Time-Environmental Impacts Tradeoff Analysis for Businesses Commuters

In 2015, the transportation sector accounted for 27% of the total greenhouse gas (GHG) emissions in the United States; only second to the electricity sector with 29% share. Half of the emissions from the transportation sector are produced from passenger cars and light-duty trucks. Substantial proportions of the transportation emissions come from drive-alone commute mode, which is reported in 2013 as the predominant commute mode with 76.4% of the total traveled miles in USA. This highlights the importance of identifying solutions that would reduce the drive-alone mode to decrease the transportation related emissions. Furthermore, employers often provide free parking spaces to their employees and accordingly existing business commute choices rely mainly on employees’ preferences, intermediate stops and time constraints. Accordingly, optimized solutions that provide individualized commute plans and comply with commuter needs are required to improve efficiency of the transportation system. This paper presents the development and implementation of a novel and innovative optimization system that is capable of identifying optimal tradeoffs among two important transportation objectives: minimizing negative environmental impacts and commute times. This system identifies the optimal commute mode for each commuter, such as drive existing vehicle, carpool, use public transit, bike, or walk to achieve the aforementioned objectives. The present system is designed to: (1) maintain convenience such as departure and arrival times, and commute duration; and (2) incentivize commuters such as providing monetary incentives, and realizing burned calories, health benefits, and saved commute time and cost due to changes in commute behavior. A case study of students at University of Colorado Denver is used to verify the system performance and demonstrate its use. The results of the case study show that GHG and air pollution emissions can be minimized in the student community by up to 26%, while minimizing total commute time and cost of students.