Mitigating Initialization Bias in Transportation Modeling Applications

Traffic simulation model is a useful tool to evaluate real world transportation solutions in a risk free environment. Traffic simulation model requires some form of initialization before their outputs can be considered meaningful. Models are typically initialized in a particular, often “empty” state and therefore must be “warmed-up” for an unknown amount of simulation time before reaching a “quasi-steady-state” representative of the systems’ performance. The portion of the output series influenced by the arbitrary initialization is referred to as the initial transient and is a widely recognized problem in other areas, but less emphasized in the transportation application. After reviewing methods of accounting for the initial transient bias, this paper selects and evaluates three techniques; two popular methods from the general simulation field, Welch’s and MSER method, and one from the current state of the practice in the transportation application, Volume Balancing. VISSIM models were created to compare the selected methods. After presenting the results of each method, advantages and criticisms of each are discussed as well as issues that arose during the implementation. It is hoped that this paper informs the current practice in transportation application as to how to account for the initial transient in order to continue facilitating meaningful and reliable results

Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair

Railway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target bridge life, bridge maintenance activities such as local inspection and repair should be undertaken properly. However, this is a challenging task because there are various sources of uncertainty associated with aging bridges, train loads, environmental conditions, and maintenance work. Therefore, to perform optimal risk-based maintenance of railway bridges, it is essential to estimate the probabilistic fatigue life of a railway bridge and update the life information based on the results of local inspections and repair. Recently, a system reliability approach was proposed to evaluate the fatigue failure risk of structural systems and update the prior risk information in various inspection scenarios. However, this approach can handle only a constant-amplitude load and has limitations in considering a cyclic load with varying amplitude levels, which is the major loading pattern generated by train traffic. In addition, it is not feasible to update the prior risk information after bridges are repaired. In this research, the system reliability approach is further developed so that it can handle a varying-amplitude load and update the system-level risk of fatigue failure for railway bridges after inspection and repair. The proposed method is applied to a numerical example of an in-service railway bridge, and the effects of inspection and repair on the probabilistic fatigue life are discussed.ope

Respirable Dust Monitoring in Construction Sites and Visualization in Building Information Modeling Using Real-time Sensor Data

Construction activities, involving cutting, drilling, and grinding of materials, often produce toxic respirable dust that can cause fatal diseases and illnesses. To protect workers from breathing excessive amounts of respirable dust at job sites, superintendents should continuously monitor the level of respirable dust in workspaces and make timely interventions for overexposed workers. However, current practices of respirable dust monitoring have critical drawbacks, and superintendents cannot accurately estimate workers’ exposures to respirable dust or make prompt decisions to protect the workers. Therefore, there is a need for real-time air dust monitoring that can be deployed ubiquitously at a construction site and be integrated as part of daily construction management. In this research, we developed a real-time dust monitoring system that comprises a network of low-cost mobile dust sensors and visualization in building information modeling (BIM). Single-board computers and dust sensors were integrated as field deployment units. Inaccurate sensors were calibrated automatically on the basis of an accurate ground truth sensor. A BIM-based visualization system was developed to present the data collected from dust sensors in real time. A prototype system was developed and tested in a controlled environment

Feasibility of LoRa for Smart Home Indoor Localization

With the advancement of low-power and low-cost wireless technologies in the past few years, the Internet of Things (IoT) has been growing rapidly in numerous areas of Industry 4.0 and smart homes. With the development of many applications for the IoT, indoor localization, i.e., the capability to determine the physical location of people or devices, has become an important component of smart homes. Various wireless technologies have been used for indoor localization includingWiFi, ultra-wideband (UWB), Bluetooth low energy (BLE), radio-frequency identification (RFID), and LoRa. The ability of low-cost long range (LoRa) radios for low-power and long-range communication has made this radio technology a suitable candidate for many indoor and outdoor IoT applications. Additionally, research studies have shown the feasibility of localization with LoRa radios. However, indoor localization with LoRa is not adequately explored at the home level, where the localization area is relatively smaller than offices and corporate buildings. In this study, we first explore the feasibility of ranging with LoRa. Then, we conduct experiments to demonstrate the capability of LoRa for accurate and precise indoor localization in a typical apartment setting. Our experimental results show that LoRa-based indoor localization has an accuracy better than 1.6 m in line-of-sight scenario and 3.2 m in extreme non-line-of-sight scenario with a precision better than 25 cm in all cases, without using any data filtering on the location estimates

Spatial Analysis of Subway Ridership: Rainfall and Ridership

In-vehicle congestion of the urban railway system is the most important indicator to reflect the operation state of the urban railway. To provide the good service quality of urban railway, the crowdedness of the urban railway should be managed appropriately. The weather is one of the critical factors for the crowdedness. That is because even though the crowdedness of the urban railway is the same, passengers feel more uncomfortable in rainy weather condition. Indeed if specific sections and stations suddenly are concentrated excessive demand, it will lead far more serious problem. Therefore, this study analysis the relationship between the number of urban railway passenger and rainfall intensity in Seoul metropolitan subway system and then conducts the spatial analysis to deduct passenger demand patterns. This study is expected to be useful base study in order to manage the congestion at the urban railway station effectively by considering the different rainfall intensity

Analysis of Macroscopic Traffic Network Impacted by Structural Damage to Bridges from Earthquakes

Highway systems play a key role in providing mobility to society, especially during emergency situations, including earthquakes. Bridges in highway systems are susceptible to damage from earthquakes, causing traffic capacity loss leading to a serious impact on surrounding areas. To better prepare for such scenarios, it is important to estimate capacity loss and traffic disruptions from earthquakes. For this purpose, a traffic-capacity-analysisbased methodology was developed to model the performance of a transportation network immediately following an earthquake using a macroscopic multi-level urban traffic planning simulation model EMME4. This method employs the second order linear approximation (SOLA) traffic assignment and calculates total system travel time for various capacity loss scenarios due to bridge damage from earthquakes. It has been applied to Pohang City in Korea to evaluate the performance of traffic networks in various situations. The results indicate a significant increase in travel time and a decrease in travel speed as the intensity of an earthquake increases. However, the impact on traffic volume varies depending on the bridges. It is assumed that the location of the bridges and traffic routing patterns might be the main reason. The results are expected to help estimate the impact on transportation networks when earthquakes cause traffic capacity loss on bridges

Online ad hoc distributed traffic simulation with optimistic execution

As roadside and in-vehicle sensors are deployed under the Connected Vehicle Research program (formerly known as Vehicle Infrastructure Integration initiative and Intellidrive), an increasing variety of traffic data is becoming available in real time. This real time traffic data is shared among vehicles and between vehicles and traffic management centers through wireless communication. This course of events creates an opportunity for mobile computing and online traffic simulations. However, online traffic simulations require faster than real time running speed with high simulation resolution, since the purpose of the simulations is to provide immediate future traffic forecast based on real time traffic data. However, simulating at high resolution is often too computationally intensive to process a large scale network on a single processor in real time. To mitigate this limitation an online ad hoc distributed simulation with optimistic execution is proposed in this study. The objective of this study is to develop an online traffic simulation system based on an ad hoc distributed simulation with optimistic execution. In this system, data collection, processing, and simulations are performed in a distributed fashion. Each individual simulator models the current traffic conditions of its local vicinity focusing only on its area of interest, without modeling other less relevant areas. Collectively, a central server coordinates the overall simulations with an optimistic execution technique and provides a predictive model of traffic conditions in large areas by combining simulations geographically spread over large areas. This distributed approach increases computing capacity of the entire system and speed of execution. The proposed model manages the distributed network, synchronizes the predictions among simulators, and resolves simulation output conflicts. Proper feedback allows each simulator to have accurate input data and eventually produce predictions close to reality. Such a system could provide both more up-to-date and robust predictions than that offered by centralized simulations within a single transportation management center. As these systems evolve, the online traffic predictions can be used in surface transportation management and travelers will benefit from more accurate and reliable traffic forecast.PhDCommittee Chair: Hunter, Michael; Committee Member: Fujimoto, Richard; Committee Member: Laval, Jorge; Committee Member: Leonard, John; Committee Member: Rodgers, Michae

Perceptions on Regional Benefit of Airport Development and Operation

Airport development and operation has a significant impact on local economy. However, the impact is assessed differently from different perspectives. In this paper, the authors investigated how the public think on the benefit of airport development and operation from a regional perspective. More specifically, the paper focuses on what the main factors are in public perceptions on the regional benefit of airport development and operation. The authors analyzed a survey collected in South Korea using structural equation models. The authors assigned five categories of perception factors and examined these factor relationships regarding the ripple effects caused by airport development and operation on each region. The five factors were “increased use in air transportation”, “increased exchange with other regions”, “regional economic benefit”, “regional development”, and “dis-benefit to the region”. The model was verified with structural equations and path analysis results for each factor. It was revealed that people perceive the increased use in air transportation and the increased exchange with other regions as bringing about the most significant ripple effects, followed by regional development and regional economic benefit in this order, according to the order of path groups. The results of this paper are expected to provide stakeholders’ perspectives and insights when planning airport development and operation

Perceptions on Regional Benefit of Airport Development and Operation

Airport development and operation has a significant impact on local economy. However, the impact is assessed differently from different perspectives. In this paper, the authors investigated how the public think on the benefit of airport development and operation from a regional perspective. More specifically, the paper focuses on what the main factors are in public perceptions on the regional benefit of airport development and operation. The authors analyzed a survey collected in South Korea using structural equation models. The authors assigned five categories of perception factors and examined these factor relationships regarding the ripple effects caused by airport development and operation on each region. The five factors were “increased use in air transportation”, “increased exchange with other regions”, “regional economic benefit”, “regional development”, and “dis-benefit to the region”. The model was verified with structural equations and path analysis results for each factor. It was revealed that people perceive the increased use in air transportation and the increased exchange with other regions as bringing about the most significant ripple effects, followed by regional development and regional economic benefit in this order, according to the order of path groups. The results of this paper are expected to provide stakeholders’ perspectives and insights when planning airport development and operation