Transportation System Technologies Research Articles

Evaluating current and future pedestrian mid-block crossing safety treatments using virtual reality simulation

Virtual reality (VR) simulation offers a proactive, cost effective, immersive, and low risk platform for studying pedestrian safety. Within immersive virtual environments (IVEs), existing and alternative design conditions and intelligent transportation systems (ITS) technologies can be directly compared, prior to real-world implementation, to assess the impacts alternatives may have on pedestrian safety, perception, and behavior. Environmental factors can be controlled within IVEs so that test trials are replicable and directly comparable. Coupled with stated preference feedback, participants’ observed preferences and behavior provide a comprehensive understanding of the impacts of proposed design alternatives. This research presents a case study of pedestrian behavior with three different mid-block crossing safety treatments modeled within a one-to-one scale IVE replication of a real-world location in Charlottesville, Virginia. The three safety treatments consider both passive and active collision avoidance designs and technologies, including (1) the existing painted crosswalk, (2) the addition of rectangular rapid flashing beacons (RRFBs), and (3) a pedestrian to everything (P2X) ITS phone application. Additionally, this paper demonstrates a VR simulation experimental design and framework for testing pedestrian safety treatments within naturalistic and replicable IVEs to assess both stated and observed preferences and behaviors of pedestrians. Repeated measures ANOVA indicated changes in both accepted gap size (p = 0.001) and crossing speed (p < 0.001) with alternative safety treatments. Generalized mixed models showed that pedestrians waited for statistically larger gap sizes (p = 0.02) without the assistance of alternative safety technologies (RRFBs and P2X application) and pedestrians crossed the street significantly faster (p = 0.001) without the alternative safety technologies, leading to unsafe dashing behavior. Through post-experiment surveys, it was found that participants perceived the As Built environment to be the least safe of the three treatments and that their sense of risk within the IVE was realistic. Considering both the observed crossing behavior and stated feedback, pedestrians exhibited intentionally unsafe darting behavior without assistive safety technology. This study demonstrates how VR simulation may be leveraged to study both stated preferences and observed behavior for understanding the safety implications of alternative roadway designs, providing a proactive approach for assessing and designing for pedestrian safety.

Rotordynamics of a rotor supported by foil bearings under various housing excitation

Proton Exchange Membrane (PEM) Fuel cell Systems(FCS) are rapid-growing technology in transportation systems. In such applications, a motor-driven oil-free air compressor is one of the critical auxiliary subsystems. Foil bearings are the perfect choice as oil-free bearings for the compressors due to high rotordynamics stability and shock-resistance. The platform of a motor-driven oil-free compressor can also be used as an electric turbocharger for traditional internal combustion engines. All electromechanical subsystems for electric vehicles must satisfy vibration endurance requirements following ISO 16750–3:2012, characterized by certain g-loading at specific frequencies. For the compressor to satisfy ISO 16750 requirement, detailed rotordynamics simulations with externally excited compressor housing under certain g-loading are essential to design the foil bearings considering the static and dynamic loads to the bearing and rotordynamics stability. The main objectives of the current research are 1) to develop a four degree of freedom (4-DOF) dynamic model of the rotor supported by foil bearings under external excitation to the compressor, 2) to simulate linear and non-linear rotordynamics of the compressor rotor supported by two radial foil bearings, and 3) to provide appropriate design guideline such as bump stiffness and axial length of the foil bearings. The simulations show that the rotor is stable for both under single frequency excitation and simultaneous excitations of all the frequencies in ISO 17650 standard. 4-DOF modal analyses were applied to identify natural mode of the system under the housing excitation.

Intelligent Transportation System Technologies, Challenges and Security

Intelligent Transportation Systems (ITS) first appeared in 1868 with traffic lights. With developing technology, the need to bring a smart approach to transportation applications within the scope of speed and environmental protection has emerged. Protecting ITS infrastructure against cyber attacks has become a matter of reputation for states. It is essential to provide the necessary technological infrastructure for the integrated operation of the systems used in ITS, especially geographical location, communication, and mapping. These technological developments bring cyber attacks, risks, and many dangers that should be avoided, especially on the systems used. This study examines ITS architecture, applications, communication technologies, and new trend technologies in detail. This study includes contributing to studies in the field of ITS and preventing attacks and incidents that may occur in terms of cyber security. The most important cyber attacks that may occur in ITS applications are included. In addition, the minimum security requirements that can be taken in ITS applications and infrastructures against these attacks are included.

A Lagrangian approach for variable speed limit implementation in C-ITS framework

With the development of Cooperative-Intelligent Transport System (C-ITS) technologies, new strategies based on embedded technologies have emerged to manage road networks. This paper focuses on adapting to this connectivity context a Variable Speed Limit (VSL) system to detect shockwaves and anticipate their propagation based on the kinematic wave theory to dampen them. We provide an alternative framework to adapt the VSL strategy, well-suited for Eulerian approaches, into a Lagrangian context. While the Eulerian approach is based on Loop Detector (LD) and macroscopic traffic indicators (e.g. flow, density), our Lagrangian approach relies on Road Side Units (RSUs) that record the GPS traces shared by Connected Vehicles (CVs). Based on the combination of CV trajectories, Fundamental and Space-Time Diagrams theory, shockwave estimation and prediction processes directly operate on congestion waves, which release the estimation issue for traffic density. The simulation-based analysis reveals that the performance of the Lagrangian approach is comparable to the Eulerian configurations.

Stripe-Assisted Global Transformer and Spatial–Temporal Enhancement for Vehicle Re-Identification

As a core technology in intelligent transportation systems, vehicle re-identification has attracted growing attention. Most existing methods use CNNs to extract global and local features from vehicle images and roughly integrate them for identifying vehicles, addressing intra-class similarity and inter-class difference. However, a significant challenge arises from redundant information between global and local features and possible misalignment among local features, resulting in suboptimal efficiency when combined. To further improve vehicle re-identification, we propose a stripe-assisted global transformer (SaGT) method, which leverages a dual-branch network based on transformers to learn a discriminative whole representation for each vehicle image. Specifically, one branch exploits a standard transformer layer to extract a global feature, while the other branch employs a stripe feature module (SFM) to construct stripe-based features. To further facilitate the effective incorporation of local information into the learning process of the global feature, we introduce a novel stripe-assisted global loss (SaGL), which combines ID losses to optimize the model. Considering redundancy, we only use the global feature for inference, as we enhance the whole representation with stripe-specific details. Finally, we introduce a spatial-temporal probability (STPro) to provide a complementary metric for robust vehicle re-identification. Extensive and comprehensive evaluations on two public datasets validate the effectiveness and superiority of our proposed method.

Fuzzy-AHP based optimal RSU deployment (Fuzzy-AHP-ORD) approach using road and traffic analysis in VANET

Vehicular Ad Hoc Network (VANET) is a proven technology in Intelligent Transportation Systems (ITS) that provides various safety and non-safety applications. The Roadside Unit (RSU) is one of the essential components of the VANET, which allows vehicles to disseminate and exchange safety and infotainment information in a broader range. RSUs are also valuable for offloading the internet data traffic of vehicular users from cellular networks. However, due to high deployment and maintenance costs and security overhead, it is essential to optimally deploy these RSUs and place them in prominent places to increase the overall network coverage and efficiency. The existing deployment strategies either analyzed the road network on one or a few topological parameters or vehicular traffic parameters and considered equal or random weights for each parameter. None of them deal with the uncertainty of parameter weightage. Thus, this paper proposes a Fuzzy-Analytic Hierarchy Process-based optimal RSU deployment (Fuzzy-AHP-ORD) approach to finding the highly influential intersection nodes for RSU deployment. The Fuzzy-AHP-ORD considers different static and dynamic parameters concerning road topology and the vehicle’s traffic behavior. The weights of the parameter are calculated through Fuzzy-AHP, then the various intersection nodes of the road networks are ranked using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) based MADM (Multiple Attribute Decision Making) method. The simulation results reveal the effectiveness of the proposed method in comparison to other benchmark methods in terms of coverage ratio, connection time, packet delivery ratio, and delay.

A Lightweight, Efficient, and Physically Secure Key Agreement Authentication Protocol for Vehicular Networks

In the contemporary era, Vehicular Ad Hoc Networks (VANETs) have emerged as a vital technology in intelligent transportation systems, substantially enhancing the overall travel experience by providing advanced services to vehicles while ensuring driver safety. Despite the notable improvements, the inherent complexity of VANETs presents persistent security challenges, encompassing issues such as privacy preservation for vehicles, message authentication, and constraints in computational power and network bandwidth. Various authentication protocols have been designed for VANETs. However, many of these protocols exhibit significant vulnerabilities, rendering them insecure and unreliable in the face of diverse security threats, such as denial of service, replay, forgery, and impersonation attacks. Moreover, some existing schemes encounter limitations, including high computational complexity and the introduction of additional communication overhead and computational costs. To tackle these concerns, we designed a lightweight and secure identity authentication protocol based on elliptic curve cryptography with the objective of furnishing an effective and secure data transmission mechanism across a public communication channel for the Internet of Vehicles. In addition, we introduce Physically Unclonable Functions (PUFs) to ensure physical layer security during the communication process. A detailed security analysis demonstrates that the proposed protocol is resilient against various attacks. Through a comparative analysis with existing relevant protocols, in scenarios with a high density of vehicles, the algorithm demonstrates significantly lower computational costs and communication overhead than the related protocols, indicating that the proposed protocol is lightweight and efficient. Consequently, the empirical findings indicate that our protocol surpasses others in terms of reliability, user convenience, and practicality for ensuring secure data transmission within VANETs.

Review of Wind Flow Modelling in Urban Environments to Support the Development of Urban Air Mobility

Urban air mobility (UAM) is a transformative mode of air transportation system technology that is targeted to carry passengers and goods in and around urban areas using electric vertical take-off and landing (eVTOL) aircraft. UAM operations are intended to be conducted in low altitudes where microscale turbulent wind flow conditions are prevalent. This introduces flight testing, certification, and operational complexities. To tackle these issues, the UAM industry, aviation authorities, and research communities across the world have provided prescriptive ways, such as the implementation of dynamic weather corridors for safe operation, classification of atmospheric disturbance levels for certification, etc., within the proposed concepts of operation (ConOps), certification standards, and guidelines. However, a notable hindrance to the efficacy of these solutions lies in the scarcity of operational UAM and observational wind data in urban environments. One way to address this deficiency in data is via microscale wind modelling, which has been long established in the context of studying atmospheric dynamics, weather forecasting, turbine blade load estimation, etc. Thus, this paper aims to provide a critical literature review of a variety of wind flow estimation and forecasting techniques that can be and have been utilized by the UAM community. Furthermore, a compare-and-contrast study of the commonly used wind flow models employed within the wind engineering and atmospheric science domain is furnished along with an overview of the urban wind flow conditions.

Exploring the Application of Blockchain Technology in Logistics and Transportation System

This paper explores the application of blockchain technology in improving the management and efficiency of logistics and transportation systems. By leveraging blockchain technology, real-time recording, traceability, data sharing, security, and trustworthiness of logistics information can be achieved, thereby enhancing the efficiency and safety of logistics operations. The paper discusses the theoretical foundations of blockchain technology and logistics and transportation systems, highlighting key concepts such as decentralization, distributed ledger, consensus mechanisms, smart contracts, operations research, supply chain management, and transportation economics. Additionally, the literature review presents an overview of existing studies on logistics and transport systems and blockchain technology, illustrating various applications and benefits, such as sustainable transport frameworks, transportation and logistics management models, smart logistics systems, and supply chain traceability platforms. In conclusion, the exploration of blockchain technology's application in logistics and transportation systems offers comprehensive support for improving logistics efficiency, reliability, and safety, promising more efficient and reliable transportation services for the logistics industry in the future.

A novel deviation measurement for scheduled intelligent transportation system via comparative spatial-temporal path networks

Transit managers can use Intelligent Transportation System technologies to access large amounts of data to monitor network status. However, the presentation of the data lacks structural information. Existing single-network description technologies are ineffective in representing the temporal and spatial characteristics simultaneously. Therefore, there is a need for complementary methods to address these deficiencies. To address these limitations, this paper proposes an approach that combines Network Snapshots and Temporal Paths for the scheduled system. A dual information network is constructed to assess the degree of operational deviation considering the planning tasks. To validate the effectiveness, discussions are conducted through a modified cosine similarity calculation on theoretical analysis, delay level description, and the ability to identify abnormal dates. Compared to some state-of-the-art methods, the proposed method achieves an average Spearman delay correlation of 0.85 and a relative distance of 3.47. Furthermore, case analyses are invested in regions of China's Mainland, Europe, and the United States, investigating both the overall and sub-regional network fluctuations. To represent the impact of network fluctuations in sub-regions, a response loss value was developed. The times that are prone to fluctuations are also discussed through the classification of time series data. The research can offer a novel approach to system monitoring, providing a research direction that utilizes individual data combined to represent macroscopic states. Our code will be released at https://github.com/daozhong/STPN.git.

Relay-node Selection Method Based on Weighted Strategy for 3D Scenario in Internet of Vehicles

&lt;p&gt;In recent years, Internet of Vehicles (IoV), as a supporting technology for Intelligent Transportation System (ITS), is flourishing with the emergence and development of new technologies such as edge computing, 5G communication, and Artificial Intelligence (AI). However, the more complexity of wireless channels and vehicle distribution in 3D scenario brings a great challenge for relay-node selection in ITS. In this paper, we focus on how to alleviate the problem that the decline of two-hop distance and two-hop connection probability caused by the relative fading of inter-layer communication radius in 3D scenario with Vehicle-to-Vehicle (V2V) communication. To face this challenge, we develop a Relay-node Selection method based on Weighted Strategy for Overpass scenario (RSWSO). The simulation results show that RSWSO achieves improvement in two-hop distance, and an increase of up to 11.2% in terms of two-hop connection probability.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

Research on car-following control and energy management strategy of hybrid electric vehicles in connected scene

To address the comprehensive optimization problem of driving performance and fuel economy in the driving process of hybrid electric vehicles (HEV) in the car-following scene in the connected environment, an energy management strategy (EMS) based on front vehicle speed prediction and ego vehicle speed planning is designed by combining intelligent transportation system (ITS) technology. The front vehicle speed predictor is first established based on the long short-term memory neural network (LSTM). Then, based on the predicted speed of the front car, the predictive cruise control (PCC) strategy is designed for realizing the speed control in the car-following scene by combining it with the adaptive cruise control (ACC). Finally, based on the planned vehicle speed, deep reinforcement learning (DRL)-based EMS is used to optimize the power distribution among different power components of HEVs. The analysis of simulation results under the SUMO-Python joint simulation platform verifies the proposed strategy.

Multi-Intersection Ecological Cooperative Control of a Pure Electric Vehicle Platoon with Dual-Motor Dual-Axis Drive

The advent of intelligent transportation system technology has expedited the advancement of eco-driving controls. Research on energy-saving cooperative control of intelligent connected vehicles in intelligent transportation environments is still in need of ongoing refinement. This article proposes a dual-level ecological driving control strategy for a pure electric vehicle platoon with dual-motor dual-axis drive in an urban multi-intersection environment. The upper-level design incorporates optimal platoon speed decision-making based on the nonlinear model predictive control algorithm. The multi-objective optimization function considers three scenarios: energy-optimal, time-optimal, and energy-time-optimal. It also takes into account platoon following control and passing efficiency, ensuring smooth passage through multi-intersections without interruptions. Built on the upper level’s optimal speed design, an energy management strategy is proposed for achieving optimal torque distribution of pure electric vehicles with front and rear independent drives. Finally, the upper and lower levels are jointly simulated in real-time. The results indicate that, compared to the energy-optimal mode, the average passage time decreased by 14.6% and 5.97% in the time-optimal and energy-time-optimal modes, respectively. Under average torque distribution, the time-optimal and energy-time-optimal modes increased the energy consumption of the vehicle platoon by 21.05% and 5.44%, respectively, compared to the energy-optimal mode. Under the optimal torque allocation strategy, the time-optimal and energy-time-optimal modes increased energy consumption by 15.31% and 6.11%, respectively, compared to the energy-optimal mode. In contrast to the average torque allocation strategy, the optimal torque allocation strategy for the dual-motor vehicles reduced energy consumption by 10.18%, 14.44%, and 9.61% in the energy-optimal mode, time-optimal mode and energy-time-optimal mode, respectively.

A cooperative longitudinal lane-changing distributions advisory for a freeway weaving segment

The lane-changing (LC) concentration problem in freeway weaving segments poses crash risks and reduces freeway efficiency. To address this issue, this paper proposes a cooperative longitudinal LC distribution (CLLCD) advisory for freeway weaving segments utilizing cooperative intelligent transport system technology. The weaving segment is divided into sections, and the CLLCD strategy distributes lane changes for each section using a general rule that allows easy calculation of each section’s CLLCD from the maximum permitted number of lane changes for different movements. A corresponding percentage of drivers in each section are then permitted to change lanes from the start of that section. The CLLCD strategy is evaluated for 27 scenarios with varying traffic demands. A sensitivity analysis is conducted to determine optimal parameters, and the performance of the proposed strategy is compared to other methods. This study also explores the working mechanism of the proposed approach using headway data and speed profiles. The effects of the section configurations and penetration rates of connected vehicles (CVs) are discussed. Simulation results show that this easy-to-apply strategy improves speed and delay as effectively as the heuristic algorithms-based strategy. The number of sections does not influence the CLLCD strategy’s performance when the maximum freeway-to-ramp lane changes per section and other parameters per 100 m remain constant. The delay in the weaving area decreases as the CV penetration rate increases; however, only marginal further improvements are observed when the penetration rate increases beyond 60%. This study provides a practical and effective solution to enhance weaving segments’ efficiency.

Secrecy Analysis of ABCom-Based Intelligent Transportation Systems With Jamming

Employing ambient backscatter communication (AmBC) technology in Intelligent Transportation Systems (ITS) has emerged as an appealing solution to boost the awareness of crosswalks. However, the AmBC-based ITS is expected to face serious security threats due to the presence of malicious eavesdroppers. In this paper, we investigate the secure multi-antenna transmission in an AmBC-based ITS coexisting with a passive eavesdropper with jamming. Specifically, a cooperative jammer is placed in the system to deliberately disrupt the eavesdropper without affecting the legitimate receiver. In order to characterize the performance of the proposed scheme, new approximate closed-form expressions of secrecy outage probability (SOP) are derived by adopting the Gauss-Chebyshev quadrature. Additionally, the asymptotic behavior of SOP at the high signal-to-noise ratio (SNR) regime is also studied to provide more insights into the system design. We also derive the asymptotic SOP, when the number of transmit antennas tends to infinity. Monte Carlo simulations are provided to demonstrate the validity of our analytical results and to show that 1) the secrecy performance can be significantly improved by allocating part of the transmit power to perform cooperative jamming and 2) the optimal power allocation factor is related to the total transmit power.

Revolution of Emerging Information Technology in Transportation and Logistics Management System Context of Indian Smart City: Economical Aspects

"Good quality transportation system enhances the growth of economy and extends social development in the country. Transportation fills the gap of communication between the places. It helps to improve trading, businesses in different states of the country. Logistic management is another side of transportation of goods from the factory source to the delivery point. Logistics management is the vital to increase the growth of business as well as economic growth of the country. Technology plays the role to improve transportation and logistics management system. Technologies are renovated in regular basis and new technologies are appeared in this era. Emerging information technologies are included to mold the transportation system as smart and intelligent. The modern city is advancing in all the directions nowadays, modern cities are comprising as smart and advance city. Smart transportation is the essential aspect of smart city. Therefore, advancement of transportation in smart city is very significant. Logistic management is emergent aspect of business. Progress of business extend the economical potency of country. Therefore, modernization of logistic management system is very essential. Role of information technology in transportation and logistics management system is portrayed in this paper. Impact of economic factors in growth of transportation and logistics management system in context of Indian smart cities are emphasis in this paper."

End-to-End Joint Multi-Object Detection and Tracking for Intelligent Transportation Systems

Environment perception is one of the most critical technology of intelligent transportation systems (ITS). Motion interaction between multiple vehicles in ITS makes it important to perform multi-object tracking (MOT). However, most existing MOT algorithms follow the tracking-by-detection framework, which separates detection and tracking into two independent segments and limit the global efficiency. Recently, a few algorithms have combined feature extraction into one network; however, the tracking portion continues to rely on data association, and requires complex post-processing for life cycle management. Those methods do not combine detection and tracking efficiently. This paper presents a novel network to realize joint multi-object detection and tracking in an end-to-end manner for ITS, named as global correlation network (GCNet). Unlike most object detection methods, GCNet introduces a global correlation layer for regression of absolute size and coordinates of bounding boxes, instead of offsetting predictions. The pipeline of detection and tracking in GCNet is conceptually simple, and does not require complicated tracking strategies such as non-maximum suppression and data association. GCNet was evaluated on a multi-vehicle tracking dataset, UA-DETRAC, demonstrating promising performance compared to state-of-the-art detectors and trackers.

Microelectronics innovation and implementation in intelligent transportation systems

Under the background of urbanization and rapid development of transportation, the innovation of intelligent transportation system has become the key to improving traffic efficiency, relieving traffic pressure, and solving traffic problems. With the continuous progress of microelectronics technology, its application in the field of intelligent transportation is becoming more and more eye-catching. This paper focuses on the innovation and realization of micro-electronic technology in intelligent transportation system, and discusses the application of micro-electronic technology in intelligent navigation, intelligent parking, traffic flow optimization, etc. Through a literature review approach, this study demonstrates how microelectronics technology can drive the development of intelligent transportation systems to improve the efficiency and sustainability of urban transportation. The research results show that microelectronics technology not only brings revolutionary changes to the field of intelligent transportation, but also provides accurate positioning and navigation functions in intelligent navigation systems, realizes more efficient parking process management in intelligent parking systems, and plays a key role in traffic flow optimization. Microelectronic technology has wide application prospects and a positive social influence in the field of intelligent transportation.

Algorithm development for Vehicle-To-Vehicle (V2V) communication

This paper presents the development of an algorithm for Vehicle-to-Vehicle (V2V) communication, a crucial technology in Intelligent Transportation Systems (ITS) that holds significant potential for enhancing road safety and traffic efficiency. One of the most common types of vehicle collisions occurs at intersections, particularly those without traffic lights. This study focuses on creating a V2V algorithm designed to prevent collisions in such scenarios. The findings were presented through visual simulations that depict various scenarios involving vehicles approaching an intersection. The algorithm follows a two-step process: Firstly, it utilizes Dedicated Short-Range Communication Systems (DSRCS) to accurately estimate the distance between vehicles. Leveraging this distance information, the algorithm dynamically adjusts the speed of each vehicle. The algorithm’s performance is assessed using Convolutional Neural Networks (CNN), which enables a comprehensive evaluation of its reliability and efficiency in V2V communication. The algorithm demonstrates notable enhancements in the reliability and efficiency of V2V communication. This paper serves as a validation of the feasibility of developing more advanced V2V communication algorithm and potentially making significant contributions to the advancement of ITS.

The application of advanced computational algorithms used for cooperative communication transmission of vehicular networks: a proposed method

Telematics will be one of the critical technologies in the future intelligent transportation system and establish communication between vehicles and vehicles, vehicles and networks, and vehicles and people. Thus, vehicles can sense mobile environments and make rational driving decisions. Therefore, the safety and efficiency of traffic flow would be enhanced. However, due to the unknown nature and higher complexity of the connected network environments of vehicles, the utilization of conventional optimization theory fails to generate satisfying results. To address the problem, this article proposes a methodology for collaborative transmission for communication regarding the Internet of Vehicles (IoV) with the help of advanced computational algorithms. The article employs a multi-intelligence advanced computational algorithm to construct a collaborative communication transmission mechanism in the telematics communication system model. The proposed algorithm fully considers the vehicle mobility and quality-of-service (QoS) of telematics services within the network slice. It adjusts the slice’s radio resource allocation and parameter settings on an expanded time scale to improve the QoS of telematics services and increase the system’s long-term revenue. The simulation results show that the proposed algorithm has a more significant performance improvement than conventional algorithms using telematics information transmission. For example, when the same load conditions are under consideration, the total capacity of the vehicle-to-infrastructure (V2I) link optimized by the proposed algorithm is still higher than that of the other three baseline strategies.