scholarly journals Kernel Sparse Representation with Hybrid Regularization for On-Road Traffic Sensor Data Imputation

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2884 ◽  
Author(s):  
Xiaobo Chen ◽  
Cheng Chen ◽  
Yingfeng Cai ◽  
Hai Wang ◽  
Qiaolin Ye
Keyword(s):  
Data Analysis ◽  
Sparse Representation ◽  
Intelligent Transportation Systems ◽  
Missing Values ◽  
Road Traffic ◽  
Linear Representation ◽  
Transportation Systems ◽  
Sensor Data ◽  
L1 Norm ◽  
L2 Norm

The problem of missing values (MVs) in traffic sensor data analysis is universal in current intelligent transportation systems because of various reasons, such as sensor malfunction, transmission failure, etc. Accurate imputation of MVs is the foundation of subsequent data analysis tasks since most analysis algorithms need complete data as input. In this work, a novel MVs imputation approach termed as kernel sparse representation with elastic net regularization (KSR-EN) is developed for reconstructing MVs to facilitate analysis with traffic sensor data. The idea is to represent each sample as a linear combination of other samples due to inherent spatiotemporal correlation, as well as periodicity of daily traffic flow. To discover few yet correlated samples and make full use of the valuable information, a combination of l1-norm and l2-norm is employed to penalize the combination coefficients. Moreover, the linear representation among samples is extended to nonlinear representation by mapping input data space into high-dimensional feature space, which further enhances the recovery performance of our proposed approach. An efficient iterative algorithm is developed for solving KSR-EN model. The proposed method is verified on both an artificially simulated dataset and a public road network traffic sensor data. The results demonstrate the effectiveness of the proposed approach in terms of MVs imputation.

scholarly journals LPWAN-based hybrid backhaul communication for intelligent transportation systems: architecture and performance evaluation

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Taghi Shahgholi ◽  
Amir Sheikhahmadi ◽  
Keyhan Khamforoosh ◽  
Sadoon Azizi
Keyword(s):  
Low Power ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Area Network ◽  
Emergency Vehicle ◽  
Wide Area Network

AbstractIncreased number of the vehicles on the streets around the world has led to several problems including traffic congestion, emissions, and huge fuel consumption in many regions. With advances in wireless and traffic technologies, the Intelligent Transportation System (ITS) has been introduced as a viable solution for solving these problems by implementing more 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 long 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 this paper, we have proposed an architecture to employ the LPWAN as a backhaul infrastructure for ITS and to understand the feasibility of the proposed model, 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 latency per user. Simulation of Urban MObility has been used for realistic traffic generation and a Python-based program has been developed for evaluation of the communication system. The simulation results demonstrate the feasibility of using LPWAN for ITS backhaul infrastructure mostly in favor of the LTE-M over NB-IoT.

scholarly journals A Multi-Loop Vehicle-Counting Method under Gray Mode and RGB Mode

2021 ◽  
Vol 11 (15) ◽  
pp. 6831
Author(s):  
Yue Chen ◽  
Jian Lu
Keyword(s):  
Intelligent Transportation Systems ◽  
High Efficiency ◽  
Road Traffic ◽  
Low Cost ◽  
Rapid Development ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Counting Method ◽  
Moving Vehicle ◽  
Available Information

With the rapid development of road traffic, real-time vehicle counting is very important in the construction of intelligent transportation systems (ITSs). Compared with traditional technologies, the video-based method for vehicle counting shows great importance and huge advantages in its low cost, high efficiency, and flexibility. However, many methods find difficulty in balancing the accuracy and complexity of the algorithm. For example, compared with traditional and simple methods, deep learning methods may achieve higher precision, but they also greatly increase the complexity of the algorithm. In addition to that, most of the methods only work under one mode of color, which is a waste of available information. Considering the above, a multi-loop vehicle-counting method under gray mode and RGB mode was proposed in this paper. Under gray and RGB modes, the moving vehicle can be detected more completely; with the help of multiple loops, vehicle counting could better deal with different influencing factors, such as driving behavior, traffic environment, shooting angle, etc. The experimental results show that the proposed method is able to count vehicles with more than 98.5% accuracy while dealing with different road scenes.

scholarly journals A Survey on Fault Tolerance Techniques for Wireless Vehicular Networks

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1358 ◽  
Author(s):  
João Almeida ◽  
João Rufino ◽  
Muhammad Alam ◽  
Joaquim Ferreira
Keyword(s):  
Fault Tolerance ◽  
Intelligent Transportation Systems ◽  
Vehicular Networks ◽  
Road Traffic ◽  
Fault Tolerant ◽  
Human Life ◽  
Transportation Systems ◽  
Vehicular Communications ◽  
Self Driving Cars ◽  
Meta Analyses

Future intelligent transportation systems (ITS) hold the promise of supporting the operation of safety-critical applications, such as cooperative self-driving cars. For that purpose, the communications among vehicles and with the road-side infrastructure will need to fulfil the strict real-time guarantees and challenging dependability requirements. These safety requisites are particularly important in wireless vehicular networks, where road traffic presents several threats to human life. This paper presents a systematic survey on fault tolerance techniques in the area of vehicular communications. The work provides a literature review of publications in journals and conferences proceedings, available through a set of different search databases (IEEE Xplore, Web of Science, Scopus and ScienceDirect). A systematic method, based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) Statement was conducted in order to identify the relevant papers for this survey. After that, the selected articles were analysed and categorised according to the type of redundancy, corresponding to three main groups (temporal, spatial and information redundancy). Finally, a comparison of the core features among the different solutions is presented, together with a brief discussion regarding the main drawbacks of the existing solutions, as well as the necessary steps to provide an integrated fault-tolerant approach to the future vehicular communications systems.

scholarly journals Networked Electronic Equipments Using the IEEE 1451 Standard—VisioWay: A Case Study in the ITS Area

2012 ◽  
Vol 8 (4) ◽  
pp. 467124 ◽  
Author(s):  
F. Barrero ◽  
S. L. Toral ◽  
M. Vargas ◽  
J. Becerra
Keyword(s):  
Video Processing ◽  
Intelligent Transportation Systems ◽  
Road Traffic ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
New Paradigm ◽  
Ieee 1451 ◽  
The Impact ◽  
Smart Transducer

The concept of Intelligent Transportation Systems (ITSs) has been recently introduced to define modern embedded systems with enhanced digital connectivity, combining people, vehicles, and public infrastructure. The smart transducer concept, on the other hand, has been established by the IEEE 1451 standard to simplify the scalability of networked electronic equipments. The synergy of both concepts will establish a new paradigm in the near future of the ITS area. The purpose of this paper is to analyze the integration of electronic equipments into intelligent road-traffic management systems by using the smart transducer concept. An automated video processing sensor for road-traffic monitoring applications is integrated into an ITS network as a case study. The impact of the IEEE 1451 standard in the development and performance of ITS equipments is analyzed through its application to this video-based system, commercialized under the name VisioWay.

scholarly journals A New Distributed and Scalable Network Protocol Targeting Intelligent Transportation Systems

2011 ◽  
Vol 2011 ◽  
pp. 1-7
Author(s):  
M. Meribout
Keyword(s):  
Intelligent Transportation Systems ◽  
Road Traffic ◽  
Response Times ◽  
Cluster Head ◽  
Data Communication ◽  
Intelligent Transportation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Traffic Information ◽  
Scalable Network

Vehicular networks are the major ingredients of the envisioned Intelligent Transportation Systems (ITS) concept. An important component of ITS which is currently attracting wider research focus is road traffic monitoring. The actual approaches for traffic road monitoring are characterized by longer response times and are also subject to higher processing requirements and possess high deployment costs. In this paper, we propose a completely distributed and scalable mechanism for wireless sensor network-based road traffic monitoring. The approach relies on the distributed and bidirectional exchange of traffic information between the vehicles traversing the routes and a miniature cluster head and takes into consideration both the security and reliability of data communication. In addition, the communication between nodes is collision-free since the underlined data link layer protocol relies on a heuristic time multiplexed-based protocol. The performance analysis shows that the proposed mechanism usually outperforms other algorithms for different traffic densities.

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):  
Low Power ◽  
Intelligent Transportation Systems ◽  
Data Exchange ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Area Network ◽  
Emergency Vehicle ◽  
Communication Infrastructure

Abstract There are more than 1.3 billion vehicles around the world and rapidly growing which causing worldwide challenges such as congestion, huge fuel consumption, and emissions. The solution to these issues could be expansion of infrastructure or making efficient use of the current infrastructure using current technological advances by implementing Intelligent Transportation Systems (ITSs). In this paper, we proposed and explored the possibility of using cellular-based Low-Power Wide-Area Network (LPWAN) communications, LTE-M and Narrowband Internet of Things (NB-IoT), for ITS applications. LTE-M and NB-IoT are designed to provide long-range, low power, and lowcost communication infrastructure and can be a viable promising option for immediate implementation in the real world. In order to understand the feasibility of using LPWAN for ITS, we investigated two applications with low and high delay requirements: road traffic monitoring and emergency vehicle management and preemption. 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 latency per user. SUMO traffic simulator has been used for realistic traffic generation and a Python-based program with the ability to live data exchange with SUMO has been developed for communication performance evaluations. The simulation results demonstrate the feasibility of using LPWAN for ITS backhaul infrastructure where it was in favor of the LTE-M over NB-IoT.

INTELLIGENT TRANSPORTATION SYSTEMS IN IMPROVING TRAFFIC FLOW IN TOURISM DESTINATIONS∗

2007 ◽  
Vol 13 (3) ◽  
pp. 627-636
Author(s):  
Edna Mrnjavac ◽  
Robert Marsanić
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Emergency Services ◽  
Road Traffic ◽  
Weather Conditions ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Transportation Infrastructure ◽  
Public Traffic ◽  
Tourism Destinations

The rapid growth and development of motorisation combined with relatively small investments made to improving transportation infrastructure in cities, as well as in tourism destinations, has led to serious problems in the unobstructed movement of vehicles in public traffic areas. Traffic congestion on roadways, in ferryboat ports and at state borders during the summer months and year-round lines of cars going to or returning from work are a regular presence in traffic in most urban and tourism destinations in Croatia, as well as in the rest of Europe. Intelligent transportation systems (ITS) can be implemented in urban and tourism centres, which, for example, have no opportunity for increasing the capacity of their traffic networks by constructing new, or expanding existing, transportation infrastructure, and no opportunity for increasing parking capacities. The only solution would be to optimise traffic networking by introducing intelligent technologies. Intelligent transportation systems and services represent a coupling of information and telecommunication technologies with transportation means and infrastructure to ensure greater efficiency in the mobility of people and goods. ITS implementation helps to provide better information to motorists and travellers (tourists); improve traffic and tourist flows, cargo transportation, public passenger-transportation; facilitate the work of emergency services; enable electronic traffic-related payments; enhance the security of people in road traffic; and monitor weather conditions and the environment. To motorists the system provides guidance to roads on which traffic is less intense, guidance to available parking spaces, and guidance, for example, to a good restaurant or interesting tourist attraction. his paper focuses, in particular, on ITS application in city and tourism destinations in connection with parking problems. Guiding vehicles to the closest vacant parking space helps to reduce traffic congestion, reduce the amount of time lost in searching and increase the occupancy rate of car-parks

Road Traffic Congestion (TraCo) Estimation Using Multi-Layer Continuous Virtual Loop (MCVL)

2021 ◽  
Vol 17 (2) ◽  
pp. 46-71
Author(s):  
Manipriya Sankaranarayanan ◽  
Mala C. ◽  
Samson Mathew
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Vehicle Detection ◽  
Transportation Systems ◽  
Traffic Information ◽  
Traffic Characteristics ◽  
Traffic Video ◽  
Virtual Loop

Any road traffic management application of intelligent transportation systems (ITS) requires traffic characteristics data such as vehicle density, speed, etc. This paper proposes a robust and novel vehicle detection framework known as multi-layer continuous virtual loop (MCVL) that uses computer vision techniques on road traffic video to estimate traffic characteristics. Estimations of traffic data such as speed, area occupancy and an exclusive spatial feature named as corner detail value (CDV) acquired using MCVL are proposed. Further, the estimation of traffic congestion (TraCo) level using these parameters is also presented. The performances of the entire framework and TraCo estimation are evaluated using several benchmark traffic video datasets and the results are presented. The results show that the improved accuracy in vehicle detection process using MCVL subsequently improves the precision of TraCo estimation. This also means that the proposed framework is well suited to applications that need traffic characteristics to update their traffic information system in real time.

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