Se pretende analizar la posibilidad de utilizar un sistema ultrasónico como elemento sensor para el control inteligente del vehículo en tráfico urbano, es decir, a bajas velocidades y distancias cortas entre vehículos. Está comprobado que la mayoría de los accidentes de circulación tienen lugar en estas condiciones. Los sensores ultrasónicos requieren de una electrónica más sencilla y son más baratos que otros tipos como los basados en radar o láser. Para ello es necesario estudiar la influencia de los factores meteorológicos en la propagación de ultrasonidos en el aire. También se deben analizar diferentes técnicas que permitan mejorar el rendimiento de los sensores ultrasónicos conformando su diagrama de radiación, como la incorporación de bocinas. / We analyze the possibility of using an ultrasonic sensor for intelligent control of the vehicle in urban traffic, i.e., at low speeds and short distances. It is proven that most accidents occur in these conditions. Ultrasonic sensors require electronics that are simpler and cheaper than other types as those based on radar or laser. This requires studying the influence of meteorological conditions in the propagation of ultrasound in air. It also should discuss different techniques to improve the performance of ultrasonic sensors, as the inclusion of horns.

As active safety systems installed in vehicles become more common and more sophisticated, a concise method of testing them in conditions as close to real risk situations as possible becomes necessary. This study looks at the possibilities of developing use cases, using video recordings of real risk situations, obtained through naturalistic driving studies. The concept of conflicts is explored as a substitute to actual accidents. A method of finding conflicts in a large data material from looking at the acceleration signal and its derivative, referred to as jerk is also sought. These possibilities are tried on material from a previously conducted naturalistic driving study. The results are an improvement in the ability to find conflict situations automatically, and a suggestion to how use cases can be produced from video recordings of conflicts obtained through naturalistic driving studies. The DREAM framework is used and modified in order to aid with data collection and interpretation.

Objective: Active safety systems, of which antilock braking is a prominent example, are going to play an important role to improve powered two-wheeler (PTW) safety. This paper presents a systematic review of the scientific literature on active safety for PTWs. The aim was to list all systems under development, identify knowledge gaps and recognize promising research areas that require further efforts. Methods: A broad search using “safety” as the main keyword was performed on Scopus, Web of Science and Google Scholar, followed by manual screening to identify eligible papers that underwent a full-text review. Finally, the selected papers were grouped by general technology type and analyzed via structured form to identify the following: specific active safety system, study type, outcome type, population/sample where applicable, and overall findings. Results: Of the 8,000 papers identified with the initial search, 85 were selected for full-text review and 62 were finally included in the study, of which 34 were journal papers. The general technology types identified included antilock braking system, autonomous emergency braking, collision avoidance, intersection support, intelligent transportation systems, curve warning, human machine interface systems, stability control, traction control, and vision assistance. Approximately one third of the studies considered the design and early stage testing of safety systems (n. 22); almost one fourth (n.15) included evaluations of system effectiveness. Conclusions: Our systematic review shows that a multiplicity of active safety systems for PTWs were examined in the scientific literature, but the levels of development are diverse. A few systems are currently available in the series production, whereas other systems are still at the level of early-stage prototypes. Safety benefit assessments were conducted for single systems, however, organized comparisons between systems that may inform the prioritization of future research are lacking. Another area of future analysis is on the combined effects of different safety systems, that may be capitalized for better performance and to maximize the safety impact of new technologies.

Objective: With the overall goal to harmonize prospective effectiveness assessment of active safety systems, the specific objective of this study is to identify and evaluate sources of variation in virtual precrash simulations and to suggest topics for harmonization resulting in increased comparability and thus trustworthiness of virtual simulation-based prospective effectiveness assessment. Methods: A round-robin assessment of the effectiveness of advanced driver assistance systems was performed using an array of state-of-the-art virtual simulation tools on a set of standard test cases. The results were analyzed to examine reasons for deviations in order to identify and assess aspects that need to be harmonized and standardized. Deviations between results calculated by independent engineering teams using their own tools should be minimized if the research question is precisely formulated regarding input data, models, and postprocessing steps. Results: Two groups of sources of variations were identified; one group (mostly related to the implementation of the system under test) can be eliminated by using a more accurately formulated research question, whereas the other group highlights further harmonization needs because it addresses specific differences in simulation tool setups. Time-to-collision calculations, vehicle dynamics, especially braking behavior, and hit-point position specification were found to be the main sources of variation. Conclusions: The study identified variations that can arise from the use of different simulation setups in assessment of the effectiveness of active safety systems. The research presented is a first of its kind and provides significant input to the overall goal of harmonization by identifying specific items for standardization. Future activities aim at further specification of methods for prospective assessments of the effectiveness of active safety, which will enhance comparability and trustworthiness in this kind of studies and thus contribute to increased traffic safety.

Indiana University-Purdue University Indianapolis (IUPUI) / This thesis addresses a critical issue of automotive safety. As traffic is increasing on the roads day by day, road safety is also a very important concern. Driving simulators can play an extensive role in the development and testing of advanced safety systems in peculiar traffic environments, respectively. Advanced Driver Assist Systems (ADAS) are getting enormous reputation but there is still need for more improvements. This thesis presents a design of an Automatic Emergency Pullover (AEP) strategy using active safety systems for a semi-autonomous vehicle. The idea for this system is that a moving vehicle equipped with an AEP system can automatically pull over on the roadside safely when the driver is considered incapable of driving. Furthermore, AEP supporting features such as; Lane Keeping Assist, Blind Spot Monitoring, Vehicle and Pedestrian Automatic Emergency Braking, Adaptive Cruise Control are also included in this work. The designs for application of each system have been explained along with its algorithms, model development, component architecture, simulation results, vehicular/pedestrian behavior and trajectory precision on software tools provided by Realtime Technologies, Inc. All major variables which influence the performance of vehicle after AEP activation, have been observed and remodeled according to control algorithms. The implementation of AEP system which can control vehicle dynamics has been verified with the help of simulation results.

Indiana University-Purdue University Indianapolis (IUPUI) / In automotive industry, driver assistance and active safety features are main areas of research. This thesis concentrates on designing one of the famous ADAS system feature called Adaptive cruise control. Feature development and analysis of various functionalities involved in the system control are done using Petri Nets. A background on the past and current ACC research is noted and taken as motivation. The idea is to implement the adaptive cruise control system in Petri net and analyze how to provide fault tolerance to the system. The system can be evaluated for various cases. The ACC technology implemented in di erent cars were compared and discussed. The interaction of the ACC module with other modules in the car is explained. The cruise system's algorithm in Petri net is used as the basis for developing Adaptive Cruise Control system's algorithm. The ACC system model is designed using Petri nets and various Petri net functionalities like place invariant, transition invariant and reachability tree of the model are analyzed. The results are veri ed using Matlab. Controllers are introduced for ideal cases and are implemented in Petri nets. Then the error cases are considered and fault tolerance techniques are carried out on the model to identify the fault places.

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No description available.

Forward Collision Avoidance Systems (FCAS) are a type of active safety system which have great potential for rear-end collision avoidance. These systems use either radar, lidar, or cameras to track objects in front of the vehicle. In the event of an imminent collision, the system will warn the driver, and, in some cases, can autonomously brake to avoid a crash. However, driver acceptance of the systems is paramount to the effectiveness of a FCAS system. Ideally, FCAS should only deliver an alert or intervene at the last possible moment to avoid nuisance alarms, and potentially have drivers disable the system. A better understanding of normal driving behavior can help designers predict when drivers would normally take avoidance action in different situations, and customize the timing of FCAS interventions accordingly. The overall research object of this dissertation was to characterize normal driver behavior in car following events based on naturalistic driving data. The dissertation analyzed normal driver behavior in car-following during both braking and lane change maneuvers. This study was based on the analysis of data collected in the Virginia Tech Transportation Institute 100-Car Naturalistic Driving Study which involved over 100 drivers operating instrumented vehicles in over 43,000 trips and 1.1 million miles of driving. Time to Collision in both braking and lane change were quantified as a function of vehicle speed and driver characteristics. In general, drivers were found to brake and change lanes more cautiously with increasing vehicle speed. Driver age and gender were found to have significant influence on both time to collision and maximum deceleration during braking. Drivers age 31-50 had a mean braking deceleration approximately 0.03 g greater than that of novice drivers (age 18-20), and female drivers had a marginal increase in mean braking deceleration as compared to male drivers. Lane change maneuvers were less frequent than braking maneuvers. Driver-specific models of TTC at braking and lane change were found to be well characterized by the Generalized Extreme Value distribution. Lastly, driver's intent to change lanes can be predicted using a bivariate normal distribution, characterizing the vehicle's distance to lane boundary and the lateral velocity of the vehicle. This dissertation presents the first large scale study of its kind, based on naturalistic driving data to report driver behavior during various car-following events. The overall goal of this dissertation is to provide a better understanding of driver behavior in normal driving conditions, which can benefit automakers who seek to improve FCAS effectiveness, as well as regulatory agencies seeking to improve FCAS vehicle tests. / Ph. D.

Intersection crashes represent one-fifth of all police reported traffic crashes and one-sixth of all fatal crashes in the United States each year. Active safety systems have the potential to reduce crashes and injuries across all crash modes by partially or fully controlling the vehicle in the event that a crash is imminent. The objective of this thesis was to evaluate crash and injury reduction in a future United States fleet equipped with intersection advanced driver assistance systems (I-ADAS). In order to evaluate this, injury risk modeling was performed. The dataset used to evaluate injury risk was the National Automotive Sampling System / Crashworthiness Data System (NASS/CDS). An injured occupant was defined as vehicle occupant who experienced an injury of maximum Abbreviated Injury Scale (AIS) of 2 or greater, or who were fatally injured. This was referred to as MAIS2+F injury. Cases were selected in which front-row occupants of late-model vehicles were exposed to a frontal, near-, or far-side crash. Logistic regression was used to develop an injury model with occupant, vehicle, and crash parameters as predictor variables. For the frontal and near-side impact models, New Car Assessment Program (NCAP) test results were used as a predictor variable. This work quantitatively described the injury risk for a wide variety of crash modes, informing effectiveness estimates. This work reconstructed 501 vehicle-to-vehicle left turn across path / opposite direction (LTAP/OD) crashes in the United States which had been originally investigated in NMVCCS. The performance of thirty different I-ADAS system variations was evaluated for each crash. These variations were the combinations of five Time to Collision (TTC) activation thresholds, three latency times, and two different intervention types (automated braking and driver warning). In addition, two sightline assumptions were modeled for each crash: one where the turning vehicle was visible long before the intersection, and one where the turning vehicle was only visible after entering the intersection. For resimulated crashes which were not avoided by I-ADAS, a new crash delta-v was computed for each vehicle. The probability of MAIS2+F injury to each front row occupant was computed. Depending on the system design, sightline assumption, I-ADAS variation, and fleet penetration, an I-ADAS system that automatically applies emergency braking could avoid 18%-84% of all LTAP/OD crashes. An I-ADAS system which applies emergency braking could prevent 44%-94% of front row occupants from receiving MAIS2+F injuries. I-ADAS crash and injured person reduction effectiveness was higher when both vehicles were equipped with I-ADAS. This study presented the simulated effectiveness of a hypothetical intersection active safety system on real crashes which occurred in the United States, showing strong potential for these systems to reduce crashes and injuries. However, this crash and injury reduction effectiveness made the idealized assumption of full installation in all vehicles of a future fleet. In order to evaluate I-ADAS effectiveness in the United States fleet the proportion of new vehicles with I-ADAS was modeled using Highway Loss Data Institute (HLDI) fleet penetration predictions. The number of potential LTAP/OD conflicts was modeled as increasing year over year due to a predicted increase in Vehicle Miles Traveled (VMT). Finally, the combined effect of these changes was used to predict the number of LTAP/OD crashes each year from 2019 to 2060. In 2060, we predicted 70,439 NMVCCS-type LTAP/OD crashes would occur. The predicted number of MAIS2+F injured front row occupants in 2060 was 3,836. This analysis shows that even in the long-term fleet penetration of Intersection Active Safety Systems, many injuries will continue to occur. This underscores the importance of maintaining passive safety performance in future vehicles. / M.S. / Future vehicles will have electronic systems that can avoid crashes in some cases where a human driver is unable, unaware, or reacts insufficiently to avoid the crash without assistance. The objective of this work was to determine, on a national scale, how many crashes and injuries could be avoided due to Intersection Advanced Driver Assistance Systems (I-ADAS), a hypothetical version of one of these up-and-coming systems. This work focused on crashes where one car is turning left at an intersection and the other car is driving through the intersection and not turning. The I-ADAS system has sensors which continuously search for other vehicles. When the I-ADAS system determines that a crash may happen, it applies the brakes or otherwise alerts the driver to apply the brakes. Rather than conduct actual crash tests, this was simulated on a computer for a large number of variations of the I-ADAS system. The basis for the simulations was real crashes that happened from 2005 to 2007 across the United States. The variations that were simulated changed the time at which the I-ADAS system triggered the brakes (or alert) and the simulated amount of computer time required for the I-ADAS system to make a choice. In some turning crashes, the car cannot see the other vehicle because of obstructions, such as a line of people waiting to turn left across the road. Because of this, simulations were conducted both with and without the visual obstruction. For comparison, we performed a simulation of the original crash as it happened in real life. Finally, since there are two cars in each crash, there are simulations when either car has the I-ADAS system or when both cars have the I-ADAS system. Each simulation either ends in a crash or not, and these are tallied up for each system variation. The number of crashes avoided compared to the number of simulations run is crash effectiveness. Crash effectiveness ranged from 1% to 84% based on the system variation. For each crash that occurred, there is another simulation of the time immediately after impact to determine how severe the impact was. This is used to determine how many injuries are avoided, because often the crashes which still happened were made less severe by the I-ADAS system. In order to determine how many injuries can be avoided by making the crash less severe, the first chapter focuses on injury modeling. This analysis was based on crashes from 2008 to 2015 which were severe enough that one of the vehicles was towed. This was then filtered down by only looking at crashes where the front or sides were damaged. Then, we compared the outcome (injury as reported by the hospital) to the circumstances (crash severity, age, gender, seat belt use, and others) to develop an estimate for how each of these crash circumstances affected the injury experienced by each driver and front row passenger. A second goal for this chapter was to evaluate whether federal government crash ratings, commonly referred to as “star ratings”, are related to whether the driver and passengers are injured or not. In frontal crashes (where a vehicle hits something going forwards), the star rating does not seem to be related to the injury outcome. In near-side crashes (the side next to the occupant is hit), a higher star rating is better. For frontal crashes, the government test is more extreme than all but a few crashes observed in real life, and this might be why the injury outcomes measured in this study are not related to frontal star rating. Finally, these crash and injury effectiveness values will only ever be achieved if every car has an I-ADAS system. The objective of the third chapter was to evaluate how the crash and injury effectiveness numbers change each year as new cars are purchased and older cars are scrapped. Early on, few cars will have I-ADAS and crashes and injuries will likely still occur at roughly the rate they would without the system. This means that crashes and injuries will continue to increase each year because the United States drives more miles each year. Eventually, as consumers buy new cars and replace older ones, left turn intersection crashes and injuries are predicted to be reduced. Long into the future (around 2050), the increase in crashes caused by miles driven each year outpaces the gains due to new cars with the I-ADAS system, since almost all of the old cars without I-ADAS have been removed from the fleet. In 2025, there will be 173,075 crashes and 15,949 injured persons that could be affected by the I-ADAS system. By 2060, many vehicles will have I-ADAS and there will be 70,439 crashes and 3,836 injuries remaining. Real cars will not have a system identical to the hypothetical I-ADAS system studied here, but systems like it have the potential to significantly reduce crashes and injuries.