An Approach to Comprehensively Evaluate Potential Park and Ride Facilities

ABSTRACTA park and ride facility provides an option to car drivers to park their cars and switch to public transportation for the remaining portions of their trips. Although park and ride has been implemented in many cities in the United States and integrated with different modes of transportation, no comprehensive approach has been developed in published literature to assess the feasibility of a potential park and ride site. This research proposes a comprehensive approach, which consists of the following tasks, to evaluate potential park and ride facilities: 1Site location analysis2Bus system reliability analysis3Parking supply and usage analysis4Mode choice model5User demand and ridership estimation6Cost estimation and economic impacts analysisThe application of the proposed tasks was demonstrated through a case study of a site in the City of El Paso, Texas

Digital Twin Technologies towards Understanding the Interactions between Transportation and Other Civil Infrastructure Systems

69A3551747119Digital Twin (DT) technology is the next step in the gradual shift from physical to digital models in civil engineering. Computer-Aided Drafting (CAD) revolutionized the industry by reducing the time and costs associated with documenting design. Building Information Modeling (BIM) has eliminated the need for physical design descriptors (i.e., drawings or physical models). DT models build off CAD and BIM but are utilized over the operational life of the infrastructure as a management tool. A DT is a relevant abstraction of the physical asset; it is most frequently used to model, improve, and control manufacturing systems. Civil engineering applications using DTs have been emerging, but transportation infrastructure represents a challenging extension of DT technology because of its spatial scale, as well as its voluminous and time-varying data. However, DT is a powerful decision support tool for the design, maintenance, and management of transportation infrastructure, particularly for studying its interdependencies with other infrastructure systems, which is of relevance to smart cities. The primary objective of this research was to explore the effectiveness of DT technology as a tool to visualize and understand interactions between transportation and other related civil infrastructure systems

Freeway traffic prediction using neural networks

Proceedings of the International Conference on Applications of Advanced Technologies in Transportation Engineering247-2540023

AN APPLICATION OF THE TRAFFIC CONFLICT TECHNIQUE FOR ON-RAMP MERGING AT EXPRESSWAY

Master'sMASTER OF ENGINEERIN

Characterization of University Parking Systems

Project VideoU.S. Department of Transportation 69A35517471191_dqqq2qe

Exploring the Influence of Carbon Footprint and Health Benefits in Parking Location Decisions

Project VideoU.S. Department of Transportation 69A35517471191_zxn3i18

Exploring the Characteristics of Faculty and Staff Parking on University Campuses

Project VideoThis project studied the characteristics of faculty and staff parking on university campuses. This project had two parts. Part one reviewed the faculty and staff parking management at four universities: Cornell University, University of California, Davis, University of South Florida, and The University of Texas at El Paso. The spatial distributions of parking zones, types of permits, and permit fees for faculty and staff were compared. Part two developed a faculty and staff annual median permit fee model called the faculty and staff base price model using campus land-use, demographics, and economic and climate data gathered from 213 universities. A faculty and staff base price mode, as a linear function of the log of city’s population, average Fall temperature, in-state tuition fee, number of employees and campus population density, has been developed using the Tobit regression technique. The model developed has been applied to four universities in a case study.U.S. Department of Transportation 69A35517471191_gpe9krs

Exploring the Characteristics of Faculty and Staff Parking on University Campuses

Project DescriptionThis project studied the characteristics of faculty and staff parking on university campuses. This project had two parts. Part one reviewed the faculty and staff parking management at four universities: Cornell University, University of California, Davis, University of South Florida, and The University of Texas at El Paso. The spatial distributions of parking zones, types of permits, and permit fees for faculty and staff were compared. Part two developed a faculty and staff annual median permit fee model called the faculty and staff base price model using campus land-use, demographics, and economic and climate data gathered from 213 universities. A faculty and staff base price mode, as a linear function of the log of city’s population, average Fall temperature, in-state tuition fee, number of employees and campus population density, has been developed using the Tobit regression technique. The model developed has been applied to four universities in a case study.U.S. Department of Transportation 69A355174711

Fault Tolerance analysis of an Adaptive Neuro-Fuzzy Inference System for mandatory lane changing decisions in automated driving

Past research has developed a binary decision model for mandatory lane changes based on the Adaptive Neuro-Fuzzy Inference System (ANFIS). This ANFIS Decision Model (simply called ADEM), developed and tested with the Next Generation Simulation (NGSIM) data, mimics the sensory inputs and decisions of human drivers. This research assumed that ADEM will be implemented as part of the automated lane changing system in Automated Vehicles (AVs). The system in AVs will depend on active radar sensors to make measurements. The sensor outputs will be converted into the input parameter values of ADEM. This research tested ADEM’s performance when the sensors could only measure the distance of surrounding vehicles within 50m, and when one of the sensors malfunctions. The original NGSIM test data set was modified to simulate the sensors’ detection range limit in Scenario 0, plus six other scenarios in which each sensor took turns to fail and assumed either the minimum or maximum possible output values. The results show that: (i) ADEM performs in a safer manner when considering the sensors’ limited detection range; (ii) the minimum value of 0m should be used as the default sensor output when a sensor fails, so that ADEM makes safer mandatory lane changing decisions; and (iii) the most critical sensors, by which failure of any of them would cause the greatest degradation to ADEM’s performance, are the two sensors that measure the distances to the preceding and the following vehicles in the target lane

Development of a Comprehensive Metric to Evaluate the Impacts of Transportation- Environment on Community Health

Project DescriptionThe objective of this research is to develop a metric which can be served as a decision support tool for engineers, planners, public health officers and other decision makers to evaluate the health status of a community with respect to transportation and environment. To measure a community’s health, this metric will consist of a few criteria, and each criterion consists of several measurable indicators, with identified sources of data. It will be developed through literature review, focus group interview and survey. Using the data gathered, a concept map will be constructed to visualize the relationship/interactions between different elements of transportation, environment and community health. An accompanying metric will then be developed. A case study will be used to demonstrate the application of the metric to a local project.U.S. Department of Transportation 69A355174711