On the Characterization of Eco-Friendly Paths for Regional Networks

Abstract

Macroscopic traffic models represent a promising tool to design strategies for ecological routing. To benefit from this tool, we must first characterize the relationship between path emissions and distance traveled or travel time on aggregated networks, i.e., a regional network. This paper investigates this relationship between two toy networks and a real urban network representing the city of Innsbruck (Austria). We utilize an accumulation-based model based on the Macroscopic Fundamental Diagram to mimic the traffic dynamics in the network and utilize the COPERT IV model to estimate the travel emissions, focusing on the carbon dioxide CO2. We show that there is a linear relationship between the total emissions of CO2 and the average travel time of internal paths, i.e. paths that take place completely within a single region. We also show that in some cases, there is a linear relationship between the total emissions and the average travel distance or travel time of paths that cross multiple regions in the network. However, the latter is not always true as traffic dynamics play an important role in path emissions. In other words, eco-friendly paths on regional networks do not necessarily follow the shortest paths in terms of distance or time.

Analyzing Shared Bike Usage Through Graph-Based Spatio-Temporal Modeling

“…Network modelling varies depending on the purpose of the analysis. Typically, traffic flows are investigated where spatial locations are viewed as nodes while trips form an edge between its starting location and destination [4], [5], [6], [7], [8], [9], [10].…”

“…Other approaches to complex network construction have also been proposed for the analysis of bike-sharing systems. For instance, Batista et al [8] built a network where each node represents a specific region. Within these regions, vehicles travel at the identical average speed, and nodes in the network are interconnected if the regions are adjacent to each other.…”

An Optimal Routing Framework for an Integrated Urban Power–Gas–Traffic Network

“…where 𝑡, 𝑟, and 𝑗 represent the indices for time intervals, traffic roads, and OD pairs, respectively. The extra travel time, ET(t), is defined in (1), where the first term shows the actual travel time, and the second term shows the minimum travel time. Uncongested travel time on road r is denoted as NT, EV traffic flow as 𝐹 𝐸𝑉 , and CFV traffic flow as 𝐹 𝐶 .…”

“…A. Motivation and Literature Review ECENTLY, the threat of climate change has prompted the development of environmentally friendly and cost-efficient transportation technologies [1]. In particular, fast charging technologies and increased battery capacity are encouraging the use of electric vehicles (EVs), and EV charging stations connected to the power grid are proliferating.…”