Automated Driving Systems Data Acquisition and Processing Platform

This paper presents an automated driving system (ADS) data acquisition and processing platform for vehicle trajectory extraction, reconstruction, and evaluation based on connected automated vehicle (CAV) cooperative perception. This platform presents a holistic pipeline from the raw advanced sensory data collection to data processing, which can process the sensor data from multiple CAVs and extract the objects' Identity (ID) number, position, speed, and orientation information in the map and Frenet coordinates. First, the ADS data acquisition and analytics platform are presented. Specifically, the experimental CAVs platform and sensor configuration are shown, and the processing software, including a deep-learning-based object detection algorithm using LiDAR information, a late fusion scheme to leverage cooperative perception to fuse the detected objects from multiple CAVs, and a multi-object tracking method is introduced. To further enhance the object detection and tracking results, high definition maps consisting of point cloud and vector maps are generated and forwarded to a world model to filter out the objects off the road and extract the objects' coordinates in Frenet coordinates and the lane information. In addition, a post-processing method is proposed to refine trajectories from the object tracking algorithms. Aiming to tackle the ID switch issue of the object tracking algorithm, a fuzzy-logic-based approach is proposed to detect the discontinuous trajectories of the same object. Finally, results, including object detection and tracking and a late fusion scheme, are presented, and the post-processing algorithm's improvements in noise level and outlier removal are discussed, confirming the functionality and effectiveness of the proposed holistic data collection and processing platform

A Multifaceted Equity Metric System for Transportation Electrification

Transportation electrification will bring significant benefits to society such as the elimination of tailpipe emissions and less dependence on fossil fuel in the transportation sector. The equitable distribution of electric vehicles (EVs) and electric vehicle supply equipment (EVSE) is a critical challenge for a successful electrification transition. While existing research of transportation equity significantly contributes to understanding either of horizontal or vertical equity issues in transportation, additional challenges are brought by the emerging trend of transportation electrification. This thesis proposes a multi-dimensional equity metric system to fill this gap, which evaluates the equity implications of the projected EV and EVSE deployment across different socio-demographic groups. Specifically, four types of equity are considered: a fair share of resources and external costs that are grouped into horizontal equity, as well as inclusivity and affordability that refer to vertical equity. This thesis also performs a case study addressing equity issues of the projected EV and EVSE adoption in Los Angeles County (LA County) in 2035 by leveraging the proposed equity metric system. The results of the case study reveal disparities in EV and public charger adoption, EV trip distance, trip purpose, and economic status. These disparities result in uneven impacts on different socio-demographic groups, highlighting the need to address equity issues in transportation electrification. Based on the case study results, this thesis proposed recommendations to address these equity issues, which provides valuable insights for local governments and transportation agencies

A Multifaceted Equity Metric System for Transportation Electrification

Transportation electrification offers societal benefits like reduced emissions and decreased dependence on fossil fuels. Understanding the deployment of electric vehicles (EVs) and electric vehicle supply equipment (EVSE) has been a popular focus, however, achieving their equitable distribution in the transportation system remains a challenge for successful electrification. To address this issue, this paper proposes a multi-dimensional equity metric system that assesses the equity status in the impacts of EV and EVSE deployment across different socio-demographic groups. Four types of equity are considered in the equity metric system: a fair share of resources and external costs that are grouped into horizontal equity, as well as inclusivity and affordability that refer to vertical equity. This paper performs a case study to examine equity concerns regarding the adoption of EVs and EVSE in Los Angeles County in 2035 by leveraging the proposed equity metric system. The results reveal disparities in the adoption of EVs and public chargers, as well as variations in EV trips and economic status across different socio-demographic groups. These disparities underscore the urgency to address equity issues during electrification. Building upon the results, this study puts forth recommendations to tackle these equity challenges to provide valuable insights for local agencies