scholarly journals Multi-Level Conditional Transit Signal Priority in Connected Vehicle Environments

2021 ◽  
Vol 67 (2) ◽  
pp. 1-12
Author(s):  
Zorica Cvijovic ◽  
Milan Zlatkovic ◽  
Aleksandar Stevanovic ◽  
Yu Song
Keyword(s):  
Salt Lake ◽  
Salt Lake City ◽  
Test Case ◽  
Connected Vehicle ◽  
Transit Signal Priority ◽  
Traffic Operations ◽  
Multi Level ◽  
Lake City ◽  
State Street ◽  
Share Information

Connected Vehicles (CV) are an emerging technology with a large potential to improve traffic operations and safety. This paper develops and tests advanced CV-based multi-level conditional Transit Signal Priority (TSP). The algorithms are using the latitude/longitude (lat/lon) coordinates of CV vehicles and intersections to establish communication, share information and request priority. The TSP strategies are implemented through controllers’ built-in features and logic processor, using Econolite ASC/3 as a representative traffic signal controller. The tests were performed in VISSIM microsimulation with the ASC/3 Software-in-the-Loop (SIL) controller emulator. State Street in Salt Lake City, UT, is selected as a test-case corridor. The paper shows that the developed signal control priority (SCP) algorithms are successful in reducing delays for target vehicles in excess of 6%, without significant impacts on other traffic. The information obtained from CV vehicles can be used to further enhance control algorithms and create adaptive SCP programs.

Conditional Transit Signal Priority for Connected Transit Vehicles

2021 ◽  
pp. 036119812110444
Author(s):  
Zorica Cvijovic ◽  
Milan Zlatkovic ◽  
Aleksandar Stevanovic ◽  
Yu Song
Keyword(s):  
Model Building ◽  
Salt Lake ◽  
Salt Lake City ◽  
Test Case ◽  
Vehicle Speed ◽  
Connected Vehicle ◽  
Transit Signal Priority ◽  
Lake City ◽  
State Street ◽  
Stop Line

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 vehicle 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 world 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.

Field Evaluation of Connected Vehicle-Based Transit Signal Priority Control under Two Different Signal Plans

2020 ◽  
Vol 2674 (7) ◽  
pp. 172-180
Author(s):  
Qinzheng Wang ◽  
Xianfeng (Terry) Yang ◽  
Blaine D. Leonard ◽  
Jamie Mackey
Keyword(s):  
Travel Time ◽  
Salt Lake ◽  
Salt Lake City ◽  
Field Evaluation ◽  
Connected Vehicle ◽  
Transit Signal Priority ◽  
Running Time ◽  
Lake City ◽  
Transit Operation ◽  
Bus Travel Time

In 2017, a connected vehicle (CV) corridor utilizing dedicated short-range communication (DSRC) technology was built along Redwood Road, Salt Lake City, Utah. One main goal of this CV corridor is to implement transit signal priority (TSP) when the bus is behind its published schedule by a certain threshold. With the data generated by the transit vehicles, transmitted through the DSRC system, logged by traffic signal controller, and coupled with the Utah Transit Authority (UTA) data from transit operation system, some performance data of the TSP can be analyzed including TSP requested, TSP served, bus reliability, bus travel time, and bus running time. For providing better signal coordination to buses, the signal plan for this CV corridor underwent retiming in October 2018. This research aims to compare the TSP performance before and after the signal retiming. The field data of August, September, November, and December in 2018 were selected to perform this evaluation. Results show that the TSP served rate after signal retiming is 35.29%, which is higher than that of 33.12% before signal retiming. In addition, compared with the signal plan before October, bus reliability northbound and southbound on the CV corridor was improved by 2.4% and 1.47%, respectively; bus travel time and bus running time were reduced as well.

Demonstrating Transit Schedule Benefits with a Dedicated Short-Range Communication-Based Connected Vehicle System

2019 ◽  
Vol 2673 (12) ◽  
pp. 215-224
Author(s):  
Blaine D. Leonard ◽  
Jamie Mackey ◽  
Michael Sheffield ◽  
David Bassett ◽  
Shawn Larson ◽  
...  
Keyword(s):  
Short Range ◽  
Salt Lake ◽  
Salt Lake City ◽  
Traffic Signals ◽  
Time Of Day ◽  
Data Sets ◽  
Connected Vehicle ◽  
Dedicated Short Range Communication ◽  
Vehicle System ◽  
Lake City

A vehicle-to-infrastructure (V2I) connected vehicle system was installed along Redwood Road in Salt Lake City, Utah, United States, in November 2017 using dedicated short-range communication (DSRC) radios to connect transit buses to traffic signals. One of the goals of this system was to improve the schedule reliability of the bus by providing signal priority at traffic signals when the bus is behind its published schedule by a certain threshold. Data for the analysis were obtained from the DSRC communications, the Automated Traffic Signal Performance Measures (ATSPM) system, and the transit operations system. The robust data available from these three systems allow for detailed analysis of priority requests made, requests served, and bus on-time performance in a way that is not possible without these data sets. By comparing actual schedules of the four DSRC-equipped buses over a 4-month period from April to July 2018 with buses which do not have the ability to request signal priority, it has been determined that the equipped buses meet their published schedule about 2% to 6% more frequently, depending on direction and time of day, with the most significant improvement of 6% in the southbound PM peak.

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