Automated driving systems (ADSs) promise a safe, comfortable and efficient experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The full potential of cannot be realized unless robustness state-of-the-art improved further. This paper discusses unsolved problems surveys technical aspect automated driving. Studies regarding present challenges, high-level system architectures, emerging methodologies core functions: localization, mapping, perception, planning,...

Automated Driving Systems (ADS) open up a new domain for the automotive industry and offer possibilities future transportation with higher efficiency comfortable experiences. However, autonomous driving under adverse weather conditions has been problem that keeps vehicles (AVs) from going to level 4 or autonomy long time. This paper assesses influences challenges brings ADS sensors in an analytic statistical way, surveys solutions against inclement conditions. State-of-the-art techniques on...

In this work, we present LIBRE: LiDAR Benchmarking and Reference, a first-of-its-kind dataset featuring 10 different sensors, covering range of manufacturers, models, laser configurations. Data captured independently from each sensor includes three environments configurations: static targets, where objects were placed at known distances measured fixed position within controlled environment; adverse weather, obstacles moving vehicle, in weather chamber LiDARs exposed to conditions (fog, rain,...

Automated vehicle technology has recently become reliant on 3D LiDAR sensing for perception tasks such as mapping, localization and object detection. This led to a rapid growth in the manufacturing industry with several competing makers releasing new sensors regularly. With this increased variety of LiDARs, each different properties number laser emitters, resolution, field-of-view, price tags, more in-depth comparison their characteristics performance is required. work compares 10 commonly...

The use of 3D LiDAR, which has proven its capabilities in autonomous driving systems, is now expanding into many other fields. sharing and transmission point cloud data from LiDAR sensors broad application prospects robotics. However, due to the sparseness disorderly nature this data, it difficult compress directly a very low volume. A potential solution utilizing raw data. We can rearrange each frame losslessly 2D matrix, making compact orderly. Due special structure texture matrix...

This paper introduces a method to extract driving behaviors from human expert driver which are applied an autonomous agent reproduce proactive behaviors. Deep learning techniques were used latent features the collected data. Extracted clustered into and create velocity profiles allowing could drive in human-like manner. By using behaviors, limit potential sources of discomfort such as jerk uncomfortable velocities. Additionally, we proposed compare trajectories where not only geometric...

Abstract This paper describes an implementation of a mobile robot system for autonomous navigation in outdoor concurred walkways. The task was to navigate through nonmodified pedestrian paths with people and bicycles passing by. has multiple redundant sensors, which include wheel encoders, inertial measurement unit, differential global positioning system, four laser scanner sensors. All the computation done on single laptop computer. A previously constructed map containing waypoints...

Driving Under the Influence (DUI) has emerged as a significant threat to public safety in recent years. Despite substantial efforts effectively detect DUI, inherent risks associated with acquiring DUI-related data pose challenges meeting requirements for training. To address this issue, we propose DUIncoder, which is an unsupervised framework designed learn exclusively from normal driving across diverse scenarios DUI behaviors and provide explanatory insights. DUIncoder aims challenge of...

In autonomous driving, retrieving a specific traffic scene in huge datasets is significant challenge. Traditional retrieval methods struggle to cope with the semantic complexity and heterogeneity of scenes are unable meet variable needs different users. This paper proposes “Query-by-Example”, approach based on Visual-Large Language Model (VLM)-generated Road Scene Graph (RSG) representation. Our method uses VLMs generate structured graphs from video data, capturing high-level attributes...

Point cloud data from LiDAR sensors is the currently basis of most L4 autonomous driving systems. Sharing and storing point clouds will also be important for future applications, such as accident investigation or V2V/V2X networks. Due to huge volume involved, collected over long periods time transmitting in real-time are difficult tasks, making compression an indispensable step before transmitting. Previous streaming methods, octree video compression-based approaches, have difficulty...

Autonomous mobile robot navigation in real unmodified outdoor areas frequented by people on their business, children playing, fast running bicycles, and even robots, remains a difficult challenge. For eleven years, the Tsukuba Challenge Real World Robot (RWRC) has brought together researchers, companies, government, ordinary citizens, under same space to push forward limits of autonomous robots. 2017 participation, our team proposed study problem sensors-to-actuators (also called...

Effective detection of people is a basic requirement for robot coexistence in human environments. In our previous work [1] we proposed method and position estimation using multiple layers Laser Range Finders (LRF) mobile robot. We extend by introducing laser reflection intensity as novel feature detection, achieving significant improvement rates. concrete, propose calibration data, segment separation intensity, introduce two new intensity-based features detection: the variance differences....

RESUMENDiversos láseres han demostrado ser potencialmente útiles a determinados parámetros de irradiación y podrían beneficiar el establecimiento siembra en condiciones adversas por radiación UV-B

Synthetic hexaploid wheat (SHW) has shown effective resistance to a diversity of diseases and insects, including tan spot, which is caused by Pyrenophora tritici-repentis, being an important foliar disease that can attack all types several grasses. In this study, 443 SHW plants were evaluated for their spot under controlled environmental conditions. Additionally, genome-wide association study was conducted genotyping entries with the DArTSeq technology identify marker-trait associations...

Weather variation in the distribution of image data can cause a decline performance existing visual algorithms during evaluation. Adding additional samples target domain to training or using pre-trained restoration methods such as de-hazing, de-raining, and de-snowing, improve quality input images are two promising solutions. In this work, we propose Multiple Translation GAN (MWTG), CycleGAN-based, dual-purpose framework that simultaneously learns weather generation its removal from data....

This work proposes a new method people detection and position estimation from mobile robot by fusion of multiple laser range finders arranged in two layers. Sensors facing opposite directions single row (layer) are fused to produce 360deg scan data robotpsilas surroundings, then every layer is further create 3D model there their position. The main problem our research an autonomous acting as member group moving public areas, simple accurate tracking important requirement. We present...

We propose a data-driven control framework for autonomous driving which combines learning-based risk assessment with personalized, safety-focused, predictive control. Different strategies are used depending on the detected level of situation (risky vs. non-risky). This requires model can understand context situation. In addition, should also be able to provide various safe and comfortable styles customized users, modeling method that capture individual preferences. To achieve this, we novel...

Rich semantic information extraction plays a vital role on next-generation intelligent vehicles. Currently there is great amount of research focusing fundamental applications such as 6D pose detection, road scene segmentation, etc. And this provides us opportunity to think about how shall these data be organized and exploited. In paper we propose graph,a special scene-graph for Different classical representation, graph not only object proposals but also their pair-wise relationships. By...

Subjective risk assessment is an important technology for enhancing driving safety, because individual adjusts his/her behavior according to own subjective perception of risk. This study presents a novel framework modeling personalized during expressway lane changes. The objectives this are twofold: (i) use ego vehicle signals and surrounding locations in data-driven explainable approach identify the possible influential factors while (ii) predict specific individual’s level just before...

In this work, we present a detailed comparison of ten different 3D LiDAR sensors for the tasks mapping and vehicle localization, using as common reference Normal Distributions Transform (NDT) algorithm implemented in self-driving open source platform Autoware. data used study is subset our Benchmarking Reference (LIBRE) dataset, captured independently from each sensor, driven on public urban roads multiple times, at times day. study, analyze performance characteristics (1) including an...