{"id":39,"date":"2022-09-01T10:32:56","date_gmt":"2022-09-01T17:32:56","guid":{"rendered":"https:\/\/faculty.engineering.asu.edu\/jzhao\/?page_id=39"},"modified":"2026-03-12T16:41:53","modified_gmt":"2026-03-12T23:41:53","slug":"research","status":"publish","type":"page","link":"https:\/\/faculty.engineering.asu.edu\/jzhao\/research\/","title":{"rendered":"Research"},"content":{"rendered":"\n<div class=\"wp-block-group is-layout-flow wp-block-group-is-layout-flow\">\n<h2 class=\"wp-block-heading\"><strong>Research Interests<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Connected and Automated Vehicles (CAV)<\/li>\n\n\n\n<li>Battery Electric Vehicles (BEV)<\/li>\n\n\n\n<li>Battery Management System (BMS)<\/li>\n\n\n\n<li>CAV system integration and safety assessment<\/li>\n\n\n\n<li>Motion planning and controls<\/li>\n\n\n\n<li>Cooperative perception<\/li>\n\n\n\n<li>AI\/ML in automotive and robotics systems<\/li>\n\n\n\n<li>Intelligent Transportation Systems (ITS)<\/li>\n<\/ul>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity is-style-copy-divider\"\/>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Research Projects<\/strong><\/h2>\n\n\n\n<div class=\"wp-block-group is-layout-constrained wp-block-group-is-layout-constrained\">\n<div class=\"wp-block-group is-layout-constrained wp-block-group-is-layout-constrained\">\n<h4 class=\"wp-block-heading\">Zero-Emission Vehicle Crash Management System<\/h4>\n\n\n\n<p><strong>PI: Dr. Jeffrey Wishart; co-PI: Prof. Junfeng Zhao<\/strong><\/p>\n\n\n\n<p>The objective of the Zero-Emission Vehicle Crash Management System (ZEV-CMS) Mission is the development and of a system that will provide training, guidance, and tools for first and second responders to use when responding to a crash involving a ZEV (electric vehicle (EV) or fuel cell vehicle (FCV)). As ZEVs become more common on public roads, it is imperative that these responders understand the unique risks and challenges posed by these vehicles.\u00a0<\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2026\/03\/ZEV-CMS-Mission.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of ZEV-CMS Mission.\"><\/object><a id=\"wp-block-file--media-2a625c32-cc3d-400f-8469-a2611a1f0123\" href=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2026\/03\/ZEV-CMS-Mission.pdf\">ZEV-CMS Mission<\/a><a href=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2026\/03\/ZEV-CMS-Mission.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-2a625c32-cc3d-400f-8469-a2611a1f0123\">Download<\/a><\/div>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\">SPR-798: Statewide Pavement Marking Assessment for Driver-Assist Vehicle Technologies <\/h4>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\">\n<p class=\"is-style-lead\"><strong>Sponsor: <strong>Arizona Department of Transportation (ADOT)<\/strong>\/AZTI<br><strong>with funding from the Federal Highway Administration (FHWA) State Planning and Research (SPR) Program<\/strong><\/strong><\/p>\n\n\n\n<p><strong>PI: Dr. Minfeng Shang; co-PI: Prof. Junfeng Zhao<\/strong><\/p>\n\n\n\n<p>The work plan for this project is designed to support the Arizona Department of Transportation (ADOT) in evaluating and modernizing pavement marking practices to meet the evolving needs of both human drivers and advanced driver-assist vehicle technologies. As reliance on systems such as Lane Departure Warning (LDW), Lane Keeping Assistance (LKA), and Lane Centering Assistance (LCA) continues to grow, the visibility and consistency of pavement markings\u2014particularly under challenging conditions such as nighttime, bad weather, and surface wear\u2014has become increasingly important. This research aims to assess the adequacy of current ADOT pavement marking standards, compare them with best practices from other states, and develop recommendations to ensure compatibility with both legacy road users<br>and emerging vehicle technologies. The findings will guide the development of a statewide assessment program and a long-term maintenance strategy that promotes safer and more reliable roadway operations.<\/p>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"570\" height=\"613\" src=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture2-2.png\" alt=\"\" class=\"wp-image-783\" style=\"width:342px;height:auto\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture2-2.png 570w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture2-2-465x500.png 465w\" sizes=\"auto, (max-width: 570px) 100vw, 570px\" \/><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1500\" height=\"389\" src=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture3-2-1500x389.png\" alt=\"\" class=\"wp-image-784\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture3-2-1500x389.png 1500w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture3-2-500x130.png 500w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture3-2-1000x259.png 1000w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture3-2-1536x399.png 1536w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture3-2.png 1869w\" sizes=\"auto, (max-width: 1500px) 100vw, 1500px\" \/><\/figure>\n<\/div>\n<\/div>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\">Transformer-based Vehicle-to-Infrastructure Cooperative Perception for CAVs<\/h4>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\">\n<p><strong>PI: Prof. Junfeng Zhao<\/strong><\/p>\n\n\n\n<p>We will develop a unified Transformer-based vehicle-to-infrastructure cooperative perception framework that enhances environmental understanding for connected and automated vehicles under occlusion, range limitation, and asynchronous sensing. VI-BEV introduces an intermediate fusion architecture in the Bird\u2019s Eye View domain, leveraging cross-attention Transformers to integrate vehicle and infrastructure camera and LiDAR features for robust 3D object detection with extended perception range. Building on this representation, VI-Track extends cooperative perception to spatiotemporal reasoning by incorporating infrastructure assisted multi-object tracking and dynamics-aware fusion, enabling consistent object state estimation despite sensing and communication delays. Complementary to detection and tracking, VI-BEVSEG generalizes the same BEV-centric, attention-based fusion paradigm to cooperative semantic segmentation, supporting scene understanding tasks such as road layout and object occupancy mapping. Collectively, these methods establish a scalable, task-agnostic vehicle infrastructure perception framework that unifies detection, tracking, and segmentation through shared BEV representations and Transformer-based fusion, demonstrating improved robustness, coverage, and temporal consistency for safety-critical CAV applications.<\/p>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"366\" height=\"223\" src=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture3-3.png\" alt=\"\" class=\"wp-image-800\" style=\"width:342px;height:auto\"\/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"826\" height=\"1301\" src=\"http:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture2-3.png\" alt=\"\" class=\"wp-image-801\" style=\"width:342px;height:auto\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture2-3.png 826w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture2-3-317x500.png 317w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture2-3-635x1000.png 635w\" sizes=\"auto, (max-width: 826px) 100vw, 826px\" \/><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1500\" height=\"621\" src=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture1-1500x621.png\" alt=\"\" class=\"wp-image-799\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture1-1500x621.png 1500w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture1-500x207.png 500w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture1-1000x414.png 1000w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture1-1536x635.png 1536w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture1-2048x847.png 2048w\" sizes=\"auto, (max-width: 1500px) 100vw, 1500px\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1500\" height=\"658\" src=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture4-1500x658.png\" alt=\"\" class=\"wp-image-805\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture4-1500x658.png 1500w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture4-500x219.png 500w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture4-1000x439.png 1000w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture4-1536x674.png 1536w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture4-2048x899.png 2048w\" sizes=\"auto, (max-width: 1500px) 100vw, 1500px\" \/><\/figure>\n<\/div>\n<\/div>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\">AI-Powered Universal Battery Management System<\/h4>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\">\n<p class=\"is-style-lead\"><strong>Sponsor: BlackTeal Energy, Greater Phoenix Economic Council<\/strong><\/p>\n\n\n\n<p><strong>PI: Prof. Junfeng Zhao<\/strong><\/p>\n\n\n\n<p>The integration of AI and Digital Twin technologies into Battery Management Systems (BMS) represents a transformative shift in energy storage management. These cutting-edge solutions address key challenges faced by traditional BMS, such as inefficiencies in state estimation, data fragmentation, and thermal management issues. By incorporating AI and Digital Twins, the proposed Unified Battery Management System (U-BMS) framework significantly enhances system performance, extends battery life, and improves compatibility and safety.<\/p>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"738\" height=\"259\" src=\"http:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2024\/11\/uBMS.png\" alt=\"\" class=\"wp-image-677\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2024\/11\/uBMS.png 738w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2024\/11\/uBMS-500x175.png 500w\" sizes=\"auto, (max-width: 738px) 100vw, 738px\" \/><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"448\" height=\"344\" src=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture6.png\" alt=\"\" class=\"wp-image-788\"\/><\/figure>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-group is-layout-constrained wp-block-group-is-layout-constrained\">\n<h4 class=\"wp-block-heading\">Development of an Operational Safety Testing Platform for Automated Vehicles<\/h4>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\">\n<p class=\"is-style-lead\"><strong>Sponsor: Arizona Commerce Authority, Science Foundation of Arizona <\/strong><\/p>\n\n\n\n<p><strong>PI: Prof. Junfeng Zhao<\/strong><\/p>\n\n\n\n<p>The industry has progressed to a point where automated vehicles (AVs) are being deployed in limited commercial applications in select locations, including Arizona. However, whether the AV is commercially deployed or is a prototype being tested on public roads, the operational safety is unknown. Arizona State University, in collaboration with Science Foundation Arizona (SFAz), is developing an operational safety assessment (OSA) method to address this critical gap in public safety related to CAVs. The OSA method includes a mix of simulation, closed course, and public road scenario-based testing in order to assess the operational safety of the vehicle in thousands of scenarios, including difficult edge cases. The OSA method includes a mix of simulation, closed course, and public road scenario-based testing in order to assess the operational safety of the vehicle in thousands of scenarios, including difficult edge cases. The objective of the proposed project is to develop a platform that (1) enables sufficiently accurate simulation results through the creation of a high-fidelity model, known as a Digital Twin (DT), of a research CAV purchased by the ASU PI and (2) ensures more edge cases are encountered in closed course and public road testing by adding Augmented Reality (AR) capability to the research CAV. The proposed platform will allow for thousands of scenarios to be tested in simulation much faster and more cheaply than with the research CAV, which allows the latter to test a subset of scenarios for validation of the simulation results purposes, some of which will have AR-injected objects added to the research vehicle\u2019s environment.<\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"605\" height=\"276\" src=\"http:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2022\/12\/OSA_platform.svg_.jpg\" alt=\"\" class=\"wp-image-264\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2022\/12\/OSA_platform.svg_.jpg 605w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2022\/12\/OSA_platform.svg_-500x228.jpg 500w\" sizes=\"auto, (max-width: 605px) 100vw, 605px\" \/><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"997\" height=\"425\" src=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture7.png\" alt=\"\" class=\"wp-image-790\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture7.png 997w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture7-500x213.png 500w\" sizes=\"auto, (max-width: 997px) 100vw, 997px\" \/><\/figure>\n<\/div>\n<\/div>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-group is-layout-constrained wp-block-group-is-layout-constrained\">\n<h4 class=\"wp-block-heading\">Intelligent Parking Guidance through AI and IoT to Empower Drivers and Autonomous Vehicles<\/h4>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\">\n<p class=\"is-style-lead\"><strong>Sponsor: Cox Communications, Inc.<\/strong>, <strong>ASU-Cox Collaboratory<\/strong><\/p>\n\n\n\n<p><strong>PI: Prof. Junfeng Zhao<\/strong><\/p>\n\n\n\n<p>Finding an open parking space at congested parking lots in urban centers, commercial areas, and public spaces is often time-consuming and frustrating, leading to wasted fuel, and increased greenhouse gas emissions. Another concern in parking lots is the occurrence of traffic accidents, often caused by distracted drivers searching for parking spaces or navigating through congested lots. It is challenging not just for human drivers but also for Robotaxi or vehicles that can be summoned to parking lots. We need an innovative navigation solution to ease the parking process for human drivers and autonomous vehicles (AVs), and make it safer, more convenient, and environmentally friendly.<\/p>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1167\" height=\"564\" src=\"http:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2023\/10\/Picture1.png.jpg\" alt=\"\" class=\"wp-image-468\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2023\/10\/Picture1.png.jpg 1167w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2023\/10\/Picture1.png-500x242.jpg 500w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2023\/10\/Picture1.png-1000x483.jpg 1000w\" sizes=\"auto, (max-width: 1167px) 100vw, 1167px\" \/><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1099\" height=\"611\" src=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture8.png\" alt=\"\" class=\"wp-image-791\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture8.png 1099w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture8-500x278.png 500w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Picture8-1000x556.png 1000w\" sizes=\"auto, (max-width: 1099px) 100vw, 1099px\" \/><\/figure>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity is-style-copy-divider\"\/>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Sponsors<\/strong><\/h2>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"400\" height=\"250\" src=\"http:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2023\/07\/aca-logo-400x250-1.jpg\" alt=\"\" class=\"wp-image-385\" style=\"width:371px;height:auto\"\/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"500\" height=\"213\" src=\"http:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2023\/07\/sfaz-logo-small-600.png\" alt=\"\" class=\"wp-image-386\" style=\"aspect-ratio:2.3475900520871544;width:352px;height:auto\"\/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1200\" height=\"399\" src=\"http:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2023\/10\/cox-logo-og-image.jpg\" alt=\"\" class=\"wp-image-469\" style=\"aspect-ratio:3.007636577246916;width:330px;height:auto\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2023\/10\/cox-logo-og-image.jpg 1200w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2023\/10\/cox-logo-og-image-500x166.jpg 500w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2023\/10\/cox-logo-og-image-1000x333.jpg 1000w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1500\" height=\"350\" src=\"http:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2024\/11\/BTELogo_White-1.png\" alt=\"\" class=\"wp-image-671\" style=\"width:448px;height:auto\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2024\/11\/BTELogo_White-1.png 1500w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2024\/11\/BTELogo_White-1-500x117.png 500w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2024\/11\/BTELogo_White-1-1000x233.png 1000w\" sizes=\"auto, (max-width: 1500px) 100vw, 1500px\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"900\" height=\"582\" src=\"http:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2026\/01\/fhwa-2-yes-3.jpg\" alt=\"\" class=\"wp-image-828\" style=\"aspect-ratio:1.5464332697935403;width:387px;height:auto\" srcset=\"https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2026\/01\/fhwa-2-yes-3.jpg 900w, https:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2026\/01\/fhwa-2-yes-3-500x323.jpg 500w\" sizes=\"auto, (max-width: 900px) 100vw, 900px\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"500\" height=\"160\" src=\"http:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/logo-adot-25.png\" alt=\"\" class=\"wp-image-794\" style=\"width:384px;height:auto\"\/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"200\" height=\"95\" src=\"http:\/\/faculty.engineering.asu.edu\/jzhao\/wp-content\/uploads\/sites\/93\/2025\/12\/Logo-AZTI_header_with-edge_95px.png.webp\" alt=\"\" class=\"wp-image-795\" style=\"width:325px;height:auto\"\/><\/figure>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\"><\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\"><\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\"><\/div>\n<\/div>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p class=\"mb-2\">Research Interests Research Projects Zero-Emission Vehicle Crash Management System PI: Dr. Jeffrey Wishart; co-PI: Prof. Junfeng Zhao The objective of the Zero-Emission Vehicle Crash Management System (ZEV-CMS) Mission is the development and of a system that will provide training, guidance, and tools for first and second responders to use when responding to a crash 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