2021

Debashis Das (debashisdas@arizona.edu), Argonne National Laboratory
Niraj Altekar, University of Arizona
Larry Head, University of Arizona
Faisal Saleem, National Operations Center of Excellence

ABSTRACT             This paper presents an emergency vehicle priority control systems based on Connected Vehicle technology, called MMITSS Priority. Traditional preemption does not consider the current traffic situation, such as the presence of a freight vehicle in the dilemma zone on an opposing movement, and can have a significant negative impact on the minor movement vehicles. A mixed-integer linear programming model is developed which can consider the priority requests from multiple emergency vehicles and dilemma zone requests from freight vehicles that could be trapped in the dilemma zone. The optimization model provides an optimal schedule that minimizes the total weighted priority request delays and dilemma zone request, as well as some flexibility to adapt to other vehicles in real time. The flexible implementation of the optimal signal timing schedule is designed to improve the mobility of the non-emergency vehicles. The approach has been tested and evaluated using microscopic traffic simulation. The simulation experiments show that the proposed priority control method is able to improve the travel time of the vehicles on the minor street while ensuring safe passage of the freight vehicle at the dilemma zone without significantly delaying the emergency vehicles. The method will be implemented in the Maricopa County SMartDRIVE ProgramSM test bed in Anthem, Arizona. Keywords: Connected Vehicle, Emergency Vehicle, Preemption, Priority, Traffic Safety, Traffic Mobility, Dilemma-Zone, Vehicle-to-Vehicle Communication, Vehicle-to-Infrastructure Communication.

Burak Cesme (bcesme@kittelson.com), Kittelson & Associates, Inc.
Peter Furth, Northeastern University
Ryan Casburn, Kittelson & Associates, Inc.
Kevin Lee, Illumine Transportation, LLC

At signalized intersections, pedestrian phases can be configured as recall or push-button actuated. While pedestrian recall results in a moderate reduction in pedestrian delay, because with recall, a pedestrian arriving during the time nominally reserved for the Walk interval will be served immediately rather than waiting to be served in the next cycle, it can also lead to longer cycle lengths, increasing delay for all users, including pedestrians. This research explores the impact of pedestrian recall along a coordinated-actuated arterial for pedestrians crossing the mainline (i.e., crossing the coordinated phase) to provide pedestrian recall versus actuation guidelines for agencies. The guidance was developed with the aim of balancing pedestrian delay with operational efficiency for vehicles. Two criteria were considered while developing the guidance: (1) pedestrian demand, and (2) vehicular green time duration for the concurrent vehicle phase that is parallel to the pedestrian crossing. VISSIM microsimulation software was utilized using a real network in Fairfax County, Virginia to model the effects of pedestrian recall and actuation. Results showed that pedestrian recall should be considered when pedestrian demand is large enough that there is a pedestrian call in most cycles (pedestrian probability in a given cycle is greater than 0.6 or pedestrian volume per cycle is greater than 0.9). The guidance also suggests setting pedestrian phases on recall when the length of the vehicular green for the concurrent phase is long enough in most cycles that a pedestrian phase would fit without constraining the signal cycle length.

Zorica Cvijovic, Trihydro Corporation
Milan Zlatkovic (mzlatkov@uwyo.edu), University of Wyoming
Aleksandar Stevanovic, University of Pittsburgh
Yu Song, University of Wyoming

Connected Vehicle (CV) technologies enable safe and interoperable wireless communication among vehicles and the infrastructure with the possibility to run many applications that can improve safety, and enhance mobility. This paper develops CV based algorithms which use transit vehicle speed and the estimated time that the vehicle needs to arrive at an intersection to trigger Transit Signal Priority (TSP) initiation. This information is updated each second based on the traffic conditions such as speed, a current distance of a transit vehicle to the intersection, and queue conditions. The algorithm uses the actual speed of a transit vehicle and its latitude/longitude (lat/lon) coordinates to compute the time that the bus needs to reach the stop line. It was tested on a real-world network using VISSIM traffic simulation, but can easily be implemented in the field since it is using word coordinates. The upgraded algorithm was applied to a future Bus Rapid Transit (BRT) scenario, and included different levels of conditional TSP, which depend on three combined conditions: the time that a transit vehicle needs to reach the stop line, the number of passengers on board, and the lateness that the transit vehicle experiences. The test-case network used for model building is a corridor consisting of ten signalized intersections along State Street in Salt Lake City, UT. The CV algorithms coupled with TSP can yield notable delay reductions for both the regular bus and the BRT of 33% and 12%, respectively.

Jiawen Wang (nightkeven@163.com), University of Shanghai for Science and Technology
Chengcheng Yang, University of Shanghai for Science and Technology
Jieshuang Dong, University of Shanghai for Science and Technology
Xizhao Zhou, University of Shanghai for Science and Technology

In most urban signalized intersections, right-turn vehicle signals do not usually control turns. In order to address the problem of signal control in a pedestrian-vehicle interaction, this paper establishes a right-turn signal optimization (RTSO) model that considers both efficiency and safety. First, the main factors influencing the behavior of vehicle and pedestrian during pedestrian-vehicle interaction are analyzed and a pedestrian-vehicle interaction (PVI) model at an urban road crosswalk is established. This model is used to determine the probabilities of four pedestrian-vehicle interaction situations. Then, based on the traffic conflict theory, we construct an objective function that minimizes the total delay of traffic participants considering pedestrian-vehicle interactions and another objective function that minimizes the potential conflicts considering pedestrian-vehicle interactions. Then, a RTSO model is obtained by introducing a safety-efficiency coefficient to combine the previously described two constructed functions. Finally, the PVI model and delay model are verified through video observation data and the establishment of a cellular automata simulation platform of pedestrian-vehicle interaction. Using these models, a field signal plan, the delay minimization scheme, conflict minimization scheme and the proposed scheme are numerically analyzed under different yielding rates. This proposed scheme is further numerically analyzed under different safety-efficiency coefficients. The results show that this paper’s RTSO model has certain advantages in increasing safety and reducing delay. In addition, using these results, this paper gives a recommended value for the safety-efficiency coefficients in different application scenarios.

Patrick Singleton, Utah State University
Mark Taylor, Utah Department of Transportation
Christopher Day, Iowa State University
Subhadipto Poddar, University of Arkansas
Sirisha Kothuri (skothuri@pdx.edu), Portland State University
Anuj Sharma, Iowa State University

The COVID-19 pandemic, the most significant public health crisis since the 1918-1919 influenza epidemic, is the first such event to occur since the development of modern transportation systems in the twentieth century. Many states across the U.S. imposed lockdowns in early spring, which reduced demand for trips of various types and impacted transportation systems. In urban areas, the shift has resulted in a reduction in traffic volumes and an increase in bicycling and walking in certain land use contexts. This paper seeks to understand the changes that have occurred at signalized intersections as a result of the lockdown and the ongoing pandemic, as well as the actions taken in response to these impacts. The results of a survey on agency reactions to COVID-19 with respect to traffic signal operations and changes in pedestrian activity during the spring lockdown using two case study examples in Utah are presented. First, the effects of placing intersections on pedestrian recall (with signage) with the goal of eliminating pedestrians from pushing the pedestrian button are examined. Next, the changes in pedestrian activity at Utah signalized intersections between the first six months of 2019 and 2020 are analyzed and the impact of land use characteristics is explored. Survey results revealed the importance of using technologies such as adaptive systems and ATSPMs to drive decisions. While pedestrian pushbuttons actuations decreased in response to the implementation of pedestrian recalls, many pedestrians continued to use the pushbutton. Pedestrian activity changes were also largely driven by surrounding land uses.

Shahadat Iqbal (miqba005@fiu.edu), New York State Department of Transportation
Taraneh Ardalan, University of Pittsburgh
Mohammed Hadi, Florida International University
Evangelos I. Kaisar, Florida Atlantic University

Transit Signal Priority (TSP) and Freight Signal Priority (FSP) allow agencies to prioritize signal service allocations considering the priority of these vehicles and potentially decrease the signal control impacts on them. However, there have been no studies to develop guidelines on implementing signal control considering both the TSP and FSP.  This paper reports on a study conducted to provide such guidelines based on a literature review, simulation study, and the utilization of a decision tree algorithm based on the simulation results.  The developed guidance provides recommendations based on the signal timing slack time, the proportion of major to minor street hourly volume, hourly truck volume per lane for the major street hourly truck volume per lane for the minor street,  the proportion of major to minor street hourly truck volume,  the proportion of major to minor street hourly bus volume, the volume to the capacity ratio for the major street, and  the volume to the capacity ratio for the minor street.  The developed guideline was validated by implementing the guideline for a case study facility. The validation result showed that the guideline works correctly for the investigated high traffic demand and low demand conditions.

Md Tausif Murshed (mmurshed2019@fau.edu), Florida Atlantic University
Md Ashraful Imran, University of Texas, Arlington
Pablo Chon Kan-Munoz, Florida Atlantic University
X. David Kan, Florida Atlantic University
Aleksandar Stevanovic, University of Pittsburgh

Congestion on multi-modal corridors can have significant impacts on the environment and travel time. And this is especially evident in many of the arterial corridors that must serve both commuting passenger cars and trucks that significantly different operating characteristics such as slower acceleration and higher fuel consumption when speeds fluctuate. Prioritizing truck traffic could help mitigate the negative impacts. This paper proposed and quantified the impact of Freight Signal Priority (FSP) on the emission and mobility of signalized intersections. The suggested approach has been evaluated using a two-mile section of San Pablo Avenue in Berkeley, California. The results show consistent improvement for fuel consumption and emissions for both 2% and 20% truck traffic, more specifically, 17% and 35% reduction, respectively. Under the typically lower traffic percentage of 2%, improvement in fuel consumption and emissions is complemented by improvements in the system-wide delay and travel time, however, as the truck percentage increases, the improvement in fuel consumption come at the expense of significantly longer system-wide delay and travel time and would not be feasible for implementation. Keywords: Freight Signal Priority (FSP), Fuel Consumption, and Emissions, Mobility.