Modal Emissions Modeling: A Physical Approach

1996 ◽  
Vol 1520 (1) ◽  
pp. 81-88 ◽  
Author(s):  
Matthew Barth ◽  
Feng An ◽  
Joseph Norbeck ◽  
Marc Ross
Keyword(s):  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Control Measures ◽  
Mobile Source ◽  
Alternative Fuel Vehicles ◽  
Modeling Approach ◽  
Emissions Modeling ◽  
Vehicle Operation ◽  
Wide Range ◽  
Emission Models

Mobile source emission models currently used by state and federal agencies (e.g., Environmental Protection Agency's MOBILE and California Air Resources Board's EMFAC) are often inadequate for analyzing the emissions impact of various transportation control measures, intelligent transportation systems, alternative fuel vehicles, and more sophisticated inspection/maintenance programs contained in most state air quality management plans. These emission models are based on the assumption that vehicle running exhaust emissions can be represented as integrated values for a specific driving cycle, and then later adjusted by speed correction factors. What is needed in addition to these “regional-type” mobile source models is an emissions model that considers at a more fundamental level the modal operation of a vehicle (i.e., emissions that directly relate to vehicle operating modes such as idle, steady-state cruise, various levels of acceleration/deceleration, and so forth). A new modal-emissions modeling approach that is deterministic and based on analytical functions that describe the physical phenomena associated with vehicle operation and emissions productions is presented. This model relies on highly time-resolved emissions and vehicle operation data that must be collected from a wide range of vehicles of varying emission control technologies. Current emission modeling techniques are discussed and the modeling approach and implementation plan for a new, three-year NCHRP Project entitled “Development of a Modal Emissions Model” are described.

scholarly journals Applications of Internet of Things

2018 ◽  
Vol 7 (9) ◽  
pp. 334
Author(s):  
Chi-Hua Chen ◽  
Kuen-Rong Lo
Keyword(s):  
Internet Of Things ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Location Privacy ◽  
High Efficiency ◽  
Transportation Systems ◽  
Location Based Services ◽  
Vehicle Operation ◽  
Vehicle Positioning ◽  
Coverage Estimation

This editorial introduces the special issue entitled “Applications of Internet of Things”, of ISPRS International Journal of Geo-Information. Topics covered in this issue include three main parts: (I) intelligent transportation systems (ITS), (II) location-based services (LBS), and (III) sensing techniques and applications. Three papers on ITS are as follows: (1) “Vehicle positioning and speed estimation based on cellular network signals for urban roads,” by Lai and Kuo; (2) “A method for traffic congestion clustering judgment based on grey relational analysis,” by Zhang et al.; and (3) “Smartphone-based pedestrian’s avoidance behavior recognition towards opportunistic road anomaly detection,” by Ishikawa and Fujinami. Three papers on LBS are as follows: (1) “A high-efficiency method of mobile positioning based on commercial vehicle operation data,” by Chen et al.; (2) “Efficient location privacy-preserving k-anonymity method based on the credible chain,” by Wang et al.; and (3) “Proximity-based asynchronous messaging platform for location-based Internet of things service,” by gon Jo et al. Two papers on sensing techniques and applications are as follows: (1) “Detection of electronic anklet wearers’ groupings throughout telematics monitoring,” by Machado et al.; and (2) “Camera coverage estimation based on multistage grid subdivision,” by Wang et al.

scholarly journals How Can Smart Mobility Innovations Alleviate Transportation Disadvantage? Assembling a Conceptual Framework through a Systematic Review

2020 ◽  
Vol 10 (18) ◽  
pp. 6306 ◽  
Author(s):  
Luke Butler ◽  
Tan Yigitcanlar ◽  
Alexander Paz
Keyword(s):  
Conceptual Framework ◽  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Technological Innovations ◽  
Potential Solution ◽  
Wide Range ◽  
Smart Mobility

Transportation disadvantage is about the difficulty accessing mobility services required to complete activities associated with employment, shopping, business, essential needs, and recreation. Technological innovations in the field of smart mobility have been identified as a potential solution to help individuals overcome issues associated with transportation disadvantage. This paper aims to provide a consolidated understanding on how smart mobility innovations can contribute to alleviate transportation disadvantage. A systematic literature review is completed, and a conceptual framework is developed to provide the required information to address transportation disadvantage. The results are categorized under the physical, economic, spatial, temporal, psychological, information, and institutional dimensions of transportation disadvantage. The study findings reveal that: (a) Primary smart mobility innovations identified in the literature are demand responsive transportation, shared transportation, intelligent transportation systems, electric mobility, autonomous vehicles, and Mobility-as-a-Services. (b) Smart mobility innovations could benefit urban areas by improving accessibility, efficiency, coverage, flexibility, safety, and the overall integration of the transportation system. (c) Smart mobility innovations have the potential to contribute to the alleviation of transportation disadvantage. (d) Mobility-as-a-Service has high potential to alleviate transportation disadvantage primarily due to its ability to integrate a wide-range of services.

scholarly journals Emissions and Fuel Consumption Modeling for Evaluating Environmental Effectiveness of ITS Strategies

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Yuan-yuan Song ◽  
En-jian Yao ◽  
Ting Zuo ◽  
Zhi-feng Lang
Keyword(s):  
Fuel Consumption ◽  
Intelligent Transportation Systems ◽  
Vehicle Emissions ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Estimation Accuracy ◽  
Road Transportation ◽  
Emission Data ◽  
Vehicle Operation ◽  
Environmental Effectiveness

Road transportation is a major fuel consumer and greenhouse gas emitter. Recently, the intelligent transportation systems (ITSs) technologies, which can improve traffic flow and safety, have been developed to reduce the fuel consumption and vehicle emissions. Emission and fuel consumption estimation models play a key role in the evaluation of ITS technologies. Based on the influence analysis of driving parameters on vehicle emissions, this paper establishes a set of mesoscopic vehicle emission and fuel consumption models using the real-world vehicle operation and emission data. The results demonstrate that these models are more appropriate to evaluate the environmental effectiveness of ITS strategies with enough estimation accuracy.

Study on Path Optimization Method of Traffic Guidance System under the Condition of the Car Networking

2014 ◽  
Vol 624 ◽  
pp. 567-570
Author(s):  
Dan Ping Wang ◽  
Kun Yuan Hu
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
System Integration ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Guidance System ◽  
Wide Range ◽  
Computer Communication Network

Intelligent Transportation System is the primary means of solving the city traffic problem. The information technology, the communication, the electronic control technology and the system integration technology and so on applies effectively in the transportation system by researching rationale model, thus establishes real-time, accurate, the highly effective traffic management system plays the role in the wide range. Traffic flow guidance system is one of cores of Intelligent Transportation Systems. It is based on modern technologies, such as computer, communication network, and so on. Supplying the most superior travel way and the real-time transportation information according to the beginning and ending point of the journey. The journey can promptly understand in the transportation status of road network according to the guidance system, then choosing the best route to reach destination.

scholarly journals An Integrative Approach to Accurate Vehicle Logo Detection

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Hao Pan ◽  
Bailing Zhang
Keyword(s):  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Human Vision ◽  
Integrative Approach ◽  
Support Vector ◽  
Adaboost Algorithm ◽  
Vehicle Recognition ◽  
Region Detection ◽  
Wide Range ◽  
Visual Attention Mechanism

Vehicle logo detection from images captured by surveillance cameras is an important step towards the vehicle recognition that is required for many applications in intelligent transportation systems and automatic surveillance. The task is challenging considering the small target of logos and the wide range of variability in shape, color, and illumination. A fast and reliable vehicle logo detection approach is proposed following visual attention mechanism from the human vision. Two prelogo detection steps, that is, vehicle region detection and a small RoI segmentation, rapidly focalize a small logo target. An enhanced Adaboost algorithm, together with two types of features of Haar and HOG, is proposed to detect vehicles. An RoI that covers logos is segmented based on our prior knowledge about the logos’ position relative to license plates, which can be accurately localized from frontal vehicle images. A two-stage cascade classier proceeds with the segmented RoI, using a hybrid of Gentle Adaboost and Support Vector Machine (SVM), resulting in precise logo positioning. Extensive experiments were conducted to verify the efficiency of the proposed scheme.

scholarly journals The Role of ICT in the Smart City Concept

2019 ◽  
Vol 14 (1) ◽  
pp. 63-74 ◽  
Author(s):  
Mariusz Czupich
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart City ◽  
Public Services ◽  
Transportation Systems ◽  
City Management ◽  
Negative Consequences ◽  
Large Cities ◽  
Wide Range ◽  
The Face

The concept of a smart city enables the effective implementation of public services despite the negative consequences related to population growth in large cities. City authorities, in the face of growing demand for public services, often use a wide range of smart city instruments in various areas of operation. Despite the fact that a large part of innovative solutions is widespread and used, such as intelligent transportation systems or e-office, new opportunities are still emerging which are aimed at improving the quality of life for city dwellers. The aim of the article is to define the role of ICT in smart city management. The subjects of analysis are innovative instruments used in technologically advanced cities as well as contemporary challenges facing city management. The functioning of the city depends to a large extent on access to the communication network, mobile devices as well as on infrastructure connected with them. Therefore, it is necessary, on the one hand, to ensure the capacity of connections and network communication, and, on the other hand, to involve citizens in the process of creating new solutions.

scholarly journals Integration of Blockchain with Connected and Autonomous Vehicles: Vision and Challenge

2022 ◽  
Vol 14 (1) ◽  
pp. 1-10
Author(s):  
Tooska Dargahi ◽  
Hossein Ahmadvand ◽  
Mansour Naser Alraja ◽  
Chia-Mu Yu
Keyword(s):  
Data Protection ◽  
Intelligent Transportation Systems ◽  
Data Security ◽  
Autonomous Vehicles ◽  
Personal Data ◽  
Transportation Systems ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Blockchain Technology ◽  
Wide Range

Connected and Autonomous Vehicles (CAVs) are introduced to improve individuals’ quality of life by offering a wide range of services. They collect a huge amount of data and exchange them with each other and the infrastructure. The collected data usually includes sensitive information about the users and the surrounding environment. Therefore, data security and privacy are among the main challenges in this industry. Blockchain, an emerging distributed ledger, has been considered by the research community as a potential solution for enhancing data security, integrity, and transparency in Intelligent Transportation Systems (ITS). However, despite the emphasis of governments on the transparency of personal data protection practices, CAV stakeholders have not been successful in communicating appropriate information with the end users regarding the procedure of collecting, storing, and processing their personal data, as well as the data ownership. This article provides a vision of the opportunities and challenges of adopting blockchain in ITS from the “data transparency” and “privacy” perspective. The main aim is to answer the following questions: (1) Considering the amount of personal data collected by the CAVs, such as location, how would the integration of blockchain technology affect transparency , fairness , and lawfulness of personal data processing concerning the data subjects (as this is one of the main principles in the existing data protection regulations)? (2) How can the trade-off between transparency and privacy be addressed in blockchain-based ITS use cases?

An Accurate Real-Time License Plate Detection Method Based On Deep Learning Approaches

2021 ◽  
pp. 2160008
Author(s):  
Saeed Khazaee ◽  
Ali Tourani ◽  
Sajjad Soroori ◽  
Asadollah Shahbahrami ◽  
Ching Yee Suen
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
Optical Character Recognition ◽  
Transportation Systems ◽  
Training Data ◽  
Detection Accuracy ◽  
License Plate ◽  
Learning Approaches ◽  
Wide Range ◽  
License Plate Detection

In vision-driven Intelligent Transportation Systems (ITS) where cameras play a vital role, accurate detection and re-identification of vehicles are fundamental demands. Hence, recent approaches have employed a wide range of algorithms to provide the best possible accuracy. These methods commonly generate a vehicle detection model based on its visual appearance features such as license plate, headlights, or some other distinguishable specifications. Among different object detection approaches, Deep Neural Networks (DNNs) have the advantage of magnificent detection accuracy in case a huge amount of training data is provided. In this paper, a robust approach for license plate detection (LPD) based on YOLO v.3 is proposed which takes advantage of high detection accuracy and real-time performance. The mentioned approach can detect the license plate location of vehicles as a general representation of vehicle presence in images. To train the model, a dataset of vehicle images with Iranian license plates has been generated by the authors and augmented to provide a wider range of data for test and train purposes. It should be mentioned that the proposed method can detect the license plate area as an indicator of vehicle presence with no Optical Character Recognition (OCR) algorithm to distinguish characters inside the license plate. Experimental results have shown the high performance of the system with a precision 0.979 and recall 0.972.

scholarly journals LPWAN-Based Hybrid Backhaul Communication for Intelligent Transportation Systems: Architecture and Performance Evaluation

2020 ◽  
Author(s):  
Taghi Shahgholi ◽  
Amir Sheikhahmadi ◽  
Keyhan Khamforoosh ◽  
Sadoon Azizi
Keyword(s):  
Performance Evaluation ◽  
Low Power ◽  
Intelligent Transportation Systems ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Area Network ◽  
Emergency Vehicle ◽  
Wide Range

Abstract Increased number of the vehicles on the streets around the world has led to several problems including traffic congestion in many regions. Intelligent Transportation Systems (ITSs) are a viable solution for this problem by implementing efficient use of the current infrastructures. In this paper, the possibility of using cellular-based Low-Power Wide-Area Network (LPWAN) communications, LTE-M and NB-IoT, for ITS applications has been investigated. LTE-M and NB-IoT are designed to provide wide-range, low power and low cost communication infrastructures and can be a promising option which has the potential to be employed immediately in real systems. In order to to understand the feasibility of using LPWAN for ITS, two applications with low and high delay requirements have been examined: road traffic monitoring and emergency vehicle management. Then, the performance of using LTE-M and NB-IoT for providing backhaul communication infrastructure has been evaluated in a realistic simulation environment and compared for these two scenarios in terms of end to end delay per user. Simulation of Urban MObility (SUMO) has been used for realistic traffic generation and a Python-based program has been developed. This program has the ability to exchange live data with SUMO for communication performance evaluation. The simulation results demonstrate the feasibility of using LPWAN for ITS backhaul infrastructure mostly in favor of the LTE-M over NB-IoT.

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