Improving roadway safety and optimizing traffic flow

As one the 15 fastest-growing metros in the country, the City of College Station is home to Texas A&M University, making college sports a major local attraction throughout the region. The growing population and increasing pedestrian activity require the City to ensure its roadways are operating efficiently and safely. Our San Antonio team was able to assist the City with this effort by developing and implementing traffic signal timing plans for the 9 traffic signals from Agronomy Road to Texas Avenue. Initial timing plans were developed based upon roadway geometry and optimized using Automated Traffic Signal Performance Measures (ATSPM). Bluetooth Travel Time data from before construction and after implementation of the signal timing plans indicate vehicle mobility was similar in the after condition to the before condition, all while providing an exclusive phase where no vehicles were moving through the intersection and pedestrians were crossing University Drive.

We have the expertise and ability to address unpredictable traffic dynamics using adaptive solutions. By deploying adaptive traffic signal controls at 51 intersections along Bell Road, Lee Engineering was able to look at traffic continuously and adjust signal timings on the fly, as well as communicate to signals up and downstream so adjacent signals could plan strategies for approaching traffic platoons. Elements of this project included concept planning, systems engineering, a design of Technical Requirements, Concept Operations, procurement documents, and post design construction monitoring services. The project was designated as an FHWA Project of Regional Significance and ITS Arizona Project of the Year for its application of innovative technology across multiple types of signal systems and multiple agencies in a single geographic metropolitan area.

At the critical request of Albuquerque’s City Council, LEE (as a sub-consultant to Bohannon Huston) completed a VISSIM visualization for the proposed Rio Grande and Candelaria Roundabout (shown left). The model was calibrated to HCS 2010 calculations and incorporated bicycles and pedestrians. The model was enhanced with 3D visual elements including 3D buildings, fences, trees, and special vehicles. LEE created emergency vehicles and a combination pickup – horse trailer specifically to address public concerns.

Rising from an accumulation of engineering issues, including crash history in the corridor as well as school access and pedestrian problems, Lee Engineering completed a Road Safety Audit and Road Diet Assessment on NM564 in Gallup. The study area included a four-lane undivided roadway, high school, middle school, two proposed traffic signals, an existing marked mid-block crossing, and a unmarked crossing location. LEE completed the initial data collection, a site visit with the project team, and the traffic analysis for the corridor. Using the RSA procedures, LEE assembled the stakeholders and flushed out issues. Using our in-house video data collection devices, LEE analyzed the traffic and pedestrian operations along the corridor, where over 170 students were counted during a peak-hour. LEE confirmed the proposed locations of the signals, provided guidance on the road diet, and a recommended a set of improvements to ensure safe routes to school.

This project had two tasks — (1) Signal coordination and timing for 157 signalized intersections on 19 major corridors in Albuquerque to improve traffic progression and reduce delay, including traffic data collection, signal timing plans, travel. This task included time runs, and timing plan implementation. (2) A GIS inventory of all City of Albuquerque traffic signals and communications infrastructure. Each conduit, pull box, vault, pole, DMS, CCTV camera, and all cabinets were GPS located and geo-located in ESRI ArcPad and ArcView. The total inventory includes 600 traffic signals, 113 school beacons, and 120 miles of communications cable. Building on the inventory, Lee Engineering supplemented the data with OSP Insight, a fiber optic and copper networking inventory software, and connection management system.

This project resulted in directly reducing One Call tickets sent to the city resulting in hundreds of thousands of dollars in savings for the municipality.

Lee Engineering has provided traffic signal timing services to the Texas Department of Transportation as part of multiple Traffic Engineering on-call contracts.  Lee Engineering has developed optimized signal timing for linear arterials ranging in size from three to 16 signals.  Timing plans were developed for multiple diamond interchanges as part of these projects.  Lee Engineering utilizes traffic signal timing tools such as Synchro, Passer, Tru-Traffic, and PC-Travel to conduct timing studies, develop optimized coordinated timings, and evaluate the improvements gained through our optimization efforts.  Lee Engineering has provided timing plans for over 155 TxDOT intersections in four TxDOT Districts (Dallas, Fort Worth, El Paso, and Yoakum).  Lee Engineering staff assisted TxDOT staff with field implementation and fine tuning for the majority of the intersections.

This project consisted of providing a coordinated signal system along Lincoln Boulevard from NE 4th Street to NE 50th Street in Oklahoma City, OK.  This heavily traveled four-mile corridor is a premier backbone of Oklahoma City, as it provides access to the State Capitol, Government Offices, and the state’s largest and most comprehensive hospital and medical institution, the OU Medical and Health Sciences Center Campus. Engineering services included preparing time of day plans, Synchro models, splits, offsets, and time-space diagrams. Field reconnaissance, fine tuning, and troubleshooting of the corridor was also performed.

Lee Engineering performed a complicated VISSIM modeling analysis of the 27th Avenue/Grand/Thomas and 35th Avenue/Grand/Indian School intersections for the City of Phoenix Street Transportation Department.  The purpose of the highway-rail grade crossing improvement analysis is to model select rail preemption solutions for the intersections and document the estimated impacts to the traffic system. This analysis considered the requirements of the BNSF railroad crossing detection and operations, motor vehicles and pedestrians, and was under the scrutiny of the Arizona Corporation Commission and the Regional FRA Office. Synchro and VISSIM traffic simulation models were used to evaluate various alternatives including a queue cutter (Red/Yellow/ Green), a flashing queue-cutter, and a crossing “median and gate” alternative.  Finally, LEE provided planning level cost estimates for each of the alternatives presented.  A follow-up study was also performed to investigate the preferred traffic control options and signal control parameters at both intersections as well as synchronization with nearby intersections.

Lee Engineering conducted a research study for the City of Mesa to perform a field performance evaluation of the real time adaptive signal system the city installed in Spring 2011. This project evaluated the performance of the pending Sydney Coordinated Adaptive Traffic System (SCATS) in the area surrounding the Superstition Springs shopping center mall (19 intersections) versus the performance of the existing time of day plans and coordination. The project required data collection (volumes, delay, and travel times) on three corridors, approximately three miles each, for the high-volume season to measure effectiveness and benefits of improvements of the two signal timing systems.  Travel time was collected in two ways for this study—1) using an in-vehicle Global Positioning System (GPS) receiver with interpretive software, and 2) field-installed devices to compare/ match time-stamps of broadcasted anonymous wireless addresses from passing Bluetooth™ devices (e.g., an enabled cell phone within a vehicle).  For this study, all devices were deployed in signal cabinets spaced a mile apart or less.  Ten devices positioned at various signal locations along the three project corridors identified 52,732 Bluetooth™ signals for the entire two weeks (eight study days) of data collection.