Times of Bicycle Crossings

2005 ◽  
Vol 1939 (1) ◽  
pp. 22-27 ◽  
Author(s):  
Daniel I. Rubins ◽  
Susan Handy
Keyword(s):  
Traffic Signals ◽  
Signalized Intersections ◽  
Signal Timing ◽  
Signal Design ◽  
Efficient Design ◽  
Current State ◽  
Crossing Time ◽  
Traffic Volumes ◽  
Traffic Signal Timing ◽  
The University

The current state of the practice for traffic signal timing does not account for bicyclists in determining the minimum green times or clearance intervals. Like pedestrians, bicyclists need sufficient time to cross an intersection safely. However, this need must be balanced against possible delays for motorist traffic. Accurate estimates of crossing times for bicyclists are thus essential to the safe and efficient design of traffic signals. This paper presents data on bicycle crossing times for different crossing distances near the campus of the University of California at Davis and provides a methodology for measuring bicycle crossing times that other researchers can use. The crossing time and speed data collected for this project can be used to develop guidelines, in conjunction with AASHTO equations, for estimation of minimum green times and clearance intervals as a function of crossing distance. Ten signalized intersections with various motorist and bicycle traffic volumes were videotaped for a total of approximately 11 h. The observed crossing times and calculated speeds for standing, rolling, and quasi-rolling starts are presented. The importance of the physical design of intersections is briefly discussed. Important findings are that the crossing times vary widely for each crossing distance and that the 2nd and 15th percentile speeds are considerably slower than the speeds suggested by AASHTO. These slower speeds may suggest that longer crossing times should be used in signal design to ensure that 98%, or even 85%, of bicyclists will be able to clear an intersection safely.

Operational Effects of the Consolidated Intersection Design on Urban and Suburban Arterials

2018 ◽  
Vol 2672 (17) ◽  
pp. 96-107
Author(s):  
Daniel J. Cook
Keyword(s):  
Travel Time ◽  
Signalized Intersections ◽  
Signal Timing ◽  
Left Turn ◽  
Vehicle Delay ◽  
Cycle Lengths ◽  
Expected Benefits ◽  
Traffic Signal Timing ◽  
Critical Phases ◽  
Pedestrian Crossing

Along urban and suburban arterials, closely-spaced signalized intersections are commonly used to provide access to adjacent commercial developments. Often, these signalized intersections are designed to provide full access to developments on both sides of the arterial and permit through, left-turn, and right-turn movements from every intersection approach. Traffic signal timing is optimized to reduce vehicle delay or provide progression to vehicles on the arterial, or both. However, meeting both of these criteria can be cumbersome, if not impossible, under high-demand situations. This research proposes a new design that consolidates common movements at three consecutive signalized intersections into strategic fixed locations along the arterial. The consolidation of common movements allows the intersections to cycle between only two critical phases, which, in turn, promotes shorter cycle lengths, lower delay, and better progression. This research tested the consolidated intersection concept by modeling a real-world site in microsimulation software and obtaining values for delay and travel time for multiple vehicle paths along the corridor and adjacent commercial developments in both existing and proposed conditions. With the exception of unsignalized right turns at the periphery of the study area, all non-displaced routes showed a reduction in travel time and delay. Additional research is needed to understand how additional travel through the commercial developments adjacent to the arterial may effect travel time and delay. Other expected benefits of the proposed design include a major reduction in conflict points, shorter pedestrian crossing and wait times, and the opportunity to provide pedestrian refuge areas in the median.

scholarly journals Multi-Agent Reinforcement Learning for Optimizing Traffic Signal Timing

2021 ◽  
Author(s):  
Areej Salaymeh ◽  
Loren Schwiebert ◽  
Stephen Remias
Keyword(s):  
Reinforcement Learning ◽  
Traffic Signals ◽  
Transportation Systems ◽  
Traffic Signal ◽  
Urban Traffic ◽  
Signal Timing ◽  
Model Free ◽  
Proposed Model ◽  
Multi Agent ◽  
Traffic Signal Timing

Designing efficient transportation systems is crucial to save time and money for drivers and for the economy as whole. One of the most important components of traffic systems are traffic signals. Currently, most traffic signal systems are configured using fixed timing plans, which are based on limited vehicle count data. Past research has introduced and designed intelligent traffic signals; however, machine learning and deep learning have only recently been used in systems that aim to optimize the timing of traffic signals in order to reduce travel time. A very promising field in Artificial Intelligence is Reinforcement Learning. Reinforcement learning (RL) is a data driven method that has shown promising results in optimizing traffic signal timing plans to reduce traffic congestion. However, model-based and centralized methods are impractical here due to the high dimensional state-action space in complex urban traffic network. In this paper, a model-free approach is used to optimize signal timing for complicated multiple four-phase signalized intersections. We propose a multi-agent deep reinforcement learning framework that aims to optimize traffic flow using data within traffic signal intersections and data coming from other intersections in a Multi-Agent Environment in what is called Multi-Agent Reinforcement Learning (MARL). The proposed model consists of state-of-art techniques such as Double Deep Q-Network and Hindsight Experience Replay (HER). This research uses HER to allow our framework to quickly learn on sparse reward settings. We tested and evaluated our proposed model via a Simulation of Urban MObility simulation (SUMO). Our results show that the proposed method is effective in reducing congestion in both peak and off-peak times.

Validation of Generalized Delay Model for Vehicle-Actuated Traffic Signals

1997 ◽  
Vol 1572 (1) ◽  
pp. 105-111 ◽  
Author(s):  
Nagui M. Rouphail ◽  
Mohammad Anwar ◽  
Daniel B. Fambro ◽  
Paul Sloup ◽  
Cesar E. Perez
Keyword(s):  
North Carolina ◽  
Field Data ◽  
Traffic Signals ◽  
Signalized Intersections ◽  
Delay Model ◽  
Highway Capacity ◽  
Generalized Model ◽  
Highway Capacity Manual ◽  
Traffic Volumes ◽  
Isolated Intersection

One limitation of the Highway Capacity Manual (HCM) model for estimating delay at signalized intersections is its inadequate treatment of vehicle-actuated traffic signals. For example, the current delay model uses a single adjustment for all types of actuated control and is not sensitive to changes in actuated controller settings. The objective in this paper was to use TRAF-NETSIM and field data to evaluate a generalized delay model developed to overcome some of these deficiencies. NETSIM was used to estimate delay at an isolated intersection under actuated control, and the delay values obtained from NETSIM were then compared with those estimated by the generalized delay model. In addition, field data were collected from sites in North Carolina, and delays observed in the field were compared with those estimated by the generalized delay model. The delays estimated by the generalized model were comparable with the delays estimated by NETSIM. The data compared favorably for degrees of saturation of less than 0.8. However, at higher degrees of saturation, the generalized model produced delays that were higher than NETSIM’s. Some possible explanations for this discrepancy are discussed. The delays estimated by the generalized model were comparable with delays observed in the field. Researchers have concluded that the generalized delay model is sensitive to changes in traffic volumes and vehicle-actuated controller settings and that the generalized delay model is much improved over the current HCM model in estimating delay at vehicle-actuated traffic signals.

Scramble and Crosswalk Signal Timing

1998 ◽  
Vol 1636 (1) ◽  
pp. 83-87 ◽  
Author(s):  
Mark R. Virkler
Keyword(s):  
Field Study ◽  
High Volume ◽  
Signalized Intersections ◽  
Signal Timing ◽  
Pedestrian Flow ◽  
Crossing Time ◽  
Time Required ◽  
Pedestrian Crossing

A variety of methods have been developed for determining appropriate pedestrian crossing times at signalized intersections. Although many of these methods have useful applications, all have significant shortcomings when estimating the crossing time required under high-volume conditions and with two-way flow within a crosswalk. Existing methods are described. A field study conducted to address these shortcomings is then described. The results of the study are used to develop relationships to describe pedestrian flow at signalized crossings. Recommendations are then made to improve the signal timing parameters used for higher-volume pedestrian flows.

Safety-Based Left-Turn Phasing Decisions for Signalized Intersections

2017 ◽  
Vol 2619 (1) ◽  
pp. 13-19 ◽  
Author(s):  
Kiriakos Amiridis ◽  
Nikiforos Stamatiadis ◽  
Adam Kirk
Keyword(s):  
Urban Areas ◽  
Primary Objective ◽  
Signalized Intersections ◽  
Safety Performance ◽  
Signal Timing ◽  
Left Turn ◽  
Crash Data ◽  
Intersection Safety ◽  
Traffic Volumes

The efficient and safe movement of traffic at signalized intersections is the primary objective of any signal-phasing and signal-timing plan. Accommodation of left turns is more critical because of the higher need for balancing operations and safety. The objective of this study was to develop models to estimate the safety effects of the use of left-turn phasing schemes. The models were based on data from 200 intersections in urban areas in Kentucky. For each intersection, approaches with a left-turn lane were isolated and considered with their opposing through approach to examine the left-turn–related crashes. This combination of movements was considered to be one of the most dangerous in intersection safety. Hourly traffic volumes and crash data were used in the modeling approach, along with the geometry of the intersection. The models allowed for the determination of the most effective type of left-turn signalization that was based on the specific characteristics of an intersection approach. The accompanying nomographs provide an improvement over existing methods and warrants and allow for a systematic and quick evaluation of the left-turn phase to be selected. The models used the most common variables that were already known during the design phase, and they could be used to determine whether a permitted or protected-only phase would suit the intersection when safety performance was considered.

scholarly journals Integrating Data Mining and Microsimulation Modelling to Reduce Traffic Congestion: A Case Study of Signalized Intersections in Dhaka, Bangladesh

Urban Science ◽  
2019 ◽  
Vol 3 (2) ◽  
pp. 41 ◽  
Author(s):  
S.M. Labib ◽  
Hossain Mohiuddin ◽  
Irfan Mohammad Al Hasib ◽  
Shariful Hasnine Sabuj ◽  
Shrabanti Hira
Keyword(s):  
Data Mining ◽  
Traffic Congestion ◽  
Traffic Signals ◽  
Fixed Time ◽  
Travel Speed ◽  
Signalized Intersections ◽  
Signal Timing ◽  
Data Set ◽  
Video Footage ◽  
Transportation Technologies

A growing body of research has applied intelligent transportation technologies to reduce traffic congestion at signalized intersections. However, most of these studies have not considered the systematic integration of traffic data collection methods when simulating optimum signal timing. The present study developed a three-part system to create optimized variable signal timing profiles for a congested intersection in Dhaka, regulated by fixed-time traffic signals. Video footage of traffic from the studied intersection was analyzed using a computer vision tool that extracted traffic flow data. The data underwent a further data-mining process, resulting in greater than 90% data accuracy. The final data set was then analyzed by a local traffic expert. Two hybrid scenarios based on the data and the expert’s input were created and simulated at the micro level. The resultant, custom, variable timing profiles for the traffic signals yielded a 40% reduction in vehicle queue length, increases in average travel speed, and a significant overall reduction in traffic congestion.

Influence of Traffic Signal Timing on Red-Light Running and Potential Vehicle Conflicts at Urban Intersections

1997 ◽  
Vol 1595 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Richard A. Retting ◽  
Michael A. Greene
Keyword(s):  
Urban Areas ◽  
Motor Vehicle ◽  
Red Light ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Signal Timing ◽  
Red Light Running ◽  
Sustained Effects ◽  
Traffic Violation ◽  
Traffic Signal Timing

Motor vehicle crashes at traffic signals are a major source of injuries and property damage, especially in urban areas. Many crashes result from vehicles entering the intersection after the onset of a red light, a traffic violation that may be affected by the duration of the change interval (the yellow and all-red periods of the traffic signal). The purpose of this study was to examine short-term and sustained effects on red-light compliance and potential vehicle conflicts as a result of an increase in change intervals to values associated with the Institute of Traffic Engineers (ITE) proposed recommended practice for determining vehicle change intervals. Data were collected during an experiment in an urban location involving changes in signal timing at some 10 intersections. Observations included the proportion of signal cycles with vehicles entering on a red light and the proportion of vehicles exiting the intersection after the onset of a conflicting green signal. Results indicate that change intervals set closer to ITE’s proposed recommended practice can reduce red-light violations and potential right-angle vehicle conflicts and that such safety benefits can be sustained.

A Two-Level Model for Traffic Signal Timing and Trajectories Planning of Multiple CAVs in a Random Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yangsheng Jiang ◽  
Bin Zhao ◽  
Meng Liu ◽  
Zhihong Yao
Keyword(s):  
Random Environment ◽  
Arrival Time ◽  
Traffic Signals ◽  
Traffic Signal ◽  
Signal Timing ◽  
Automated Vehicles ◽  
Gasoline Consumption ◽  
Level Model ◽  
Traffic Signal Timing ◽  
Two Level Model

Connected and automated vehicles (CAVs) trajectories not only provide more real-time information by vehicles to infrastructure but also can be controlled and optimized, to further save travel time and gasoline consumption. This paper proposes a two-level model for traffic signal timing and trajectories planning of multiple connected automated vehicles considering the random arrival of vehicles. The proposed method contains two levels, i.e., CAVs’ arrival time and traffic signals optimization, and multiple CAVs trajectories planning. The former optimizes CAVs’ arrival time and traffic signals in a random environment, to minimize the average vehicle’s delay. The latter designs multiple CAVs trajectories considering average gasoline consumption. The dynamic programming (DP) and the General Pseudospectral Optimal Control Software (GPOPS) are applied to solve the two-level optimization problem. Numerical simulation is conducted to compare the proposed method with a fixed-time traffic signal. Results show that the proposed method reduces both average vehicle’s delay and gasoline consumption under different traffic demand significantly. The average reduction of vehicle’s delay and gasoline consumption are 26.91% and 10.38%, respectively, for a two-phase signalized intersection. In addition, sensitivity analysis indicates that the minimum green time and free-flow speed have a noticeable effect on the average vehicle’s delay and gasoline consumption.

Calibration of Saturation Flow for Signalized Intersections

2015 ◽  
Vol 713-715 ◽  
pp. 2093-2096
Author(s):  
Liang Ren
Keyword(s):  
Regression Models ◽  
Signalized Intersections ◽  
Urban Transport ◽  
Transport Infrastructure ◽  
Signal Timing ◽  
Speed Limit ◽  
Linear Regression Models ◽  
Traffic Signal Timing ◽  
Saturation Flow ◽  
Important Design

Transport infrastructure has been playing an increasingly important role to the world economy. Intersections have been widely accepted as the bottlenecks for an urban transport system. As such, the intersection design has been of great importance for transport agencies. Saturation flow is the most important design parameter for traffic signal timing. In this study, we aim to calibrate saturation flows for signalized intersections. Based on calibrated saturation flows, we thus intend to examine whether headways between consecutive vehicles during a queue are affected by intersection shapes and speed limit. To this end, five signalized intersections are observed to collect time headways. According to collected time headways, saturation headways in various cycles are calibrated using linear regression models. Finally, according to analysis of variance (referred to as ANOVA hereafter), we reveal that there is no direct relationship among speed limit, intersection shape, and saturation headways.

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