Informatisation of transport process using GPS navigation system

Nowadays, internal business processes are one of the crucial factors of firms’ competitive advantage achievement, which is becoming increasingly important, not only on local but also on global markets. Firms’ performance improvement depends to a large extent on its flexibility, adjustability and especially ability to manage internal business processes. Hence, use of information technology is among the fundamental elements of business process change, which not only improve competitiveness but also assure long term development and growth of the firm. For all these reasons, the main purpose of this article is firstly to establish that use of information technology is feasible in all industries, explain what possible obstacles for successful informatisation are, and which are major advantages after its implementation. Secondly, within theoretical aspect we present broaden view of informatisation in logistics, whilst practical example illustrates successful informatisation of transport process with adoption of GPS (Global Positioning System) in a transport firm. Furthermore, in this article we are also introducing a case study of three transport firms describing process flow before and after implementation identifying enhanced information quality, service quality and communication as a foremost advantages and achievements after informatisatio

Using Operations Data for Planning the the Delaware Valley: First Steps

Real-time traffic operations data has been gathered for several years on an increasing number of roads throughout the Delaware Valley. The archives of this data are a tremendous potential resource for transportation planning. Use of the data, however, has posed significant technical challenges. This report summarizes how the data can be used, the state of operations data for planning in the Delaware Valley, and the results of two case studies. The first case study used data from the Pennsylvania Department of Transportation's Dynac system about speed and travel time on a section of I-76. The second case study used data provided by the I-95 Corridor Coalition Vehicle Probe Project (VPP) from INRIX, a private-sector traffic data company. The second case study analyzed duration of congestion on weekdays in 2009 for freeways in the Delaware Valley. This analysis was used in the region's 2011 Congestion Management Process

Implementation and Development of Vehicle Tracking and Immobilization Technologies

Since the mid-1980s, limited use has been made of vehicle tracking using satellite communications to mitigate the security and safety risks created by the highway transportation of certain types of hazardous materials. However, vehicle-tracking technology applied to safety and security is increasingly being researched and piloted, and it has been the subject of several government reports and legislative mandates. At the same time, the motor carrier industry has been investing in and implementing vehicle tracking, for a number of reasons, particularly the increase in efficiency achieved through better management of both personnel (drivers) and assets (trucks or, as they are known, tractors; cargo loads; and trailers). While vehicle tracking and immobilization technologies can play a significant role in preventing truck-borne hazardous materials from being used as weapons against key targets, they are not a & ”silver bullet.” However, the experience of DTTS and the FMCSA and TSA pilot projects indicates that when these technologies are combined with other security measures, and when the information they provide is used in conjunction with information supplied outside of the tracking system, they can provide defensive value to any effort to protect assets from attacks using hazmat as a weapon. This report is a sister publication to MTI Report 09-03, Potential Terrorist Uses of Highway-Borne Hazardous Materials. That publication was created in response to the Department of Homeland Security´s request that the Mineta Transportation Institute´s National Transportation Security Center of Excellence provide research and insights regarding the security risks created by the highway transportation of hazardous materials

Sharing Mobility Data for Planning and Policy Research

A California Public Utilities Commission (CPUC) rulemaking and possible legislative action in 2020 could affect data sharing requirements, with implications for shared mobility providers. The purpose of this brief is to inform this regulatory and legislative decision-making. We solicited policy and planning questions and data needs for shared mobility from within the University of California Institute of Transportation Studies research network. We defined shared mobility as including shared mobility devices, such as e-bikes and e-scooters, and transportation network companies (TNCs). We evaluated whether data shared in accordance with each of six mobility data specifications could be used to support analyses that would answer these questions. We then defined three approaches to data sharing and analysis to address these and other questions, presenting the advantages and disadvantages of each. This brief does not address the full breadth of the questions raised in the CPUC rulemaking nor does it introduce the complexities of this topic. Beyond the scope of this brief are issues of user privacy, the legal authority for sharing data, and contractual or requirements for each possible model of data sharing and analysis

Real-time automated road, lane and car detection for autonomous driving

In this paper, we discuss a vision based system for autonomous guidance of vehicles. An autonomous intelligent vehicle has to perform a number of functionalities. Segmentation of the road, determining the boundaries to drive in and recognizing the vehicles and obstacles around are the main tasks for vision guided vehicle navigation. In this article we propose a set of algorithms which lead to the solution of road and vehicle segmentation using data from a color camera. The algorithms described here combine gray value difference and texture analysis techniques to segment the road from the image, several geometric transformations and contour processing algorithms are used to segment lanes, and moving cars are extracted with the help of background modeling and estimation. The techniques developed have been tested in real road images and the results are presented

Space Transportatioin System (STS) propellant scavenging system study. Volume 3: Cost and work breakdown structure-dictionary

Fundamentally, the volumes of the oxidizer and fuel propellant scavenged from the orbiter and external tank determine the size and weight of the scavenging system. The optimization of system dimensions and weights is stimulated by the requirement to minimize the use of partial length of the orbiter payload bay. Thus, the cost estimates begin with weights established for the optimum design. Both the design, development, test, and evaluation and theoretical first unit hardware production costs are estimated from parametric cost weight scaling relations for four subsystems. For cryogenic propellants, the widely differing characteristics of the oxidizer and the fuel lead to two separate tank subsystems, in addition to the electrical and instrumentation subsystems. Hardwares costs also involve quantity, as an independent variable, since the number of production scavenging systems is not firm. For storable propellants, since the tankage volume of the oxidizer and fuel are equal, the hardware production costs for developing these systems are lower than for cryogenic propellants

Offline reconstruction of missing vehicle trajectory data from 3D LIDAR

LIDAR has become an important part of many autonomous vehicles with its advantages on distance measurement and obstacle detection. LIDAR produces point clouds which have important information about surrounding environment. In this paper, we collected trajectory data on a two lane urban road using a Velodyne VLP-16 Lidar. Due to dynamic nature of data collection and limited range of the sensor, some of these trajectories have missing points or gaps. In this paper, we propose a novel method for recovery of missing vehicle trajectory data points using microscopic traffic flow models. While short gaps (less than 5 seconds) can be recovered with simple linear regression, and longer gaps are recovered with the proposed method that makes use of car following models calibrated by assigning weights to known points based on proximity to the gaps. Newell's, Pipes, IDM and Gipps' car following models are calibrated and tested with the ground truth trajectory data from LIDAR and NGSIM I-80 dataset. Gipps' calibrated model yielded the best result