The job of a package delivery driver (PDD) is complex and demanding. These drivers must possess many skills in order to succeed in their work, including physical stamina, appropriate decision-making, positive customer interaction, and most importantly, operational safety. Companies must use significant resources, not only to provide insurance for existing drivers, but also to train new drivers to use their visual attention effectively while driving, and companies have a vested interest in ensuring that the most capable trainees are selected for jobs. Currently, subjective assessments of supervisors or managers are typically used to make these determinations. While these are valuable methods for assessing drivers, an objective measure of how well the driver is using his/her visual attention would both assist evaluators in making judgments, as well as make those judgments more accurate. The purpose of the study described herein was to 1) conduct a task analysis of the driving component of the PDD job responsibilities, and 2) create and test an objective measure that a package delivery company could use to evaluate the performance of its drivers. A detailed task analysis based on numerous observations of drivers in their normal work routines was conducted for this research in order to understand these complex tasks. A framework was created for understanding this system of tasks, which was then used to organize all tasks that drivers were observed to perform into more general, goal-oriented activities. Using this task analysis, incidents were identified that were observed while drivers were behind the wheel. This information demonstrated that breakdowns were occurring within the tasks drivers were performing and that improved methods of training and evaluations may be needed as a result. A construct of visual behavior called Head Down Time (HTD) was then created and tested. An individual HDT is defined as the sum of time of all eye gazes away from the primary display (i.e. windshield) between two distinct eye gazes at the primary display while the vehicle is in motion. HDT was evaluated for its ability to differentiate levels of experience between drivers, its relationship to types of route on which drivers delivered, and its relationship to the driving-related incidents that were observed. HDTs were shown to be differed significantly between drivers of low and high experience, with experienced drivers displaying shorter durations of HDT when compared to inexperienced drivers. HDTs also differed in duration when analyzed by the type of route upon which drivers operated. Commercial and urban routes, while not significantly different with respect to HDT, were shown to have increased HDT durations when compared to rural routes and, in turn, residential routes were found to have significantly longer HDTs than did rural routes and may have significantly shorter durations compared to commercial and urban. Finally, HDTs that were associated with observed driving incidents in terms of chronological proximity were shown to be of significantly longer duration than were HDTs that were not associated with incidents. All tests were conducted using appropriate statistical measures, including t-tests at a level of α = 0.05 for each dataset. Applications of this research include: 1) improvement of PDD training and evaluation methods through use of a detailed task analysis, 2) improvement in how package delivery companies define incidents and train PDD toward the prevention of incidents based on task analysis and observations as to incident frequency, and 3) the further development of HDT as a possible objective measure to supplement the training and evaluation of PDD. / Master of Science

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Missed deliveries are a major issue for package carriers and a source of great hassle for the customers. Either the carrier attempts to redeliver the package, incurring the additional expense of visiting the same house up to three times, or they leave the package on the doorstep, vulnerable to package thieves. In this dissertation, a system of collection-and-delivery-points (CDPs) has been proposed to improve customer service and reduce carrier costs. A CDP is a place, either in an existing business or a new location, where the carrier drops any missed deliveries and the customers can pick the packages at their convenience. To examine the viability of a CDP system in North America, a variation on a location-routing problem (LRP) was created, a mixed-integer programming model called the CDP-LRP. Unlike standard LRPs, the CDP-LRP takes into account both the delivery truck route distance and the direct customer travel to the CDPs. Also, the facilities being placed are not located at the beginning and ending of the truck routes, but are stops along the routes. After testing, it became clear that, because of the size and complexity of the problem, the CDP-LRP is unable to be solved exactly in a reasonable amount of time. Heuristics developed for the standard LRP cannot be applied to the CDP-LRP because of the differences between the models. Therefore, three heuristics were created to approximate the solution to the CDP-LRP, each with two different embedded modified vehicle routing problem (VRP) algorithms, the Clark-Wright and the Sweep, modified to handle the additional restrictions caused by the CDPs. The first is an improvement heuristic, in which each closed CDP is tested as a replacement for each open CDP, and the move that creates the most savings is implemented. The second begins with every CDP open, and closes them one at a time, while the third does the reverse and begins will only one open CDP, then opens the others one by one. In each case, a penalty is applied if the customer travel distance is too long. Each heuristic was tested for each possible number of open CDPs, and the least expensive was chosen as the best solution. Each heuristic and VRP algorithm combination was tested using three delivery failure rates and different data sets: three small data sets pulled from VRP literature, and randomly generated clustered and uniformly distributed data sets with three different numbers of customers. OpenAll and OpenOne produced better solutions than Replacement in most instances, and the Sweep Algorithm outperformed the Clark-Wright in both solution quality and time in almost every test. To judge the quality of the heuristic solutions, the results were compared to the results of a simple locate-first, route-second sequential algorithm that represents the way the decision would commonly be made in industry today. The CDPs were located using a simple facility location model, then the delivery routes were created with the Sweep algorithm. These results were mixed: for the uniformly distributed data sets, if the customer travel penalty threshold and customer density are low enough, the heuristics outperform the sequential algorithm. For the clustered data sets, the sequential algorithm produces solutions as good as or slightly better than the sequential algorithm, because the location of the potential CDP inside the clusters means that the penalty has less impact, and the addition of more open CDPs has less effect on the delivery route distances. The heuristic solutions were also compared to a second value – the route costs incurred by the carrier in the current system of redeliveries, calculated by placing additional customers in the routes and running the Sweep algorithm – to judge the potential savings that could be realized by implementing a CDP system in North America. Though in some circumstances the current system is less expensive, depending on the geographic distribution of the customers and the delivery failure rate, in other circumstances the cost savings to the carrier could be as high as 27.1%. Though the decision of whether or not to set up a CDP system in an area would need to be made on a case-by-case basis, the results of this study suggest that such a system could be successful in North America. / Doctor of Philosophy / Missed deliveries are a major issue for package carriers and a source of great hassle for the customers. Either the carrier attempts to redeliver the package, incurring the additional expense of visiting the same house up to three times, or they leave the package on the doorstep, vulnerable to package thieves. In this dissertation, a system of collection-and-delivery-points (CDPs) has been proposed to improve customer service and reduce carrier costs. A CDP is a place, either in an existing business or a new location, where the carrier drops any missed deliveries and the customers can pick the packages at their convenience. To examine the viability of a CDP system in North America, a mathematical programming model was created called the CDP-LRP. Because of the size and complexity of the problem, it is unable to be solved exactly in a reasonable amount of time. Therefore, three heuristics were created to approximate the solution to the CDP-LRP, each with two different embedded modified vehicle routing problem (VRP) algorithms. For all the heuristics, a penalty is applied if the customer travel distance is too long. Each heuristic and VRP algorithm combination was tested using different data sets: three small data sets pulled from VRP literature, and randomly generated clustered and uniformly distributed data sets with three different numbers of customers. To judge the quality of the heuristic solutions, the results were compared to the results of a simple locate-first, route-second sequential algorithm that represents the way the decision would commonly be made in industry today. These results were mixed: for the uniformly distributed data sets, if the customer travel penalty threshold and customer density are low enough, the heuristics outperform the sequential algorithm. For the clustered data sets, the sequential algorithm produces solutions as good as or slightly better than the sequential algorithm, because the location of the potential CDP inside the clusters means that the penalty has less impact, and the addition of more open CDPs has less effect on the delivery route distances. The heuristic solutions were also compared to a second value – the route costs incurred by the carrier in the current system of redeliveries – to judge the potential savings that could be realized by implementing a CDP system in North America. Though in some circumstances the current system is less expensive, depending on the geographic distribution of the customers and the delivery failure rate, in other circumstances the cost savings to the carrier could be as high as 27.1%. Though the decision of whether or not to set up a CDP system in an area would need to be made on a case-by-case basis, the results of this study suggest that such a system could be successful in North America.

This bachelor thesis aims to investigate the viability of using two wheeled self-balancing robots for package deliveries. The movement of the two wheeled self-balancing robot resembles the human movement more than a traditional four wheeled vehicle. The goal of the report is to build a selfbalancing robot to investigate how far from the center axis a weight can be added, as well as what the response time of a Wireless Fidelity (WiFi) connection for steering the robot is and how it compares to a Bluetooth connection. Balance of the robot was achieved by using a Proportional-IntegralDerivative (PID) controller with inputs from a gyroscope and accelerometer. Stepper motors were used to maneuver the robot. When the robot was constructed tests were performed to evaluate how far from the center axis a weight could be added. A test was also performed to evaluate the WiFi connection response time with regard to the distance between the operator and the robot, as well as the maximum range and how it compares to Bluetooth. The results showed that a one kilogram weight could be added five centimeters from the center axis, that the response time was around 10-20 milliseconds for a distance up to 35 meters. A WiFi connection has a longer range compared to Bluetooth and also has a lower response time. / Denna rapport strävar efter att undersöka möjligheterna av att använda en själv-balanserande robot för paketleveranser. Rörelsen av en tvåhjulig själv-balanserande robot liknar den mänskliga rörelsen mer än ett traditionellt fyrhjuligt fordon. Målet med rapporten är att bygga en självbalanserande robot för att undersöka hur långt från dess centeraxel en vikt kan placeras, samt undersöka vilken responstid som uppnås med en Wireless Fidelity (WiFi)-länk och hur en WiFi-länk jämför med en Bluetooth-länk. Balans uppnåddes genom att använda en Proportional-IntegralDerivative (PID) regulator med input från ett gyroskop och en accelerometer. Stegmotorer användes för att manövrera roboten. När roboten hade konstruerats utfördes tester för att undersöka hur långt från centrumaxeln en vikt kunde placeras. Ett test utfördes för att undersöka responstiden för en WiFi-länk med avseende på avståndet mellan operatör och robot, samt att undersöka den maximala räckvidden och jämföra den mot Bluetooth. Resultaten visade att en vikt på ett kilogram kunde placeras fem centimeter från centeraxeln, att responstiden var ungefär 10-20 millisekunder för avstånd upp till 35 meter. En WiFi-länk har en längre räckvidd än Bluetooth och kortare responstid.

The field of this work was to create a web application easing shipper's and carrier's work with consignments. The purpouse of the application is evidence of packages combined with label printing. A prewiew of present-day web application development techniques is provided first. Recent package delivery systems are discussed then. The application specification is the next topic. Implementation process using C# ASP .NET and the results of this work is analyzed in the last chapters.

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