Abstract

In this paper, we present a comprehensive analysis of the current transit systems in the Tri-Valley of the Eastern Region of the San Francisco Bay Area. Using the most recent data available from various sources and significant research we provide a close look into ridership trends, public surveys and transit reports. System maps, connections, routes and schedules are analyzed from all the mass transit systems available in the Tri-Valley region. Transit system infrastructure, resources and limitations are assessed and presented. Different performance metrics are also evaluated and compared against mass transit systems available in other parts of the San Francisco Bay Area. Throughout various data analysis techniques, the extend of societal, geographic, economic and environmental factors are studied and assessed. Demographics are closely studied and analyzed with an aim to understand commuting behaviors and needs for the residents of all cities, towns and unincorporated areas within the Tri-Valley. Predictions for the Tri-Valley region are also presented along with data and data visualizations for all seven counties in the San Francisco Bay Area by the year 2040. Throughout data mining and statistical techniques a number of initiatives to effectively help reduce traffic congestion in the Tri-Valley are assessed and presented. This paper is written to our best professional competence and aiming to present a high quality research with the purpose of raising awareness and understanding to a public problem, and its alternative solutions. General ethical principles are also discussed and presented.

Recommended Citation

Leon Castaneda, Paola Selene and Catalano, Christian Joseph (2018) "Initiatives to Effectively Help Reduce Traffic Congestion in the Tri-Valley," SMU Data Science Review: Vol. 1: No. 4, Article 14.
Available at: https://scholar.smu.edu/datasciencereview/vol1/iss4/14