Journal articles: '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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Wang, Hong, Li Qin Xie, Yong Xia Lu, Jian Guo Gao, and Qiang Zeng. "Research of Vehicle Collision Warning System." Applied Mechanics and Materials 220-223 (November 2012): 1602–5. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.1602.

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The safety performance of vehicles are divided into two types, one type is called" active safety", i.e. before the accident prevention, prevention measures.The other type is referred to as" passive safety", i.e. when the accident happened, the vehicles and personnel to take protection measures. People usually focuses on the passive safety of this idea seriously quite, people now pay more attention to the active safety design. This paper introduces several kinds of vehicle collision avoidance system ranging modes, and discusses the intelligent collision warning system.

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Kuschel, Heiner, Jörg Heckenbach, and Martin Ummenhofer. "Passive radar collision warning system PARASOL." IEEE Aerospace and Electronic Systems Magazine 32, no. 2 (February 2017): 40–52. http://dx.doi.org/10.1109/maes.2017.150267.

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Ulrich, Matthias, Carsten Dolar, Camille Marbach, and Carina Engelhart. "Collision Warning System for Forklift Trucks." ATZheavy duty worldwide 13, no. 4 (November 2020): 16–21. http://dx.doi.org/10.1007/s41321-020-0109-4.

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Zhang, Yuting, Xuedong Yan, and Zhuo Yang. "Discrimination of Effects between Directional and Nondirectional Information of Auditory Warning on Driving Behavior." Discrete Dynamics in Nature and Society 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/980281.

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This study examines the impacts of directional and nondirectional auditory warning information in a collision warning system (CWS) on driving behavior. The data on driving behavior is collected through experiment, with scenarios containing unexpected hazard events that include different warning content. As drivers approached the collision event, either a CWS auditory warning was given or no warning was given for a reference group. Discriminant analysis was used to investigate the relationship between directional auditory warning information and driving behavior. In the experiment, the CWS warnings significantly reduced brake reaction time and prompted drivers to press the brake pedal more heavily, demonstrating the effectiveness of CWS warnings in alerting drivers to avoid red-light running (RLR) vehicles when approaching a signalized intersection. Providing a clear warning with directional information about an urgent hazard event could give drivers adequate time to prepare for the potential collision. In terms of deceleration, a directional information warning was shown to greatly help drivers react to critical events at signalized intersections with more moderate braking. From these results, requirements can be derived for the design of effective warning strategies for critical intersections.

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Lerner, Neil D., Jeffrey L. Harpster, Richard W. Huey, and Geoffrey V. Steinberg. "Driver Backing-Behavior Research: Implications for Backup Warning Devices." Transportation Research Record: Journal of the Transportation Research Board 1573, no. 1 (January 1997): 23–29. http://dx.doi.org/10.3141/1573-04.

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Collisions during backing maneuvers are a common accident type and cause a significant number of injuries and fatalities. Backup warning systems are among the intelligent vehicle warning applications being developed. Designing effective warning criteria and display characteristics is a serious challenge because little is known about how drivers behave during backing maneuvers. Drivers often intentionally back their vehicles into close proximity to objects, and backing speeds vary greatly, so appropriate conditions for warning a driver are unclear. A series of experiments was conducted to provide a basis for the design of effective vehicle-based backup warning devices. The experiments concerned driver behavior, perceptions, and responses to warning signals. One experiment measured common behaviors and vehicle control aspects during backing maneuvers. Another experiment measured driver brake reaction time and stopping distance to an acoustic signal during various backing maneuvers. A third experiment required participants in a car that was backing toward an object to identify the point at which they would want to receive cautionary and imminent crash warnings. Key findings are highlighted and their implications for the design of backup warning systems are discussed. Findings suggest the most effective design is a two-level warning system using acoustic signals as the primary mode and time to collision as a primary means of recognizing probable driver errors. Although preliminary, a time to collision of approximately 1.5 to 2.0 sec appears to be a reasonable criterion for an imminent crash warning, based on joint consideration of normal maneuver characteristics, driver reaction times, and driver judgments of appropriate warning times.

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Eskandarian, Azim, and Ce Zhang. "A Brain Wave-Verified Driver Alert System for Vehicle Collision Avoidance." SAE International Journal of Transportation Safety 9, no. 1 (June 18, 2021): 105–22. http://dx.doi.org/10.4271/09-09-01-0002.

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Collision alert and avoidance systems (CAS) could help to minimize driver errors. They are instrumental as an advanced driver-assistance system (ADAS) when the vehicle is facing potential hazards. Developing effective ADAS/CAS, which provides alerts to the driver, requires a fundamental understanding of human sensory perception and response capabilities. This research explores the premise that external stimulation can effectively improve drivers’ reaction and response capabilities. Therefore this article proposes a light-emitting diode (LED)-based driver warning system to prevent potential collisions while evaluating novel signal processing algorithms to explore the correlation between driver brain signals and external visual stimulation. When the vehicle approaches emerging obstacles or potential hazards, an LED light box flashes to warn the driver through visual stimulation to avoid the collision through braking. Thirty (30) subjects completed a driving simulator experiment under different near-collision scenarios. The Steady-State Visually Evoked Potentials (SSVEP) of the drivers’ brain signals and their collision mitigation (control performance) data were analyzed to evaluate the LED warning system’s effectiveness. The results show that (1) The proposed modified canonical correlation analysis evaluation (CCA-EVA) algorithm can detect SSVEP responses with 4.68% higher accuracy than the Adaptive Kalman filter; (2) The proposed driver monitoring and alert system produce on average a 52% improvement in time to collision (TTC), 54% improvement in reaction distance (RD), and an overall 26% reduction in collision rate as compared to similar tests without the LED warning.

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Chang, Chien-Yen, and Ting-Wei Chang. "The Development of Parameters and Warning Algorithms for an Intersection Bus-Pedestrian Collision Warning System." International Journal of Information Systems in the Service Sector 3, no. 4 (October 2011): 73–92. http://dx.doi.org/10.4018/jisss.2011100105.

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This study presents the conceptual design of an intersection bus-pedestrian collision warning system for bus drivers approaching an intersection. The basic parameters of the proposed design concept include the bus drivers’ perception-reaction time, the emergency deceleration rate of the bus, and pedestrian walking speed. A bus driving simulation was designed and conducted to analyze bus drivers’ responses to unexpected pedestrians crossing unsignalized intersections or signalized intersections during a green light interval for parameter analysis. The timings of auditory warnings and visual warnings, the locations for vehicle detectors and pedestrian detectors, and the locations for visual warning devices were also developed after analyzing the experimental results. The experimental results also highlight some important characteristics of bus driving behavior at intersections. Moreover, bus drivers really pay attention to the warning messages. Finally, this study develops and discusses some warning algorithms.

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Baek, Minjin, Donggi Jeong, Dongho Choi, and Sangsun Lee. "Vehicle Trajectory Prediction and Collision Warning via Fusion of Multisensors and Wireless Vehicular Communications." Sensors 20, no. 1 (January 4, 2020): 288. http://dx.doi.org/10.3390/s20010288.

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Driver inattention is one of the leading causes of traffic crashes worldwide. Providing the driver with an early warning prior to a potential collision can significantly reduce the fatalities and level of injuries associated with vehicle collisions. In order to monitor the vehicle surroundings and predict collisions, on-board sensors such as radar, lidar, and cameras are often used. However, the driving environment perception based on these sensors can be adversely affected by a number of factors such as weather and solar irradiance. In addition, potential dangers cannot be detected if the target is located outside the limited field-of-view of the sensors, or if the line of sight to the target is occluded. In this paper, we propose an approach for designing a vehicle collision warning system based on fusion of multisensors and wireless vehicular communications. A high-level fusion of radar, lidar, camera, and wireless vehicular communication data was performed to predict the trajectories of remote targets and generate an appropriate warning to the driver prior to a possible collision. We implemented and evaluated the proposed vehicle collision system in virtual driving environments, which consisted of a vehicle–vehicle collision scenario and a vehicle–pedestrian collision scenario.

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Batayneh, Wafa, Omar Al-Araidah, Khaled Bataineh, and Adnan Al-Ghasem. "Fuzzy-Based Adaptive Cruise Controller with Collision Avoidance and Warning System." Mechanical Engineering Research 3, no. 1 (May 2, 2013): 143. http://dx.doi.org/10.5539/mer.v3n1p143.

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The paper presents a Fuzzy-based adaptive cruise control system with collision avoidance and collision warning (ACC/CA/CW). The proposed control scheme aims to improve driver's comfort while keeping him/her safe by avoiding possible collisions. Depending on inputs from both the driver and the installed sensors, the controller accelerates/decelerates the vehicle to keep its speed at the desired limit. In case of a possible collision, the controller decelerates (accelerates) the vehicle to prevent possible crash with the vehicle ahead (behind). Moreover, the controller issues visual and/or audio alerts for the driver in order to warn him/her in case of the need for applying an uncomfortable deceleration level and/or to warn the driver for risky situations where he/she might need to change the lane. Simulation results illustrate the robustness of the proposed system over various ranges of inputs.

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Lee, Donghoun, Sehyun Tak, Sungjin Park, and Hwasoo Yeo. "Real-Time Associative Memory–Based Rear-End Collision Warning System." Transportation Research Record: Journal of the Transportation Research Board 2621, no. 1 (January 2017): 1–9. http://dx.doi.org/10.3141/2621-01.

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In the intelligent transportation system field, there has been a growing interest in developing collision warning systems based on artificial neural network (ANN) techniques in an effort to address several issues associated with parametric approaches. Previous ANN-based collision warning algorithms were generally based on predetermined associative memories derived before driving. Because collision risk is highly related to the current traffic situation, such as traffic state transition from free flow to congestion, however, updating associative memory in real time should be considered. To improve further the performance of the warning system, a systemic architecture is proposed to implement the multilayer perceptron neural network–based rear-end collision warning system (MCWS), which updates the associative memory with the vehicle distance sensor and smartphone data in a cloud computing environment. For the practical use of the proposed MCWS, its collision warning accuracy is evaluated with respect to various time intervals for updating the associative memories and market penetration rates. Results show that the MCWS exhibits a steady improvement in its warning performance as the time interval decreases, whereas the MCWS works more efficiently as the sampling ratio increases overall. When the sampling ratio reaches 50%, the MCWS shows a particularly stable warning accuracy, regardless of the time interval. These findings suggest that the MCWS has great potential to provide an acceptable level of warning accuracy for practical use, as it can obtain the well-trained associative memories reflecting current traffic situations by using information from widespread smartphones.

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Horowitz, Avraham D., and Thomas A. Dingus. "Warning Signal Design: A Key Human Factors Issue in an In-Vehicle Front-To-Rear-End Collision Warning System." Proceedings of the Human Factors Society Annual Meeting 36, no. 13 (October 1992): 1011–13. http://dx.doi.org/10.1177/154193129203601320.

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Warning signal effectiveness issues associated with the design of a front-to-rear-end collision warning system are discussed. Potential negative effects are that warnings may occur rarely, startling the driver and adding to cognitive load and stress, or alternatively, warnings may occur frequently and be ignored by the driver. To minimize negative effects, four design concepts are considered: (a) a graded sequence of warnings, from mild to severe, (b) a parallel change in modality, from visual to auditory, (c) individualization of warnings, and (d) a headway – distance to lead car – display.

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Wang, Xu, Jiangchen Li, Can Zhang, and Tony Z. Qiu. "Active Warning System for Highway-Rail Grade Crossings Using Connected Vehicle Technologies." Journal of Advanced Transportation 2019 (February 11, 2019): 1–11. http://dx.doi.org/10.1155/2019/3219387.

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Highway-rail grade crossing (HRGC) collisions are a significant safety concern around the world. HRGC collisions have a high risk of injuries and fatalities. To mitigate that risk, safety countermeasures for both active and passive HRGCs have been implemented. Leveraging the latest developments in connected vehicle (CV) technologies, CV-based warning systems perform well in safety applications for roadway networks. However, few have been developed to focus on safety improvements specifically for HRGCs. To bridge this gap, this paper proposes a novel active warning system that was created with readily available CV technologies and devices. A crossing risk assessment model was developed and evaluated in simulation and field applications. The proposed model predicts the crossing risk probabilities in the near future. When road users are in great risk of a collision, the warning system sends out auditory and visual alerts and displays the estimated waiting time. The test results reveal that the proposed warning system is promising for field implementation to improve safety at grade crossings.

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Kim, Beomseong, Baehoon Choi, Jhonghyun An, Jaeho Hwang, and Euntai Kim. "Novel Collision Warning System using Neural Networks." Journal of Korean Institute of Intelligent Systems 24, no. 4 (August 25, 2014): 392–97. http://dx.doi.org/10.5391/jkiis.2014.24.4.392.

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E.Z, Orji, Oleka C.V, and Nduanya U.I. "Arduino Based Forward Collision Detection Warning System." IJARCCE 7, no. 9 (September 30, 2018): 35–40. http://dx.doi.org/10.17148/ijarcce.2018.797.

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Gong Tian’an, 龚天安, 王云才 Wang Yuncai, 孔令琴 Kong Linqin, 李海忠 Li Haizhong, and 王安帮 Wang Anbang. "Chaotic Lidar for Automotive Collision Warning System." Chinese Journal of Lasers 36, no. 9 (2009): 2426–30. http://dx.doi.org/10.3788/cjl20093609.2426.

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Lambert, Alain, Dominique Gruyer, Anthony Busson, and Husnain Mansoor Ali. "Usefulness of collision warning inter-vehicular system." International Journal of Vehicle Safety 5, no. 1 (2010): 60. http://dx.doi.org/10.1504/ijvs.2010.035319.

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Li, Wen Jun, Kui Feng, and Hong Kun Zhang. "Anti-Rear-End Collision Warning System Based-on Zigbee for Highway Vehicle." Applied Mechanics and Materials 130-134 (October 2011): 3511–14. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.3511.

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The majority of traffic accidents on the highway is rear-end collision. According to statistics about ninety percent rear-end collision can be avoided if there is 1 second pretreatment time for drivers. So it is necessary to develop automotive rear-end collision warning system to prevent the occurrence of accidents. The anti-rear-end collision warning system based on Zigbee technology is designded in this paper. Vehicle speed, acceleration and other traffic information among the nodes can be exchanged on real-time by using self-organizing wireless sensor networks consisted by Zigbee network nodes. A vehicle safe distance model is established after considered the effects of other traffic safety factors, and then, the actual distance measured by radar is compared with the safe distance so as to provide early warning, alarm and other driving information to drivers. The experiment results show that the system can effectively provide early warning, avoid rear-end collision, and improve active safety of vehicles.

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Ding, Tongqiang, Xiaorong Li, Lili Zheng, and Zhiguo Hao. "Research on Safety Lane Change Warning Method Based on Potential Angle Collision Point." Journal of Advanced Transportation 2019 (June 27, 2019): 1–14. http://dx.doi.org/10.1155/2019/1281425.

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In order to ensure safe lane change and avoid traffic accidents, an effective lane change assist system is required. In a lane change assist system, it is very important to obtain the following elements in time, such as actual distance between vehicles, minimum safety distance, and warning signal. To this end, this paper analyzed four kinds of lane change angle collision scenes. Initial position, initial velocity, acceleration, heading angle, and kinematics of vehicles were used to calculate the position of potential angle collision points between lane change vehicle and obstacle vehicles. Then, actual distance model was constructed based on potential angular collision points. The minimum safety distance model was also established under the two most unfavorable conditions. In order to achieve the lane change warning, three early warning rules were formulated. We verified the validity of models and early warning rules using vehicle driving video data of Interstate 80 in California. Models and early warning rules constructed in our research can be applied to the advanced active safety systems of vehicle, such as vehicle lane change assist system and active collision early warning system, which can improve the active safety and reduce traffic accidents.

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Cheng, Wen Ming, Zhong Ke Xiang, and Fei Fei Xiang. "Development of Braking Force Size Warning System against Rear End Collision." Applied Mechanics and Materials 687-691 (November 2014): 331–35. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.331.

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There are a large proportion of rear end collisions in a road accident. Based on high level brake lights, the authors developed a set of warning system to reflect the size of the braking force of the front moving vehicle. The rear moving vehicle would be correctly understand brake intention of the front moving vehicle according to vivid, intuitive and timely high level light signal. Thus, the following vehicle would take appropriate measures promptly according to further reduce the probability of rear-end collision accidents.

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Wu, Xingwei, Linda Ng Boyle, and Dawn Marshall. "Drivers’ Avoidance Strategies When Using a Forward Collision Warning (FCW) System." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 1939–43. http://dx.doi.org/10.1177/1541931213601964.

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Forward collision warning (FCW) systems help prevent rear-end collisions by identifying and alerting drivers of threats ahead. Understanding drivers’ avoidance strategies i.e. the tendency to brake or steer is important for the design and effectiveness of these systems. A driving simulator study was performed across five US locations to examine three driver avoidance maneuvers: braking only, steering only and combined braking and steering. A log-linear analysis was used to investigate the likelihood of an avoidance maneuver given the driver characteristics (age, gender) and study location. Findings showed that drivers aged 40 years and older were more likely to use a combined braking and steering maneuver to avoid a rearend collision. Drivers from two coastal urban areas (Washington, D.C. and Seattle, WA) were less likely to choose braking only in response to FCW alerts. Younger drivers and drivers that live in more rural areas (Clemson, SC and Iowa City, IA) were more likely to select braking only to avoid a crash, which could be due to their experience in less congested traffic environment. The findings of this study provide some insights on the factors associated with various avoidance strategies among drivers. This understanding can help guide the design of future in-vehicle collision warning systems.

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Patra, Subhadeep, Peter Veelaert, Carlos Calafate, Juan-Carlos Cano, Willian Zamora, Pietro Manzoni, and Fabio González. "A Forward Collision Warning System for Smartphones Using Image Processing and V2V Communication." Sensors 18, no. 8 (August 14, 2018): 2672. http://dx.doi.org/10.3390/s18082672.

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In this paper, we present a forward collision warning application for smartphones that uses license plate recognition and vehicular communication to generate warnings for notifying the drivers of the vehicle behind and the one ahead, of a probable collision when the vehicle behind does not maintain an established safe distance between itself and the vehicle ahead. The application was tested in both static and mobile scenarios, from which we confirmed the working of our application, even though its performance is affected by the hardware limitations of the smartphones.

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Zhang, Yunfan, Xuedong Yan, Jiawei Wu, and Ke Duan. "Effect of Warning System on Interactive Driving Behavior at Unsignalized Intersection under Fog Conditions: A Study Based on Multiuser Driving Simulation." Journal of Advanced Transportation 2020 (December 29, 2020): 1–16. http://dx.doi.org/10.1155/2020/8871875.

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The intersection collision warning system (ICWS) is an emerging technology designed to assist drivers in avoiding collisions at intersections. ICWS has an excellent performance in reducing the number of collisions and improving driving safety. Previous studies demonstrated that when visibility was low under fog conditions, ICWS could help drivers timely detect hazardous conflicting vehicles. However, the influences of ICWS on interactive driving behavior at unsignalized intersection between different vehicles have barely been discussed. This study aimed to investigate the patterns of drivers’ interactive behaviors with the assistance of a new kind of ICWS under fog conditions based on Multiuser Driving Simulation. The Multiuser Driving Simulation allowed multiple drivers to operate in the same simulation scenario at the same time, and it could capture drivers’ interactions preferably. Forty-eight licensed drivers completed the driving simulation experiment in three fog conditions (no fog, light fog, and heavy fog) and two warning conditions (warning and no warning), in which the drivers drove in a straight-moving situation at unsignalized intersection with potential collision risks caused by the encounter of two vehicles. The results verified that warning and fog conditions were significant factors that affected the interactive driving behavior in the unsignalized intersection collision avoidance process, including the driver’s decision, TTC of action point, average acceleration (deceleration) rate, and postencroachment time. Compared to conditions without ICWS, the ICWS could help drivers make collision avoidance actions earlier and change the speed more smoothly. In addition, with the help of Multiuser Driving Simulation, associations between decision driving behaviors of vehicles were discussed with caution. The results revealed the decision-making mechanism of drivers in the process of interaction with other drivers. Under the influence of fog, interactive driving processes were fraught with increased risk at unsignalized intersection. However, the ICWS helped drivers interact more harmoniously, safely, and efficiently. The findings shed some light on the further development of ICWS and the study on interactive driving behavior.

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Brown, Timothy L., John D. Lee, and Daniel V. McGehee. "Attention-Based Model of Driver Performance in Rear-End Collisions." Transportation Research Record: Journal of the Transportation Research Board 1724, no. 1 (January 2000): 14–20. http://dx.doi.org/10.3141/1724-03.

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Several driver-performance factors contribute to rear-end collisions—driver inattention, perception-reaction time, and limitations of the human visual system. Although many evaluations have examined driver response to various rear-end collision avoidance systems (RECAS) display and algorithm alternatives, little research has been directed at creating a quantitative model of driver performance to evaluate these alternatives. Current considerations of driver behavior in developing warning algorithms tend to ignore the fundamental problem of driver inattention and assume a fixed driver reaction time with no further adjustment after the initial response. A more refined model of driver response to rear-end crash scenarios can identify more appropriate and timely information to be displayed to the driver. An attention-based rear-end collision avoidance model (ARCAM) is introduced that describes the driver’s attention distribution, information extraction and judgment process, and the reaction process. ARCAM predicts the closed-loop nature of collision response performance and explains how the driver might use RECAS warnings.

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Ito, Toshio, and Kenta Osawa. "Effective Method for Rear-end Collision Warning System." Procedia Computer Science 60 (2015): 700–707. http://dx.doi.org/10.1016/j.procs.2015.08.214.

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Koustanaï, Arnaud, Viola Cavallo, Patricia Delhomme, and Arnaud Mas. "Simulator Training With a Forward Collision Warning System." Human Factors: The Journal of the Human Factors and Ergonomics Society 54, no. 5 (April 3, 2012): 709–21. http://dx.doi.org/10.1177/0018720812441796.

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Albarella, Nicola, Francesco Masuccio, Luigi Novella, Manuela Tufo, and Giovanni Fiengo. "A Forward-Collision Warning System for Electric Vehicles: Experimental Validation in Virtual and Real Environment." Energies 14, no. 16 (August 10, 2021): 4872. http://dx.doi.org/10.3390/en14164872.

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Driver behaviour and distraction have been identified as the main causes of rear end collisions. However a promptly issued warning can reduce the severity of crashes, if not prevent them completely. This paper proposes a Forward Collision Warning System (FCW) based on information coming from a low cost forward monocular camera for low end electric vehicles. The system resorts to a Convolutional Neural Network (CNN) and does not require the reconstruction of a complete 3D model of the surrounding environment. Moreover a closed-loop simulation platform is proposed, which enables the fast development and testing of the FCW and other Advanced Driver Assistance Systems (ADAS). The system is then deployed on embedded hardware and experimentally validated on a test track.

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Hassein, Udai, Maksym Diachuk, and Said M. Easa. "In-Vehicle Passing Collision Warning System for Two-Lane Highways Considering Driver Characteristics." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 37 (September 7, 2018): 101–12. http://dx.doi.org/10.1177/0361198118795004.

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Passing collisions are one of the most dangerous traffic safety problems. These head-on collisions occur when the driver of the passing vehicle is distracted or does not assess the situation appropriately. The purpose of this study is to develop a passing collision warning system (PCWS) for drivers on two-lane highways to prevent passing collisions and improve road safety. This paper presents a framework and algorithm design for a PCWS that ensures that drivers have an adequate sight distance for a safe passing maneuver. The system uses an available radar sensor to detect the closest opposing vehicle traveling in the left lane and calculates its position, speed, and acceleration rate to estimate the time to collision and compare it with the time required for the passing vehicle to clear the lane. Realistic initial time and passing time models were established using actual experimental field data collected using a global positioning system (GPS) data logger device that was installed in the passing, impeding, and opposing vehicles and used to record the position and speed of different passing vehicles at 1-s intervals. The MATLAB simulation was developed and used to replicate real-life passing maneuvers and was also used to create the algorithm for the proposed warning system. The passing maneuver parameters were selected from probability distribution curves based on field data. The simulation model determines the relative distance and speed of the opposing vehicle at four different time intervals. The different factors that impact system accuracy were also examined.

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Liu, Gang, Hua Liang Liu, and Bao Sheng He. "Anti-Collision Distance Prediction Model Based on Spherical Wave Propagation Theory." Applied Mechanics and Materials 333-335 (July 2013): 1736–41. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.1736.

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Inspired by the personal monitoring method in the anti-collision section drilling, the cluster well anti-collision monitoring and early warning system are developed to prevent the well bore collision in the drilling process. Distance prediction model of the warning system is developed based on the theory of elastic waves in spherical spreading and absorption attenuation. By monitoring the well casing vibration and then the data processing, the relative distance between the drill bit and adjacent well casing is obtained in real time. If the estimating possibility of well collision is occurred, then the alarm is given. The results show that the measurement model was effective in shallow strata for anti-collision warning. The model can improve the effect of present anti-collision monitoring, and provides a guarantee for the safe and efficient drilling.

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Et.al, Jung Kyu Park. "UAV Collision Detection Algorithm based on Formulafor Fast Calculation." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (April 10, 2021): 452–56. http://dx.doi.org/10.17762/turcomat.v12i6.1869.

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Collision Avoidance System (CAS) is known as a pre-collision system or a forward collision warning system, and research has first begun as a vehicle safety system. In this paper, we propose an algorithm for collision detection of UAV. The proposed algorithm uses a mathematical method and detects the collision of the UAV by modeling it in a two-dimensional plane. Using the mathematical modeling method, it is possible to determine the collision location of the UAV in advance. Experiments were conducted to measure the performance and accuracy of the proposed algorithm. In the experiment, we proceeded assuming three environments and were able to detect an accurate collision when the UAV moved. By applying the algorithm proposed in the paper to CAS, many collision accidents can be prevented. The proposed algorithm detects collisions through mathematical calculations. In addition, the movement time of the UAV was modeled in a 2D environment to shorten the calculation time.

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Bella, Francesco, and Roberta Russo. "A Collision Warning System for rear-end collision: a driving simulator study." Procedia - Social and Behavioral Sciences 20 (2011): 676–86. http://dx.doi.org/10.1016/j.sbspro.2011.08.075.

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Lee, Jaesik, Daniel V. McGehee, Thomas A. Dingus, and Terry Wilson. "Collision Avoidance Behavior of Unalerted Drivers Using a Front-to-Rear-End Collision Warning Display on the Iowa Driving Simulator." Transportation Research Record: Journal of the Transportation Research Board 1573, no. 1 (January 1997): 1–7. http://dx.doi.org/10.3141/1573-01.

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This study investigated whether drivers who operate a vehicle equipped with a front-to-rear-end collision warning system can avoid crashing when a lead vehicle brakes at its maximum potential (e.g., -0.85 g). Drivers in the experimental condition drove a 1993 General Motors Saturn mounted on the Iowa Driving Simulator’s six-degree-of-freedom motion base. The simulator cab was equipped with a collision warning display that provided a primary auditory warning and secondary visual warning based on a time-to-collision algorithm between the subject’s vehicle and the lead vehicle. Two headway distances were tested (2.7 sec and 3.2 sec). The collision avoidance performance of subject drivers was compared to the behavior of drivers in a baseline condition where no collision warning display was present. Relative to the baseline condition, results indicate that drivers using the collision warning display ( a) showed significantly fewer crashes in the shorter headway condition, ( b) collided with the lead vehicle at significantly slower impact speeds, ( c) released the accelerator significantly faster, and ( d) had longer headways both at accelerator release and brake initiation.

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Pai, Neng-Sheng, Pi-Yun Chen, Shih-An Chen, and Shi-Xiang Chen. "Realization of Internet of vehicles technology integrated into an augmented reality system." Journal of Low Frequency Noise, Vibration and Active Control 39, no. 3 (March 19, 2019): 704–19. http://dx.doi.org/10.1177/1461348419835054.

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The goal of this study is to develop an internet of vehicles system with augmented reality technology. The system deals mainly with three subjects, namely, lane departure warning, forward collision detection and warning, and internet of vehicles. First, to deal with the subject of lane departure warning, the Hough transform is used in this study to extract the possible positions of lane lines from the region of interest of an image. The Kalman filter is further employed to remove noises and estimate the actual positions of car lane lines. The lane departure decision is then used to determine whether a lane departure situation occurs. Second, the Sobel edge detector and taillight detection method are used to locate the hypothetical region of the vehicle. The characteristic parameters within the hypothetical region can also be obtained through the Harris corner detection method. To verify the hypothetical region and identify the vehicle, the support vector machine algorithm is used. The collision decision is then applied to determine whether the distance between two vehicles is short, thus fulfilling the goal of forward collision detection and warning. In addition, a secure and easy-to-use internet of vehicles is achieved with the use of the Rivest–Shamir–Adleman encryption algorithm, which uses public and secret keys to encrypt and decrypt messages to achieve the task of user identification. Upon obtaining control of the vehicle, the driver has full access to the most up-to-date information provided by the driver assistance system. Finally, internet of vehicles applications incorporating the previously mentioned methods, smart glasses, and augmented reality are implemented in this study. Smart glasses provide the drivers easy access to information about the vehicle and warnings, which helps enhance driver convenience and safety considerably.

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Tsai, Ming-Fong, Naveen Chilamkurti, Ping-Fan Ho, and Yin-Chih Lu. "Implementation of Dedicated Short Range Communications Combined with Radar Detection for Forward Collision Warning System." International Journal of Wireless Networks and Broadband Technologies 2, no. 1 (January 2012): 49–63. http://dx.doi.org/10.4018/ijwnbt.2012010104.

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The Forward Collision Warning System (FCWS) has become an important research topic in recent years. Many FCWS products are used in the real world. However, these FCWS products cannot provide emergency braking events warning from the vehicle in front. Hence, this paper proposes a Dedicated Short Range Communications (DSRC) system combined with radar detection for an FCWS mechanism. The mechanism proposed by this paper will actively probe the emergency brakes of the vehicle in front and broadcast warning information with the Global Positioning System (GPS) position. Moreover, this mechanism uses warning information based on the GPS position to calculate the time of collision in order to alert the driver.

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Hu, Shu Guang, Chang Cheng Li, Shao Yang Yan, and Xin Xin. "Study on Control Strategy of Intelligent Guidance System for Foggy Area Traffic Safety." Applied Mechanics and Materials 209-211 (October 2012): 654–62. http://dx.doi.org/10.4028/www.scientific.net/amm.209-211.654.

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In recent years, an innovative Intelligent Guidance System for traffic safety under limited visibility conditions appeared and evolved. According to prevailing visibility and traffic conditions, such systems can provide roadway outline reinforcement, vehicle active guidance, rear-end collision warning functions by changing brightness, color, flashing frequency, etc. of the illuminant guidance facilities. Rear-end collision warning function is the marked feature different from traditional guidance facilities. This paper elaborates main principle, system configuration, word mode, control strategy of such system. Especially, emphasis is put on the analysis of key control parameters such as threshold of red lamp duration, quantity of trigged red lamps, which impact practical effects of such system greatly. Regarding the particular rear-end collision warning function, the author use time series chart of trigged red lamps status and list table of key parameters change to induce and optimize key control parameters configuration. The relationship of safe spacing between vehicles, advised speed limit, threshold of red lamp duration and quantity of trigged red lamps is established. And this can be referred to improve the practical effectiveness when such systems are constructed and used.

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Guan, Zhiying, Yan Wang, Zheng Zhou, and Hongbo Wang. "Research on Early Warning of Ship Danger Based on Composition Fuzzy Inference." Journal of Marine Science and Engineering 8, no. 12 (December 8, 2020): 1002. http://dx.doi.org/10.3390/jmse8121002.

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Ship collision avoidance measures are important for reducing marine accidents caused by human factors and various natural environmental factors and can also prevent property loss and casualties. In recent years, various methods have been used to study collision avoidance, including ship domain models. This paper proposes a ship domain model based on fuzzy logic aimed at providing early warning of ship collision risk and a reasonable reference that can be used in combination with the International Regulation for Preventing Collisions at Sea (COLREGs). The composition fuzzy inference combining more than one fuzzy inference process is first used to introduce as many factors as possible related to ship collision risk for calculating the ship domain. In this way, the calculation of the ship domain size is more accurate, and a more accurate reference can be provided to sailors, which could save both time and labor by reducing errors. A fuzzy inference system based on if-then fuzzy rules was established in MATLAB and simulation experiments were conducted. The simulation results suggest that the proposed method is feasible and can help sailors make subjective decisions to effectively avoid the occurrence of collision accidents.

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Venkatesan, M., and Selvakumar S. Raja. "Analysis of Safety Communication in a Highway Environment." Journal of Computational and Theoretical Nanoscience 16, no. 2 (February 1, 2019): 676–81. http://dx.doi.org/10.1166/jctn.2019.7789.

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This paper proposes an idea to develop security applications in vehicular ad hoc network (VANET) need upon propagation the security based messages. A self-arranging MAC protocol is proposed for high-collisions situations. The protocol permits vehicles to sort with others in a collision warning way before information transmission. Vehicles in the waiting line will get to the channel by time-division multiple accesses (TDMA) based channel access. A queue determine the accessing the channels on queue based channel access to on one node access from all nodes. Distinction with completely random access, the slot of queue select access the channel needs on completion time of selfsorting operation. In this paper queue achieve self sorting process mainly determined identify and avoid the collisions with another list areas during they self sorting operations. This simulation results output main purpose for highways securities show the proposed methodologies can considerable decrease the packet loss and delay in collision warning system in highway collisions situations.

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Agarkar, Arpit S. "Effectiveness of ADAS in Existing Vehicles." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 14, 2021): 2471–72. http://dx.doi.org/10.22214/ijraset.2021.34760.

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Around the whole world, lot of accidents occur due to inattentive driving and human errors. Partial Autonomous Driver Assistance System can be of lot of help to the driver in avoiding the collision and maintain the control of the vehicle by giving different warning signals. The system consists of (i) Forward Collision Warning (ii) Lane Departure Warning. In the existing vehicles, by adding RADAR Sensors and Camera and a microcontroller for processing, it can be used to track the lanes and gives an acoustic warning in advance if there is lane departure or any vehicle or pedestrian ahead. The proposed system can be implemented on raspberry pi microcontroller board.

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Wang, Mingyang, Xinbo Chen, Baobao Jin, Pengyuan Lv, Wei Wang, and Yong Shen. "A Novel V2V Cooperative Collision Warning System Using UWB/DR for Intelligent Vehicles." Sensors 21, no. 10 (May 17, 2021): 3485. http://dx.doi.org/10.3390/s21103485.

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The collision warning system (CWS) plays an essential role in vehicle active safety. However, traditional distance-measuring solutions, e.g., millimeter-wave radars, ultrasonic radars, and lidars, fail to reflect vehicles’ relative attitude and motion trends. In this paper, we proposed a vehicle-to-vehicle (V2V) cooperative collision warning system (CCWS) consisting of an ultra-wideband (UWB) relative positioning/directing module and a dead reckoning (DR) module with wheel-speed sensors. Each vehicle has four UWB modules on the body corners and two wheel-speed sensors on the rear wheels in the presented configuration. An over-constrained localization method is proposed to calculate the relative position and orientation with the UWB data more accurately. Vehicle velocities and yaw rates are measured by wheel-speed sensors. An extended Kalman filter (EKF) is applied based on the relative kinematic model to combine the UWB and DR data. Finally, the time to collision (TTC) is estimated based on the predicted vehicle collision position. Furthermore, through UWB signals, vehicles can simultaneously communicate with each other and share information, e.g., velocity, yaw rate, which brings the potential for enhanced real-time performance. Simulation and experimental results show that the proposed method significantly improves the positioning, directing, and velocity estimating accuracy, and the proposed system can efficiently provide collision warning.

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Kim, Yang Ho, Kwangsoo Kim, and Sooyeong Kwak. "A Pedestrian Collision Warning System using a Fuzzy Logic." Journal of Broadcast Engineering 20, no. 3 (May 30, 2015): 440–48. http://dx.doi.org/10.5909/jbe.2015.20.3.440.

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Kortli, Yassin, Mehrez Marzougui, and Mohamed Atri. "High-reliability Vehicle Detection and Lane Collision Warning System." International Journal of Wireless and Microwave Technologies 8, no. 2 (March 8, 2018): 1–14. http://dx.doi.org/10.5815/ijwmt.2018.02.01.

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Journal articles on the topic 'Collision Warning System'

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