Relevant bibliographies by topics / Collision Warning System

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Collision Warning System'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Collision Warning System"

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Prof. V.V. Joshi, Prof V. V. Joshi, and Hanmant S. Gore Hanmant S. Gore. "Cooperative Driving using Anti-Collision Warning System." Indian Journal of Applied Research 3, no. 7 (October 1, 2011): 203–5. http://dx.doi.org/10.15373/2249555x/july2013/63.

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Lyu, Nengchao, Jiaqiang Wen, and Chaozhong Wu. "Novel Time-Delay Side-Collision Warning Model at Non-Signalized Intersections Based on Vehicle-to-Infrastructure Communication." International Journal of Environmental Research and Public Health 18, no. 4 (February 5, 2021): 1520. http://dx.doi.org/10.3390/ijerph18041520.

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In complex traffic environments, collision warning systems that rely only on in-vehicle sensors are limited in accuracy and range. Vehicle-to-infrastructure (V2I) communication systems, however, offer more robust information exchange, and thus, warnings. In this study, V2I was used to analyze side-collision warning models at non-signalized intersections: A novel time-delay side-collision warning model was developed according to the motion compensation principle. This novel time-delay model was compared with and verified against a traditional side-collision warning model. Using a V2I-oriented simulated driving platform, three vehicle-vehicle collision scenarios were designed at non-signalized intersections. Twenty participants were recruited to conduct simulated driving experiments to test and verify the performance of each collision warning model. The results showed that compared with no warning system, both side-collision warning models reduced the proportion of vehicle collisions. In terms of efficacy, the traditional model generated an effective warning in 84.2% of cases, while the novel time-delay model generated an effective warning in 90.2%. In terms of response time and conflict time difference, the traditional model gave a longer response time of 0.91 s (that of the time-delay model is 0.78 s), but the time-delay model reduced the driving risk with a larger conflict time difference. Based on an analysis of driver gaze change post-warning, the statistical results showed that the proportion of effective gaze changes reached 84.3%. Based on subjective evaluations, drivers reported a higher degree of acceptance of the time-delay model. Therefore, the time-delay side-collision warning model for non-signalized intersections proposed herein can improve the applicability and efficacy of warning systems in such complex traffic environments and provide reference for safety applications in V2I systems.
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O’Brien, West M., Xingwei Wu, and Linda Ng Boyle. "Examining Speech-Based Auditory Alerts for Intersection Collision Warning Systems using a Driving Simulator." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (September 2018): 1939–43. http://dx.doi.org/10.1177/1541931218621440.

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Collision warning systems alert drivers of potential safety hazards. Forward collision warning (FCW) systems have been widely implemented and studied. However, intersection collision warning systems (ICWS), such as intersection movement assist (IMA), are more complex. Additional studies are needed to identify the best alert for directing the driver toward the hazard. A driving simulator study with 48 participants was conducted to examine three speech-based auditory alerts (general, directional, and command) in a simulated red light running (RLR) collision scenario. The command alert that informed the drivers to brake was the most effective in reducing the number of collisions. The post-drive questionnaire showed that drivers also rated the brake alert to be best in terms of interpretation (based on the Kruskal Wallis test). This study provides insight into the performance of different types of speech-based alerts for an intersection collision warning system and can provide guidance for future studies.
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Hubele, Norma, and Kathryn Kennedy. "Forward collision warning system impact." Traffic Injury Prevention 19, sup2 (September 25, 2018): S78—S83. http://dx.doi.org/10.1080/15389588.2018.1490020.

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Tak, Sehyun, Jinsu Yoon, Soomin Woo, and Hwasoo Yeo. "Sectional Information-Based Collision Warning System Using Roadside Unit Aggregated Connected-Vehicle Information for a Cooperative Intelligent Transport System." Journal of Advanced Transportation 2020 (July 21, 2020): 1–12. http://dx.doi.org/10.1155/2020/1528028.

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Vehicular collision and hazard warning is an active field of research that seeks to improve road safety by providing an earlier warning to drivers to help them avoid potential collision danger. In this study, we propose a new type of a collision warning system based on aggregated sectional information, describing vehicle movement processed by a roadside unit (RSU). The proposed sectional information-based collision warning system (SCWS) overcomes the limitations of existing collision warning systems such as the high installation costs, the need for high market penetration rates, and the lack of consideration of traffic dynamics. The proposed SCWS gathers vehicle operation data through on-board units (OBUs) and shares this aggregated information through an RSU. All the data for each road section are locally processed by the RSU using edge computing, allowing the SCWS to effectively estimate the information describing the vehicles surrounding the subject vehicle in each road section. The performance of the SCWS was evaluated through comparison with other collision warning systems such as the vehicle-to-vehicle communication-based collision warning system (VCWS), which solely uses in-vehicle sensors; the hybrid collision warning system (HCWS), which uses information from both infrastructure and in-vehicle sensors; and the infrastructure-based collision warning system (ICWS), which only uses data from infrastructure. In this study, the VCWS with a 100% market penetration rate was considered to provide the most theoretically similar result to the actual collision risk. The comparison results show that in both aggregation and disaggregation level analyses, the proposed SCWS exhibits a similar collision risk trend to the VCWS. Furthermore, the SCWS shows a high potential for practical application because it provides acceptable performance even with a low market penetration rate (30%) at the relatively low cost of OBU installation, compared to the VCWS requirement of a high market penetration rate at a high installation cost.
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Chen, Keng-Pin, and Pao-Ann Hsiung. "Vehicle Collision Prediction under Reduced Visibility Conditions." Sensors 18, no. 9 (September 10, 2018): 3026. http://dx.doi.org/10.3390/s18093026.

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Rear-end collisions often cause serious traffic accidents. Conventionally, in intelligent transportation systems (ITS), radar collision warning methods are highly accurate in determining the inter-vehicle distance via detecting the rear-end of a vehicle; however, in poor weather conditions such as fog, rain, or snow, the accuracy is significantly affected. In recent years, the advent of Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication systems has introduced new methods for solving the rear-end collision problem. Nevertheless, there is still much left for improvement. For instance, weather conditions have an impact on human-related factors such as response time. To address the issue of collision detection under low visibility conditions, we propose a Visibility-based Collision Warning System (ViCoWS) design that includes four models for prediction horizon estimation, velocity prediction, headway distance prediction, and rear-end collision warning. Based on the history of velocity data, future velocity volumes are predicted. Then, the prediction horizon (number of future time slots to consider) is estimated corresponding to different weather conditions. ViCoWs can respond in real-time to weather conditions with correct collision avoidance warnings. Experiment results show that the mean absolute percentage error of our velocity prediction model is less than 11%. For non-congested traffic under heavy fog (very low visibility of 120 m), ViCoWS warns a driver by as much as 4.5 s prior to a possible future collision. If the fog is medium with a low visibility of 160 m, ViCoWs can give warnings by about 2.1 s prior to a possible future collision. In contrast, the Forward Collision Probability Index (FCPI) method gives warnings by only about 0.6 s before a future collision. For congested traffic under low visibility conditions, ViCoWS can warn a driver by about 1.9 s prior to a possible future collision. In this case, the FCPI method gives 1.2 s for the driver to react before collision.
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Cheng, Zhiyou, Yaling Li, and Bing Wu. "Early Warning Method and Model of Inland Ship Collision Risk Based on Coordinated Collision-Avoidance Actions." Journal of Advanced Transportation 2020 (July 20, 2020): 1–14. http://dx.doi.org/10.1155/2020/5271794.

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To reduce the occurrence of ship collisions, immediate danger, and close-quarters situations in narrow inland waterways, a step-by-step early warning system for ship collision-avoidance actions was developed, along with an early warning method and model of collision risk based on coordinated collision-avoidance actions. This study first analyzed the importance of coordinated collision-avoidance actions in inland waterways, and the process and key components of coordinated collision-avoidance actions were studied. Then, the early warning method of inland ship collision risk based on coordinated collision-avoidance actions was introduced; the effectiveness of the early warning method was comparatively analyzed via experimental observations. A framework of early warning model of inland ship collision risk was created based on the early warning method; a collision risk early warning model for inland ships based on coordinated collision-avoidance actions was proposed according to the relationship between the distance/time to the closest point of approach (DCPA, TCPA), coordination degree of collision-avoidance actions of the two considered ships and collision risk; moreover, the early warning model of inland ship collision risk was further considered for quantitative calculation. Finally, the application of the early warning method and model was demonstrated using a case study. The results indicate that the early warning method of inland ship collision risk based on coordinated collision-avoidance actions could effectively reduce the emergence of close-quarters situations and immediate danger, and the early warning model could quantitatively show the evolution of collision risk of two ships along with the process of coordinated collision-avoidance actions.
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Belz, Steven M., Gary S. Robinson, and John G. Casali. "Auditory Icons as Impending Collision System Warning Signals in Commercial Motor Vehicles." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42, no. 15 (October 1998): 1127–31. http://dx.doi.org/10.1177/154193129804201515.

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This simulator-based study examined the use of conventional auditory warnings (tonal, non-verbal sounds) and auditory icons (representational, non-verbal sounds), alone and in combination with a dash-mounted visual display to warn commercial motor vehicle operators of impending front-to-rear and side collision situations. Driver performance was measured in the simulated driving task via brake response time in the front-to-rear collision scenarios and via a count of accident occurrence in the side collision scenarios. For both front-to-rear and side collision scenarios, auditory icons elicited significantly improved driver performance over conventional auditory warnings. Driver performance improved when collision warning information was presented through multiple modalities.
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Ka, Dongho, Donghoun Lee, Sunghoon Kim, and Hwasoo Yeo. "Study on the Framework of Intersection Pedestrian Collision Warning System Considering Pedestrian Characteristics." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 5 (April 12, 2019): 747–58. http://dx.doi.org/10.1177/0361198119838519.

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One of the most widely used advanced driver assistance systems (ADAS) for preventing pedestrian–vehicle collisions is the intersection collision warning system (ICWS). Most previous ICWSs have been implemented with in-vehicle distance sensors, such as radar and lidar. However, the existing ICWSs show some weaknesses in alerting drivers at intersections because of limited detection range and field-of-view. Furthermore, these ICWSs have difficulties in identifying the pedestrian’s crossing intention because the distance sensors cannot capture pedestrian characteristics such as age, gender, and head orientation. To alleviate these defects, this study proposes a novel framework for vision sensor-based ICWS under a cloud-based communication environment, which is called the intersection pedestrian collision warning system (IPCWS). The IPCWS gives a collision warning to drivers approaching an intersection by predicting the pedestrian’s crossing intention based on various machine learning models. With real traffic data extracted by image processing in the IPCWS, a comparison study is conducted to evaluate the performance of the IPCWS in relation to warning timing. The comparison study demonstrates that the IPCWS shows better performance than conventional ICWSs. This result suggests that the proposed system has a great potential for preventing pedestrian–vehicle collisions by capturing the pedestrian’s crossing intention.
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Kang, Hyunmin, Kwanghee Han, and Jaesik Lee. "Differences in drivers’ pedestrian avoidance response based on Warning timing, stimulus-response compatibility and Drivers’ distraction of auditory pedestrian collision warning system." Korean Journal of Industrial and Organizational Psychology 29, no. 2 (May 31, 2016): 257–77. http://dx.doi.org/10.24230/kjiop.v29i2.257-277.

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In this study, the effects of auditory pedestrian collision warning system’s stimulus-response compatibility (compatible vs. incompatible) and warning timing(TTC: 2sec. vs. 4sec.) and type of driver distraction (control condition vs. auditory distraction vs. visual distraction) on pedestrian avoidance response were examined. The dependent measures were time to initial steering wheel maneuvering, steering wheel rotation angle, clearance distance to the pedestrian, ratio of pedestrian-collision and ratio of lane departure. The experiment used driving simulator and the results was as follows. First, the effects of stimulus-response compatibility appeared to differ as warning timing and types of driver distraction were varied. To be specific, stimulus-response incompatible condition was more suitable for auditory pedestrian collision warning system than stimulus-response compatible condition. Second, compare to 4sec, 2sec TTC condition yielded larger steering wheel rotation angle and higher ratios both in pedestrian-collision and lane departure. Third, among the types of driver distraction, the visual distraction impaired drivers’ ability to avoid the pedestrian most seriously. In conclusion, stimulus-response incompatible warnings which provided 4sec TTC condition seemed to be more reliable and useful in providing pedestrian-collision warning to drivers.
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Dissertations / Theses on the topic "Collision Warning System"

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Kon, Tayfun. "Collision Warning and Avoidance System for Crest Vertical Curves." Master's thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/37169.

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In recent years, State Road Route 114 which is located in Montgomery County, Virginia, has gained a bad reputation because of numerous traffic accidents. Most of these accidents resulted in loss of lives and property. Although there are many suggestions and proposals designed to prevent these acidents, to date no actions is taken yet. The focus of this research is to explore a technology-based, low cost solution that will lower or eliminate the risk of accidents on this two-lane rural highway.
Master of Science
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Wen, Wen. "Forward Leading Vehicle Detection for Driver Assistant System." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42127.

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Keeping a safe distance from the forward-leading vehicle is an essential feature of modern Advanced Driver Assistant Systems (ADAS), especially for transportation companies with a fleet of trucks. We propose in this thesis a Forward Collision Warning (FCW) system, which collects visual information using smartphones attached for instance to the windshield of a vehicle. The basic idea is to detect the forward-leading vehicle and estimate its distance from the vehicle. Given the limited resources of computation and memory of mobile devices, the main challenge of this work is running CNN-based object detectors at real-time without hurting the performance. In this thesis, we analyze the bounding boxes distribution of the vehicles, then propose an efficient and customized deep neural network for forward-leading vehicle detection. We apply a detection-tracking scheme to increase the frame rate of vehicle detection and maintain good performance. Then we propose a simple leading vehicle distance estimation approach for monocular cameras. With the techniques above, we build an FCW system that has low computation and memory requirements that are suitable for mobile devices. Our FCW system has 49% less allocated memory, 7.5% higher frame rate, and 21% less battery consumption speed than popular deep object detectors. A sample video is available at https://youtu.be/-ptvfabBZWA.
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Vaidya, Varun, and Kushal Bheemesh. "Adaptive Warning Field System." Thesis, Högskolan i Halmstad, CAISR Centrum för tillämpade intelligenta system (IS-lab), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-35312.

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This thesis is based on the work carried out in the field of safety systems for Autonomous Guided Vehicles(AGV). With autonomous vehicles being more prominent today, safe traversing of these is a major concern. The same is true for AGVs working in industry environment like forklift trucks etc. Our work applies to industrial robots. The method described here is developed by closely following an algorithm developed for safe traversing of a robot using a warning field. The report describes the literature review with work related to the safe traversing, path planning and collision avoidance in robots. The next part is dedicated to describing the methodology of implementation of the Adaptive Warning Field Method and the Dynamic Window Approach. The evaluation of the Adaptive Warning Method with the previous developed Warning Field Methods is done and test cases are designed to test the working of the designed method. Vrep simulation environment and Industrial data is used to run a simulation of the robot using the method developed in this work. We find that the method performs better compared to the previous methods in the designed scenarios. Lastly we conclude the report with the future work that can be carried out to improve and extend the algorithm.
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Kim, Yong-Seok. "Effects of Driver, Vehicle, and Environment Characteristics on Collision Warning System Design." Thesis, Linköping University, Department of Science and Technology, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1121.

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The purpose of the present study was to examine effects of driver, vehicle, and environment characteristics on Collision Warning System (CWS) design. One hypothesis was made that the capability of collision avoidance would not be same among a driver, vehicle, and environment group with different characteristics. Accident analysis and quantitative analysis was used to examine this hypothesis in terms of ‘risk’ and ‘safety margin’ respectively. Rear-end collision had a stronger focus in the present study.

As a result of accident analysis, heavy truck showed a higher susceptibility of the fatal rear-end accidents than car and light truck. Also, dry road surface compared to wet or snow, dark condition compared to daylight condition, straight road compared to curved road, level road compared to grade, crest or sag, roadway having more than 5 travel lanes compared to roadway having 2, 3 or 4 travel lanes showed a higher susceptibility of the fatal rear-end accidents. Relative rear-end accidents involvement proportion compared to the other types of collision was used as a measure of susceptibility.

As a result of quantitative analysis, a significant difference in terms of Required Minimum Warning Distance (RMWD) was made among a different vehicle type and braking system group. However, relatively small difference was made among a different age, gender group in terms of RMWD. Based on the result, breaking performance of vehicle should be regarded as an input variable in the design of CWS, specifically warning timing criteria, was concluded.

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Xie, Bingqian. "Lane Departure and Front Collision Warning System Using Monocular and Stereo Vision." Digital WPI, 2015. https://digitalcommons.wpi.edu/etd-theses/274.

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Driving Assistance Systems such as lane departure and front collision warning has caught great attention for its promising usage on road driving. This, this research focus on implementing lane departure and front collision warning at same time. In order to make the system really useful for real situation, it is critical that the whole process could be near real-time. Thus we chose Hough Transform as the main algorithm for detecting lane on the road. Hough Transform is used for that it is a very fast and robust algorithm, which makes it possible to execute as many frames as possible per frames. Hough Transform is used to get boundary information, so that we could decide if the car is doing lane departure based on the car's position in lane. Later, we move on to use front car's symmetry character to do front car detection, and combine it with Camshift tracking algorithm to fill the gap for failure of detection. Later we introduce camera calibration, stereo calibration, and how to calculate real distance from depth map.
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Jacob, Paravila O. "Intelligent Collision Warning System Based on Fuzzy Logic and Neural Network Technologies." NSUWorks, 1997. http://nsuworks.nova.edu/gscis_etd/605.

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The recent technological changes in computer and industrial control systems have been steadily extending the capabilities to handle a broad range of complex systems. The emergence and development of computer technology and intelligent systems during the past few decades have created a highly promising direction in the field of artificial intelligence. It is increasingly difficult to describe any real system as the level of complexity continues to increase. A combination of systems and techniques are necessary to solve many complex problems. This new direction involves the use of fuzzy logic and artificial neural network theory to enhance the ability of intelligent systems that can learn from experience and to adapt to changes in an environment of uncertainty and imprecision. The Intelligent Automotive Collision Warning System was developed as a rule based system by integrating a fuzzy logic controller with artificial neural network software. The Intelligent Automotive Collision Warning system constantly monitors the speed of the vehicle and the distance of any object in front of the vehicle using an ultrasonic ranging module to warn the operator to maintain a safe operating distance by using fuzzy logic theory and artificial neural network software. Descriptive statistics was used for collecting and organizing the data. Inferential statistics was used to prove the hypotheses based on the results of the collected data. NeuFuz4 software was used to train the neural network and to optimize the fuzzy rule base. The fuzzy logic technology provided a means of converting a linguistic control strategy to operate the warning system. The input/output relationship was defined by fuzzy membership functions which enabled the numerical inputs to be expressed as fuzzy variables using linguistic terms. A new fuzzy logic operator was also developed to optimize the fuzzy input/output relationship.
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Winkler, Susann, Julia Werneke, and Mark Vollrath. "Timing of early warning stages in a multi stage collision warning system: Drivers' evaluation depending on situational influences." Elsevier, 2016. https://publish.fid-move.qucosa.de/id/qucosa%3A33941.

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By means of car2x communication technologies (car2x) driver warnings can be presented to drivers quite early. However, due to their early timing they could be misunderstood by drivers, distract or even disturb them. These problems arise if, at the moment of the warning, the safety–critical situation is not yet perceivable or critical. In order to examine, when drivers want to receive early warnings as a function of the situation criticality, a driving simulator study was conducted using the two early warning stages of a multi stage collision warning system (first stage: informing the driver; second stage: prewarning the driver). The optimum timing to activate these two early warning stages was derived by examining the drivers’ evaluation of these timings concerning their appropriateness and usefulness. As situational variation, drivers traveling at about 100 km/h were confronted with slow moving traffic either driving at 25 km/h or 50 km/h at the end of a rural road. In total, 24 participants were tested in a within-subjects design (12 female, 12 male; M = 26.6 years, SD = 7.2 years). For both stages, drivers preferred an earlier timing when approaching slow moving traffic traveling at 25 km/h (first stage: 447 m, second stage: 249 m ahead of the lead vehicle) compared to 50 km/h (first stage: 338 m, second stage: 186 m ahead of the lead vehicle). The drivers’ usefulness rating also varied with the timing, spanning a range of 8 s for driver-accepted timing variations and showed correspondence to the drivers’ appropriateness ratings. Based on these results and those of a previous study, a timing function for each of the two early warning stages depending on the speed difference between the safety–critical object and the host vehicle is presented. Indirectly, similar adaptations are already implemented in current collision warning systems, which use the time-to-collision to give drivers acute warnings in a later stage, when an immediate reaction of the driver may still prevent a collision. However, this study showed that drivers also favor this kind of adaptation for earlier warning stages (information and prewarning). Thus, adapting the timing according to the drivers’ preferences will contribute to a better acceptance of these collision warning systems.
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Ewing, Jr Paul Lee. "The design and implementation of tracking and filtering algorithms for an aircraft Beacon collision warning system." Ohio University / OhioLINK, 1989. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1182435307.

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Fitch, Gregory M. "Driver Comprehension of Integrated Collision Avoidance System Alerts Presented through a Haptic Driver Seat." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/26281.

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Active safety systems that warn automobile drivers of various types of impending collisions have been developed. How these systems alert drivers when integrated, however, is a crucial component to their effectiveness that hinges on the consideration of human factors. Driversâ ability to comprehend multiple alerts presented through a haptic driver seat was investigated in this dissertation. Twenty-four participants, balanced for age and gender, drove an instrumented vehicle on a test-track while haptic alerts (vibrations in the driver seat) were generated. Driversâ ability to transmit the information conveyed by the alerts was investigated through two experiments. The first experiment investigated the effects of increasing the number of potential alerts on driversâ response performance. The second experiment investigated whether presenting haptic alerts through unique versus common locations in the driver seat affects driversâ response performance. Younger drivers (between the ages of 18 and 25 years old) were found to efficiently process the increased information contained in the alerts, while older drivers were not as efficient. However, it is foreseeable that older driver performance decrements may be assuaged when a crash context is provided. A third experiment evaluated the haptic driver seatâ s ability to alert distracted drivers to an actual crash threat. Drivers that received a haptic seat alert returned their gaze to the forward roadway sooner, removed their foot from the throttle sooner, pressed the brake pedal sooner, and stopped farther away from an inflatable barricade than drivers that did not receive a haptic seat alert. No age or gender effects were found in this experiment. Furthermore, half of the drivers that received the haptic seat alert lifted up on the throttle before returning their eyes to the forward roadway. This suggests these drivers developed an automatic response to the haptic seat alerts through their experience with the previous two experiments. A three-alert haptic seat approach, the intermediate alternative tested, is recommended providing specific design requirements are met.
Ph. D.
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Abe, Genya. "The impact of trust on driver response to forward collision warning systems." Thesis, Loughborough University, 2005. https://dspace.lboro.ac.uk/2134/34525.

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This thesis reports five studies that investigate the impact of trust on driver response to forward collision warning systems (FCWS). The experiments, while self-contained were conceived to relate together in a cohesive way. The first three studies investigated the relationship between alarm timing and driver performance in collision situations in a broad range of driving conditions. These studies also established trust models describing changes in driver subjective ratings of trust in response to alarm timing. It was found that an early alarm timing led to quick braking reaction times, resulting from prompt accelerator release. A middle alarm timing induced more consistent braking response than a control condition in which no alarms were presented. A late alarm timing had the potential to delay braking response when driving with long time headways. With respect to trust, early alarm timings induced higher levels of trust than late or middle alarm timings. Moreover the results suggest that the conflict between driver expectation of alarm performance and actual alarm timing results in decreased trust.
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Books on the topic "Collision Warning System"

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Szabo, S. The AUTONAV/DOT project: Baseline measurement system for evaluation of roadway departure warning system. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1999.

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Ruff, T. M. Test results of collision warning systems for surface mining dump trucks. Pittsburgh, PA: U.S. Dept. of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory, 2000.

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United States. Congress. House. Committee on Transportation and Infrastructure. Subcommittee on Aviation. Proposal to require traffic alert and collision avoidance systems on cargo aircraft: Hearing before the Subcommittee on Aviation of the Committee on Transportation and Infrastructure, House of Representatives, One Hundred Fifth Congress, first session, February 26, 1997. Washington: U.S. G.P.O., 1997.

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Goka, Tsuyoshi. Analysis of estimation algorithms for CDTI and CAS applications. Mountain View, Calif: Analytical Mechanics Associates, Inc., 1985.

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Goka, Tsuyoshi. Analysis of estimation algorithms for CDTI and CAS applications. Mountain View, Calif: Analytical Mechanics Associates, Inc., 1985.

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United States. Federal Highway Administration., ed. TEXHBRIEF... INTERSECTION COLLISION WARNING SYSTEM... U.S. DEPARTMENT OF TRANSPORTATION. [S.l: s.n., 1999.

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Karl, Murphy, Juberts Maris, and National Institute of Standards and Technology (U.S.), eds. The AUTONAV/DOT project: Baseline measurement system for evaluation of roadway departure warning system. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1999.

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Karl, Murphy, Juberts Maris, and National Institute of Standards and Technology (U.S.), eds. The AUTONAV/DOT project: Baseline measurement system for evaluation of roadway departure warning system. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1999.

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L, Neale Vicki, McGhee Catherine C, Virginia Transportation Research Council, Virginia Polytechnic Institute and State University. Transportation Institute., Virginia. Dept. of Transportation., and United States. Federal Highway Administration., eds. Intersection decision support: Evaluation of a violation warning system to mitigate straight crossing path collisions. Charlottesville, Va: Virginia Transportation Research Council, 2006.

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Multiple vehicle collision with fire during fog near milepost 118 on Interstate 40, Menifee, Arkansas, on January 9, 1995, and special investigation of collision warning system. Washington, D.C: The Board, 1995.

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Book chapters on the topic "Collision Warning System"

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Chen, Hong-tao, Hong-jun Pan, and Xiao-qiu Yao. "Collision-Proof Warning System for Sea-Cross Bridge." In Frontiers in Computer Education, 813–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27552-4_107.

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Lind, Henrik, Andrea Saroldi, Magnus Kamel, and Gerard Delaval. "AWARE A Collision Warning and Avoidance Radar System." In Advanced Microsystems for Automotive Applications 98, 79–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-39696-4_7.

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Lind, Henrik, Andrea Saroldi, Magnus Kamel, and Gerard Delaval. "AWARE A Collision Warning and Avoidance Radar System." In Advanced Microsystems for Automotive Applications 98, 79–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-72146-5_7.

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Meng, S. H., S. B. Hu, A. C. Huang, T. J. Huang, J. J. Jia, and Xuhong Huang. "Car Collision Warning System for Cornering on Mountain Roads." In Proceedings of the Fourth Euro-China Conference on Intelligent Data Analysis and Applications, 221–27. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68527-4_24.

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Leu, Adrian, Dorin Aiteanu, and Axel Gräser. "High Speed Stereo Vision Based Automotive Collision Warning System." In Applied Computational Intelligence in Engineering and Information Technology, 187–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28305-5_15.

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Stang, Marco, Martin Sommer, Daniel Baumann, Yuan Zijia, and Eric Sax. "Adaptive Customized Forward Collision Warning System Through Driver Monitoring." In Advances in Intelligent Systems and Computing, 757–72. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63089-8_50.

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Hancock, P. A. "Evaluating In-Vehicle Collision Avoidance Warning Systems for IVHS." In Concurrent Engineering: Tools and Technologies for Mechanical System Design, 947–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78119-3_39.

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Park, Hye Sun, and Kyong-Ho Kim. "AR-Based Vehicular Safety Information System for Forward Collision Warning." In Virtual, Augmented and Mixed Reality. Applications of Virtual and Augmented Reality, 435–42. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07464-1_40.

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Wang, Yuncheng, Xie Fei, Jianhua Wang, and Xu Hao. "Study on the Highway Vehicle Collision Avoidance and Warning System." In Lecture Notes in Electrical Engineering, 557–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33805-2_45.

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Xu, Yueru, Zhirui Ye, Chao Wang, and Kun Gao. "Modeling Commercial Vehicle Drivers’ Acceptance of Forward Collision Warning System." In Smart Innovation, Systems and Technologies, 167–80. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2324-0_17.

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Conference papers on the topic "Collision Warning System"

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Peisen, Xu. "Collision Warning and Avoidance System." In 2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI). IEEE, 2020. http://dx.doi.org/10.1109/ichci51889.2020.00071.

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Bhandari, A., P. Raju, S. Chavan, P. Das, and S. Rajguru. "3-way associative collision warning system." In ICWET '10: International Conference and Workshop on Emerging Trends in Technology. New York, NY, USA: ACM, 2010. http://dx.doi.org/10.1145/1741906.1741934.

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Wilson, Terry B., Walker Butler, Dan V. McGehee, and Tom A. Dingus. "Forward-Looking Collision Warning System Performance Guidelines." In SAE International Congress and Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1997. http://dx.doi.org/10.4271/970456.

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van Dijck, T., and G. A. J. van der Heijden. "VisionSense: an advanced lateral collision warning system." In IEEE Proceedings. Intelligent Vehicles Symposium, 2005. IEEE, 2005. http://dx.doi.org/10.1109/ivs.2005.1505118.

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Uribe, Jonny A., Luis Fonseca, and J. F. Vargas. "Video based system for railroad collision warning." In 2012 IEEE International Carnahan Conference on Security Technology (ICCST). IEEE, 2012. http://dx.doi.org/10.1109/ccst.2012.6393573.

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Costea, Aurelian D., Paul Schiopu, and Marian Vladescu. "Stand alone collision warning and avoidance system." In Advanced Topics in Optoelectronics, Microelectronics and Nanotechnologies IX, edited by Ionica Cristea, Marian Vladescu, and Razvan D. Tamas. SPIE, 2018. http://dx.doi.org/10.1117/12.2325472.

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Cabrera, Adrian, Sven Gowal, and Alcherio Martinoli. "A new collision warning system for lead vehicles in rear-end collisions." In 2012 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2012. http://dx.doi.org/10.1109/ivs.2012.6232244.

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Woll, Jerry D. "Vehicle Collision Warning System with Data Recording Capability." In International Truck & Bus Meeting & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1995. http://dx.doi.org/10.4271/952619.

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Saleh, S. M., H. M. Saleh, N. T. Toure, and Wolfram Hardt. "Towards A Vision-Based Forward Collision Warning System." In FIT-M 2020. Знание-М, 2020. http://dx.doi.org/10.38006/907345-75-1.2020.66.72.

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Abstract:
The annual number of road deaths is still increasing, especially in less developed and developing countries. Road accidents are the 5th cause of death and the leading reason for death among young people between 5 and 29 years of age in 2030. In this study, a robust solution is implemented by integrating object recognition with distance estimation to maximize driving safety. The proposed system will be able to detect common objects within the region of interest on the road and estimate how far these objects are from the camera position. The system will trigger an alarm to attract the driver’s attention in real time when the distance to one of the detected objects is less than a predefined threshold value. In this work YOLO (You Only Look Once) approach is used to detect the objects in real time and the properties of the depth map based on deep learning is applied to estimate the distance at a given point
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Minami, Kiyoshi, Tohru Yasuma, Shigeru Okabayashi, Masao Sakata, Itsuro Muramoto, and Tadao Kohzu. "A Collision-Avoidance Warning System Using Laser Radar." In SAE International Truck and Bus Meeting and Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1988. http://dx.doi.org/10.4271/881859.

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Reports on the topic "Collision Warning System"

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Miyoshi, Noboru, Masao Nagai, Takayoshi Kamada, and Hidehisa Yoshida. Development of Forward-Collision Avoidance Warning System Adapted for Driver Characteristics. Warrendale, PA: SAE International, September 2005. http://dx.doi.org/10.4271/2005-08-0554.

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Test results of collision warning systems for surface mining dump trucks. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, May 2000. http://dx.doi.org/10.26616/nioshpub2000120.

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Recommendations for testing radar-based collision warning systems on heavy equipment. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, May 2002. http://dx.doi.org/10.26616/nioshpub2002135.

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Test results of collision warning systems on off-highway dump trucks: phase 2. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, February 2001. http://dx.doi.org/10.26616/nioshpub2001100.

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