of human-machine interfaces between driver and assistance system. Finally, important characteristic features of driver assistance systems for particular vehicles are presented: Systems for commercial vehicles and motorcycles.

Applied physical engineering --- Transport engineering --- Programming --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- beeldverwerking --- ACC (adaptive cruise control) --- ADAS (advanced driver assistance system) --- automatisering --- informatica --- motorrijtuigen --- KI (kunstmatige intelligentie) --- ingenieurswetenschappen --- robots --- signaalverwerking --- interfaces

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According to the National Research Council, the use of embedded systems throughout society could well overtake previous milestones in the information revolution. Mechatronics is the synergistic combination of electronic, mechanical engineering, controls, software and systems engineering in the design of processes and products. Mechatronic systems put “intelligence” into physical systems. Embedded sensors/actuators/processors are integral parts of mechatronic systems. The implementation of mechatronic systems is consistently on the rise. However, manufacturers are working hard to reduce the implementation cost of these systems while trying avoid compromising product quality. One way of addressing these conflicting objectives is through new automatic control methods, virtual sensing/estimation, and new innovative hardware topologies.

independent-wheel drive --- steering assistance --- nonlinear system --- active disturbance rejection control --- smooth road feeling --- city bus transport --- electric vehicles --- electrification --- software tool --- planning --- control --- charging management --- simulation --- analysis --- energy management --- hybrid electric vehicle --- powertrain electrification --- equivalent consumption minimization --- supercharging --- hardware-in-the-loop experiments --- driving force distribution --- decentralized traction system --- 4WD electric vehicle --- energy efficiency --- traction control --- efficiency optimization --- air mobility --- fuel cell hybrid aircraft --- stochastic optimal control --- drift counteraction optimal control --- normal force estimation --- unbiased minimum variance estimation --- controller output observer --- youla parameterization --- adaptive cruise control --- automated driving --- energy-saving --- fuel-saving --- optimal control --- passenger comfort --- new energy vehicles --- speed prediction --- macroscopic traffic model --- traffic big-data --- deep learning --- vehicle lateral dynamic and control --- unresolved issues --- application of speed prediction --- electric vehicle --- hybrid vehicle --- lithium ion --- ultracapacitor --- battery aging --- EHB --- EMB --- EWB --- system modeling --- bond graph --- optimization --- control design --- Youla parameterization --- robust control --- nonlinear optimization --- brake-by-wire --- actuator --- electro-mechanical brake --- electronic wedge brake --- electro-hydraulic brake --- n/a

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Electrification, automation of vehicle control, digitalization and new mobility are the mega-trends in automotive engineering, and they are strongly connected. While many demonstrations for highly automated vehicles have been made worldwide, many challenges remain in bringing automated vehicles to the market for private and commercial use. The main challenges are as follows: reliable machine perception; accepted standards for vehicle-type approval and homologation; verification and validation of the functional safety, especially at SAE level 3+ systems; legal and ethical implications; acceptance of vehicle automation by occupants and society; interaction between automated and human-controlled vehicles in mixed traffic; human–machine interaction and usability; manipulation, misuse and cyber-security; the system costs of hard- and software and development efforts. This Special Issue was prepared in the years 2021 and 2022 and includes 15 papers with original research related to recent advances in the aforementioned challenges. The topics of this Special Issue cover: Machine perception for SAE L3+ driving automation; Trajectory planning and decision-making in complex traffic situations; X-by-Wire system components; Verification and validation of SAE L3+ systems; Misuse, manipulation and cybersecurity; Human–machine interactions, driver monitoring and driver-intention recognition; Road infrastructure measures for the introduction of SAE L3+ systems; Solutions for interactions between human- and machine-controlled vehicles in mixed traffic.

Technology: general issues --- History of engineering & technology --- automated driving --- scenario-based testing --- software framework --- traffic signs --- ADAS --- traffic sign recognition system --- cooperative perception --- ITS --- digital twin --- sensor fusion --- edge cloud --- autonomous drifting --- model predictive control (MPC) --- successive linearization --- adaptive control --- vehicle motion control --- varying road surfaces --- vehicle dynamics --- Mask R-CNN --- transfer learning --- inverse gamma correction --- illumination --- instance segmentation --- pedestrian custom dataset --- deep learning --- wheel loaders --- throttle prediction --- state prediction --- automation --- safety validation --- automated driving systems --- decomposition --- modular safety approval --- modular testing --- fault tree analysis --- adaptive cruise control --- informed machine learning --- physics-guided reinforcement learning --- safety --- autonomous vehicles --- autonomous conflict management --- UTM --- UAV --- UGV --- U-Space --- framework development --- lane detection --- simulation and modelling --- multi-layer perceptron --- convolutional neural network --- driver drowsiness --- ECG signal --- heart rate variability --- wavelet scalogram --- automated driving (AD) --- driving simulator --- expression of trust --- acceptance --- simulator case study --- NASA TLX --- advanced driver assistant systems (ADAS) --- system usability scale --- driving school --- virtual validation --- ground truth --- reference measurement --- calibration method --- simulation --- traffic evaluation --- simulation and modeling --- connected and automated vehicle --- driver assistance system --- virtual test and validation --- radar sensor --- physical perception model --- virtual sensor model --- automated driving --- scenario-based testing --- software framework --- traffic signs --- ADAS --- traffic sign recognition system --- cooperative perception --- ITS --- digital twin --- sensor fusion --- edge cloud --- autonomous drifting --- model predictive control (MPC) --- successive linearization --- adaptive control --- vehicle motion control --- varying road surfaces --- vehicle dynamics --- Mask R-CNN --- transfer learning --- inverse gamma correction --- illumination --- instance segmentation --- pedestrian custom dataset --- deep learning --- wheel loaders --- throttle prediction --- state prediction --- automation --- safety validation --- automated driving systems --- decomposition --- modular safety approval --- modular testing --- fault tree analysis --- adaptive cruise control --- informed machine learning --- physics-guided reinforcement learning --- safety --- autonomous vehicles --- autonomous conflict management --- UTM --- UAV --- UGV --- U-Space --- framework development --- lane detection --- simulation and modelling --- multi-layer perceptron --- convolutional neural network --- driver drowsiness --- ECG signal --- heart rate variability --- wavelet scalogram --- automated driving (AD) --- driving simulator --- expression of trust --- acceptance --- simulator case study --- NASA TLX --- advanced driver assistant systems (ADAS) --- system usability scale --- driving school --- virtual validation --- ground truth --- reference measurement --- calibration method --- simulation --- traffic evaluation --- simulation and modeling --- connected and automated vehicle --- driver assistance system --- virtual test and validation --- radar sensor --- physical perception model --- virtual sensor model