List of Titles

Dynamic V2I/V2V cooperative scheme for connectivity and throughput enhancement

- Nguyen, Bach, Ngo, Duy, Tran, Nguyen, Dao, Minh, Vu, Hai

Authors: Nguyen, Bach , Ngo, Duy , Tran, Nguyen , Dao, Minh , Vu, Hai
Date: 2022
Type: Text , Journal article
Relation: IEEE Transactions on Intelligent Transportation Systems Vol. 23, no. 2 (2022), p. 1236-1246
Full Text: false
Reviewed:
Description: Automotive infotainment systems are expected to be first deployed on highways to service drivers travelling long distances, who are more likely to utilize the infotainment applications. In order to meet the stringent requirements of the infotainment systems, road side units (RSUs) are installed along the highway to facilitate a continuous vehicle-to-infrastructure (V2I) connectivity. Due to the long travelling distance and small coverage of the individual RSU, a more cost-effective solution would be to combine V2I with the vehicle-to-vehicle (V2V) communications to maintain the continuous connectivity. In this paper, we propose a new dynamic cooperation scheme that employs a dynamic forwarder selection strategy to generate an adaptive multi-hop V2V path for connectivity maintenance and throughput enhancement at a vehicle located outside of the RSU's coverage range. For the commonly assumed scenario that all vehicles travel in the same direction and at the same speed, we develop an analytical model and derive closed-formed expressions for the average out-of-range connection time, number of service resumptions and achieved throughput. The developed analytical model provides insights into the impacts of inter-RSU distance, vehicles' assistance willingness and the target vehicle's buffer size to the network performance. Simulation results with practical parameter settings show that our proposed scheme is effective in improving connectivity while offering a high throughput for the target vehicle. In particular, a high vehicle density, more assistance willingness by the forwarders and a large buffer size at the target vehicle are shown to be helpful in sparse RSU deployments. © 2000-2011 IEEE.

Traffic accident detection and condition analysis based on social networking data

- Ali, Farman, Ali, Amjad, Imran, Muhammad, Naqvi, Rizwan, Siddiqi, Muhammad, Kwak, Kyung-Sup

Authors: Ali, Farman , Ali, Amjad , Imran, Muhammad , Naqvi, Rizwan , Siddiqi, Muhammad , Kwak, Kyung-Sup
Date: 2021
Type: Text , Journal article
Relation: Accident Analysis and Prevention Vol. 151, no. (2021), p.
Full Text: false
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Description: Accurate detection of traffic accidents as well as condition analysis are essential to effectively restoring traffic flow and reducing serious injuries and fatalities. This goal can be obtained using an advanced data classification model with a rich source of traffic information. Several systems based on sensors and social networking platforms have been presented recently to detect traffic events and monitor traffic conditions. However, sensor-based systems provide limited information, and may fail owing to the long detection times and high false-alarm rates. In addition, social networking data are unstructured, unpredictable, and contain idioms, jargon, and dynamic topics. The machine learning algorithms utilized for traffic event detection might not extract valuable information from social networking data. In this paper, a social network–based, real-time monitoring framework is proposed for traffic accident detection and condition analysis using ontology and latent Dirichlet allocation (OLDA) and bidirectional long short-term memory (Bi-LSTM). First, the query-based search engine effectively collects traffic information from social networks, and the data preprocessing module transforms it into structured form. Second, the proposed OLDA-based topic modeling method automatically labels each sentence (e.g., traffic or non-traffic) to identify the exact traffic information. In addition, the ontology-based event recognition approach detects traffic events from traffic-related data. Next, the sentiment analysis technique identifies the polarity of traffic events employing user's opinions, which helps determine accurate conditions of traffic events. Finally, the FastText model and Bi-LSTM with softmax regression are trained for traffic event detection and condition analysis. The proposed framework is evaluated using traffic-related data, comparing OLDA and Bi-LSTM with existing topic modeling methods and traditional classifiers using word embedding models, respectively. Our system outperforms state-of-the-art methods and achieves accuracy of 97 %. This finding demonstrates that the proposed system is more efficient for traffic event detection and condition analysis, in comparison to other existing systems. © 2021 Elsevier Ltd

An efficient caching policy for content retrieval in autonomous connected vehicles

- Rahim, Muddasir, Javed, Muhammad, Alvi, Alvi, Imran, Muhammad

Authors: Rahim, Muddasir , Javed, Muhammad , Alvi, Alvi , Imran, Muhammad
Date: 2020
Type: Text , Journal article
Relation: Transportation Research Part A: Policy and Practice Vol. 140, no. (2020), p. 142-152
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Description: Connected vehicles will enable the smart and autonomous transportation systems in the future. Cellular Vehicle-to-Everything (C-V2X) communication will provide wireless connectivity to enable large number of connected vehicle applications. Vehicles will receive traffic and infotainment contents from the city traffic command center using C-V2X communications. In this context, infrastructure Road Side Units (RSUs) will cache urgent and popular data in their memory storage, hence providing vehicles to retrieve information from a closer vicinity at a RSU. In this paper, we present a content caching policy for the connected vehicles operator to improve the efficiency of the content retrieval in terms of download rate and delay. We propose the utility functions for the RSUs and vehicles to cache a particular content at a given RSU. Moreover, Gale-Shapley stable matching algorithm is used to efficiently allocate RSU cache to the contents. We also provide rules to update the cache slots. The proposed caching scheme is compared with random caching policy and market matching based caching policies. Results show that the proposed content caching policy improves the efficiency of the content retrieval with 60% more data transmission with reduced downloading time and better link utilization as compared to other two scheme. © 2020 Elsevier Ltd

Scheduling and power control for connectivity enhancement in multi-hop I2V/V2V networks

- Nguyen, Bach, Ngo, Duy, Dao, Minh, Bao, Vo, Vu, Hai

Authors: Nguyen, Bach , Ngo, Duy , Dao, Minh , Bao, Vo , Vu, Hai
Date: 2022
Type: Text , Journal article
Relation: IEEE Transactions on Intelligent Transportation Systems Vol. 23, no. 8 (2022), p. 10322-10332
Full Text: false
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Description: Infrastructure-to-vehicle (I2V) and vehicle-to-vehicle (V2V) communications are often combined to extend the connectivity and coverage in the Intelligent Transportation System (ITS) and its applications, e.g., augmented reality, real-time parking management and online shopping. Through multi-hop I2V and V2V communications, requesting vehicles are always connected to road side units (RSUs) even when they do not reside within the RSUs' coverage range. However, there may be not adequate network resource for several I2V and V2V links when multiple vehicles request services simultaneously. In this paper, we propose a joint frequency scheduling and power control scheme to enhance connectivity in multi-hop I2V/V2V networks. We associate I2V and V2V links with tuple-links, then formulate an NP-hard problem in which a frequency scheduler and a power controller are jointly designed for the tuple-links. The NP-hard problem is decomposed into two separate subproblems by employing the delayed column generation technique. Then, we employ a method for linear programming and a greedy algorithm to address these subproblems. Through numerical experiments with practical parameter settings, we demonstrate the proposed scheme outperforms several existing ones in terms of connectivity enhancement, measured by the service resumption number and average achieved throughput. Furthermore, the efficiency of our scheme is further enhanced when the number of available channels is high, and buffer size equipped to the requesting vehicles is large. © 2000-2011 IEEE.

Cognitive AmBC-NOMA IoV-MTS networks with IQI : reliability and security analysis

- Li, Xingwang, Zheng, Yike, Alshehri, Mohammad, Hai, Linpeng, Balasubramanian, Venki, Zeng, Ming, Nie, Gaofeng

Authors: Li, Xingwang , Zheng, Yike , Alshehri, Mohammad , Hai, Linpeng , Balasubramanian, Venki , Zeng, Ming , Nie, Gaofeng
Date: 2023
Type: Text , Journal article
Relation: IEEE Transactions on Intelligent Transportation Systems Vol. 24, no. 2 (2023), p. 2596-2607
Full Text: false
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Description: Internet-of-Vehicle (IoV) enabled Maritime Transportation Systems (MTS) communication is anticipated to support ultra-reliable and low latency, diverse quality-of-service (QoS) and large-scale connectivities. To meet such stringent demands, a cognitive ambient backscatter non-orthogonal multiple access (C-AmBC-NOMA) IoV-MTS network is proposed. We explore the reliable and secure performance of the proposed C-AmBC-NOMA IoV-MTS network with in-phase and quadrature phase imbalance (IQI) at radio-frequency (RF) front-ends and the existence of an eavesdropper. In particular, the analytical expressions on the outage probability (OP) and intercept probability (IP) are obtained after a series of calculations. For a deeper understanding, we discuss the asymptotic behavior of OPs in the high signal-to-noise ratio (SNR) region, the diversity orders of OPs, and IPs in the high main-to-eavesdropper ratio (MER) regime. The results of Monte-Carlo simulation and a series of corresponding theoretical analysis show that: i) As the SNR approaches infinity, the OPs tend to be fixed non-negative values, indicating that the diversity orders of the OPs have error floors; ii) When the MER approaches infinity, the IPs of legitimate users decrease continuously, while the IP of backscatter device (BD) increases; iii) Compared with the system performance under ideal condition, the system performance is less reliable under IQI condition, but the security performance is enhanced; iv) By carefully selecting the system parameters, a trade-off can be achieved between reliability and security. © 2000-2011 IEEE.

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Exploring human mobility for multi-pattern passenger prediction : a graph learning framework

- Kong, Xiangjiea, Wang, Kailai, Hou, Mingliang, Xia, Feng, Karmakar, Gour, Li, Jianxin

Authors: Kong, Xiangjiea , Wang, Kailai , Hou, Mingliang , Xia, Feng , Karmakar, Gour , Li, Jianxin
Date: 2022
Type: Text , Journal article
Relation: IEEE Transactions on Intelligent Transportation Systems Vol. 23, no. 9 (2022), p. 16148-16160
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Description: Traffic flow prediction is an integral part of an intelligent transportation system and thus fundamental for various traffic-related applications. Buses are an indispensable way of moving for urban residents with fixed routes and schedules, which leads to latent travel regularity. However, human mobility patterns, specifically the complex relationships between bus passengers, are deeply hidden in this fixed mobility mode. Although many models exist to predict traffic flow, human mobility patterns have not been well explored in this regard. To address this research gap and learn human mobility knowledge from this fixed travel behaviors, we propose a multi-pattern passenger flow prediction framework, MPGCN, based on Graph Convolutional Network (GCN). Firstly, we construct a novel sharing-stop network to model relationships between passengers based on bus record data. Then, we employ GCN to extract features from the graph by learning useful topology information and introduce a deep clustering method to recognize mobility patterns hidden in bus passengers. Furthermore, to fully utilize spatio-temporal information, we propose GCN2Flow to predict passenger flow based on various mobility patterns. To the best of our knowledge, this paper is the first work to adopt a multi-pattern approach to predict the bus passenger flow by taking advantage of graph learning. We design a case study for optimizing routes. Extensive experiments upon a real-world bus dataset demonstrate that MPGCN has potential efficacy in passenger flow prediction and route optimization. © 2000-2011 IEEE.

Views of American and Australian mobility device users and ambulant bus users regarding occupant restraint systems on public buses

- Unsworth, Carolyn, Baker, Anne, Brito, Sara, Das Neves, B., Dickson, N., Gohil, Apeksha, Kahandawa, Gayan, Naweed, Anjum, Timmer, Amanda

Authors: Unsworth, Carolyn , Baker, Anne , Brito, Sara , Das Neves, B. , Dickson, N. , Gohil, Apeksha , Kahandawa, Gayan , Naweed, Anjum , Timmer, Amanda
Date: 2022
Type: Text , Journal article
Relation: Journal of Transport and Health Vol. 25, no. (2022), p.
Full Text: false
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Description: Introduction: With an ageing population, increasing numbers of people are using mobility devices, such as wheelchairs or scooters, whilst travelling on public route buses. The regulations and availability of active (wheelchair tie down and occupant restraint systems or WTORS) and passive (rearward facing) mobility device restraint systems on buses varies between countries. To date few studies have investigated passenger feedback on the use of restraint systems. This study aimed to gather feedback about WTORS on buses from passengers where these are in use (United States) and not in routine use (Australia) to guide decisions on their introduction. Methods: A prospective study using a purpose-designed electronic survey. Participants, predominantly recruited by Qualtrics, comprised two groups; mobility device and ambulant bus users in two countries; Australia and the United States (US). Results: The 448 participants rated the top two most important factors when deciding if buses should have WTORS as safety and comfort. Ninety-two percent of respondents believed people using mobility devices should use a WTORS which was rated 7.66/10 (SD1.97) as effective to prevent injuries to self or others. Only a minority of participants (13.2%) had ever slid or fallen from their mobility device, or seen a person slide or fall (13.6%) while on a bus with no differences between countries despite WTORS not being in use in Australia. Respondents reported it was OK to delay a journey an average of 5.52 (SD 2.89) minutes to secure/release a restraint system, which compares favourably to literature-reported real time of one to 4 min. Conclusions: Although WTORS were widely perceived by participants as important for safety, questions concerning their effectiveness to prevent slide or tip remain. Prior to the introduction of any securement system in Australia, the effectiveness of passive occupant containment systems to prevent slide or tip also warrants investigation. © 2022

A novel optimization approach towards improving separability of clusters

- Bagirov, Adil, Hoseini-Monjezi, Najmeh, Taheri, Sona

Authors: Bagirov, Adil , Hoseini-Monjezi, Najmeh , Taheri, Sona
Date: 2023
Type: Text , Journal article
Relation: Computers and Operations Research Vol. 152, no. (2023), p.
Relation: http://purl.org/au-research/grants/arc/DP190100580
Full Text: false
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Description: The objective functions in optimization models of the sum-of-squares clustering problem reflect intra-cluster similarity and inter-cluster dissimilarities and in general, optimal values of these functions can be considered as appropriate measures for compactness of clusters. However, the use of the objective function alone may not lead to the finding of separable clusters. To address this shortcoming in existing models for clustering, we develop a new optimization model where the objective function is represented as a sum of two terms reflecting the compactness and separability of clusters. Based on this model we develop a two-phase incremental clustering algorithm. In the first phase, the clustering function is minimized to find compact clusters and in the second phase, a new model is applied to improve the separability of clusters. The Davies–Bouldin cluster validity index is applied as an additional measure to compare the compactness of clusters and silhouette coefficients are used to estimate the separability of clusters. The performance of the proposed algorithm is demonstrated and compared with that of four other algorithms using synthetic and real-world data sets. Numerical results clearly show that in comparison with other algorithms the new algorithm is able to find clusters with better separability and similar compactness. © 2022

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