18-01 Sustainable and Smart-growth City Ranking: Multifaceted Transportation Performance Measures in Smart Cities

The concept of smart city is fast becoming a key instrument in transforming living environments in a way better to enhance operational efficiency of a transportation system. This study identifies a framework to assess transportation performance measures and smart-growth of cities around the U.S. The proposed assessment framework is comprised of the evaluation of individual criterion and the assessment of comprehensive results. The criteria are categorized into four groups including network performance, traffic safety, environmental impact, and physical activity. This study provides a multifaceted approach to integrate the criteria’s performance measures. As a case example, the proposed performance measures were examined for forty-six cities in the U.S. and the required data were gathered from multiple sources. A multi-criteria decision analysis (MCDA) method was employed to integrate and evaluate the score associated with each city. The output of the framework contains a sustainable and smart-growth ranking of the selected cities as well as uncertainty and sensitivity analysis. The sensitivity analysis was utilized to determine the quantity that each performance measure or weighting factor requires to alter the smart-growth score. It has been illustrated that the dominancy between reversible pairs in the ranking are critically sensitive for almost 15% of cases. The results of the proposed framework can be an effective decision supporting tool in analyzing traffic management strategies. Results from the score sensitivity calculation indicate that the proposed framework can be adopted in multifaceted transportation system performance in sustainable and smart-growth of cities

14-08 Big Data Analytics to Aid Developing Livable Communities

In transportation, ubiquitous deployment of low-cost sensors combined with powerful computer hardware and high-speed network makes big data available. USDOT defines big data research in transportation as a number of advanced techniques applied to the capture, management and analysis of very large and diverse volumes of data. Data in transportation are usually well organized into tables and are characterized by relatively low dimensionality and yet huge numbers of records. Therefore, big data research in transportation has unique challenges on how to effectively process huge amounts of data records and data streams. The purpose of this study is to conduct research on the problems caused by large data volume and data streams and to develop applications for data analysis in transportation. To process large number of records efficiently, we have proposed to aggregate the data at multiple resolutions and to explore the data at various resolutions to balance between accuracy and speed. Techniques and algorithms in statistical analysis and data visualization have been developed for efficient data analytics using multiresolution data aggregation. Results will be helpful in setting up a primitive stage towards a rigorous framework for general analytical processing of big data in transportation

14-01 Exploring the Equity Dimensions of US Bicycle Sharing Systems

Research over the past several decades has made it increasingly clear that livable communities are inextricably linked with the provision of opportunities for active and/or non-motorized transportation; i.e., walking, cycling and their variants. An emerging phenomena that is working within the broader movement of active transportation is public bicycle sharing systems (BSS). Such systems have grown considerably in the US in recent years and, in some cases, are dramatically changing the ecology of urban transport. Alongside celebrations of the early successes of US BSS, have been criticisms that these systems have not been adequately integrated into lower-income communities; a pattern that mirrors (motorized) transportation injustices-both past and present-that have burdened lower-income while simultaneously advantaging middle to higher-income communities. And while diverse communities are embracing non-motorized transportation, there is valid concern that traditionally underserved populations will again be marginalized or unable to share in the full benefits of existing and future bicycle- and pedestrian-oriented infrastructure including BSS. This research explores the spatial arrangements and allocations of US BSS and examines the extent to which lower-income communities experience differential access to bike-sharing infrastructure. Spatial regression models are employed to examine the degree to which race, ethnicity and/or economic hardship explain variations in the distribution of bike-sharing stations

16-04 Effectiveness of Bicycle Signals for Improving Safety and Multimodal Mobility at Urban Intersections

With the dramatic increase of non-motorized transportation users, more people are concerned about the non-motorized traffic safety. Unfortunately, bicyclists and pedestrians are prone to more severe injuries when involved in a crash. For bicycle crashes, failing to yield/disregarding traffic control device, and lack of non-motorized facilities were identified to be the main causes of bicycle crashes in urban intersections. This research investigated the effectiveness of two bicycle crash countermeasures with bicycle signal treatments at urban signalized intersections. These two countermeasures are the bike boxes and the protected intersections. The bicycle signal treatments that were tested simultaneously with these countermeasures are the leading bicycle interval and the exclusive bicycle phase. A before and after bicyclist survey was conducted to measure bicyclist perception of safety of the bike box and bicycle signal heads. Additionally, these engineering countermeasures were evaluated from both traffic operation and traffic safety prospective in a virtual test environment built in VISSIM. Users delay were compared before and after implementing these countermeasures. While a surrogate safety measure “conflicts” among users was used to measure the safety impact of such treatments. Through performing benefit-cost analysis, the threshold values of traffic and bike volumes that are needed to justify the bike box and the protected intersection treatments were found. This research also provided a general guideline that can be used by the decision makers to facilitate bicyclist left turn movement at urban signalized intersections

16-06 Vehicle-to-Device (V2D) Communications: Readiness of the Technology and Potential Applications for People with Disability

IEEE 802.11p was developed as an amendment to IEEE 802.11 for wireless access in vehicular environments (WAVE). While WAVE is considered the de facto standard for V2V communications, in the past few years a number of communications technologies have emerged that enable direct device-to-device (D2D) communications. Technologies like Bluetooth Smart, WiFi-Direct and LTE-Direct allow devices to communicate directly without having to rely on existing communications infrastructure (e.g., base stations). More importantly, these technologies are quickly penetrating the smartphones market. The goal of this research is to conduct extensive simulation and experimental studies to assess the efficacies of utilizing D2D communications technologies in transportation scenarios focused around pedestrians and bicyclists. Specifically, we design, develop, and experiment with Smart Cone and Smart Cane systems to evaluate the readiness of D2D technologies to support transportation applications