Ecological traffic management: A review of the modeling and control strategies for improving environmental sustainability of road transportation

Abstract

As road transportation energy use and environmental impact are globally rising at an alarming pace, authorities seek in research and technological advancement innovative solutions to increase road traffic sustainability. The unclear and partial correlation between road congestion and environmental impact is promoting new research directions in traffic management. This paper aims to review the existing modeling approaches to accurately represent traffic behavior and the associated energy consumption and pollutant emissions. The review then covers the transportation problems and control strategies that address directly environmental performance criteria, especially in urban networks. A discussion on the advantages of the different methods and on the future outlook for the eco-traffic management completes the proposed survey.

Introduction

While energy-related air pollution is considered today one of the primary premature death causes (World Health Organization, 2016), the global carbon dioxide (CO₂) emissions are on a rising trend destined to grow well above the levels imposed by the international climate goals (International Energy Agency, 2018). Population surge and economic growth of the developing countries have been identified as the main causes of the drastic increase of energy demand and pollutant emissions in all sectors (International Energy Agency, 2018).

The worldwide transportation sector alone accounts for 55% of the total liquid fuels consumption and, with the increasing travel demand, this share is not expected to decrease for the next two decades (U.S. Energy Information Administration, 2017a). In the member countries of the Organisation for Economic Co-operation and Development (OECD), projections show that the improved energy efficiency in transportation may lead to a net decline of about 2% in energy use until 2040, thus outpacing the predicted increase of vehicle-miles traveled (VMT). However, in OECD-Europe, transportation still represents the biggest source of carbon emissions (Transport & Environment, 2018), contributing about 25% of the total CO₂ emissions, with cars and vans representing more than two thirds of this share (Mandl & Pinterits, 2018). The situation is even more alarming in non-OECD countries, where the transportation energy demand is expected to rise by 64% until 2040, implying an increase of about 15% of energy-related CO₂ emissions (U.S. Energy Information Administration, 2017a).

Therefore, a lot of attention has been drawn worldwide to finding the most effective measures to help reduce the current contribution to greenhouse gas emissions from transportation. Governments, practitioners and researchers seem to agree on the fact that a combination of short-term and long-term strategies must be adopted. In the short-term, policies and regulations encouraging changes in behavior and travel habits represent a key lever. Attractiveness of alternative means of transportation should be enhanced, a shift to less polluting transport modes should be promoted, and a change in purchasing habits favoring smaller and more energy-efficient cars should be encouraged (Chapman, 2007). In the long-term, the widespread adoption of innovative technological solutions such as electrification, connectivity and automation are expected to enable a significant shift in the future of personal transportation and mobility. The way for such a technological transformation of mobility is already being paved thanks to the diffusion of connected and automated vehicles (CAVs), multi-vehicle (V2V) and vehicle-infrastructure (V2I) cooperation and communication networks, in- and over-roadway sensors, cloud-computing capabilities, etc. (Guanetti, Kim, & Borrelli, 2018).

However, the potential energy benefits of these technologies remain uncertain, mostly because of the high level of non-linear dependence between different aspects of an automated transportation system operating with conventional vehicles, as well as possible side-effects of automation (U.S. Energy Information Administration, 2017b). Among the features enabled by the aforementioned technologies that promise to increase energy efficiency and reduce pollutant emissions of transportation, it is worth mentioning eco-driving, eco-routing, platooning, roadway throughput optimization, powertrain electrification, vehicle down-sizing, parking search time reduction, ride-sharing. On the other hand, as for the side-effects that may endanger energy efficiency and emission reduction, it is likely that technology may increase traffic congestion as a consequence of an increased access to mobility, increase travel speeds as a consequence of enhanced safety, increase commute distances as an effect of increased comfort and reduced travel costs, etc. (U.S. Energy Information Administration, 2017b).

From a single-vehicle efficiency perspective, research suggests that lightweight, low-speed, autonomous vehicles have the potential to achieve fuel economies an order of magnitude higher than current cars (U.S. Energy Information Administration, 2017b). However, at system-wide level, current estimates suggest that the total energy consumption impacts can range from a 90% decrease to a 200% increase in fuel consumption as compared to a projected 2050 baseline energy (Brown, Gonder, & Repac, 2014).

Such a large variability in the possible outcome of the adoption of the new vehicular and traffic technologies makes it somewhat difficult to focus and prioritize the research efforts to increase energy efficiency of mobility. Nowadays, the general trend in research and policy seems to aim to reduce CO₂ emissions by pushing for more efficient vehicles and reducing VMT. This is based on a generally accepted paradigm that congestion mitigation programs should reduce CO₂ emissions. However, it is difficult to prove a clear direct proportionality between congestion and CO₂ emissions (Fiori et al., 2018). The most reliable approach to improve energy efficiency and reduce pollutant emissions in the design of a traffic regulation measure consists in directly considering these aspects as decision and optimization criteria. Therefore, interest in transportation regulation problems with explicit environmental considerations is growing (Vreeswijk, Mahmod, van Arem, 2013, Wang, Szeto, Han, Friesz, 2018).

This paper surveys the existing scientific literature on energy consumption and emission models, as well as road transportation problems directly addressing the issue of energy consumption and pollutant emissions reduction. Such problems can be tackled at different levels depending on the granularity and the object of the control action. At vehicle level, the energy-efficient control strategies typically act on single vehicles or groups of cooperating vehicles by modifying their individual speed profiles or route choices. At traffic level, the control strategies aim to influence the vehicular flow as a whole by acting on the typical flow regulation actuators, such as traffic lights, speed limits, etc. The adopted categorization in terms of modeling and control approaches both at vehicle and traffic level for the general problem of reducing environmental impact of road transportation is illustrated in Fig. 1.

The contributions of this paper are summarized as follows:

• A comprehensive literature review of the existing energy consumption and pollutant emissions models is provided. The review distinguishes between data and physics-based models and discusses their adaptation for usage with both single-vehicles and traffic flow.

• An overview of the existing vehicle and traffic control strategies to improve energy and environmental efficiency of transportation is given. The review focuses on the control techniques that explicitly address energy consumption and emissions. The connection and interaction between traffic congestion and energy efficiency is also discussed.

• As an outcome of this review, research gaps in the current state of the art have been identified and discussed in order to inspire future works in this field.

The body of the paper is organized as follows. Section 2 presents the energy consumption and emission models for the single vehicle with a brief discussion of how the vehicle kinematics can be obtained. Analogously, Section 3 introduces the modeling approaches to describe traffic kinematics, with a particular focus on the most popular fluid-dynamics traffic models, as well as the energy consumption and emission models for vehicular flow. The energy-optimal control strategies for single vehicles are presented in Section 4, while the transportation problems dealing with traffic energy efficiency are reviewed in Section 5. Finally, Section 6 contains concluding remarks and discussion on the current research gaps and future outlooks.