Developing and analyzing eco-driving strategies for on-road emission reduction in urban transport systems - A VR-enabled digital-twin approach

Abstract

A vast number of pollutants are generated from on-road commuting vehicles, and there is an increasing need to explore vehicle emission monitoring and mitigation strategies. Traditionally, vehicle emissions can be monitored and measured directly from on-vehicle devices such as a sensor at the tailpipe, or based on expensive data collection tools such as roadside units; while another mainstream research estimates vehicle emissions by relying on the connection to the vehicle motions, which can approximately calculate vehicle emissions under certain traffic conditions. This paper proposes a virtual reality (VR) enabled digital twin platform for on-road emission monitoring, and it develops and evaluates eco-driving strategies within a specific area. The proposed approach, integrating a VR-based digital environment, a micro-simulation model for background traffic, and a Motor Vehicle Emission Simulator for emission estimation, offers an alternative to collect and examine vehicle emissions such as NOx under various traffic conditions. A case study on a central business area in Melbourne is conducted and eco-driving strategies are tested in two scenarios. The first scenario concerns the impact of hybrid electric vehicles and connected autonomous vehicles, which points to the long-term benefit of having controllable and cleaner modes of transportation as a strategy. Results showed that manipulating the penetration rate of emission-friendly engines or motions could reduce vehicle emissions effectively. The second scenario concerns the real-time eco-routing based on emission-optimum, which points to the short-term benefit of emission control strategies. Human-in-the-loop experiments were conducted to test drivers’ responses toward routing options. Results showed that over 90% of participants would follow the eco-routing recommendations completely. The presented study offers an alternative to data-generating, analyzing, and managing approaches for on-road emissions in urban transportation systems.