Work

On the Necessity and Effects of Considering Correlated Stochastic Speeds in Shortest Path Problems Under Sustainable Environments

Year: 2019

Type: article

Abstract: This research addresses how the stochasticity and correlation of travel speeds affect the shortest path solutions in sustainable environments. We consider a shortest path problem with the objective function of minimizing a linear combination of the mean and standard deviation of carbon emissions. By adjusting the proportion of the standard deviation in the objective function, the effects of speed stochasticity and correlation are studied under different preferences of the decision-makers on the fluctuations of carbon emissions. Based on 102-day real speed data from the Los Angeles freeway network, this research conducts extensive numerical experiments on 200 randomly chosen origin-destination pairs. Experimental results demonstrate the necessity of considering speed stochasticity and correlation, especially when the standard deviation of carbon emissions takes a large proportion in the objective function. As the weight of the standard deviation in the objective function increases from 0 to 1.5, the reduction of emission objective values increases from 0.03% to 0.13% by considering speed stochasticity, and increases from 0.02% to 0.20% by considering speed correlation. Taking the city Los Angeles with about 2361 taxis and about 525,945 passenger orders in January 2017 as an example, 0.03% and 0.02% reductions respond to about 3156 kg and 2630 kg carbon emission, respectively.

Source: Sustainability

DOI: 10.3390/su12010238

Authors: Dongqing Zhang, Zhaoxia Guo

Institutions: National University of Singapore, Sichuan University

Language: English

Topic: Transportation Planning and Optimization

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Climate action, Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,722