Search Results (5)

To solve the problems associated with the poor harvesting ability of existing sunflower harvester cutting tables, and high seed drop rates, we designed a sunflower cutting table that can greatly improve the operational performance of sunflower combine harvesters. In this paper, we introduce the structure and principle of the whole machine and select the key parameters of the cutting table with the goal of adapting to a variety of planting modes in Xinjiang, China. Since the harvesting of sunflower in the wrong row easily causes the sunflower stalks to break, ADAMS (Version: 2020) simulation experiments were carried out to investigate the effects of the forward speed of the machine, the height of the sunflower insertion disk, and the angle of inclination of the harvest divider on the offset angle of the sunflower. With the goal of reducing the offset angle of the stalks in the forward direction of the harvest divider and reducing the size of the cutting table, the harvest divider inclination angle was chosen to be 45°; by using Design-Expert V13.0.15 software, a three-factor, three-level field test was carried out to determine the optimal parameter combinations that resulted in the minimum seed loss rate and the maximum success rate of the disk picking. Moreover, a validation test was conducted. The results show that when the forward speed is set to 0.62 m/s, the lifting speed of the pick-up disk device is set to 0.42 m/s, and the height of the inserted disk is set to 1000 mm, the relative errors between the theoretical values of the disk-picking success rate of the cutting table and the seed loss rate and the field test values are 6.5% and 1.3%, respectively. The results of the present study can provide a reference for improving the performance of sunflower harvester cutting tables and for the mechanical harvesting of inserted disk sunflowers. Full article

This paper addresses the drop-and-pickup container drayage problem with empty container constraints. In this problem, a truck is allowed to drop off the container at the customer and then leave. After the container has been packed/unpacked, the truck returns to pick it up. The problem is further complicated by the fact that empty containers at the depot are often limited in number. This container drayage problem is of great practical importance but seldom investigated. In this paper, we first formulate the problem as a directed graph and then mathematically model it as a mixed-integer linear program (MILP) with the objective of minimizing total travel costs. To solve the MILP effectively, we devise a branch and price algorithm that incorporates several performance enhancement strategies, including three versions of the bi-directional label setting algorithm, preprocessing of time windows and a heuristic for high-quality upper bounds. The experimental results indicate that (1) the proposed algorithm significantly outperforms CPLEX in terms of efficiency and effectiveness, (2) an average cost saving of 9.95∼12.25% can be achieved from the drop-and-pickup mode and (3) the benefit of drop-and-pickup mode increases when the customer density and the fixed cost increase. Full article

The shared e-scooter is a popular and user-convenient mode of transportation, owing to the free-floating manner of its service. The free-floating service has the advantage of offering pick-up and drop-off anywhere, but has the disadvantage of being unavailable at the desired time and place because it is spread across the service area. To improve the level of service, relocation strategies for shared e-scooters are needed, and it is important to predict the demand for their use within a given area. Therefore, this study aimed to develop a demand prediction model for the use of shared e-scooters. The temporal scope was selected as October 2020, when the demand for e-scooter use was the highest in 2020, and the spatial scope was selected as Seocho and Gangnam, where shared e-scooter services were first introduced and most frequently used in Seoul, Korea. The spatial unit for the analysis was set as a 200 m square grid, and the hourly demand for each grid was aggregated based on e-scooter trip data. Prior to predicting the demand, the spatial area was clustered into five communities using the community structure method. The demand prediction model was developed based on long short-term memory (LSTM) and the prediction results according to the activation function were compared. As a result, the model employing the exponential linear unit (ELU) and the hyperbolic tangent (tanh) as the activation function produced good predictions regarding peak time demands and off-peak demands, respectively. This study presents a methodology for the efficient analysis of the wider spatial area of e-scooters. Full article

Dispersed settlement areas (e.g., Slovenia) result in lower development of fixed public transport lines and thereby car-dependent lifestyles. To avoid congestion inside the cities and on highways in these areas, shared mobility modes e.g., carpooling, is one of the effective solutions, increasing the occupancy of personal vehicles. However, passenger pick-up and drop-off locations still remain an important challenge for carpool users and transport officials. As a collection point for carpooling, we can consider “park and pool (P+P)” lots near highways’ interchanges. This study aims to examine the impacts of P+P lots near interchanges on carpooling behavior of users and on improving sustainable mobility on highways in such dispersed settlement areas. To do so, we employed a field survey, incorporated the P+P lots into the mode choice model, and examined different scenarios using the macroscopic transport model. It is found that factors such as travel cost, public transport service limitations, and improved parking facilities impact highway users’ mode choice. Sixty percent of respondents are willing to leave their car in P+P lots near interchanges. The results also show that P+P lots can increase the number of carpool users. It causes remarkable savings in terms of operating and external costs because of the reduction in total distance and time travelled by personal vehicles as well as parking demand reduction in cities. At the moment, especially in Central Europe, it is easier to invest in a “demand reduction” infrastructure than to increase the capacity of infrastructure. Therefore, P+P lots could be a “win-win” situation for both users and operators. Full article

Urban public green space (UPGS) plays an important role in sustainable development. In China, the planning, classification, and management of green spaces are based on the Standard for Classification of Urban Green Space (SCUGS). However, limitations to the UPGS exist due to the over-emphasis on quantitative standards and insufficient consideration of the actual access mode of residents. Though the taxi trajectory data are widely selected to study public service facilities, its adoption in UPGSs research remains limited. Based on the case of UPGSs in the three districts of Shenzhen, we used the taxi (including cruise taxis and Didi cars, which are like Uber) trajectory data to investigate the spatial layout and the allocation of management resource of the UPGSs from the spatial interaction perspective. By rasterizing and visualizing the percentage of pick-up and drop-off points in the UPGSs’ buffer, the service scope of UPGSs was defined, which reflected the spatial distribution and activity intensity of the visitors. Then, an unsupervised classification method was introduced to reclassify the twenty two municipal parks in the three districts. Compared to the traditional planning method, the results show that the service scope of the same type of UPGS in the traditional classification is not the same as the one obtained by the study. Visitors to all UPGSs are distributed as a quadratic function and decay as the distance increases. In addition, the attenuation rates of the same type of UPGSs are similar. The findings of this study are expected to assist planners in improving the spatial layout of UPGSs and optimizing the allocation of UPGS management resources based on new classifications. Full article