STAR award winners

Presenter: Omar Martinez, Assistant Director of Legislative Affairs, City of El Paso Primary Technology Areas

Project lead: City of El Paso

Project partners: TxDOT El Paso District, Texas A&M Transportation Institute, El Paso MPO: Smart Infrastructure, Data

Challenge definition and background

El Paso is a confluence of cultures and commerce. Home to six Ports of Entry (POEs) that are responsible for processing $109+ billion in U.S.-Mexico trade, it is an epicenter for international goods movement. Four bridges in the region support commercial vehicle traffic. With the rapid rise in truck traffic, however, El Paso’s roadways are facing gridlock, idling vehicles are polluting its air, and the health of its communities is suffering. Reducing pollution from the transportation sector is an essential component to mitigating poor air quality, which has a major health impact on El Paso residents. Focusing on mitigating congestion at ports will reduce transportation-related disparities and increase air quality for disadvantaged communities.

Proposed solutions

• ITS technologies for the Bridge of the Americas and Ysleta Port of Entry: Software integration, fiber optic communications, lane management systems, dynamic message signs, closed-circuit television cameras, ground vehicle sensors, signal phasing and timing
• Low-cost emissions sensors: Emissions sensor data will measure air quality at ports of entry and throughout the network. Air quality information will be integrated with regional ITS systems to inform infrastructure design, operations, and efficiency improvements at ports.

Expected benefits and performance measures

• Reducing Congestion: Integrating ITS design at ports of entry will improve movement of commercial vehicles
• Improving Air Quality: Idling-related emissions disproportionately impact Historically Disadvantaged Communities in El Paso

Scalability

National supply chain reshoring trends along the U.S.-Mexico border are leading to increases in demand for industrial, commercial, and warehousing space in border communities. The proposed ITS and emissions sensors can be replicated along every land port in the U.S.-Mexico border (in both countries) and in other ports around the world with similar congestion issues and traffic volumes.

Presenter: Michele Hagemann, Grant Writer, City of Midland

Project Lead: City of Midland

Primary Technology Areas: Unmanned Aerial Systems

Project Partners: Permian Basin MPO, City of Odessa, Ector County, Permian Road Safety Coalition

Challenge definition and background

Litter along roadways in Midland and Odessa has grown significantly over the past decade with the heavy commercial vehicle activity in the region. Debris can create hazardous driving conditions, impacting driver’s visibility and safety. Much of the litter in the region is caused by tires from blow outs or failure to properly secure items in the back of truck beds or commercial vehicles. TxDOT Odessa District was determined to have the most litter along roadways of all the surveyed areas throughout the state. In 2024, TxDOT Odessa District budgeted over $400,000 just for litter removal in the Permian Basin. This project proposes a regional effort to use a shared UAS fleet for hazard identification and litter mitigation.

Proposed solutions

• Regional UAS Fleet: Partnership between regional transportation stakeholder to co-own and operate a UAS fleet to collect real-time information on the transportation network and hazards
• Data Integration: Leveraging crowd-sourced Waze data on traffic incidents and roadway debris to inform response and mitigation

Expected benefits and performance measures

• Asset Management: Inventory and inspection of assets using a regional shared UAS fleet
• Improved Corridor Operations: Collecting real-time information on traffic incidents, roadway conditions, and hazards.

Scalability

• Expanded Use Cases: Once the partnership model is established, the Permian Basin region can expand use cases beyond incident management, hazard identification, and asset inspection.
• Strategic Partnerships: Rural regions that have constrained resources may replicate the shared-fleet model for equipment purchases.

Presenter: Sabas Avila, P.E., Director of Public Works, City of San Marcos

Primary Technology Areas: Data

Project Partners: Google Public Sector

Project Lead: City of San Marcos

Challenge definition and background

San Marcos, TX is located on the I- 35 corridor between Austin and San Antonio. The city is bisected by two Union Pacific Rail Lines and includes 24 at-grade railroad crossings. Nationally, more than 2,000 incidents and 200 fatalities occur each year at railroad crossings. Railroad crossings are causing 656 hours of vehicle delays per day in San Marcos and can add 6 minutes to emergency response times. Most railroad crossings lack interoperability with existing traffic management systems and real-time communication infrastructure. Small and Rural Multimodal Transportation Providers do not have the personnel or resources to develop or staff a Traffic Management Center (TMC). Basic railroad communication and interoperability improvements start at $1M. There is a need to provide low-cost, interoperable, and automated solutions to improve safety and connectivity.

Proposed solutions

• Utilize Google Cloud to automatically detect trains using common traffic cameras and YouTube feeds.
• Develop automated train detection system using traffic video and Google Cloud to provide near real-time alerts.
• Leverage IoT to develop alert system to broadcast alerts to emergency management providers, multi-modal transportation providers, and the traveling public through WAZE.

Expected benefits and performance measures

• Improve Safety: Address safety at major intersections
  • Metric: Emergency Management response times
• Enhance Connectivity: Improve connectivity to multi-modal transportation partners
  • Metrics: Views and impressions on notifications to transportation providers and public
• Increase Efficiency: Provide reliable transportation service and reduce congestion at major intersections
  • Metrics: Delay and congestion

Scalability

• Low-Cost Entry using standard traffic cameras and cloud storage.
• Infinite Applications using AI to solve problems and reduce overburdening the workforce.
• Transferable to all multi-modal transportation providers.
• Replicate public-private partnership easily from small to large communities and transportation providers.