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The purpose of this study is to explore the influence of the electronic throttle (ET) dynamics and the average speed of multiple preceding vehicles on the stability of traffic flow.

An extended car-following model integrating the ET dynamics and the average speed of multiple preceding vehicles is presented in this paper. The novel model’s stability conditions are obtained by using the thought of control theory, and the modified Korteweg–de Vries equation is inferred in terms of the nonlinear analysis method. In addition, some simulation experiments are implemented to explore the properties of traffic flow, and the results of these experiments confirm the correctness of theoretical analysis.

In view of the results of theoretical analysis and numerical simulation, traffic flow will become more stable when the average speed and ET dynamics of multiple preceding vehicles are considered, and the stability of traffic flow will also be enhanced by increasing the number of preceding vehicles considered.

This study leaves the factors such as the mixed traffic flow, the multilane and so on out of account in real road environment, which more or less influences the traffic flow’s stability, so the real traffic environment is not fully reflected.

There is little research integrating ET dynamics and the average velocity of multiple preceding vehicles to study the properties of traffic flow. The enhanced model constructed in this study can better reflect the real traffic, which can also give some theoretical reference for the development of connected and autonomous vehicles.

In an intelligent transportation system (for short, ITS) environment, a vehicle’s motion is affected by the information in a large scale. The purpose of this paper is to study the integration effect of multiple vehicles’ delayed velocities on traffic flow.

This paper constructed a new car-following model to study the integration effect of multiple vehicles’ delayed velocities on traffic flow. The new model is analyzed by linear and nonlinear perturbation method theoretically and also verified by simulation.

It is found out that the integration of preceding vehicles’ delayed velocities affect the stability of traffic flow importantly, and three preceding vehicles’ delayed velocities information should be considered in real traffic.

The new car-following model by considering the integration effect of multiple vehicles’ delayed velocities is firstly proposed in this paper. The research result shows that three preceding vehicles’ delayed velocities information is the best choice to stabilizing traffic flow.

In the era of connected and autonomous vehicles, a large amount of surrounding vehicular information can be acquired by the focal vehicle in real time using vehicle-to-vehicle communication technology, such as the core variable of electronic throttle opening angle. Meanwhile, the traffic jerk, such as the non-compliance of drivers and pedestrians, worsens the chaos of the surrounding traffic environment. To reflect the future traffic environment, the authors simultaneously incorporate the electronic throttle (ET) and traffic jerk into the traditional continuum model. The authors derive the stability criterion of the enhanced continuum model via the perturbation method.

To facilitate insight into the propagation and evolution mechanism of traffic jam near the stability condition, the authors use the nonlinear stability analysis method to derive the KdV-Burgers equation of proposed continuum model.

The new item of ET opening angle and traffic jerk have a positive impact on suppressing traffic congestion and improving road robustness.

The research on autonomous continuum models is rare. This model can better reflect the actual traffic, which can also provide a theoretical reference for the future traffic governance.

The value chain of the Norwegian meat production industry has recently been through major structural changes resulting in increased flows and transportation needs at all levels. The purpose of this paper is to present results of the initial stage of a five‐year research project between the Norwegian Meat Research Centre, Norwegian meat companies and Molde University College. The main goal of the project is to develop a decision support system for the transport of live animals to a slaughterhouse to reduce transportation costs while maintaining high level of livestock welfare and meat quality, as these are three main factors for the profitability of both farmers and industry.

The paper presents a mixed integer programming model that combines vehicle routing and inventory control. We introduce the possibility for multiple routes for a given vehicle on a given day in a multiple‐period planning perspective. Arrival times of the loaded vehicles to the slaughterhouse are controlled by production (slaughter) rate and inventory level at the abattoirs so that the supply of animals for slaughter is steady and production breaks are avoided. Livestock welfare is secured by the route duration constraints.

The model has been formulated and tested on small data sets. The major future challenge is to solve real‐life problems from the involved companies.

The main limitation is the present inability to solve large cases.

The model combining transportation and inventory control in a setting of animal welfare constraints is original.

The purpose of this paper is to propose a new algorithm for in‐mission trajectories and speed adjustment of multiple unmanned aerial vehicles (UAVs) participating in a mission that requires them to arrive at target location simultaneously with switching and imperfect communication among the vehicles.

This algorithm, programmed at each UAV level, is based on the repeated consensus seeking among the participating vehicles about the time‐on‐target (ToT) through an imperfect inter‐vehicle communication link. The vehicles exchange their individual ToT values repeatedly for a particular duration to pick the highest value among all the vehicles in communication. A consensus confidence flag is set high when consensus is successful. After every consensus cycle with high confidence value, the mission adjustment is carried out by computing difference value between ToT consensus and a threshold value. For the difference values higher than a certain limit, vehicle's trajectory is adjusted by in‐mission insertion of new waypoint (WP) and for lower values the vehicle's speed is varied under allowable limits. The consensus seeking followed by the mission adjustment is repeated periodically to quash the imperfect communication effects.

A mathematical analysis has been carried out to establish the conditions for convergence of the algorithm. The simultaneous arrival of the vehicles subjected to switching communication is achieved only when the union of the switching links during the consensus period enables a vehicle to receive information from all the other vehicles and the switching rate is sufficiently high. This algorithm has been tested in a 6‐degree‐of‐freedom (DoF) multiple UAV simulation environment and achieves simultaneous arrival of multiple fixed wing UAVs under imperfect communication links that meets the aforementioned conditions.

The presented algorithm and design strategy can be extended for other types of cooperative control missions where certain variable of interest is shared among all the vehicles over imperfect communication environment. The design is modular in functionality and can be incorporated into existing vehicles or simulations.

This research presents a new consensus algorithm that repeatedly performs polling of ToT among the vehicles through intermittent communication. The continual nature of consensus seeking covers the weakness of the imperfect communication. A two‐level mission adjustment provides better accuracy in simultaneous arrival at the target location.

Describes a study to measure the quality of service provided by food‐poisoning surveillance agencies in England and Wales in terms of the requirements of a representative consumer ‐ the egg producing industry ‐ adopting “egg associated” outbreak investigation reports as the reference output. Defines and makes use of four primary performance indicators: accessibility of information; completeness of evidence supplied in food‐poisoning outbreak investigation reports as to the sources of infection in “egg‐associated” outbreaks; timeliness of information published; and utility of information and advice aimed at preventing or controlling food poisoning. Finds that quality expectations in each parameter measured are not met. Examines reasons why surveillance agencies have not delivered the quality demanded. Makes use of detailed case studies to illustrate inadequacies of current practice. Attributes failure to deliver “accessibility” to a lack of recognition on the status or nature of “consumers”, combined with a self‐maintenance motivation of the part of the surveillance agencies. Finds that failures to deliver “completeness” and “utility” may result from the same defects which give rise to the lack of “accessibility” in that, failing to recognize the consumers of a public service for what they are, the agencies feel no need to provide them with the data they require. The research indicates that self‐maintenance by scientific epidemiologists may introduce biases which when combined with a politically inspired need to transfer responsibility for food‐poisoning outbreaks, skew the conduct of investigations and their conclusions. Contends that this is compounded by serious and multiple inadequacies in the conduct of investigations, arising at least in part from the lack of training and relative inexperience of investigators, the whole conditioned by interdisciplinary rivalry between the professional groups staffing the different agencies. Finds that in addition failures to exploit or develop epidemiological technologies has affected the ability of investigators to resolve the uncertainties identified. Makes recommendations directed at improving the performance of the surveillance agencies which, if adopted will substantially enhance food poisoning control efforts.

The purpose of this study is to extensively explore the vehicular network paradigm, challenges faced by them and provide a reasonable solution for securing these vulnerable networks. Vehicle-to-everything (V2X) communication has brought the long-anticipated goal of safe, convenient and sustainable transportation closer to reality. The connected vehicle (CV) paradigm is critical to the intelligent transportation systems vision. It imagines a society free of a troublesome transportation system burdened by gridlock, fatal accidents and a polluted environment. The authors cannot overstate the importance of CVs in solving long-standing mobility issues and making travel safer and more convenient. It is high time to explore vehicular networks in detail to suggest solutions to the challenges encountered by these highly dynamic networks.

This paper compiles research on various V2X topics, from a comprehensive overview of V2X networks to their unique characteristics and challenges. In doing so, the authors identify multiple issues encountered by V2X communication networks due to their open communication nature and high mobility, especially from a security perspective. Thus, this paper proposes a trust-based model to secure vehicular networks. The proposed approach uses the communicating nodes’ behavior to establish trustworthy relationships. The proposed model only allows trusted nodes to communicate among themselves while isolating malicious nodes to achieve secure communication.

Despite the benefits offered by V2X networks, they have associated challenges. As the number of CVs on the roads increase, so does the attack surface. Connected cars provide numerous safety-critical applications that, if compromised, can result in fatal consequences. While cryptographic mechanisms effectively prevent external attacks, various studies propose trust-based models to complement cryptographic solutions for dealing with internal attacks. While numerous trust-based models have been proposed, there is room for improvement in malicious node detection and complexity. Optimizing the number of nodes considered in trust calculation can reduce the complexity of state-of-the-art solutions. The theoretical analysis of the proposed model exhibits an improvement in trust calculation, better malicious node detection and fewer computations.

The proposed model is the first to add another dimension to trust calculation by incorporating opinions about recommender nodes. The added dimension improves the trust calculation resulting in better performance in thwarting attacks and enhancing security while also reducing the trust calculation complexity.

This study aims to evaluate the influence of connected and autonomous vehicle (CAV) merging algorithms on the driver behavior of human-driven vehicles on the mainline.

Previous studies designed their merging algorithms mostly based on either the simulation or the restricted field testing, which lacks consideration of realistic driving behaviors in the merging scenario. This study developed a multi-driver simulator system to embed realistic driving behavior in the validation of merging algorithms.

Four types of CAV merging algorithms were evaluated regarding their influences on driving safety and driving comfort of the mainline vehicle platoon. The results revealed significant variation of the algorithm influences. Specifically, the results show that the reference-trajectory-based merging algorithm may outperform the social-psychology-based merging algorithm which only considers the ramp vehicles.

To the best of the authors’ knowledge, this is the first time to evaluate a CAV control algorithm considering realistic driver interactions rather than by the simulation. To achieve the research purpose, a novel multi-driver driving simulator was developed, which enables multi-drivers to simultaneously interact with each other during a virtual driving test. The results are expected to have practical implications for further improvement of the CAV merging algorithm.

Each of the four objectives can be applied within the military training environment. Military training often requires that soldiers achieve specific levels of performance or proficiency in each phase of training. For example, training courses impose entrance and graduation criteria, and awards are given for excellence in military performance. Frequently, training devices, training media, and training evaluators or observers also directly support the need to diagnose performance strengths and weaknesses. Training measures may be used as indices of performance, and to indicate the need for additional or remedial training.