Recognition of Operating Characteristics of Heavy Trucks Based on the Identification of GPS Trajectory Stay Points

As an emerging data source, feature identification based on GPS trajectory data has become a hot issue in the field of data mining and freight management. A method of trajectory data extraction, classification, and visualization based on stay points was proposed in this paper to analyze the operation characteristics of heavy trucks from the perspectives of intracity transportation, intraprovincial transportation, and interprovincial transportation. The GPS trajectory data of heavy trucks in Sichuan Province in March 2019 were taken as an example to analyze the operation characteristics. The results show that the heavy trucks in Sichuan Province are mainly transported within the province, and the freight efficiency is slightly better than the average level of the national freight trucks in the same period, failing to give full play to the advantages of long transport distance. The manufacturing industry is the main service object of heavy trucks, and the vehicles engaged in transportation within the province are more dependent on logistics enterprises and their ancillary facilities. The north-south longitudinal line and east-west horizontal line are the main interprovincial transport channels, and the provincial and municipal transport is mainly concentrated in some urban trunk lines, ring lines, and express routes. The proposed technical method can describe the operating characteristics of freight trucks from the perspective of microscopic and service market, not only to guide the layout of highway freight yards, logistics parks, and logistics hubs and the determination of service functions but also to provide a reference basis for freight management-related departments and drivers to formulate transportation plans and establish freight information platforms to improve freight efficiency and safety.

Influence of Logistics Optimization on Performance of Freight Forwarding Companies in Kenya

Purpose: The purpose of the study is to investigate the influence of logistics optimization on performance of freight forwarding companies in Kenya. Methodology: Descriptive research design was adopted. The study preferred this method because it allows an in-depth study of the subject. Data was collected from deputy heads and heads of procurement in 45 freight forwarding companies in Kenya, who are registered members of KIFWA according to its 2019 directory. Questionnaires were used to collect data. The questionnaires were tested for validity and reliability using 10% of the total sample respondents. Data was analyzed through descriptive statistical methods such as means, standard deviation, frequencies and percentage. Inferential analyses were used in relation to correlation analysis and regression analysis to test the relationship between the four explanatory variables and the explained variable. Multiple regression models were used to show the relationship between the predicted variable and the predictor variables. Results and conclusion: The independent variables reported R value of 0.846 indicating that there is perfect relationship between dependent variable and independent variables. R square value of 0.716 which means that 71.6% of the corresponding variation in performance of the freight forwarding companies can be explained or predicted by (logistics information system, freight management, distributor base rationalization and transport planning) which indicated that the model fitted the study data. The findings of the study indicated that logistics information system, freight management, distributor base rationalization and transport planning have a positive relationship with performance of freight forwarding companies in Kenya. Unique contribution to theory, policy and practice: the study recommended that freight forwarding companies should embrace logistics optimization so as to improve performance and further researches should to be carried out in other institutions to find out if the same results can be obtained.

An Application for Load Sharing in Trucks

The paradigm of the world has shifted to mobile applications. The services that you need are at your fingertips because of the mobile applications which provide online access to the services you have. Several mobile applications like uber freight, ola are present to facilitate the freight service providers. The existing freight management system depends on the model of separating the users on the basis of fleet provider, normal user and one with the large number of vehicles called as freight provider. For a user to login to the system the user can easily enter his desired destination and send his or her belongings to that destination with the online reservation platform provided by the mobile application. Though the existing system is good but it has one limitation. The limitation of all the existing system is that they don’t monitor the load in the vehicle. In order to overcome this limitation, we propose a system which will monitor the load present in the vehicle in real time. We propose a cross platform mobile application which will work on all the available platform. The main aim of the proposed system is to monitor the load present in the truck. The proposed system will use the ultrasonic sensor in the load bearing part of the truck and the total volume as well as the available space in the truck will be continuously monitored and notified to the user who wants to send the load. We will also take into consideration the density of the material so that if the user wants to add a new load the existing load won’t be affected. The path of the truck will also be monitored from origin to destination. The proposed method will develop an application for continuous monitoring of the load in the truck. The main application of the system is use in freight management system for monitoring the load of the vehicle and notifying the users whether the space is available for the vehicle to carry their loads.