Gotowe bibliografie tematyczne / Intelligent cruise control

Gotowa bibliografia na temat „Intelligent cruise control”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 20 lutego 2023

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Artykuły w czasopismach na temat "Intelligent cruise control"

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Ioannou, P. A., i C. C. Chien. "Autonomous intelligent cruise control". IEEE Transactions on Vehicular Technology 42, nr 4 (1993): 657–72. http://dx.doi.org/10.1109/25.260745.

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Björnberg, A. "Control Design for Autonomous Intelligent Cruise Control". IFAC Proceedings Volumes 27, nr 12 (sierpień 1994): 835–40. http://dx.doi.org/10.1016/s1474-6670(17)47576-8.

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Palmquist, U. "Intelligent cruise control and roadside information". IEEE Micro 13, nr 1 (luty 1993): 20–28. http://dx.doi.org/10.1109/40.210522.

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Song, Gui Qiu, Ying Yang, Haiqiang Hang i Shu Hong Wang. "Study on Vehicle Collision-Avoiding Radar and Intelligent Cruise Control System". Key Engineering Materials 297-300 (listopad 2005): 311–15. http://dx.doi.org/10.4028/www.scientific.net/kem.297-300.311.

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An integrated vehicle collision-avoiding radar and intelligent cruise control system is proposed. Collision-avoiding radar measures the distance of a vehicle-to-vehicle and roadblocks automatically, and then Cruise Control System design optimal acceleration for the vehicle-to-vehicle distance control. An integrated radar and intelligent cruise control law has been proposed. Using this control law, the brake controller forces the vehicle acceleration to converge to the desired acceleration. It has been shown via the simulations with good distance control performance in both high speed and low speed stop and good driving situations. Vehicle Collision-avoiding Radar System and Intelligent Cruise Control System have very important significance on improving vehicle active safety and reducing driver’s fatigue. Collision-avoiding Radar System and Intelligent Cruise Control System will be the necessary equipment in future vehicle.
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Bian, Chentong, Guodong Yin, Liwei Xu i Ning Zhang. "Bidirectional adaptive cruise control for intelligent vehicles". International Journal of Heavy Vehicle Systems 28, nr 4 (2021): 467. http://dx.doi.org/10.1504/ijhvs.2021.118238.

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Zhang, Ning, Liwei Xu, Guodong Yin i Chentong Bian. "Bidirectional adaptive cruise control for intelligent vehicles". International Journal of Heavy Vehicle Systems 28, nr 4 (2021): 467. http://dx.doi.org/10.1504/ijhvs.2021.10041913.

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Zhang, Xiwen, i Thomas Benz. "SIMULATION AND EVALUATION OF “INTELLIGENT CRUISE CONTROL”". I V H S Journal 1, nr 2 (styczeń 1993): 181–90. http://dx.doi.org/10.1080/10248079308903791.

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Han, Yong Qi, Li Ying Cao i Chun Guang Bi. "Research of an Automatic Cruise Intelligent Vehicle Control Program". Advanced Materials Research 1049-1050 (październik 2014): 1030–32. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.1030.

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Control core of Intelligent automatic patrol car track (photovoltaic group) uses G128 chip, which function modules include: laser sensor, speed control module, the servo control module. The basic principle is that the control center sends a signal to the laser sensor module, which controls laser tube launching and receives data by laser receiver returning. According to the data of the receiver, the core module synchronously controls servo module and the speed module. The main program uses a PID algorithm by C language.
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Minderhoud, Michiel M., i Piet H. L. Bovy. "Impact of Intelligent Cruise Control on Motorway Capacity". Transportation Research Record: Journal of the Transportation Research Board 1679, nr 1 (styczeń 1999): 1–9. http://dx.doi.org/10.3141/1679-01.

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Darbha, Swaroop, i K. R. Rajagopal. "Intelligent cruise control systems and traffic flow stability". Transportation Research Part C: Emerging Technologies 7, nr 6 (grudzień 1999): 329–52. http://dx.doi.org/10.1016/s0968-090x(99)00024-8.

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Rozprawy doktorskie na temat "Intelligent cruise control"

1

Patterson, Angela K. "Intelligent Cruise Control System Impact Analysis". Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36966.

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Intelligent cruise control (ICC) has the potential to impact both roadway throughput and safety by assisting drivers in maintaining safe headways. This thesis explores this potential through comparisons of ICC to conventional cruise control (CCC) and manual driving. Accordingly, descriptions are given of both CCC and ICC systems. Furthermore, descriptions of ICC evaluation studies and car-following models are presented.

The evaluation of ICC is conducted using data collected as part of the Field Operational Test (FOT) performed in Ann Arbor, Michigan. Two levels of analysis are presented in this thesis. The first level of analysis compares the usage of ICC to CCC from a macro level. This study demonstrated that ICC was used more along similar trips. In addition, it was shown that there was no difference in usage of the ON, SET, CANCEL and RESUME buttons. ICC resulted in a higher usage of the ACCEL button and a lower usage of the COAST button compared to CCC. Furthermore, the number of brake interventions while ICC was engaged was higher than CCC. Lastly, the macro-level analysis indicated that there was no difference in the number of near encounters for ICC and CCC. The second analysis makes comparisons at a micro level. The most probable speed, acceleration and headway for each driving mode as well as the probability of using cruise control (based on speed) were determined. The probability of ICC use exceeded CCC use for every freeway speed bin and all but two high-speed arterial speed bins. Finally, a car-following behavior comparison was performed. Manual driving resulted in larger headway values for speeds less than 80 km/h. The ICC speed-headway curve was similar to the CCC speed-headway curve created from high-speed arterial data. The mean headway-speed charts, however, indicated that ICC was more similar to manual driving. Exploration into the specific differences is needed in order to determine the impact of ICC on system safety.
Master of Science

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Yan, Jingsheng. "Platoon modal operations under vehicle autonomous adaptive cruise control model". Thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-07102009-040612/.

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Sun, Xi. "An impedance model approach for adaptive cruise control". To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2009. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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Spaeth, Mark Christian 1974. "A low-cost hybrid vision system for intelligent cruise control applications". Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/16728.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
Includes bibliographical references (p. 95-96).
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
In recent years, automobiles have become increasingly computerized and varying degrees of intelligent control has been integrated into automotive systems. A natural extension of this trend is full intelligent and autonomous control of vehicle by onboard computer systems. This thesis presents the design, development, and construction of a low-cost, low-power vision system suitable for on-board automated vehicle systems such as intelligent cruise control. The apparatus leverages vision algorithms, simplified by a prescribed camera geometry, to compute depth maps in real-time, given the input from three imagers mounted on the vehicle. The early vision algorithms are implemented using Dr. David Martin's ADAP mixed signal array processor. The back-end algorithms are mplemented in software on PC for simplicity, but could easily be implemented in hardware in a later design. The final apparatus was able to compute depth maps at a rate of 24 frames per second, limited only by the interrupt latency of the PC executing the algorithms.
by Mark Christian Spaeth.
S.M.
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Chen, Shih-Ken. "Estimation of car-following safety : application to the design of intelligent cruise control". Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/28159.

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Hitchings, Mark R., i n/a. "Distance and Tracking Control for Autonomous Vehicles". Griffith University. School of Microelectronic Engineering, 1999. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20050902.084155.

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The author's concept of the distance and tracking control problem for autonomous vehicles relates to the cooperative behaviour of two successive vehicles travelling in the same environment. This behaviour requires one vehicle, designated the leader to move autonomously around it's environment with other vehicles, designated followers maintaining a coincident travel path and desired longitudinal distance with respect to the leader. Distance and tracking control is beneficial in numerous applications including guiding autonomous vehicles in Intelligent Transport Systems (ITS) which increases traffic safety and the capacity of pre-existing road infrastructure. Service robotics may also benefit from the cost savings and flexibility offered by distance and tracking control which enables a number of robots to cooperate together in order to achieve a task beyond the capabilities ofjust one robot. Using a distance and tracking control scheme an intelligent leader robot may guide a number of less intelligent (and therefore less costly and less complex) followers to a work-site to perform a task. The author's approach to the distance and tracking control problem consisted of two separate solutions - an initial solution used as a starting point and learning experience and a second, more robust, fuzzy control-based solution. This thesis briefly describes the initial solution, but places a greater emphasis on the second solution. The reason for this is that the fuzzy control-based solution offers significant improvement on the initial solution and was developed based on conclusions drawn from the initial solution. Most implementations of distance and tracking control, sometimes referred to as Intelligent Cruise Control (ICC) or platooning, are limited to longitudinal distance control only. The leader tracking control is performed either implicitly by a separate lane-following control system or by human drivers. The fuzzy control-based solution offered in this thesis performs both distance and tracking control of an autonomous follower vehicle with respect to a leader vehicle in front of it. It represents a simple and cost effective solution to the requirements of autonomous vehicles operating in ITS schemes - particularly close formation platooning. The follower tracks a laser signal emitted by the leader and monitors the distance to the follower at the same time using ultrasonic ranging techniques. The follower uses the data obtained from these measuring techniques as inputs to a fuzzy controller algorithm to adjust its distance and alignment with respect to the leader. Other systems employed on road vehicles utilise video-based leader tracking, or a range of lane-following methods such as magnetometer or video-based methods. Typically these methods are disadvantaged by substantial unit and/or infrastructure costs associated with their deployment. The limitations associated with the solutions presented in this thesis arise in curved trajectories at larger longitudinal distance separations between vehicles. The effects of these limitations on road vehicles has yet to be fully quantified, however it is thought that these effects would not disadvantage its use in close formation platooning. The fuzzy control-based distance and tracking control solution features two inputs, which are the distance and alignment of the follower with respect to the leader. The fuzzy controller asserts two outputs, which are left and right wheel velocities to control the speed and trajectory of a differential drive vehicle. Each of the input and output fuzzy membership functions has seven terms based around lambda, Z-type and S-type functions. The fuzzy rule base consists of 49 rules and the fuzzy inference stage is based on the MAX/MIN method. A Centre of Maximum (CoM) def'uzzification method is used to provide the two crisp valued outputs to the vehicle motion control. The methods chosen for the fuzzy control of distance and tracking for autonomous vehicles were selected based on a compromise between their computational complexity and performance characteristics. This compromise was necessary in order to implement the chosen controller structure on pre-existing hardware test beds based on an 8-bit microcontrollers with limited memory and processing resources. Overall the fuzzy control-based solution presented in this thesis effectively solves the distance and tracking control problem. The solution was applied to differential drive hardware test-beds and was tested to verify performance. The solution was thoroughly tested in both the simulation environment and on hardware test-beds. Several issues are identified in this thesis regarding the application of the solution to other platforms and road vehicle use. The solution will be shown to be directly portable to service robotics applications and, with minor modifications, applicable to road vehicle close-formation platooning.
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Hitchings, Mark. "Distance and Tracking Control for Autonomous Vehicles". Thesis, Griffith University, 1999. http://hdl.handle.net/10072/366396.

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The author's concept of the distance and tracking control problem for autonomous vehicles relates to the cooperative behaviour of two successive vehicles travelling in the same environment. This behaviour requires one vehicle, designated the leader to move autonomously around it's environment with other vehicles, designated followers maintaining a coincident travel path and desired longitudinal distance with respect to the leader. Distance and tracking control is beneficial in numerous applications including guiding autonomous vehicles in Intelligent Transport Systems (ITS) which increases traffic safety and the capacity of pre-existing road infrastructure. Service robotics may also benefit from the cost savings and flexibility offered by distance and tracking control which enables a number of robots to cooperate together in order to achieve a task beyond the capabilities ofjust one robot. Using a distance and tracking control scheme an intelligent leader robot may guide a number of less intelligent (and therefore less costly and less complex) followers to a work-site to perform a task. The author's approach to the distance and tracking control problem consisted of two separate solutions - an initial solution used as a starting point and learning experience and a second, more robust, fuzzy control-based solution. This thesis briefly describes the initial solution, but places a greater emphasis on the second solution. The reason for this is that the fuzzy control-based solution offers significant improvement on the initial solution and was developed based on conclusions drawn from the initial solution. Most implementations of distance and tracking control, sometimes referred to as Intelligent Cruise Control (ICC) or platooning, are limited to longitudinal distance control only. The leader tracking control is performed either implicitly by a separate lane-following control system or by human drivers. The fuzzy control-based solution offered in this thesis performs both distance and tracking control of an autonomous follower vehicle with respect to a leader vehicle in front of it. It represents a simple and cost effective solution to the requirements of autonomous vehicles operating in ITS schemes - particularly close formation platooning. The follower tracks a laser signal emitted by the leader and monitors the distance to the follower at the same time using ultrasonic ranging techniques. The follower uses the data obtained from these measuring techniques as inputs to a fuzzy controller algorithm to adjust its distance and alignment with respect to the leader. Other systems employed on road vehicles utilise video-based leader tracking, or a range of lane-following methods such as magnetometer or video-based methods. Typically these methods are disadvantaged by substantial unit and/or infrastructure costs associated with their deployment. The limitations associated with the solutions presented in this thesis arise in curved trajectories at larger longitudinal distance separations between vehicles. The effects of these limitations on road vehicles has yet to be fully quantified, however it is thought that these effects would not disadvantage its use in close formation platooning. The fuzzy control-based distance and tracking control solution features two inputs, which are the distance and alignment of the follower with respect to the leader. The fuzzy controller asserts two outputs, which are left and right wheel velocities to control the speed and trajectory of a differential drive vehicle. Each of the input and output fuzzy membership functions has seven terms based around lambda, Z-type and S-type functions. The fuzzy rule base consists of 49 rules and the fuzzy inference stage is based on the MAX/MIN method. A Centre of Maximum (CoM) def'uzzification method is used to provide the two crisp valued outputs to the vehicle motion control. The methods chosen for the fuzzy control of distance and tracking for autonomous vehicles were selected based on a compromise between their computational complexity and performance characteristics. This compromise was necessary in order to implement the chosen controller structure on pre-existing hardware test beds based on an 8-bit microcontrollers with limited memory and processing resources. Overall the fuzzy control-based solution presented in this thesis effectively solves the distance and tracking control problem. The solution was applied to differential drive hardware test-beds and was tested to verify performance. The solution was thoroughly tested in both the simulation environment and on hardware test-beds. Several issues are identified in this thesis regarding the application of the solution to other platforms and road vehicle use. The solution will be shown to be directly portable to service robotics applications and, with minor modifications, applicable to road vehicle close-formation platooning.
Thesis (Masters)
Master of Philosophy (MPhil)
School of Microelectronic Engineering
Science, Environment, Engineering and Technology
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Kesting, Arne. "Microscopic Modeling of Human and Automated Driving: Towards Traffic-Adaptive Cruise Control". Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2008. http://nbn-resolving.de/urn:nbn:de:bsz:14-ds-1204804167720-57734.

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The thesis is composed of two main parts. The first part deals with a microscopic traffic flow theory. Models describing the individual acceleration, deceleration and lane-changing behavior are formulated and the emerging collective traffic dynamics are investigated by means of numerical simulations. The models and simulation tools presented provide the methodical prerequisites for the second part of the thesis in which a novel concept of a traffic-adaptive control strategy for ACC systems is presented. The impact of such systems on the traffic dynamics can solely be investigated and assessed by traffic simulations. The focus is on future adaptive cruise control (ACC) systems and their potential applications in the context of vehicle-based intelligent transportation systems. In order to ensure that ACC systems are implemented in ways that improve rather than degrade traffic conditions, the thesis proposes an extension of ACC systems towards traffic-adaptive cruise control by means of implementing an actively jam-avoiding driving strategy. The newly developed traffic assistance system introduces a driving strategy layer which modifies the driver's individual settings of the ACC driving parameters depending on the local traffic situation. Whilst the conventional operational control layer of an ACC system calculates the response to the input sensor data in terms of accelerations and decelerations on a short time scale, the automated adaptation of the ACC driving parameters happens on a somewhat longer time scale of, typically, minutes. By changing only temporarily the comfortable parameter settings of the ACC system in specific traffic situations, the driving strategy is capable of improving the traffic flow efficiency whilst retaining the comfort for the driver. The traffic-adaptive modifications are specified relative to the driver settings in order to maintain the individual preferences. The proposed system requires an autonomous real-time detection of the five traffic states by each ACC-equipped vehicle. The formulated algorithm is based on the evaluation of the locally available data such as the vehicle's velocity time series and its geo-referenced position (GPS) in conjunction with a digital map. It is assumed that the digital map is complemented by information about stationary bottlenecks as most of the observed traffic flow breakdowns occur at these fixed locations. By means of a heuristic, the algorithm determines which of the five traffic states mentioned above applies best to the actual traffic situation. Optionally, inter-vehicle and infrastructure-to-car communication technologies can be used to further improve the accuracy of determining the respective traffic state by providing non-local information. By means of simulation, we found that the automatic traffic-adaptive driving strategy improves traffic stability and increases the effective road capacity. Depending on the fraction of ACC vehicles, the driving strategy "passing a bottleneck" effects a reduction of the bottleneck strength and therefore delays (or even prevents) the breakdown of traffic flow. Changing to the driving mode "leaving the traffic jam" increases the outflow from congestion resulting in reduced queue lengths in congested traffic and, consequently, a faster recovery to free flow conditions. The current travel time (as most important criterion for road users) and the cumulated travel time (as an indicator of the system performance) are used to evaluate the impact on the quality of service. While traffic congestion in the reference scenario was completely eliminated when simulating a proportion of 25% ACC vehicles, travel times were significantly reduced even with much lower penetration rates. Moreover, the cumulated travel times decreased consistently with the increase in the proportion of ACC vehicles
In der Arbeit wird ein neues verkehrstelematisches Konzept für ein verkehrseffizientes Fahrverhalten entwickelt und als dezentrale Strategie zur Vermeidung und Auflösung von Verkehrsstaus auf Richtungsfahrbahnen vorgestellt. Die operative Umsetzung erfolgt durch ein ACC-System, das um eine, auf Informationen über die lokale Verkehrssituation basierende, automatisierte Fahrstrategie erweitert wird. Die Herausforderung bei einem Eingriff in das individuelle Fahrverhalten besteht - unter Berücksichtigung von Sicherheits-, Akzeptanz- und rechtlichen Aspekten - im Ausgleich der Gegensätze Fahrkomfort und Verkehrseffizienz. Während sich ein komfortables Fahren durch große Abstände bei geringen Fahrzeugbeschleunigungen auszeichnet, erfordert ein verkehrsoptimierendes Verhalten kleinere Abstände und eine schnellere Anpassung an Geschwindigkeitsänderungen der umgebenden Fahrzeuge. Als allgemeiner Lösungsansatz wird eine verkehrsadaptive Fahrstrategie vorgeschlagen, die ein ACC-System mittels Anpassung der das Fahrverhalten charakterisierenden Parameter umsetzt. Die Wahl der Parameter erfolgt in Abhängigkeit von der lokalen Verkehrssituation, die auf der Basis der im Fahrzeug zur Verfügung stehenden Informationen automatisch detektiert wird. Durch die Unterscheidung verschiedener Verkehrssituationen wird ein temporärer Wechsel in ein verkehrseffizientes Fahrregime (zum Beispiel beim Herausfahren aus einem Stau) ermöglicht. Machbarkeit und Wirkungspotenzial der verkehrsadaptiven Fahrstrategie werden im Rahmen eines mikroskopischen Modellierungsansatzes simuliert und hinsichtlich der kollektiven Verkehrsdynamik, insbesondere der Stauentstehung und Stauauflösung, auf mehrspurigen Richtungsfahrbahnen bewertet. Die durchgeführte Modellbildung, insbesondere die Formulierung eines komplexen Modells des menschlichen Fahrverhaltens, ermöglicht eine detaillierte Analyse der im Verkehr relevanten kollektiven Stabilität und einer von der Stabilität abhängigen stochastischen Streckenkapazität. Ein tieferes Verständnis der Stauentstehung und -ausbildung wird durch das allgemeine Konzept der Engstelle erreicht. Dieses findet auch bei der Entwicklung der Strategie für ein stauvermeidendes Fahrverhalten Anwendung. In der Arbeit wird die stauvermeidende und stauauflösende Wirkung eines individuellen, verkehrsadaptiven Fahrverhaltens bereits für geringe Ausstattungsgrade nachgewiesen. Vor dem Hintergrund einer zu erwartenden Verbreitung von ACC-Systemen ergibt sich damit eine vielversprechende Option für die Steigerung der Verkehrsleistung durch ein teilautomatisiertes Fahren. Der entwickelte Ansatz einer verkehrsadaptiven Fahrstrategie ist unabhängig vom ACC-System. Er erweitert dessen Funktionalität im Hinblick auf zukünftige, informationsbasierte Fahrerassistenzsysteme um eine neue fahrstrategische Dimension. Die lokale Interpretation der Verkehrssituation kann neben einer verkehrsadaptiven ACC-Regelung auch der Entwicklung zukünftiger Fahrerinformationssysteme dienen
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Kesting, Arne. "Microscopic Modeling of Human and Automated Driving: Towards Traffic-Adaptive Cruise Control". Doctoral thesis, Technische Universität Dresden, 2007. https://tud.qucosa.de/id/qucosa%3A24070.

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Streszczenie:
The thesis is composed of two main parts. The first part deals with a microscopic traffic flow theory. Models describing the individual acceleration, deceleration and lane-changing behavior are formulated and the emerging collective traffic dynamics are investigated by means of numerical simulations. The models and simulation tools presented provide the methodical prerequisites for the second part of the thesis in which a novel concept of a traffic-adaptive control strategy for ACC systems is presented. The impact of such systems on the traffic dynamics can solely be investigated and assessed by traffic simulations. The focus is on future adaptive cruise control (ACC) systems and their potential applications in the context of vehicle-based intelligent transportation systems. In order to ensure that ACC systems are implemented in ways that improve rather than degrade traffic conditions, the thesis proposes an extension of ACC systems towards traffic-adaptive cruise control by means of implementing an actively jam-avoiding driving strategy. The newly developed traffic assistance system introduces a driving strategy layer which modifies the driver's individual settings of the ACC driving parameters depending on the local traffic situation. Whilst the conventional operational control layer of an ACC system calculates the response to the input sensor data in terms of accelerations and decelerations on a short time scale, the automated adaptation of the ACC driving parameters happens on a somewhat longer time scale of, typically, minutes. By changing only temporarily the comfortable parameter settings of the ACC system in specific traffic situations, the driving strategy is capable of improving the traffic flow efficiency whilst retaining the comfort for the driver. The traffic-adaptive modifications are specified relative to the driver settings in order to maintain the individual preferences. The proposed system requires an autonomous real-time detection of the five traffic states by each ACC-equipped vehicle. The formulated algorithm is based on the evaluation of the locally available data such as the vehicle's velocity time series and its geo-referenced position (GPS) in conjunction with a digital map. It is assumed that the digital map is complemented by information about stationary bottlenecks as most of the observed traffic flow breakdowns occur at these fixed locations. By means of a heuristic, the algorithm determines which of the five traffic states mentioned above applies best to the actual traffic situation. Optionally, inter-vehicle and infrastructure-to-car communication technologies can be used to further improve the accuracy of determining the respective traffic state by providing non-local information. By means of simulation, we found that the automatic traffic-adaptive driving strategy improves traffic stability and increases the effective road capacity. Depending on the fraction of ACC vehicles, the driving strategy "passing a bottleneck" effects a reduction of the bottleneck strength and therefore delays (or even prevents) the breakdown of traffic flow. Changing to the driving mode "leaving the traffic jam" increases the outflow from congestion resulting in reduced queue lengths in congested traffic and, consequently, a faster recovery to free flow conditions. The current travel time (as most important criterion for road users) and the cumulated travel time (as an indicator of the system performance) are used to evaluate the impact on the quality of service. While traffic congestion in the reference scenario was completely eliminated when simulating a proportion of 25% ACC vehicles, travel times were significantly reduced even with much lower penetration rates. Moreover, the cumulated travel times decreased consistently with the increase in the proportion of ACC vehicles.
In der Arbeit wird ein neues verkehrstelematisches Konzept für ein verkehrseffizientes Fahrverhalten entwickelt und als dezentrale Strategie zur Vermeidung und Auflösung von Verkehrsstaus auf Richtungsfahrbahnen vorgestellt. Die operative Umsetzung erfolgt durch ein ACC-System, das um eine, auf Informationen über die lokale Verkehrssituation basierende, automatisierte Fahrstrategie erweitert wird. Die Herausforderung bei einem Eingriff in das individuelle Fahrverhalten besteht - unter Berücksichtigung von Sicherheits-, Akzeptanz- und rechtlichen Aspekten - im Ausgleich der Gegensätze Fahrkomfort und Verkehrseffizienz. Während sich ein komfortables Fahren durch große Abstände bei geringen Fahrzeugbeschleunigungen auszeichnet, erfordert ein verkehrsoptimierendes Verhalten kleinere Abstände und eine schnellere Anpassung an Geschwindigkeitsänderungen der umgebenden Fahrzeuge. Als allgemeiner Lösungsansatz wird eine verkehrsadaptive Fahrstrategie vorgeschlagen, die ein ACC-System mittels Anpassung der das Fahrverhalten charakterisierenden Parameter umsetzt. Die Wahl der Parameter erfolgt in Abhängigkeit von der lokalen Verkehrssituation, die auf der Basis der im Fahrzeug zur Verfügung stehenden Informationen automatisch detektiert wird. Durch die Unterscheidung verschiedener Verkehrssituationen wird ein temporärer Wechsel in ein verkehrseffizientes Fahrregime (zum Beispiel beim Herausfahren aus einem Stau) ermöglicht. Machbarkeit und Wirkungspotenzial der verkehrsadaptiven Fahrstrategie werden im Rahmen eines mikroskopischen Modellierungsansatzes simuliert und hinsichtlich der kollektiven Verkehrsdynamik, insbesondere der Stauentstehung und Stauauflösung, auf mehrspurigen Richtungsfahrbahnen bewertet. Die durchgeführte Modellbildung, insbesondere die Formulierung eines komplexen Modells des menschlichen Fahrverhaltens, ermöglicht eine detaillierte Analyse der im Verkehr relevanten kollektiven Stabilität und einer von der Stabilität abhängigen stochastischen Streckenkapazität. Ein tieferes Verständnis der Stauentstehung und -ausbildung wird durch das allgemeine Konzept der Engstelle erreicht. Dieses findet auch bei der Entwicklung der Strategie für ein stauvermeidendes Fahrverhalten Anwendung. In der Arbeit wird die stauvermeidende und stauauflösende Wirkung eines individuellen, verkehrsadaptiven Fahrverhaltens bereits für geringe Ausstattungsgrade nachgewiesen. Vor dem Hintergrund einer zu erwartenden Verbreitung von ACC-Systemen ergibt sich damit eine vielversprechende Option für die Steigerung der Verkehrsleistung durch ein teilautomatisiertes Fahren. Der entwickelte Ansatz einer verkehrsadaptiven Fahrstrategie ist unabhängig vom ACC-System. Er erweitert dessen Funktionalität im Hinblick auf zukünftige, informationsbasierte Fahrerassistenzsysteme um eine neue fahrstrategische Dimension. Die lokale Interpretation der Verkehrssituation kann neben einer verkehrsadaptiven ACC-Regelung auch der Entwicklung zukünftiger Fahrerinformationssysteme dienen.
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Park, Jaeyong. "Safe Controller Design for Intelligent Transportation System Applications using Reachability Analysis". The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1366201401.

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Książki na temat "Intelligent cruise control"

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Hoedemaeker, Marika. Driving with intelligent vehicles: Driving behaviour with adaptive cruise control and the acceptance by individual drivers. Delft, Netherlands: Delft University Press, 1999.

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Shladover, S. Literature review on recent international activity in cooperative vehicle-highway automation systems. McLean, VA: Office of Operations Research and Development, Turner-Fairban Highway Research Center, 2012.

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Shladover, S. Recent international activity in cooperative vehicle-highway automation systems. McLean, VA: Office of Operations Research and Development, Turner-Fairban Highway Research Center, 2012.

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United States. Congress. Senate. Committee on Armed Services. Intelligence briefing on smuggling of nuclear material and the role of international crime organizations, and on the proliferation of cruise and ballistic missiles: Hearing before the Committee on Armed Services, United States Senate, One Hundred Fourth Congress, first session, January 31, 1995. Washington: U.S. G.P.O., 1995.

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United States. Congress. Senate. Committee on Armed Services. Intelligence briefing on smuggling of nuclear material and the role of international crime organizations, and on the proliferation of cruise and ballistic missiles: Hearing before the Committee on Armed Services, United States Senate, One Hundred Fourth Congress, first session, January 31, 1995. Washington: U.S. G.P.O., 1995.

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United States. Congress. Senate. Committee on Armed Services. Intelligence briefing on smuggling of nuclear material and the role of international crime organizations, and on the proliferation of cruise and ballistic missiles: Hearing before the Committee on Armed Services, United States Senate, One Hundred Fourth Congress, first session, January 31, 1995. Washington: U.S. G.P.O., 1995.

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Części książek na temat "Intelligent cruise control"

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Winner, Hermann. "Adaptive Cruise Control". W Handbook of Intelligent Vehicles, 613–56. London: Springer London, 2012. http://dx.doi.org/10.1007/978-0-85729-085-4_24.

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Taghavipour, Amir, Mahyar Vajedi i Nasser L. Azad. "Ecological Cruise Control". W Intelligent Control of Connected Plug-in Hybrid Electric Vehicles, 169–83. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00314-2_9.

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Bu, Fanping, i Ching-Yao Chan. "Adaptive and Cooperative Cruise Control". W Handbook of Intelligent Vehicles, 191–207. London: Springer London, 2012. http://dx.doi.org/10.1007/978-0-85729-085-4_9.

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Bharathi, R., Sunanda Dixit i R. Bhagya. "Modern Automobile Adaptive Cruise Control". W Advances in Intelligent Systems and Computing, 1109–21. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5113-0_93.

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Lee, Yongjun, i Young-Jae Ryoo. "Design of Cruise Control System for Electric Vehicle Using Piece-Wised Control". W Advances in Intelligent Systems and Computing, 37–44. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05573-2_4.

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Swetha, Annam, N. R. Anisha Asmy, V. Radhamani Pillay, V. Kumaresh, R. Saravana Prabu, Sasikumar Punnekkat i Santanu Dasgupta. "Algorithm for Autonomous Cruise Control System - Real Time Scheduling and Control Aspects". W Advances in Intelligent Systems and Computing, 449–56. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11933-5_49.

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Dellnitz, Michael, Julian Eckstein, Kathrin Flaßkamp, Patrick Friedel, Christian Horenkamp, Ulrich Köhler, Sina Ober-Blöbaum, Sebastian Peitz i Sebastian Tiemeyer. "Multiobjective Optimal Control Methods for the Development of an Intelligent Cruise Control". W Mathematics in Industry, 633–41. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23413-7_87.

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Gao, Zhenhai, i Hai Song. "Study on the Electric Vehicle Adaptive Cruise Control Based on the Model Predictive Control Algorithm". W Green Intelligent Transportation Systems, 39–51. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0302-9_5.

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Ruan, Shumin, Yue Ma i Qi Yan. "Adaptive Cruise Control for Intelligent Electric Vehicles Based on Explicit Model Predictive Control". W Lecture Notes in Electrical Engineering, 860–69. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-6324-6_87.

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Lakshmisowjanya, Manne, Annam Swetha i V. Radhamani Pillay. "Fault Tolerant Scheduling - Dual Redundancy in an Automotive Cruise Control System". W Advances in Intelligent Systems and Computing, 497–504. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13728-5_56.

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Streszczenia konferencji na temat "Intelligent cruise control"

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Baret, Marc, Thierry T. Bomer, C. Calesse, L. Dudych i P. L'Hoist. "Autonomous intelligent cruise control system". W Photonics for Industrial Applications, redaktor Richard J. Becherer. SPIE, 1995. http://dx.doi.org/10.1117/12.198921.

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Woll, Jerry D. "Monopulse Radar for Intelligent Cruise Control". W 1997 SAE Future Transportation Technology Conference and Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1997. http://dx.doi.org/10.4271/972669.

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Sayer, James R. "Intelligent Cruise Control - Issues for Consideration". W Future Transportation Technology Conference & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1996. http://dx.doi.org/10.4271/961667.

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Changboon Han, Jaeboon Sul, Seungchul Kim, Youngdo Lim i Joontak Lee. "Development of intelligent cruise control system". W Proceedings of 8th International Fuzzy Systems Conference. IEEE, 1999. http://dx.doi.org/10.1109/fuzzy.1999.793280.

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Montanaro, Umberto, Manuela Tufo, Giovanni Fiengo, Mario di Bernardo, Alessandro Salvi i Stefania Santini. "Extended Cooperative Adaptive Cruise Control". W 2014 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2014. http://dx.doi.org/10.1109/ivs.2014.6856530.

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Pananurak, W., S. Thanok i M. Parnichkun. "Adaptive cruise control for an intelligent vehicle". W 2008 IEEE International Conference on Robotics and Biomimetics. IEEE, 2009. http://dx.doi.org/10.1109/robio.2009.4913274.

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Martin, Peter. "Autonomous Intelligent Cruise Control Incorporating Automatic Braking". W International Congress & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1993. http://dx.doi.org/10.4271/930510.

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He, Chaozhe R., i Gabor Orosz. "Safety Guaranteed Connected Cruise Control". W 2018 21st International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2018. http://dx.doi.org/10.1109/itsc.2018.8569979.

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Ornik, Melkior, Mateus S. Moura, Alexander Peplowski i Mireille E. Broucke. "Adaptive Cruise Control Design Using Reach Control". W 2018 21st International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2018. http://dx.doi.org/10.1109/itsc.2018.8569963.

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Journet, Bernard A., i Gaelle Bazin. "Laser rangefinders for autonomous intelligent cruise control systems". W Intelligent Systems & Advanced Manufacturing, redaktorzy Marten J. de Vries, Pushkin Kachroo, Kaan Ozbay i Alan C. Chachich. SPIE, 1998. http://dx.doi.org/10.1117/12.300874.

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