Intersection Capacity Research Articles

Using Simulation Modeling to Determine Optimum Operating Modes of Traffic Lights at Investigated Crossroads

The problem of traffic regulation has been a big problem in many countries for many years. One of the most acceptable methods of decoupling the traffic flow is to optimize the operation of the traffic light. This article presents a simulation method used to find the optimal modes of operation of a traffic light at a given intersection. Models were created that simulate the transport networks of the city, on the basis of which the experimental results of this simulation were obtained. The simulation was carried out on the basis of optimizing the time of the traffic light on the given sections of the routes. To optimize the operation of traffic lights, the following sequence of operations was implemented: during the iteration, optimization parameters were selected from those specified in the database, followed by work on the model based on these parameters; at the end of one cycle of the model, the value of the optimizing function was determined at the time of the cycle completion. The resulting optimizing function is analyzed and, if necessary, new values of the optimization parameters are introduced, a new value of the optimization function is found, and the process is repeated until the function satisfies the specified initial conditions or reaches a constant value. The data obtained as a result of the optimization showed that the optimization made it possible to increase the capacity of busy intersections by almost three times.

Control and allocation at an intersection with traffic lights

Managing road infrastructure in highly urbanized areas during the Industry 4.0 era poses a significant technological challenge for traffic engineers. Steadily growing traffic volume, both of motor vehicles and pedestrians, cyclists or scooters, necessitates the development of advanced traffic control algorithms and systems. Improvement of the efficiency and capacity of intersections without any intervention into the physical structure of roadways is one of the two aspects of today's traffic engineering. In this paper, however, emphasis is placed on the aspect of coordination of conflicting flows of motorized and pedestrian traffic. Consideration is given to ensuring that each traffic light phase at an intersection is maximally utilized while maintaining the required safety factor. The empirical part of the study consists in identifying inefficiencies in the traffic light cycle. The analysis of traffic phases has revealed that there were certain periods in the cycle during which pedestrians were given the right of way while, in fact, it was not necessary. The study proposes a solution to optimize the green signal timing for conflicting vehicular and pedestrian flows in real-time. By eliminating delays in traffic signal phases as a result of not having to give a green signal for pedestrians, the proposed solution will improve the efficiency of urban networks with respect to an aspect whose potential has not been exploited so far. Coordination and adaptation of each light phase to the most effective extent is a feasible answer to the needs and requirements of modern urban areas.

Behavior and Psychological Analysis of Electric Bike Rider Turning Left to Cross the Street at Signal Intersections

As a more convenient and environmentally friendly green way of travel, electric bicycle has shown a rapid development trend in many cities in China in recent years [1-3], the impact on urban traffic is also increasing, especially in the signal intersection with traffic flow, electric vehicles is an important factor affecting the capacity of signal intersection, and the illegal behavior of electric vehicles is widespread, which has become one of the main causes of traffic accidents. This paper uses the combination of video survey method and questionnaire survey method to analyze the behavior and psychology of the motorcyclists with the left turn of the signal intersection. First, the field video survey is used to collect the behavior data of the riders, and then the questionnaire survey is used to analyze the psychological activities of the riders, and to compare the actual behavior results with the psychological analysis results, so as to establish the connection between behavior and psychology. To optimize the traffic and improve traffic safety and strengthen the standard management.

Optimization of Trunk Phase Difference for Seeking Maximum Bidirectional Green Wave Bandwidth

This paper first analysis the shortcomings of the existing traditional numerical solution algorithm to solve the two-way green wave bandwidth problem, then improves the traditional numerical solution algorithm, constructs the objective function, proposes a trunk phase difference optimization method to seek the maximum two-way green wave bandwidth, constructs the model and solves it using Lingo optimization software, which can overcome the disadvantages of artificially fixed speed and common signal period and the lack of connection between green wave speed and common signal period. It can overcome the disadvantages of artificially fixed speed and common signal period and the lack of connection between green wave speed and common signal period, and optimize the signal period, phase difference, green signal ratio and green wave speed simultaneously. Meanwhile, the simulation analysis by VISSIM software verifies that the method can significantly reduce the stopping delay and improve the intersection capacity.

Modelling discharge flows at signalised intersections with adjustment of downstream effects

Former studies revealed that before spillbacks happen intersection capacities can still be greatly affected by downstream queues and signals. However, there is no methodology reasonably accounting for this effect. This research aims to propose adjustment factor models (Adj models) for both saturation flow rate (SFR) and start-up lost time (SLT) in through lane groups considering downstream conditions. An improved cell transmission model is created to build a simulation platform that can well reproduce the downstream influence. By the experimental data, Adj models are derived through heuristic optimisation based regression analyses. Proposed adjustment factors are governed by common traffic indicators. Sensitivity analyses proved that approaches with high volumes, short segment lengths, large green ratios, positive offset, or large cycle lengths are more easily affected by downstream conditions. Through the validation, it is proved that the estimation error of SFR and SLT can be significantly reduced by the proposed adjustment factors.

Distributed Control for an Urban Traffic Network

In this paper, we develop a distributed control method for an urban traffic network in order to improve traffic conditions and guarantee a smooth operation for all roads and intersections. An optimal coordination among traffic flows is determined by a model predictive control idea. The control objective is formulated as a constrained optimization problem in which the cost function to be minimized is a combination of some traffic network-related performance indexes and the constraints are derived from capacities of roads and intersections. The green time assigned to each road link is computed from its optimal downstream traffic flow. In the proposed algorithms, every road link uses only its local information to determine its control decision which corresponds to a global optimal solution. The algorithms are developed by using a gradient projection-based method and properties of the minimal polynomial of a matrix pair. The effectiveness of the proposed algorithms is validated via numerical simulations with MATLAB and VISSIM.

EVALUASI KINERJA LALU LINTAS SIMPANG KRANJI KOTA BEKASI

Taking into account the worsening congestion conditions and the impact on public health and the environment, it is concluded that strategic steps are needed to overcome congestion in Jabodetabek, especially in the Bekasi area. In detail, intersection capacity management aims to reduce traffic conflict points caused by confluence of traffic flows from different intersection legs. If the confluence of these traffic flows and the number of conflict points are not managed properly, it is certain that there will be acute congestion at the intersection. it is necessary to conduct research on "Evaluation of Traffic Performance at the Kranji Intersection in Bekasi City". Some secondary data and the results of obtaining primary data are then compiled and processed, so that information or an initial study will be obtained about the current condition of road traffic volume. In this stage, a synthesis of the data obtained from secondary data and primary surveys will be carried out. The data and information will be used in the context of modeling the performance of the road network sections around the Kranji Intersection, Bekasi City. Based on the evaluation of traffic performance at the Kranji intersection, there was a percentage decrease in the average delay value of vehicles from the existing condition to the planned condition of 72.04%, while the percentage decrease in the value of the average queue of vehicles at the intersection was 62.18%.

Traffic signal control in mixed traffic environment based on advance decision and reinforcement learning

Abstract Reinforcement learning-based traffic signal control systems (RLTSC) can enhance dynamic adaptability, save vehicle travelling time and promote intersection capacity. However, the existing RLTSC methods do not consider the driver's response time requirement, so the systems often face efficiency limitations and implementation difficulties. We propose the advance decision-making reinforcement learning traffic signal control (AD-RLTSC) algorithm to improve traffic efficiency while ensuring safety in mixed traffic environment. First, the relationship between the intersection perception range and the signal control period is established and the trust region state (TRS) is proposed. Then, the scalable state matrix is dynamically adjusted to decide the future signal light status. The decision will be displayed to the human-driven vehicles (HDVs) through the bi-countdown timer mechanism and sent to the nearby connected automated vehicles (CAVs) using the wireless network rather than be executed immediately. HDVs and CAVs optimize the driving speed based on the remaining green (or red) time. Besides, the Double Dueling Deep Q-learning Network algorithm is used for reinforcement learning training; a standardized reward is proposed to enhance the performance of intersection control and prioritized experience replay is adopted to improve sample utilization. The experimental results on vehicle micro-behaviour and traffic macro-efficiency showed that the proposed AD-RLTSC algorithm can simultaneously improve both traffic efficiency and traffic flow stability.

Intersection control strategy optimization based on exchangeable lanes modeling

Purpose Due to the conflicts between left turn traffic and opposite straight-going traffic in urban traffic network, some of the traffic lanes cannot be used to discharge vehicles during its green phases and the intersection capacity can be greatly reduced. This study/paper aims to reduce the effect of conflicts and increase its capacity through the reasonable pre-signal phase time with the exchangeable lanes. Design/methodology/approach This paper took into consideration various influence factors to intersection capacity and formulated the capacity optimization model based on 0-1 mixed-integer programming model. This model is efficiently solved by standard branch-and-bound algorithms. Findings The authors took an intersection as an example and solved the optimal signal timing and entrance lane capacity via this model. Then, simulations were carried out to verify the effect of the exchangeable lanes strategy of this intersection through the simulation software VISSIM and take the traffic volume and delay as outputs, which indicated that this model has better performance. Originality/value The front-end control strategy can not only exploit the full potential of the intersection but also significantly improve the operational efficiency of the intersection. It plays a positive role in improving urban intersection congestion.

Impact of Side Friction on Saturation Flow at Signalized Intersections in Mixed Traffic Conditions

Saturation flow rate is the prime important parameter for the design of capacity of signal-controlled intersections. The width of the approach is one of the most important factors for the evaluation of saturation flow. But, in countries like India, due to the increase in commercial and social land usage, especially on roadsides, there are many factors that affect road width performance, among which side friction is one of the most important factors. In the present research study, an attempt is made to find the impact of side friction on saturation flow at signalized intersections in mixed traffic conditions. For this purpose, the data was collected from four different cities: Hyderabad, Hanmakonda, Raipur and Calicut. A multiple linear regression model is developed for estimating saturation flow in the present study. In addition to the saturation flow model, the present work provides adjustment factors for side friction to calculate saturation flow.

Optimal traffic operation for maximum energy efficiency in signal-free urban networks: A macroscopic analytical approach

The integration of artificial intelligence and wireless communication technologies in communicant autonomous vehicles (CAVs) enables coordinating the movement of CAV platoons at signal-free intersections. The capacity of signal-free intersections can be significantly improved by adjusting traffic variables at a macroscopic scale; however, the resulting improvement in the capacity does not necessarily have a positive impact on the energy consumption of CAVs at the network level. In this research, we develop an analytical model to enhance energy efficiency by optimizing macroscopic traffic variables in signal-free networks. To this end, we adopt a macroscopic modeling approach to estimate the operational capacity by accounting for the stochasticity resulting from the error in synchronizing the arrival and departure of consecutive platoons in crossing directions at intersections. We also develop a macrolevel analytical model to estimate expected energy loss during the acceleration/deceleration maneuver required for resynchronization at intersections as a function of synchronization success probability. We then maximize energy efficiency by minimizing expected energy loss and maximizing expected capacity in a biobjective optimization framework. We solve the energy efficiency problem using an analytical approach to derive a closed-form solution for the optimal traffic speed and the length of the marginal gap between the passage of consecutive platoons in crossing directions through intersections for a (general) normal distribution of the operational error. Having the closed-form solution of the energy efficiency problem, we balance the trade-off between energy loss and operational capacity at a large scale by extending the analytical model to the network level using the Macroscopic Fundamental Diagram (MFD) concept. The results of our two-ring simulation model indicate the accuracy of the proposed analytical model in estimating the macroscopic relationship between the expected energy loss at intersections and the vehicular density in signal-free networks. Our numerical results also show that optimizing the traffic speed and marginal gap length can improve energy efficiency by 31% at the cost of a 16% decrease in maximum capacity.

Effect of two-stage crossing of right-turning vehicles on capacity of urban uncontrolled intersections under mixed traffic conditions

Occupancy time is a microscopic traffic stream parameter used for evaluating the service performance of uncontrolled or unsignalized intersections. Several studies have conducted in the past used occupancy time concept to estimate critical gaps considering single-stage crossing. However, various roadway and traffic characteristics influence the right-turning vehicles and allow them to wait at the median. The present study demonstrates a procedure to examine the critical gap behavior of minor road vehicles turning right from the approaches of uncontrolled intersections. The study analyzes the occupancy time of vehicles by developing frequency distribution profiles considering single-stage and two-stage crossings. Field data for the study was collected for eight hours at six different uncontrolled T-intersections in India. The analysis of occupancy time performed for each vehicle type observed in the field revealed that the ability of vehicles to turn through intersection-conflicting zone in single-stage crossing is 36% lower when compared to two-stage crossing. The distribution models fitted on occupancy time data pertaining to right-turning vehicles are varied under single-stage and two-stage crossings. The critical gap values are estimated using distribution model profiles for both stages of crossing at each intersection. Further, the movement capacity of the minor approach right turning calculated using estimated critical gap values is compared under both types of crossing stages. The percentage change in capacity is found to be significant with a small change in the percentage of two-stage crossings.

ANALISIS SIMPANG TIGA BERSINYAL TUGU ADIPURA KOTA PAYAKUMBUH MENGGUNAKAN METODE MKJI 1997

AbstractThe rapid growth in the number of vehicles each year is not accompanied by an increase in road infrastructure. The population of Payakumbuh which is increasing from year to year causes the need for transportation equipment to increase. 36,960 vehicles and cars pass through the streets of Payakumbuh every day. Of the 36,960 vehicles, 70% were two-wheelers and 30% were four-wheelers. Comparing road conditions and transportation facilities will cause traffic congestion, especially during peak hours, and will have an impact on increasing pollution, travel time, costs, social and actual working time. The actual capacity of all intersections is 4106 pcu/hour, the degree of saturation of all intersections can be DS = 0.25 < 0.6 so the road category is smooth. The delay time for all these intersections is Dtot = 4.66 sec/pcu and the highest queue probability at all intersections is 13.61% Keywords: Signalized intersections, road lanes, intersection performance, queuing opportunities, degree of saturation, intersection capacity

Distracted Driving Effects on Headways at Signalized Intersections

Distracted driving poses one of the most difficult challenges to ensuring a safe and efficient transportation system. Modern communications have delivered greater convenience. However, this has come at the cost of attention spans. Safety has been thoroughly explored from the perspective of distracted driving. However, impacts on traffic operations have received minimal research attention. A few studies have provided a theoretical mechanism on how intersection operations can be affected, but fail to quantify the real-life impacts on traffic operations. This research aims to quantify how distracted driving affects vehicle discharge headways at signalized intersections for through lanes. Thousands of observations were collected from four intersections in Orange County, Florida, covering a variety of land uses, intersection configurations, and periods of high demand. The results demonstrated that approximately a quarter of all drivers were distracted. Drivers were less distracted in commercial zones and more attentive to signal changes compared to school and residential areas. Cell phone usage had the primary effect on headways among distraction types with a 20% increase, which resulted in reducing the intersection capacity by 16.5%. The statistical model demonstrated that the overall effect of distraction on the discharge headway is significant. The base headway increased by 0.93 s, which resulted in reducing the intersection capacity by 45.5%. The results also revealed that the 10th vehicle position in the queue had a detrimental effect on the headway and the overall intersection capacity. The green phase gaps out because of the amount of time needed to reach the stop bar.

Dynamic capacity estimation of mixed traffic flows with application in adaptive traffic signal control

Intersection control plays a vital role in influencing transportation efficiency inside urban areas. Connected and Automated Vehicle (CAV) technology enables frequent traffic information sharing through vehicular networks, which emerges as a promising way to reduce vehicle traveling time and improve intersection capacity. Meanwhile, with the gradual deployment of CAVs, the traditional traffic flow consisting of human driven vehicles will evolve into a mixed traffic flow composed of traffic participants with differing intelligence capabilities. Considering the evolution towards the mixed traffic environment, we propose a dynamic capacity-aware traffic signal control method: max-pressure for mixed traffic flow (MPMF) traffic signal controller. Firstly, the lane capacity is modeled and approximated based on the saturation flow rate in mixed traffic flow considering the penetration rate of CAVs. Then the dynamic capacity is involved in calculating pressure in the max-pressure method to indicate the importance of a path in mixed traffic flow. A modification strategy for the max-pressure input value is also proposed. An isolated intersection scenario was simulated first to assess the proposed method locally. A multi-intersection network experiment was also conducted to verify the network-level performance of the proposed MPMF method. Comparative results between the proposed MPMF method, the classic max-pressure control, and the existing fixed time control method demonstrate that the MPMF can effectively improve the performance of intersections and be suitable for the multi-intersection road network.

Capacity Analysis of Intersections When CAVs Are Crossing in a Collaborative and Lane-Free Order

Connected and autonomous vehicles (CAVs) improve the throughput of intersections by crossing in a lane-free order as compared to a signalised crossing. However, it is challenging to quantify such an improvement because the available frameworks to analyse the capacity of the conventional intersections do not apply to the lane-free ones. This paper proposes a novel framework including a measure and an algorithm to calculate the capacity of the lane-free intersections. The results show that a lane-free crossing of CAVs increases the capacity of intersections by 127% and 36% as compared to a signalised crossing of, respectively, human-driven vehicles and CAVs. The paper also provides a sensitivity analysis indicating that, in contrast to the signalised ones, the capacity of the lane-free intersections improves by an increase in the initial speed, maximum permissible speed and acceleration of vehicles.

A population-based incremental learning algorithm to identify optimal location of left-turn restrictions in urban grid networks

The treatment of left turns at signalized intersections drives the development of signal phasing and timing plans and also plays an important role in overall traffic network operations. Accommodating left turns allows for the most direct routeing but reduces intersection capacity, whereas restricting left turns improves capacity but requires some vehicles to travel longer distances. This paper proposes a population-based incremental learning (PBIL) algorithm to determine at which intersections left-turn restrictions should be enacted to maximize a network's operational performance. The performance of each configuration is tested in a micro-simulation environment on both perfect and imperfect square grid networks. Comparison with a partial enumeration of feasible options reveals that the PBIL algorithm is effective at identifying a near-optimal configuration of left-turn restrictions. The resulting configurations suggest that left turns should be generally restricted at intersections that carry the most flow. These intersections typically occur in the central portion of the network when demands are relatively uniform. Doing so helps to provide additional intersection capacity at the locations where it is most necessary, while minimizing the additional travel distance that is incurred due to detours caused by the left-turn restrictions. These provide insight as to how urban traffic networks might be managed to improve network efficiency by only enacting left-turn restrictions at a subset of locations.

Assessing the Traffic Capacity of Urban Road Intersections

Assessing the Traffic Capacity of Urban Road Intersections

Traffic Signal Timing Optimisation for Several Intersections in High-Priority Congested Networks Improved on Genetic Algorithm

Nowadays, getting around has become an essential aspect of everyday life, whether it be public transport or personal vehicles, the vast network formed by these means of transport is immensely complex to manage. Unfortunately, this activity presents serious problems in most cities around the world. In this paper we upgrade traffic capacity of intersections using Genetic algorithm in order to decrease traffic congestion and crossing time of a road network. The main focus of this study is on improving the quality of solutions for the traffic light optimization problem. This proposition calculated and simulated through programming. As it shows, It improve results for solving the cycle traffic light problem (CTLP).

Analisis Kinerja Simpang Non-APILL (Studi Kasus: Simpang Jalan Pulau Galang – Jalan Taman Pancing – Jalan Tukad Baru)

Population growth in Denpasar City continues to increase from year to year. This indirectly causes the number of vehicle ownership in Denpasar City to continue to increase while the existing facilities are inadequate. We can see this in traffic problems such as congestion that often occurs, especially at intersections. Jalan Pulau Galang - Jalan Taman Pancing - Jalan Tukad Baru is an example of an intersection that has irregular traffic conflict points, especially during rush hours. This junction is a non APILL junction. This location was chosen as the research because in addition to the irregular traffic flow at certain hours, at this intersection there are also residential and shopping areas which trigger more congestion at this intersection. From the problems that arise at the Jalan Pulau Galang intersection - Jalan Taman Pancing - Jalan Tukad Baru, a study was carried out which aims to determine the performance and service level of the intersection. If the service level at the intersection is in the safe category, then preventive measures to avoid congestion must be analyzed. The results of the calculations that have been carried out show that the value for the intersection capacity (C) is 6,213 smp/jam with the degree of saturation (DS) being 0,363 smp/jam. The DS (Degree of Saturation) value indicates that the intersection is included in the service level category B according to the 2014 PKJI, which has stable flow characteristics, but the operating speed is starting to be limited by traffic conditions. Service level B has an NVK value between 0.20-0.44. For this reason, it is necessary to supervise the location of the intersection so that the location of the intersection still has an adequate level of service and does not increase in height to avoid severe traffic jam