Examining Transit Service Improvements with Internet-of-Things (IoT): A Disparity Analysis

The operationalization of the Internet-of-Things (IoT) in transportation is revolutionizing day-to-day passenger travel ensuring improved safety, mobility, and reliability of multimodal transportation systems. With IoT-based Intelligent Public Transportation System (IoT-IPTS), passengers can easily manage first/last mile travel to and from their origin or destination once arrival and departure times of transit are known. The application of IoT-IPTS seems promising for smart trains, however, no research exists for evaluating the technology’s impacts in alleviating disparities (if at all) for the low-income communities served. This proposed research will examine if IoT-IPTS would make stations and cities in low-income communities more equally connected and accessible for transit.  A suitable inequality measure will be developed in this proposed research by integrating IoT-IPTS features into two important performance measures often used for rail, namely, connectivity and accessibility. The hypothesis to be tested is that IoT-IPTS can reduce inequalities among regions of low-income commuters connected and served by transit. To demonstrate the application of the inequality measure, LA Metro’s light rail lines (A, B, C, D, E, and L) will be used as a case study. Subsequently, rail lines will be identified as winners and losers using a performance persistence analysis to show if improvements in connectivity and accessibility (through increased frequency of service and access) are needed in specific rail lines of the LA Metro despite IoT-IPTS deployment. The recommendations of this proposed research will help attract more transit riders from households with no car ownership and from low-income communities served by the LA Metro light rail lines.

Principal Investigator: 
Shailesh Chandra, Ph.D.
PI Contact Information: 
April 2023
Impacts/Benefits of Implementation: 

Knowing (rail lines) as winners or losers will further help planners and policy-makers channel appropriate capital investments to rail lines of LA Metro and increase its connectivity and/or accessibility to minimize their disparities. Compared to all the past research, our methodology is unique as it will deploy socioeconomic data, station-level connectivity and accessibility of the rail lines incorporating IoT-IPTS to deduce percentage changes in inequality developed in this research. This approach encompasses sensitivity both from the disparity and performance measures perspectives of rail transit.

Project Number: 



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