Dusan Jolovic

New Mexico State University, Civil Engineering, Graduate Student

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I have graduated with BA from University of Belgrade in 2009. My undergraduate studies are closely related to the traffic and transportation engineering. In August 2010 I started my Master studies at Florida Atlantic University. I worked on the projects related to the traffic signal optimization, transportation safety evaluations, freeway assessments and traffic management centers.
After I graduated in May 2012, I was working as Engineering Assistant at Florida Atlantic University. My duties were to schedule meetings, write quarterly and draft reports, manage the transportation lab and work with undergraduate students.
Since 2013 I am working on my PhD degree at New Mexico State University. I have duties as Teaching and Research assistant. I am also the Secretary of Civil Engineering Graduate Student Association, where I am involved in community service and volunteering work for the city and the University.
Since 2014, I am married and I live with my wife in Las Cruces. We like to travel, go hiking to Organ mountains and go camping.
Supervisors: Peter T Martin

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Ambulance Cross-Border Operations Along the U.S.-Mexico Border: Current Practices in the El Paso-Ciudad Juarez Region

Journal of Transport & Health

Assessment of the Robustness of Signal Timing Plans in an Arterial Corridor Through Seasonal Variation of Traffic Flows

Arterial traffic signal systems, predominantly in the United States, deploy multiple signal timin... more Arterial traffic signal systems, predominantly in the United States, deploy multiple signal timing plans to account for daily variability of traffic demand. Those types of traffic flow deviations should be anticipated when timing plans are designed and, therefore, serviced satisfactorily. When traffic flow patterns are no longer predictable, a predetermined time-of-day (TOD) plan may no longer be the optimal one. This research aimed to examine signal timing optimality by applying a method similar to the selection of a traffic responsive plan to recognize automatically the best timing plan suited to current traffic conditions. The proposed method attempted to determine whether the optimality of signal timing settings could have been effectively estimated when systematic detector counts of the major approach were available. The study used 4 months of data from field microwave detectors coupled with data of turning-movement counts obtained over several days. The findings show that TOD signal timing plans mainly depended on adequate data collection that best describes a specific set of traffic conditions. Thus, the designed plan was as optimal as the related traffic information was reliable, whereas a problem arose in the case of limited-availability and low-quality data. New technologies are capable of collecting and storing massive amounts of data. Even if the granularity of collected data is low, the data can be used to improve traffic performance (i.e., reduce corridor delay). This realization could be of particular importance to traffic agencies that have installed, or plan to install, new field devices. Most urban traffic signal systems in the United States deploy multiple signal timing plans to account for within-day variability of traffic demand (i.e., morning peak, midday, evening peak, off peak, and nighttime). Signal groups forming a zone or section usually operate in a coordinated manner along an urban arterial. This coordination essentially means that signal timing plans change at the same time for all signals in a given group (zone, section etc.) to facilitate vehicle progression throughout a series of signals (1). Any type of unusual circumstances, such as incidents, construction, or severe weather, causes a significant change in anticipated traffic conditions. Traffic flow patterns are no longer predictable a priori, and a predetermined time-of-day (TOD) plan may substantially underperform under these conditions. In contrast, day-today and diurnal variations in traffic volumes and patterns are typically considered to be served in a satisfactory manner by the developed plans, because these deviations should be anticipated when the plans are originally designed. Traffic responsive plan selection (TRPS) and adaptive traffic control systems designed and deployed over the past several decades were intended to provide quicker response to constantly varying traffic conditions (2). A recent application included development of a real-time weather-responsive signal control (3). These advances attempted to incorporate more robustness into designed signal timing plans. Common existing engineering practice tends to rely on limited observations of relevant traffic patterns and volumes by considering a small data set only over several weekdays. Traffic signal settings (e.g., cycle length, splits, and offsets) are fixed within each TOD period, but traffic demands may still fluctuate significantly. Examining historical volume variations in daily traffic and corresponding responsiveness of the traffic control system can assist traffic engineers in assessing deficiencies in the state of the current traffic system. Well-designed signal control settings reduce delay and unnecessary stops at intersections and thus improve traffic flow without roadway widening. Hence, a key priority for transportation agencies is to ensure demand-suitable traffic signal timings. Yet, despite readily available detector counts, many do not regularly collect, review, or assess the quality of the traffic information they use when signal timings are designed and updated. This study attempts to demonstrate the benefit of using a large set of directional sensor data to estimate day-today variations in demand and proposing a straightforward method to evaluate current performance of TOD signal plans. The proposed approach estimates how the system would perform if it deployed an adaptive-TRPS signal control logic and whether the difference in performance warrants system retiming or upgrade. The practicality of this method is reflected in reducing the time and effort required by the existing signal design-retiming practice. Therefore, the purpose of this research is to devise a methodology to assess the extent to which existing timing plans along an arterial corridor are serving observed demands in a manner that is close to optimal and thereby to provide an upper bound on the potential

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