Integrated Traffic Signal Control Along Corridors With Multiple Intersections Near Highway-Rail Grade Crossings

2013 ◽  
Author(s):  
Yifeng Chen ◽  
Laurence R. Rilett
Keyword(s):  
Traffic Control ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Railway Track ◽  
Test Bed ◽  
Control Logic ◽  
Grade Crossings ◽  
The Impact ◽  
Multiple Intersections ◽  
Near Highway

Traffic signal optimization for traffic signals located near highway-rail grade crossings (HRGC) can be difficult because of the complex nature of the interactions between the two systems and the necessity of considering multiple objectives, such as safety and operational efficiency. The problems are magnified when considering traffic control for corridors that have multiple intersections located near HRGCs. This paper develops a methodology for optimizing traffic signals along a highway-railway corridor while considering the dual objectives of maximizing safety and efficiency. The Highway 6 (Cornhusker Hwy) corridor in Lincoln, Nebraska was used as a test bed. The corridor was modeled in VISSIM, and was used to emulate the traffic control along Highway 6, including the preemption logic. The traffic control logic was modeled using the Vehicle Actuated Programming (VAP) in the VISSIM simulation model. In addition, the logic allows multiple train events on the railway track that runs parallel to Highway 6 to be modeled. The model was calibrated to local traffic conditions using empirical field data. The impact of train frequency, length, direction, speed, etc., on the performance of the network and pedestrian safety will be evaluated.

scholarly journals Quantifying the impact of non-stationarity in reinforcement learning-based traffic signal control

2021 ◽  
Vol 7 ◽  
pp. e575
Author(s):  
Lucas N. Alegre ◽  
Ana L.C. Bazzan ◽  
Bruno C. da Silva
Keyword(s):  
Reinforcement Learning ◽  
Traffic Control ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Traffic Signal Control ◽  
Traffic Patterns ◽  
Learning Agent ◽  
Traffic Optimization ◽  
The Impact ◽  
Different Sources

In reinforcement learning (RL), dealing with non-stationarity is a challenging issue. However, some domains such as traffic optimization are inherently non-stationary. Causes for and effects of this are manifold. In particular, when dealing with traffic signal controls, addressing non-stationarity is key since traffic conditions change over time and as a function of traffic control decisions taken in other parts of a network. In this paper we analyze the effects that different sources of non-stationarity have in a network of traffic signals, in which each signal is modeled as a learning agent. More precisely, we study both the effects of changing the context in which an agent learns (e.g., a change in flow rates experienced by it), as well as the effects of reducing agent observability of the true environment state. Partial observability may cause distinct states (in which distinct actions are optimal) to be seen as the same by the traffic signal agents. This, in turn, may lead to sub-optimal performance. We show that the lack of suitable sensors to provide a representative observation of the real state seems to affect the performance more drastically than the changes to the underlying traffic patterns.

Preliminary Analysis of Light Rail Crashes in Denver, Colorado

2012 ◽  
Vol 2275 (1) ◽  
pp. 12-21 ◽  
Author(s):  
Pamela M. Fischhaber ◽  
Bruce N. Janson
Keyword(s):  
Traffic Control ◽  
Preliminary Analysis ◽  
Prediction Models ◽  
Hazard Index ◽  
Traffic Signals ◽  
Control Device ◽  
Light Rail ◽  
Crash Prediction ◽  
Grade Crossing ◽  
Grade Crossings

This paper presents a preliminary analysis of light rail crashes at at-grade crossings in Denver, Colorado, based on Regional Transportation District data for 1999 through 2009. Differences in design and operation of at-grade crossings are discussed for light rail versus common carrier railroad (railroad). The differences appear to warrant the development of separate crash prediction and hazard index models because models developed for railroad at-grade crossing operations may not accurately predict the number and severity of crashes at light rail at-grade crossings. In addition, the models developed for railroads do not predict crashes at crossings for some traffic control device types such as traffic signals. The lack of information for crossings controlled by traffic signals in the railroad crash prediction equations is one reason why equations specific to light rail may need to be developed. This study identifies patterns in light rail crossing crash data that warrant further investigation and support the development of crash prediction models and hazard index equations specific to light rail at-grade crossing configurations and operations.

Advanced Prediction of Train Arrival and Crossing Times at Highway-Railroad Grade Crossings

2000 ◽  
Vol 1708 (1) ◽  
pp. 68-76 ◽  
Author(s):  
R. Matthew Estes ◽  
Laurence R. Rilett
Keyword(s):  
Traffic Control ◽  
Intelligent Transportation System ◽  
Motor Vehicles ◽  
Practical Reasons ◽  
Test Bed ◽  
Potential Applications ◽  
Grade Crossings ◽  
The Right ◽  
Traffic Operation ◽  
Warning Time

There are many issues related to highway–railroad grade crossings. For historic and practical reasons, trains have the right-of-way at grade crossings, which results in delays to motorists. In addition, the differential in size, speed, and stopping ability between motor vehicles and trains raises many serious safety concerns. Historically, the methods used to address these delay and safety problems at grade crossings have been reactive in nature. For example, the Manual on Uniform Traffic Control Devices specifies a minimum of 20 s of warning time for active warning devices at grade crossings. Intelligent transportation system (ITS) technology offers potential solutions for increasing the warning time at grade crossings. Advanced on-board devices and off-track detection equipment can allow train position and speed to be monitored. This information can be shared through wireless and wireline telecommunications equipment being deployed for ITS. Transportation management center personnel can then predict the arrival and crossing times of trains at grade crossings. It is hypothesized that if the warning time could reliably be increased, the traffic-operation strategies in the vicinity of grade crossings could be more proactive, reducing delay to motorists and increasing safety for both trains and automobiles. The research focuses on a second-generation technology approach to an advanced prediction of train arrival and crossing (gate-up and gate-down) times at highway–railroad grade crossings, including problems faced at grade crossings, background on detection and prediction technology for grade crossings, the train monitoring system used as the test bed for the research, the development of the methodology, the results of the analysis, and the conclusions of the research and potential applications for the model.

Developing Signal Warrants for Restricted Crossing U-Turn Intersections

2021 ◽  
pp. 036119812110469
Author(s):  
Justice Appiah
Keyword(s):  
Traffic Control ◽  
Simulation Analysis ◽  
Traffic Signals ◽  
Traffic Volume ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Left Turn ◽  
Minor Road ◽  
Intersection Configuration

The restricted crossing U-turn (RCUT) intersection is a form of innovative intersection design that reroutes left-turn and through traffic from the minor road to U-turn crossovers on the major road. When implemented correctly, an RCUT intersection can provide significant safety and operational benefits over the conventional intersection configuration. The RCUT may be controlled by traffic signals, STOP control, merges and diverges, or a combination of these. There is currently no concrete guidance in relation to when the use of traffic signal control is warranted at an RCUT intersection. This study investigated traffic volume conditions that may warrant consideration of traffic signal control at an RCUT intersection. Simulation experiments including two geometric configurations and three traffic control schemes were designed and run in VISSIM to evaluate the effects of traffic conditions on intersection delay and queue lengths. Traffic was varied by changing the composition, approach volumes, and origin–destination flow patterns to reflect different conditions that may occur at the intersection on any given day. For the range of conditions studied, the results of the simulation analysis suggested that the RCUT intersection may operate better with traffic signals (at all junctions) when the minor roadway traffic volume is more than 450 vehicles per hour (vph) and the major roadway has two through lanes. The corresponding minor roadway volume threshold increases to 575 vph when the major roadway has four through lanes.

scholarly journals Smart Accident Detection and Switching of Traffic Signal

2019 ◽  
Vol 9 (2) ◽  
pp. 1142-1145
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Rf Receiver ◽  
Mems Sensor ◽  
Traffic Control System ◽  
Traffic Management System ◽  
Smart Traffic ◽  
Accident Detection

An accident is one of the major causes of unnatural and untimely death. This is one of the serious issues throughout the world. Most of the accidents occur due to vehicle factors, improper traffic management, and lack of timely help. With the increase in the number of vehicles, it may be little hard to keep away from such accidents on road. The main objective is to implement the new advancements in saving human lives by detecting the occurrence of the accident in a vehicle and by directing the ambulance to the accident location without time delay. Also by implementing smart traffic control system, the ambulance moves to medical centre in an effective way without any stall in the traffic signals. Automation of accident detection is implemented by sensor-based ambulance management with the smart traffic management system. It consists of Crash sensor and MEMS sensor for detecting the accident in the vehicle and RF transmitter on the ambulance to communicate with the RF Receiver located on the traffic signal. This helps the ambulance to cross the junction switching the signals from Red to Green when the signal is received by the ambulance.

The Influence of Traffic Signal Solutions on Self-Reported Road-Crossing Behavior

2014 ◽  
Vol 17 ◽  
Author(s):  
Leandro L. Di Stasi ◽  
Alberto Megías ◽  
Antonio Cándido ◽  
Antonio Maldonado ◽  
Andrés Catena
Keyword(s):  
Modern Society ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Motor Vehicles ◽  
Signal Design ◽  
Traffic Light ◽  
Modern Cities ◽  
The Impact ◽  
Road Crossing

AbstractInjury to pedestrians is a major safety hazard in many countries. Since the beginning of the last century, modern cities have been designed around the use of motor vehicles despite the unfavourable interactions between the vehicles and pedestrians. This push towards urbanization resulted in a substantial number of crashes and fatalities involving pedestrians every day, all over the world. Thus, improving the design of urban cities and townships is a pressing issue for modern society. The study presented here provides a characterization of pedestrian safety problems, with the emphasis on signalized crosswalks (i.e. traffic signal) design solutions. We tested the impact of seven different traffic light configurations (steady [green, yellow, and red], flashing [green, yellow, and red], and light off) on pedestrian self-reported road-crossing behavior, using a 11-point scale -ranging from 0 (“I never cross in this situation”) to 10 (“I always cross in this situation”). Results showed that mandatory solutions (steady green vs. steady red) are the best solutions to avoid unsafe pedestrian behaviors while crossing controlled intersections (frequency of crossing: Mgreen = 9.4 ± 1 vs. Mred = 2.6 ± 2). These findings offer important guidelines for the design of future traffic signals for encouraging a pedestrian/transit-friendly environment.

Effect of Distance between Ramp and Upstream Signal on Ramp Meter Operation

2020 ◽  
Vol 02 (02) ◽  
pp. 43-49
Author(s):  
Khaled Shaaban ◽  
Muhammad Asif Khan ◽  
Ridha Hamila
Keyword(s):  
Traffic Signal ◽  
Ramp Metering ◽  
Control Logic ◽  
Freeway Traffic ◽  
Signal Coordination ◽  
The Impact ◽  
Ramp Control

Ramp metering is typically proposed as a responsive strategy that takes freeway traffic parameters as control inputs to the ramp control logic. Such a strategy can be implemented in two ways; isolated ramp control or coordinated ramp control. Coordinated ramp control typically involves the cooperation between several ramp meters connected to a freeway segment to manage traffic on the freeway and traffic all ramps. Few studies also proposed the coordination between the on-ramp and the upstream traffic signal. Such coordination can help to mitigate congestion on the freeway and to avoid queue formation at the on-ramp. In this study, the authors' previous work on ramp metering and upstream signal coordination was extended to further evaluate the performance of such schemes by considering the impact of the distance between the upstream traffic signal and freeway. Extensive simulations in SUMO were performed to evaluate the benefit of the proposed coordinated strategy and the impact of ramp distance on the effectiveness of such coordination.

scholarly journals Floating Car Data Adaptive Traffic Signals: A Description of the First Real-Time Experiment with “Connected” Vehicles

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 114 ◽  
Author(s):  
Vittorio Astarita ◽  
Vincenzo Giofré ◽  
Demetrio Festa ◽  
Giuseppe Guido ◽  
Alessandro Vitale
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Connected Vehicles ◽  
Test Bed ◽  
Floating Car Data ◽  
Better Regulation

The future of traffic management will be based on “connected” and “autonomous” vehicles. With connected vehicles it is possible to gather real-time information. The main potential application of this information is in real-time adaptive traffic signal control. Despite the feasibility of using Floating Car Data (FCD), for signal control, there have been practically no real experiments with all “connected” vehicles to regulate traffic signals in real-time. Most of the research in this field has been carried out with simulations. The purpose of this study is to present a dedicated system that was implemented in the first experiment of an FCD-based adaptive traffic signal. For the first time in the history of traffic management, a traffic signal has been regulated in real time with real “connected” vehicles. This paper describes the entire path of software and system development that has allowed us to make the steps from just simulation test to a real on-field implementation. Results of the experiments carried out with the presented system prove the feasibility of FCD adaptive traffic signals with commonly-used technologies and also establishes a test-bed that may help others to develop better regulation algorithms for these kinds of new “connected” intersections.

Evaluation of Multiple Hardware and Software in the Loop Signal Controllers in Simulation Environment

2018 ◽  
Vol 2672 (18) ◽  
pp. 93-106
Author(s):  
Sharmin-E-Shams Chowdhury ◽  
Aleksandar Stevanovic ◽  
Nikola Mitrovic
Keyword(s):  
Traffic Control ◽  
Control Strategies ◽  
Traffic Signal ◽  
Signal Timing ◽  
Hardware In The Loop ◽  
Microscopic Simulation ◽  
The Impact ◽  
Signal Operations ◽  
Traffic Signal Operations

This study evaluates two groups of methods to model traffic signal operations in microscopic simulation: hardware-in-the-loop simulation (HILS) and software-in-the-loop simulation (SILS). These methods have become standards for accurate modeling of traffic signal operations, but in spite of the large number of available options there are no studies that have conducted relevant comparative evaluations. This study bridges this gap by investigating signal timing and operational differences of these two methods in basic actuated operations of a single signalized intersection. The emphasis is given to broad examination of various platforms as opposed to more complex experiments done with individual platforms. A representative number of 65-minute simulation runs was executed for each experimental scenario. The results showed that differences between various HILS and SILS platforms are large enough that one cannot confidently switch between the platforms without affecting the final outcomes. The study confirmed previous findings about the impact of the initialization process on the simulation results, but the initialization itself does not seem to be the major source of discrepancy. Further investigation is needed to reveal role of consistency of internal NEMA-based controller logics among various controllers. These findings put a considerable dilemma/restriction on how various HILS and SILS platforms, either alone or in conjunction with other higher forms of traffic control strategies, can be used in joint fashion.

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