Development of rear-end collision avoidance in automobiles

The goal of this work is to develop a Rear-End Collision Avoidance System for automobiles. In order to develop the Rear-end Collision Avoidance System, it is stated that the most important difference from the old practice is the fact that new design approach attempts to completely avoid collision instead of minimizing the damage by over-designing cars. Rear-end collisions are the third highest cause of multiple vehicle fatalities in the U.S. Their cause seems to be a result of poor driver awareness and communication. For example, car brake lights illuminate exactly the same whether the car is slowing, stopping or the driver is simply resting his foot on the pedal. In the development of Rear-End Collision Avoidance System (RECAS), a thorough review of hardware, software, driver/human factors, and current rear-end collision avoidance systems are included. Key sensor technologies are identified and reviewed in an attempt to ease the design effort. The characteristics and capabilities of alternative and emerging sensor technologies are also described and their performance compared. In designing a RECAS the first component is to monitor the distance and speed of the car ahead. If an unsafe condition is detected a warning is issued and the vehicle is decelerated (if necessary). The second component in the design effort utilizes the illumination of independent segments of brake lights corresponding to the stopping condition of the car. This communicates the stopping intensity to the following driver. The RECAS is designed the using the LabVIEW software. The simulation is designed to meet several criteria: System warnings should result in a minimum load on driver attention, and the system should also perform well in a variety of driving conditions. In order to illustrate and test the proposed RECAS methods, a Java program has been developed. This simulation animates a multi-car, multi-lane highway environment where car speeds are assigned randomly, and the proposed RECAS approaches demonstrate rear-end collision avoidance successfully. The Java simulation is an applet, which is easily accessible through the World Wide Web and also can be tested for different angles of the sensor

Safety implications of a pedestrian protection system - the driver's point of view

Pedestrians can sustain fatal injuries, even in low-speed collisions. Active pedestrian protection systems, such as an Active Bonnet, have been shown to mitigate the outcome of a collision. The study reported here aimed to discover whether such a system could have any negative impacts on the driver. One of the characteristics of the Active Bonnet is that, when deployed, it partially occludes the driver’s visual field. This driving simulator study quantified the amount of disruption to normal driving when the system is deployed, for drivers of three different heights. Curved and straight sections of road were simulated and occlusion time varied between 0.5 seconds and 4 seconds. In general, drivers’ reaction to the deployment of the bonnet was to decrease their speed; this was most noticeable for drivers at the lowest eye-height both in the straight and curved sections of road. On straight sections of road, drivers were able to maintain vehicle speed and lateral control for up to three seconds of partial occlusion of the visual field. For curved sections, this upper threshold was found to be only two seconds, reflecting the higher workload in the curved sections. When occlusion was lifted, drivers tended to then deviate in lane – a possible “panic” effect. As drivers became more familiar with the system, they applied the brakes less. In conclusion, according to the scenarios tested in this study, drivers appear to be able to cope with partial occlusions of two seconds or less and there is some evidence that a panic reaction can be lessened by familiarisation

Ergonomics of intelligent vehicle braking systems

The present thesis examines the quantitative characteristics of driver braking and pedal operation and discusses the implications for the design of braking support systems for vehicles. After the current status of the relevant research is presented through a literature review, three different methods are employed to examine driver braking microscopically, supplemented by a fourth method challenging the potential to apply the results in an adaptive brake assist system. First, thirty drivers drove an instrumented vehicle for a day each. Pedal inputs were constantly monitored through force, position sensors and a video camera. Results suggested a range of normal braking inputs in terms of brake-pedal force, initial brake-pedal displacement and throttle-release (throttle-off) rate. The inter-personal and intra-personal variability on the main variables was also prominent. [Continues.

Chitosan-zinc oxide composite for active food packaging Applications

Chitosan-zinc oxide (C-ZnO) films were prepared by a simple one pot procedure. In order to investigate the property of C-ZnO films, two composite films were prepared by varying the loading of ZnO and compared with pure chitosan film (C). The films were character-ized by various techniques such as FTIR, DSC, tensile, contact angle and water vapour permeability. FTIR analysis showed changes in hydrogen bonds band at 3351 cm-1 compared to pure chitosan film. The incorporation of ZnO in chitosan films increased the contact angle by 30.5% in C-ZnO1.0 film while water vapour transmission rate decreased by 7.8% compared to C film. From the tensile test, C-ZnO0.5 and C-ZnO1.0 films were found to be much superior by 1.5 times and 2.5 times respectively compared to bare chitosan film. Larger inhibition ring (by 47%) was exhibited by C-ZnO1.0 as compared to C-ZnO0.5 when tested against S.aureus. From the results, it is displayed that the incorporation of zinc oxide to chitosan improve their properties which also shown the potential to become a candi-date for food active packaging

Potential safety applications of advanced technology. Final Report

Notes: Report covers the period Sept 1990 - June 1993. Originally dated June 1993Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, McLean, Va.http://deepblue.lib.umich.edu/bitstream/2027.42/1045/2/85136.0001.001.pd

User-centred car design and the role of feedback in driving

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A survey of car manufacturers reveals an impressive list of upcoming technologies, the combined effect of which is likely to have a profound impact upon feedback to the driver. Feedback is information that the situation provides back to the driver and is specified with reference to content, source, and timing. Feedback quality is achieved when the information requirements of the task, derived from a new task analysis of driving, are matched to the sources, content, and timing of feedback provided by the environment and the vehicle. An exploratory on-road study begins by observing that better quality feedback is implicated in increasing driver's situational awareness (even though drivers have little self awareness of this fact), and optimising mental workload. The exploratory level of analysis builds into the experimental, whereby a highly controlled simulator study replicates and builds upon these findings. Feedback is again seen to positively influence situational awareness, where changes in driver's confidence ratings as to the presence or absence of feedback information in the simulation were observed, according to the modality of feedback presented. This was achieved with a probe recall paradigm, and using psychophysical techniques as a useful extension to the Situational awareness Global Assessment Technique (SAGAI). Similarly, an analysis of mental workload via the NASA TLX self report questionnaire demonstrates that a combination of visual, steering force feedback and auditory feedback gives rise to lower mental workload, lower driver frustration, and lower, though possibly more realistic self ratings of performance. This knowledge can be discussed with reference to a feedback framework of driving that provides the theoretical backdrop to the key psychological variables implicated in driving task performance. Overall, the findings contribute to knowledge in terms of new and imaginative ways of designing future vehicle technologies in order to maximise safety, efficiency, and enjoyment.This research is funded by the Hamilton Research Studentship

Maximum risk reduction with a fixed budget in the railway industry

Decision-makers in safety-critical industries such as the railways are frequently faced with the complexity of selecting technological, procedural and operational solutions to minimise staff, passengers and third parties’ safety risks. In reality, the options for maximising risk reduction are limited by time and budget constraints as well as performance objectives. Maximising risk reduction is particularly necessary in the times of economic recession where critical services such as those on the UK rail network are not immune to budget cuts. This dilemma is further complicated by statutory frameworks stipulating ‘suitable and sufficient’ risk assessments and constraints such as ‘as low as reasonably practicable’. These significantly influence risk reduction option selection and influence their effective implementation. This thesis provides extensive research in this area and highlights the limitations of widely applied practices. These practices have limited significance on fundamental engineering principles and become impracticable when a constraint such as a fixed budget is applied – this is the current reality of UK rail network operations and risk management. This thesis identifies three main areas of weaknesses to achieving the desired objectives with current risk reduction methods as: Inaccurate, and unclear problem definition; Option evaluation and selection removed from implementation subsequently resulting in misrepresentation of risks and costs; Use of concepts and methods that are not based on fundamental engineering principles, not verifiable and with resultant sub-optimal solutions. Although not solely intended for a single industrial sector, this thesis focuses on guiding the railway risk decision-maker by providing clear categorisation of measures used on railways for risk reduction. This thesis establishes a novel understanding of risk reduction measures’ application limitations and respective strengths. This is achieved by applying ‘key generic engineering principles’ to measures employed for risk reduction. A comprehensive study of their preventive and protective capability in different configurations is presented. Subsequently, the fundamental understanding of risk reduction measures and their railway applications, the ‘cost-of-failure’ (CoF), ‘risk reduction readiness’ (RRR), ‘design-operationalprocedural-technical’ (DOPT) concepts are developed for rational and cost-effective risk reduction. These concepts are shown to be particularly relevant to cases where blind applications of economic and mathematical theories are misleading and detrimental to engineering risk management. The case for successfully implementing this framework for maximum risk reduction within a fixed budget is further strengthened by applying, for the first time in railway risk reduction applications, the dynamic programming technique based on practical railway examples

CPSOR-GCN: A Vehicle Trajectory Prediction Method Powered by Emotion and Cognitive Theory

Active safety systems on vehicles often face problems with false alarms. Most active safety systems predict the driver's trajectory with the assumption that the driver is always in a normal emotion, and then infer risks. However, the driver's trajectory uncertainty increases under abnormal emotions. This paper proposes a new trajectory prediction model: CPSOR-GCN, which predicts vehicle trajectories under abnormal emotions. At the physical level, the interaction features between vehicles are extracted by the physical GCN module. At the cognitive level, SOR cognitive theory is used as prior knowledge to build a Dynamic Bayesian Network (DBN) structure. The conditional probability and state transition probability of nodes from the calibrated SOR-DBN quantify the causal relationship between cognitive factors, which is embedded into the cognitive GCN module to extract the characteristics of the influence mechanism of emotions on driving behavior. The CARLA-SUMO joint driving simulation platform was built to develop dangerous pre-crash scenarios. Methods of recreating traffic scenes were used to naturally induce abnormal emotions. The experiment collected data from 26 participants to verify the proposed model. Compared with the model that only considers physical motion features, the prediction accuracy of the proposed model is increased by 68.70%. Furthermore,considering the SOR-DBN reduces the prediction error of the trajectory by 15.93%. Compared with other advanced trajectory prediction models, the results of CPSOR-GCN also have lower errors. This model can be integrated into active safety systems to better adapt to the driver's emotions, which could effectively reduce false alarms.Comment: 15 pages, 31 figures, submitted to IEEE Transactions on Intelligent Vehicle