Using Socio-economic Indicators, Smart Transit Systems, and Urban Simulator to Accelerate ZEV Adoption and Reduce VMT

TL;DR

This paper develops a simulation-based framework integrating socio-economic data, smart transit systems, and urban modeling to promote ZEV adoption and reduce VMT in low-density, auto-dependent cities aiming for net-zero emissions by 2050.

Contribution

It introduces a novel simulation environment using Unity 3D to evaluate policies leveraging socio-economic indicators and ITS for accelerating ZEV adoption and reducing VMT.

Findings

Simulation environment enables dynamic urban mobility modeling.

Policy analysis identifies effective strategies for ZEV adoption.

Urban indicators and smart systems improve transit modal split.

Abstract

Globally, on-road transportation accounts for 15% of greenhouse gas (GHG) emissions and an estimated 385,000 premature deaths from PM2.5. Cities play a critical role in meeting IPCC targets, generating 75% of global energy-related GHG emissions. In Houston, Texas, on-road transportation represents 48% of baseline emissions in the Climate Action Plan (CAP). To reach net-zero by 2050, the CAP targets a 70% emissions reduction from a 2014 baseline, offset by 30% renewable energy. This goal is challenging because Houston is low-density and auto-dependent, with 89% of on-road emissions from cars and small trucks and limited public transit usage. Socio-economic disparities further constrain Zero Emissions Vehicle (ZEV) adoption. Strategies focus on expanding ZEV access and reducing Vehicle Miles Traveled (VMT) by 20% through transit improvements and city design. This paper presents methods for establishing an on-road emissions baseline and evaluating policies that leverage socio-economic indicators and Intelligent Transportation Systems (ITS) to accelerate ZEV adoption and reduce VMT. Smart parking, transit incentives, secure data systems, and ZEV fleet management support improvements in modal split and system reliability. Policy options are analyzed and potential actions identified. To support evaluation, a simulation environment was developed in Unity 3D, enabling dynamic modeling of urban mobility and visualization of policy scenarios. Auto-dependent cities aiming for 2050 emission targets can benefit from the indicators, metrics, and technologies discussed.