Driver Response Time in Cut-Off Scenarios from the Second Strategic Highway Research Program Naturalistic Database

A cut-in or cut-off scenario involves a vehicle intruding into the path of another vehicle traveling in the same direction. These lane changes can lead to potentially dangerous situations, either a sideswipe or a rear-end crash. In this study, 552 cut-in events were analyzed, including four crash and 548 near-crash events from the Second Strategic Highway Research Program (SHRP-2) data set. Video and onboard-data-recorder data from the responding vehicle were used to analyze various factors associated with drivers’ responses. Driver response times were measured from three different event onsets, and the effects of different factors on the respective response times were measured. These factors included the behavior of the subject driver, the behavior of the intruding vehicle/principal other vehicle (POV), and different environmental and infrastructural factors. The results showed that drivers responded more slowly when the POV took longer to move laterally to the subject driver’s lane edge and faster when this time was short. Similarly, drivers responded faster to merging vehicles that started from a stop. Yet, response times were no different when the POV utilized a directional signal. These results point to a kinematic threshold involving lateral distance and lateral speed that best describes how drivers were triggered to respond. Drivers also responded faster near intersections, and at night. The results can be utilized to design crash mitigation systems in autonomous vehicles, as well as non-automated vehicles, to supplement human responses where their abilities may be lacking.

Investigation and MASH Full-Scale Crash Testing of the Buried-in-Backslope Terminal Compatible with Midwest Guardrail System

Buried-in-backslope (BIB) terminal designs for beam guardrails were developed under the National Cooperative Highway Research Program (NCHRP) Report 350 criteria for 27¾-in. high guardrail systems. The design terminates a W-beam guardrail installation by burying the end terminal in the backslope. When properly designed and located, this type of anchor eliminates the possibility of an end-on impact with the barrier terminal and minimizes the likelihood of vehicular intrusion behind the barrier. Considering the increase in guardrail height to 31 in. in recent years, there is a need to modify the BIB terminal design for a 27¾-in. high guardrail to satisfy current crashworthiness standard criteria for a 31-in. high guardrail. The crash tests reported in this paper were performed in accordance with the Manual for Assessing Safety Hardware (MASH) Tests 3-34 and 3-35 for non-gating terminals, which represent the tests considered necessary to demonstrate MASH compliance of the device. The TL-3 BIB terminal system met MASH requirements and is considered MASH compliant. It is considered suitable for implementation at V-ditch locations with a 4H:1V or flatter foreslope where a MASH TL-3 BIB terminal system is needed and/or desired.

Convolutional Neural Network-Based In-Vehicle Occupant Detection and Classification Method using Second Strategic Highway Research Program Cabin Images

This paper describes an approach for automatic detection and localization of drivers and passengers in automobiles using in-cabin images. We used a convolutional neural network (CNN) framework and conducted experiments based on the Faster R-CNN and Cascade R-CNN detectors. Training and evaluation were performed using the Second Strategic Highway Research Program (SHRP 2) naturalistic dataset. In SHRP 2, the cabin images have been blurred to maintain privacy. After detecting occupants inside the vehicle, the system classifies each occupant as driver, front-seat passenger, or back-seat passenger. For one SHRP 2 test set, the system detected occupants with an accuracy of 94.5%. Those occupants were correctly classified as front-seat passenger with an accuracy of 97.3%, as driver with 99.5% accuracy, and as back-seat passenger with 94.3% accuracy. The system performed slightly better for daytime images than for nighttime images. Unlike previous work, this method is capable of presence classification and location prediction of occupants. By fine-tuning the object detection model, there is also significant improvement in detection accuracy as compared with pretrained models. The study also provides a fully annotated dataset of in-cabin images. This work is expected to facilitate research involving interactions between drivers and passengers, particularly related to driver attention and safety.

Nonparametric Multivariate Adaptive Regression Splines Models for Investigating Lane-Changing Gap Acceptance Behavior Utilizing Strategic Highway Research Program 2 Naturalistic Driving Data

Gap acceptance is one of the crucial components of lane-changing analysis and an important parameter in microsimulation modeling. Drivers’ poor gap judgment, and failure to accept a necessary safety gap, make it one of the major causes of lane-changing crashes on roadways. Several studies have been conducted to investigate lane-changing gap acceptance behavior; however, very few studies examined the behavior in complex real-world situations, such as in naturalistic settings. This study examined lane-changing gap acceptance behavior from the big Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study (NDS) datasets using a nonparametric multivariate adaptive regression splines (MARS) approach to better understand the complex effects of different factors in gap acceptance behavior. The study developed a unique methodology to identify lane-changing events of the non-NDS-vehicles using the front-mounted radar data from NDS vehicles and extract necessary parameters for analyzing gap acceptance behavior. In addition, surrogate measures of safety, that is, time-to-collision (TTC), was utilized to understand the impact of lane-changing on the NDS following vehicle safety. Moreover, different distributions of gap acceptance were fitted to identify the trend of gap acceptance behavior. The results from the MARS model revealed that different factors including relative speed between lane-changing vehicle (LCV) and lead vehicle (LV)/following vehicle (FV), traffic conditions, acceleration of LCV and FV, and roadway geometric characteristics have significant effects on gap acceptance behavior. The results of this study have significant implications, which could be used in microsimulation model calibration and safety improvements in connected and autonomous vehicles (CAV).

Análisis y optimización del nivel de servicio peatonal en la intersección de las Avenidas Garcilaso y Bolivia, Lima

El objetivo de la investigación es optimizar los niveles de servicio peatonal en la intersección de las avenidas Inca Garcilaso de la Vega y Bolivia debido a su alta incidencia de peatones. Realizando un análisis teórico y de campo, siguiendo procedimientos estandarizados por el Highway Capacity Manual 2010 (HCM 2010) y el National Cooperative Highway Research Program (NCHRP reporte 562). Los datos se recolectaron en el mes de septiembre del año 2019; realizando un aforo vehicular y peatonal durante 3 días de la misma semana; 14 horas por día. Se hizo el levantamiento topográfico para describir la geometría del lugar y realizar el inventario de las dimensiones de vías, ancho de esquinas, ancho de pasos peatonales, tiempos de semáforos, así como la señalización horizontal y vertical existente. Con los datos obtenidos en campo se calculó el nivel de servicio vehicular y peatonal (análisis de pasos peatonales y esquinas) para identificar el estado actual de la intersección en estudio. El nivel de servicio vehicular obtenido es F, para los pasos peatonales el nivel de servicio obtenido es F y para el estudio de esquinas el nivel de servicio obtenido es A, según el HCM 2010. Se identificar las mejoras que permitan optimizar el nivel de servicio peatonal. Como medida de solución se implementa un paso peatonal en forma “X”, modificaciones en los rebajes peatonales con pendientes adecuadas y postes de protección para peatones, lo cual permitirá una mayor fluidez y seguridad peatonal en la intersección analizada.

Caracterização hidrogeológica de áreas de atividades cemiteriais – Estudo de caso

Cemitérios são locais onde pessoas são sepultadas; a maioria da população não vê estes locais como possíveis poluidores ambientais. Nestes locais ocorre a decomposição da matéria orgânica que gera um resíduo viscoso, castanho-acinzentado e com forte odor, o necrochorume, possível poluidor do solo que pode facilmente ser transportado pelas águas pluviais e contaminar os lençóis freáticos com vírus, bactérias e protozoários proliferando doenças como febre tifoide, febre amarela, cólera, entre outras. Neste cenário, o objetivo deste estudo é caracterizar solos de duas áreas de atividades cemiteriais localizados no estado de Santa Catarina. O desenvolvimento do estudo considerou ensaios in situ e laboratoriais de caracterização geotécnica. Os resultados apresentaram índice alto a extremo de vulnerabilidade dos mananciais, coeficientes de permeabilidade em desacordo com Conselho Nacional do Meio Ambiente (CONAMA) Resolução nº 368/2006, presença de matéria orgânica no solo, tempo de trânsito no solo insuficiente para reter os microrganismos presentes no necrochorume e classificação HRB (Highway Research Bord) dos solos inadequada para locais com atividade cemiterial. A análise dos resultados sugere que o solo e o manancial das áreas estudadas apresentam provável contaminação por necrochorume.