Indiana University-Purdue University Indianapolis (IUPUI) / An important topic in autonomous vehicle related research in recent times is road departure warning (RDW) and road keeping assistance (RKA). RDW or RKA should be able to recognize and avoid roadside objects. Standard tests are needed to evaluate the performance of RDW and RKA feature of cars from different manufacturers. To avoid damage to the cars under test and the test environment during testing, there is a need of soft, durable and reusable surrogate targets representing various real roadside objects such as curb, concrete divider and metal guardrail. These surrogate objects should have representative characteristics of real roadside objects from the point of view of various commonly used object detection sensors on the vehicles such as camera, radar and LIDAR. Transportation Active Safety Institute (TASI) at Indian University-Purdue University Indianapolis (IUPUI) is in the process of developing surrogate concrete divider, curb metal guardrail and grass that should be recognized as real roadside objects by LIDAR sensors, can be crashed without damage to the test vehicle and can be reused even after multiple crashes. The first step is to understand what the representative roadside objects should look like from the point of view of LIDAR units using laser of various wavelengths, and the next step is to design surrogate objects that successfully emulate the properties of the real roadside objects. Reflectance of an object is an important property for LIDAR detection. This thesis describes an approach for the determination of infrared reflectance property of concrete, metal guardrail and grass for different LIDAR view angles. Various samples of each of these roadside objects were evaluated. Based on these measurements, the suggested reflectance of surrogate roadside objects in the common LIDAR wavelength range of 800-1100 nm is specified. Finally, the design of surrogate roadside objects that satisfy these requirements is described, and the infrared reflectance of these surrogate objects are compared to the suggested reflectance bounds for different LIDAR view angles.

Each year roughly there are roughly 40,000 traffic-related fatalities. Common roadside objects such as trees, poles, guardrails, embankments, culverts, and fences result account for roughly 46% of these fatalities. Efforts to reduce to injury risk and risk exposure in these crashes have been hampered by the difficulty in performing reconstructions. To address the need for accurate reconstructions in order to assess injury risk, a vehicle-specific stiffness database was added to the WinSmash reconstruction program. This single modification increased the average estimated delta-V by 8% and reduced error from 23% to 13% on average. A method to extend the WinSmash energy-based reconstruction approach to poles and trees that were damaged or broken was implemented to provide delta-V estimates for these crashes. The error of the pole and tree reconstruction component was roughly 44% but still represented a significant step forward for these crashes which previously could not be reconstructed. The use of strong-post w-beam guardrail along roadsides is the primary method by which exposure to risk is reduced. Efforts to model guardrails using finite element methods were hampered by the large number of unknowns and lack of knowledge about the sensitivity of the crash outcome to each variable. Through a parametric study the soil properties and rail mesh density were identified as the most significant influences in simulation outcome. This knowledge was applied to finite element models of damaged guardrail to identify when the damage compromises the guardrail ability to prevent risk exposure. Models of guardrail with rail deflection, missing posts, and missing blockouts identified rail deflection over 6 inches and any number of missing posts as hazardous conditions. The removal of a single blockout was found to be acceptable if not desirable. These findings have far-reaching implications. The enhanced WinSmash reconstruction program has been adopted by NASS/CDS to generate delta-V estimates used by researchers in all areas of transportation research. The identification of hazardous guardrail was of great interest to transportation agencies responsible for prioritizing and performing repairs of damaged guardrail. / Ph. D.

Road departure crashes are among the deadliest crash modes in the U.S. each year. In response, automakers have been developing lane departure active safety systems to alert drivers to impending departures. These lane departure warning (LDW) and lane departure prevention (LDP) systems have great potential to reduce the frequency and mitigate the severity of serious lane and road departure crashes. The objective of this thesis was to characterize lane and road departures to better understand the effect of systems such as LDW and LDP on single vehicle road departure crashes. The research includes the following: 1) a characterization of lane departures through analysis of normal lane keeping behavior, 2) a characterization of road departure crashes through the development and validation of a real-world crash database of road departures (NCHRP 17-43 Lite), and 3) develop enhancements to the Virginia Tech LDW U.S. fleetwide benefits model. Normal lane keeping behavior was found to vary with road characteristics such as lane width and road curvature. Consideration of the dynamic driving behaviors observed in the naturalistic driving study (NDS) data is important to avoid LDW false alarms and driver annoyance. Departure characteristics computed in normal driving were much less severe than the departure parameters measured in real-world road departure crashes. The real-world crash data collected in NCHRP 17-43 Lite database was essential in developing enhancements to the existing Virginia Tech LDW fleetwide benefits model. Replacement of regression model predictions with measured crash data and improvement of the injury criteria resulted in an 11-16% effectiveness for road departure crashes, and an 11-15% reduction in seriously injured drivers. / Master of Science / Road departure crashes account for nearly one-third of the roughly 30,000 automobile traffic fatalities in the U.S. each year. Lane departure warning (LDW) and lane departure prevention (LDP) systems are two safety systems developed to reduce the large number of fatalities resulting from road departures. The safety systems warn drivers if the vehicle begins to drift out of the intended lane of travel, and automatically steer the vehicle back into the lane of travel if it continues to drift. While LDW and LDP systems have potential to lower the number of fatal lane and road departure crashes, the technology is not yet a standard feature in production vehicles. There has been a lower than expected acceptance rate, and real-world benefits of the systems have not been published. The research objective for this thesis was to characterize lane and road departures to investigate the effect of these safety systems on road departure crashes. The first section of this thesis analyzed large amounts of time series data recorded from people in normal driving scenarios to model lane keeping behavior in non-crash, drift out of lane departures. We found driving behavior varied with road characteristics such as lane width and road curvature. These dynamic driving behaviors may lead to LDW false alarms and contribute to driver annoyance with the systems. The second portion of this research involved the development and validation of a real-world road departure crash database. The database included key departure parameters such as angle, speed, and road curvature. These parameters were used in the third section of the thesis to enhance the Virginia Tech LDW U.S. fleetwide benefits model, which is a mathematical trajectory simulation model that determines whether or not these road departure crashes could have been prevented if every vehicle in the U.S. was equipped with LDW. We found an effectiveness of 11-16% prevention for road departure crashes, and an 11-15% reduction in serious driver injury.

Indiana University-Purdue University Indianapolis (IUPUI) / Driving safety is a very important topic in vehicle development. One of the biggest threat of driving safety is road departure. Many vehicle active safety technologies have been developed to warn and mitigate road departure in recent years. In order to evaluate the performance of road departure warning and mitigation technologies, the standard testing environment need to be developed. The testing environment shall be standardized to provide consistent and repeatable features in various locations worldwide and in various seasons. The testing environment should also be safe to the vehicle under test in case the safety features do not function well. Therefore, soft, durable and reusable surrogates of roadside objects need to be used. Meanwhile, all surrogates should have the same representative characteristics of real roadside objects to di erent automotive sensors (e.g. radar, LIDAR and camera). This thesis describes the study on identifying the radar characteristics of common roadside objects, metal guardrail, grass, and concrete divider, and the development of the required radar characteristics of surrogate objects. The whole process is divided into two steps. The rst step is to nd the proper methods to measure the radar properties of those three roadside objects. The measurement result of each roadside object will be used as the requirement for making its surrogate. The second step is to create the material for developing the surrogate of each roadside object. In the experimental results demonstrate that all three surrogates satisfy their radar characteristics requirements.

<div>Driving safety is a very important topic in vehicle development. One of the biggest threat of driving safety is road departure. Many vehicle active safety technologies have been developed to warn and mitigate road departure in recent years. In order to evaluate the performance of road departure warning and mitigation technologies, the standard testing environment need to be developed. The testing environment shall be standardized to provide consistent and repeatable features in various locations worldwide and in various seasons. The testing environment should also be safe to the vehicle under test in case the safety features do not function well. Therefore, soft, durable and reusable surrogates of roadside objects need to be used. Meanwhile, all surrogates should have the same representative characteristics of real roadside objects to different automotive sensors (e.g. radar, LIDAR and camera). This thesis describes the study on identifying the radar characteristics of common roadside objects, metal guardrail, grass, and concrete divider, and the development of the required radar characteristics of surrogate objects. The whole process is divided into two steps. The first step is to find the proper methods to measure the radar properties of those three roadside objects. The measurement result of each roadside object will be used as the requirement for making its surrogate. The second step is to create the material for developing the surrogate of each roadside object. In the experimental results demonstrate that all three surrogates satisfy their radar characteristics requirements.</div>