2023 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST)最新文献

{"title":"Modeling and Property Analysis of the Message Synchronization Policy in ROS","authors":"Ruoxiang Li, Zheng Dong, Jen-Ming Wu, C. Xue, Nan Guan","doi":"10.1109/MOST57249.2023.00016","DOIUrl":"https://doi.org/10.1109/MOST57249.2023.00016","url":null,"abstract":"Sensor fusion plays a significant role in autonomous driving (AD) systems. In reality, the sensor data sent to the fusion algorithm may have substantially different sampling times, especially when different sensors are deployed in a distributed way (e.g., in V2X systems). Without proper management, this could lead to poor sensor fusion quality. ROS is the most popular robotic software framework, which provides a sophisticated message synchronization component to manage the temporal inconsistency in sensor fusion. However, although widely used, there is little information about how the ROS synchronization policy works exactly, and people have to use it as a blackbox. In this paper, we formally model the message synchronization policy in ROS and analyze its important properties, including the uniqueness property, disjunction property, continuity property, optimum property, and delay-dependent property, which were discussed on the ROS website but without formal proofs. Our analysis reveals that some of these properties indeed hold but some only hold under certain conditions. We conducted experiments to validate our formal model’s correctness and evaluate the synchronization policy’s performance in terms of time disparity.","PeriodicalId":338621,"journal":{"name":"2023 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125524584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-Time Vehicle Localization Using Steering Wheel Angle in Urban Cities","authors":"Raef Abdallah, Baofu Wu, Jian Wan","doi":"10.1109/MOST57249.2023.00015","DOIUrl":"https://doi.org/10.1109/MOST57249.2023.00015","url":null,"abstract":"Whether it is a small autonomous shuttle picking up and dropping off passengers, a robot navigating a large warehouse, a pizza delivery autonomous vehicle, or a truck fleet delivering goods and services, the precise localization of a moving object plays an important role in its safety and reliability. An integrated system composed of an onboard Inertial Measurement Unit (IMU) and a Global Positioning System (GPS) is utilized in vehicles nowadays and can precisely determine the location of a vehicle in real time; however, the vehicle localization accuracy degrades significantly even during the short duration of unavailable satellite signal. In this work, we propose using steering wheel angle and odometer data to determine the vehicle location during GPS satellite outages. Several test-driving experiments were conducted using an OBD-II Vehicle Interface (VI) and a tablet. We augmented our approach using reference GPS coordinates to enhance the vehicle location and rectify bias caused by odometer readings. We compared our approach with the vehicle’s GPS navigation system in an urban environment and verified that our proposed approach performs better. Comparing our approach to IMU has shown that the former predicted locations more accurately and with fewer error drifts.","PeriodicalId":338621,"journal":{"name":"2023 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123458803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FollowMe: A Robust Framework for the Guidance of Sensorless Indoor Mobile Robots","authors":"Sanjith Udupa, Liangkai Liu, Weisong Shi","doi":"10.1109/MOST57249.2023.00012","DOIUrl":"https://doi.org/10.1109/MOST57249.2023.00012","url":null,"abstract":"In this paper, we present FollowMe, a new system that allows one sensorless robot to autonomously follow another autonomous robot that has multiple sensors. By offloading both the localization and planning computations to the main robot, we are able to maintain a very small hardware requirement on the follower robot (i.e. it only needs to be able to drive). FollowMe works irrespective of what system it is run on and assumes that the main robot has some method of localizing itself and the follower robot, as well as software for navigation (driving itself to a target point). Given this, we can run FollowMe on different kinds of robots, as we have done through our tests on both physical and simulated robots.The FollowMe system is comprised of three main components. The first is the State Machine that takes input from arbitrary localization sources and coordinates through the PathSplitter algorithm to dynamically segment a given path into sequential target positions for each robot. Then, the Evaluator adjusts parameters for both following and path splitting depending on the following performance. As such, FollowMe only handles the queuing of new target points given a predefined path and assumes the master robot can handle the actual driving of each robot (follower and main) to the points. In order to make this possible, the PathSplitter algorithm ensures the follower robot is in view of the main robot at all times so accurate localization can occur. Finally, the state machine has recovery states as needed.After running experiments in both a physical and a simulation environment, we determined that FollowMe is effective at accomplishing the task of guiding both robots along a predefined path accurately, but because of the iterative nature of the following process, it is relatively slow. Our results highlight the potential for using existing autonomous driving technology in robot navigation and suggest promising directions for future research in this area, specifically for use in autonomous wheelchairs or in the warehouse industry.","PeriodicalId":338621,"journal":{"name":"2023 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131565047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conservative Estimation of Perception Relevance of Dynamic Objects for Safe Trajectories in Automotive Scenarios","authors":"Kent Mori, Kai Storms, Steven C. Peters","doi":"10.1109/MOST57249.2023.00017","DOIUrl":"https://doi.org/10.1109/MOST57249.2023.00017","url":null,"abstract":"Having efficient testing strategies is a core challenge that needs to be overcome for the release of automated driving. This necessitates clear requirements as well as suitable methods for testing. In this work, the requirements for perception modules are considered with respect to relevance. The concept of relevance currently remains insufficiently defined and specified.In this paper, we propose a novel methodology to overcome this challenge by exemplary application to collision safety in the highway domain. Using this general system and use case specification, a corresponding concept for relevance is derived. Irrelevant objects are thus defined as objects which do not limit the set of safe actions available to the ego vehicle under consideration of all uncertainties. As an initial step, the use case is decomposed into functional scenarios with respect to collision relevance. For each functional scenario, possible actions of both the ego vehicle and any other dynamic object are formalized as equations. This set of possible actions is constrained by traffic rules, yielding relevance criteria.As a result, we present a conservative estimation which dynamic objects are relevant for perception and need to be considered for a complete evaluation. The estimation provides requirements which are applicable for offline testing and validation of perception components. A visualization is presented for examples from the highD dataset, showing the plausibility of the results. Finally, a possibility for a future validation of the presented relevance concept is outlined.","PeriodicalId":338621,"journal":{"name":"2023 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115352258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ForDeen: Towards Formal Design for Ensuring Reliable UAV-Assisted Multi-Access Edge Computing: A Scenario-Based Approach","authors":"Yuxuan Wang, Charles F. Wingate, Jingshu Chen","doi":"10.1109/MOST57249.2023.00033","DOIUrl":"https://doi.org/10.1109/MOST57249.2023.00033","url":null,"abstract":"In this work, we focus on providing reliable design of UAV-assisted MEC systems via a formal way. Specifically, we are currently working on developing ForDeen, a formal framework that assures the reliability for MEC systems using a scenario-based synthesis approach. The framework will first construct a formal model to dynamically adjust the parameters of an UAV-assisted MEC system based on its state, environment, and objectives. To achieve this, we will adopt a combined approach of using Markov-chain Process and temporal logics to capture the behaviors and mission objectives of the target MEC systems. Typical scenarios such as data offloading will be modeled and integrated dynamically to generate the components whose behavior can be specified by a Markov chain. Our preliminary results have demonstrated the feasibility of the proposed framework via a case study.","PeriodicalId":338621,"journal":{"name":"2023 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117108011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Game Theory of Cheating Autonomous Vehicles","authors":"Zhen Li, Qi Liao","doi":"10.1109/MOST57249.2023.00035","DOIUrl":"https://doi.org/10.1109/MOST57249.2023.00035","url":null,"abstract":"The future of transportation will be autonomous vehicles, which communicate with each other making smart and intelligent decisions. For example, vehicles need not to stop at intersections when vehicles autonomously coordinate themselves for the order of crossing. Cooperative decision-making has the potential to solve challenging traffic management problems and enhance transportation safety and efficiency. Nevertheless, the ideal communication and coordination protocols for the Connected and Autonomous Vehicles (CAVs) have unexpected security concerns. Self-interested vehicles may not always want to cooperate. We consider an advanced CAV network in which vehicles can directly communicate with each other sharing intentions and other information such as location and speed. Game theory is applied to study the interactions of CAVs in a conflicting environment. Both cooperative and noncooperative scenarios are considered, especially when one party may be untruthful (i.e., lying to gain advantage, e.g., crossing intersection first while asking other vehicles to slow down). The untruthful player benefits at the cost of the cooperative players. Socially optimal game outcomes are only possible when players are cooperative. Through game theoretical study, we identify two preventive measures, i.e., speed limits and safety gaps, which may be dynamically adjusted to induce CAVs to play truthfully thus reaching the socially optimal solution.","PeriodicalId":338621,"journal":{"name":"2023 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125246137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wind Sensitivity of Electric Vehicle Energy Consumption and Influence on Range Prediction and Optimal Vehicle Routes","authors":"Trung B. Tran, I. Kolmanovsky, Erik Biberstein, Omar Makke, Marina Tharayil, O. Gusikhin","doi":"10.1109/MOST57249.2023.00020","DOIUrl":"https://doi.org/10.1109/MOST57249.2023.00020","url":null,"abstract":"The energy consumption of electric vehicles (EVs) depends on multiple factors. As it affects vehicle range, it must be accurately predicted. After a summary of the relevant literature, this paper focuses on the sensitivity of energy consumption to wind velocity and wind direction. The outcomes from model-based sensitivity analysis of the wind effects on energy consumption and the range of EVs over real-world routes are presented. Data sources available for online and offline wind velocity and wind direction determination are discussed. Recognizing the interplay between range prediction and the route chosen, we consider a Markov Decision Process (MDP) based framework for battery-charge and travel-time aware route planning that accounts for the impact of the wind on optimal routing decisions including stops at the charging stations. Finally, we propose a framework that includes wind in the operation of EVs, which consists of learning the impact of wind, incorporating wind forecasting into range and energy prediction, and using that prediction to perform optimal routing.","PeriodicalId":338621,"journal":{"name":"2023 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124096463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Autonomous Shuttle Integrated in a Communication and Sensing City Infrastructure","authors":"J. Amaral, J. Viegas, B. Lemos, P. Almeida, Rodrigo Rosmaninho, Gonçalo Perna, P. Rito, S. Sargento","doi":"10.1109/MOST57249.2023.00018","DOIUrl":"https://doi.org/10.1109/MOST57249.2023.00018","url":null,"abstract":"On the road to autonomous mobility, this paper presents a platform that has been developed to run an autonomous shuttle in the city of Aveiro, in Portugal. The autonomous shuttle was integrated within the living lab infrastructure in the city, equipped with sensors and with an On-Board Unit (OBU) with Vehicle to Everything (V2X) communications. Through this approach, the shuttle is able to communicate and exchange information with the infrastructure and other vehicles, exchanging Collective Perception Messages (CPMs) with information regarding perceived objects from the sensors installed in the vehicles and in the roads.This platform also contains a web platform that is able to provide real-time information from both communication and sensing devices in both the vehicle and infrastructure, including the information on the virtual traffic lights.The obtained results show the correct operation of the shuttle according to the context of the road and the objects/obstacles detected, the detection performance, the timely reaction to the events, and the great user experience feedback from the users experiencing the travel.","PeriodicalId":338621,"journal":{"name":"2023 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123739363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What does a Panoptic Perception Model Learn?","authors":"Lanyu Xu","doi":"10.1109/MOST57249.2023.00032","DOIUrl":"https://doi.org/10.1109/MOST57249.2023.00032","url":null,"abstract":"Panoptic driving perception is a promising technology for autonomous driving, which aims to provide a comprehensive understanding of the surrounding environment by processing multiple tasks together. Given the constrained resource on autonomous vehicles, it is essential to develop panoptic perception models with high precision and low resource consumption to assist autonomous driving in real-time. To achieve this goal, it is urgent to understand what a panoptic perception model learns, and get insights to efficiently improve the model design. In this work, we focus on analyzing the explainability of panoptic perception models. Specifically, we use YOLOP as an example, analyze the model explainability and propose several insights for designing the panoptic perception model in the future. To facilitate further research, the source codes are released at https://github.com/lori930/panoptic_visualization.","PeriodicalId":338621,"journal":{"name":"2023 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130250704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"m-BMC: Exploration of Magnetic Field Measurements for Indoor Positioning Using mini-Batch Magnetometer Calibration","authors":"Hamaad Rafique, Davide Patti, M. Palesi, V. Catania","doi":"10.1109/MOST57249.2023.00014","DOIUrl":"https://doi.org/10.1109/MOST57249.2023.00014","url":null,"abstract":"Due to the ubiquity and lack of infrastructure, magnetic field-based (MF) indoor localization is garnering a lot of attention. However, there are still issues with discernability, interference from ferromagnetic materials, and heterogeneous devices for MF-based location signals. In this work, we investigate the importance of signal calibration for fingerprint development, showing how particle filtering can be used in conjunction with magnetometer calibration to predict and remove irregularities from MF signals. With this regard, we also evaluate the impact of the heterogeneity of device sensors on the performance of MF-based indoor localization. Finally, we apply and compare a set of machine learning classifiers for the sake of localization performance assessment on both homogeneous and heterogeneous setups. The results show that, in both scenarios, fuzzy KNN can outperform other classifiers by up to 85% and 78%, respectively.","PeriodicalId":338621,"journal":{"name":"2023 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126492567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}