Search results

This study aims to propose and evaluate the progress in the basic-pixel (a strategy to generate continuous trajectories that fill out the entire surface) algorithm towards performance gain. The objective is also to investigate the operational efficiency and effectiveness of an enhanced version compared with conventional strategies.

For the first objective, the proposed methodology is to apply the improvements proposed in the basic-pixel strategy, test it on three demonstrative parts and statistically evaluate the performance using the distance trajectory criterion. For the second objective, the enhanced-pixel strategy is compared with conventional strategies in terms of trajectory distance, build time and the number of arcs starts and stops (operational efficiency) and targeting the nominal geometry of a part (operational effectiveness).

The results showed that the improvements proposed to the basic-pixel strategy could generate continuous trajectories with shorter distances and comparable building times (operational efficiency). Regarding operational effectiveness, the parts built by the enhanced-pixel strategy presented lower dimensional deviation than the other strategies studied. Therefore, the enhanced-pixel strategy appears to be a good candidate for building more complex printable parts and delivering operational efficiency and effectiveness.

This paper presents an evolution of the basic-pixel strategy (a space-filling strategy) with the introduction of new elements in the algorithm and proves the improvement of the strategy’s performance with this. An interesting comparison is also presented in terms of operational efficiency and effectiveness between the enhanced-pixel strategy and conventional strategies.

The purpose of this paper is to develop a real-time trajectory planner with optimal maneuver for autonomous vehicles to deal with dynamic obstacles during parallel parking.

To deal with dynamic obstacles for autonomous vehicles during parking, a long- and short-term mixed trajectory planning algorithm is proposed in this paper. In long term, considering obstacle behavior, A-star algorithm was improved by RS curve and potential function via spatio-temporal map to obtain a safe and efficient initial trajectory. In short term, this paper proposes a nonlinear model predictive control trajectory optimizer to smooth and adjust the trajectory online based on the vehicle kinematic model. Moreover, the proposed method is simulated and verified in four common dynamic parking scenarios by ACADO Toolkit and QPOASE solver.

Compared with the spline optimization method, the results show that the proposed method can generate efficient obstacle avoidance strategies, safe parking trajectories and control parameters such as the front wheel angle and velocity in high-efficient central processing units.

It is aimed at improving the robustness of automatic parking system and providing a reference for decision-making in a dynamic environment.

The purpose of this paper is to develop a proof-of-concept (POC) Forward Collision Warning (FWC) system for the motorcyclist, which determines a potential clash based on time-to-collision and trajectory of both the detected and ego vehicle (motorcycle).

This comes in three approaches. First, time-to-collision value is to be calculated based on low-cost camera video input. Second, the trajectory of the detected vehicle is predicted based on video data in the 2 D pixel coordinate. Third, the trajectory of the ego vehicle is predicted via the lean direction of the motorcycle from a low-cost inertial measurement unit sensor.

This encompasses a comprehensive Advanced FWC system which is an amalgamation of the three approaches mentioned above. First, to predict time-to-collision, nested Kalman filter and vehicle detection is used to convert image pixel matrix to relative distance, velocity and time-to-collision data. Next, for trajectory prediction of detected vehicles, a few algorithms were compared, and it was found that long short-term memory performs the best on the data set. The last finding is that to determine the leaning direction of the ego vehicle, it is better to use lean angle measurement compared to riding pattern classification.

The value of this paper is that it provides a POC FWC system that considers time-to-collision and trajectory of both detected and ego vehicle (motorcycle).

This paper aims to review the studies on intersection control with connected and automated vehicles (CAVs).

The most seminal and recent research in this area is reviewed. This study specifically focuses on two categories: CAV trajectory planning and joint intersection and CAV control.

It is found that there is a lack of widely recognized benchmarks in this area, which hinders the validation and demonstration of new studies.

In this review, the authors focus on the methodological approaches taken to empower intersection control with CAVs. The authors hope the present review could shed light on the state-of-the-art methods, research gaps and future research directions.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

The purpose of this paper is to analyze if the sport trajectory could be an impact factor in leadership development.

A qualitative research method has been adopted by conducting 17 in-depth, semi-structured interviews. The data were analyzed with the program Open Code (4.03).

The findings of this study revealed that the interviewed managers perceived that their sport trajectory has had an important influence in the development of their leadership. This influence is determined by four factors: (1) sport profile, (2) sport referents, (3) competences, values and abilities and (4) experiences from different sport roles played during their lifespan.

The research is based on interviews with a small sample of managers. In order to develop the research further, a more extensive sample is required.

The paper is unique as it examines the impact of the sport trajectory as an impact factor in leadership development.

How learning is facilitated in inter-organizational projects remains underdeveloped in the literature. The aim of this study is to focus on viewing the relationship between the multiple organizations in a project, from a perspective of the learning aspect.

This research analyses the learning trajectory that occurred in the largest tunnel project in the Netherlands. Data were collected through archival documents, in-depth interviews, and site visits. Answering the research question will be done through inductive research.

The results indicate that the most significant change that exploitative learning has led to is the change in mind-set. The learning paradox of projects does not play a factor in the learning trajectory present at the GSP project.

While the research was conducted in a Dutch context, it is suggested that the findings presented would align with the experiences of construction organizations in other parts of the world.

The findings have implications for understanding learning in practical project management. The organizations need to focus on learning initiatives on people, and not on the collection of data.

This research responds to the debate over the learning in projects. Learning stimulates openness and that this has positive impact om collaboration.

This paper aims to propose a train timetable rescheduling (TTR) approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.

Firstly, a single-train trajectory optimization (STTO) model is constructed based on train dynamics and operating conditions. The train kinematics parameters, including acceleration, speed and time at each position, are calculated to predict the arrival times in the train timetable. A STTO algorithm is developed to optimize a single-train time-efficient driving strategy. Then, a TTR approach based on multi-train tracking optimization (TTR-MTTO) is proposed with mutual information. The constraints of temporary speed restriction (TSR) and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train. The multi-train trajectories at each position are optimized to generate a time-efficient train timetable.

The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF. The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay (TTD). As for the TSR scenario, the proposed TTR-MTTO can reduce TTD by 60.60% compared with the traditional TTR approach with dispatchers’ experience. Moreover, TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.

With the cooperative relationship and mutual information between train rescheduling and control, the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.

The purpose of this paper aims to model interaction relationship of traffic agents for motion prediction, which is critical for autonomous driving. It is obvious that traffic agents’ trajectories are influenced by physical lane rules and agents’ social interactions.

In this paper, the authors propose the social relation and physical lane aggregator for multimodal motion prediction, where the social relations of agents are mainly captured with graph convolutional networks and self-attention mechanism and then fused with the physical lane via the self-attention mechanism.

The proposed methods are evaluated on the Waymo Open Motion Dataset, and the results show the effectiveness of the proposed two feature aggregation modules for trajectory prediction.

This paper proposes a new design method to extract traffic interactions, and the attention mechanism is used in each part of the model to extract and fuse different relational features, which is different from other methods and improves the accuracy of the LSTM-based trajectory prediction method.

The underrepresentation of women in engineering has important consequences for meeting the need for a larger, talented scientific and technological labor force. Increasing the proportion of women faculty in engineering will help increase the persistence probabilities of women undergraduate and graduate students in engineering, as well as contribute to the range and diversity of ideas toward innovations and solutions to the greatest engineering challenges. This study aims to examine the association among gender, family formation and post-PhD employment patterns of a cohort of engineering doctorates.

Using the National Science Foundation’s Survey of Doctorate Recipients data, 2001–2010, descriptive and multinomial logit regression analyses are conducted to illustrate the career trajectories of engineering PhDs over a ten-year period.

The career trajectories of engineering PhDs are nonlinear, and transitions between employment sectors commonly occur over the ten-year time period studied. Although women engineering PhDs with young dependents are less likely to be employed initially after PhD completion, they tend to enter the workforce in the academic sector as time progresses. Early post-PhD employment as a postdoctoral researcher or in the academic sector contributes to the pursuit of the professoriate downstream.

While previous studies tend to focus on the early career outcomes of science and engineering students, this study contributes to the literature by focusing on the long-term career outcomes of engineering doctorates. Research findings provide engineering PhD students and PhDs with more information regarding potential post-PhD career trajectories, highlighting the multitude of career options and transitions that occur over time. Research findings also provide higher education administrators and doctoral program stakeholders with foundational information toward designing and revitalizing professional development programs to help PhD students prepare for the workforce. The findings have the potential to be applied toward helping increase diversity by shaping policies and programs to encourage multiple alternative career pathways to the professoriate.