Vehicle Queue Research Articles

The Effect of Different Lane Occupancy on Road Traffic Capacity

In this paper, the data of video is extracted and processed, and the change process of road capacity during the accident is described by using the fuzzy comprehensive evaluation method. By means of cellular automata, the change of road capacity when different lanes are blocked is simulated, and the influence of different lanes on road capacity is analyzed. Then the formula of vehicle queue length based on mathematical relation is established.

Research on Speed Optimization Strategy of Hybrid Electric Vehicle Queue Based on Particle Swarm Optimization

Traffic lights intersections are common in cities and have an impact on the energy consumption of vehicles, so it is significant to optimize the velocities of vehicles in urban road conditions. The novel speed optimization strategy for hybrid electric vehicle (HEV) queue that helps reduce fuel consumption and improve traffic efficiency is presented in this paper, where real-world traffic signal information is used to construct the research scenario. The initial values of the target velocities are obtained based on the signal phase and timing (SPAT). Then the particle swarm optimization (PSO) algorithm is used to solve the nonlinear constrained problem and obtain the optimal target velocities based on vehicle to vehicle communication (V2V) and vehicle to infrastructure communication (V2I). The lower controller, which applies rule based control strategy, is designed to split the power of the engine and two electric motors in a power split HEV, which is quite promising because of its advantages in fuel economy. Simulation results demonstrate the superior performance of the proposed strategy in reducing fuel consumption of the HEV queue and improving traffic smoothness.

TRAM: a New Quantitative Methodology for Tunnel Risk Analysis

The paper illustrates and describes the structure of a new quantitative model of risk analysis for road tunnels named TRAM (Tunnel Risk Analysis Model). The result of the model, in accordance with the European Directive and the Italian Legislative Decree, returns the F-N curves of societal risk, in other words functions that relate the frequency of occurrence of an accidental scenario (F) with the expected consequences in terms of potential victims (N).Starting from two types of initial events, a fire and a Dangerous Goods (DG) release, a total of 18 accidental scenarios was defined. The frequencies of occurrence of each accidental scenario is obtained using the Event Tree Analysis (ETA) technique. For each scenario, the number of fatalities, expressed in terms of deaths, is obtained by simulating the formation dynamics of the queue of vehicles, using a model able to calculate the queue length, depending on traffic, the vehicle type, as well as the closure time of the tunnel. Then, a distribution model of the potentially exposed users has been defined and coupled with an egress model. The users’ tenability is estimated on the basis of the egress model and the evolution of each accidental scenario, which is evaluated using a zone model. The proposed model can simulate each of the 18 accidental scenarios in several different positions along the tunnel, considering the impact that different tunnel infrastructure measures, equipment and management procedures can have on the users egress and on the propagation of the effects of the accidental scenarios. The model is able to consider the interdependence between these measures and their reliability in terms of their availability in an emergency situation. Finally, to validate the model, comparisons are made with the QRAM software developed by PIARC for some representative case studies. Through this model, it is possible to perform the risk analysis of a tunnel in an actual configuration and compare the expected value of damage with the corresponding one of the tunnel in a virtual configuration, as prescribed by the Italian decree compliant with the European Directive 2004/54/EC.

Road Users Exposed to Harm from Transportation of Dangerous Goods - Definition and Estimation

The Italian Interreg Project DESTINATION was intended to acquire data on the transportation of dangerous goods and use them, developing a tool to protect the territory. The Project developed a risk analysis model for examination and assessment of the elements exposed to harm in the event of accident scenarios involving hazardous substances. Defining the risk model, the need emerged for a procedure able of explicitly estimating the number of road users that could be affected in case of dangerous goods accident. After a brief presentation of the risk model, this paper describes the method adopted for the quantification of the possible involved road users, in coherence with the Project’s objectives and requirements. Due to the specific nature of the subject, it was necessary to consider parameters not included in traditional vehicle queuing models, such as the possibility of assessing users in transit on roads not directly affected by the accident and of differentiating analyses depending on the temporal development of the event (instantaneous vs. non-instantaneous events).

Study of the Operation of Actuated signal control Based on Vehicle Queue Length estimated by Deep Learning

Study of the Operation of Actuated signal control Based on Vehicle Queue Length estimated by Deep Learning

Analyze traffic forecast for decentralized multi agent system using I-ACO routing algorithm

Traffic congestion is a condition on road networks that may cause the vehicle to move very slow, longer trip timing changes, and vehicle queue length increase. We need accurate predictions which require accurate status information about vehicles—the fact that the vehicles are distributed over large-scale road infrastructure that makes mostly challenging one. Advanced vehicle guidance systems use real time traffic information but unfortunately can only react upon the presence of traffic. Anticipatory vehicle routing is promising approach, accounting for traffic forecast information. This concept presents an efficient decentralized approach for anticipatory vehicle routing that is particularly useful in large-scale dynamic environments with some additional techniques and experiments. The approach is based on delegate multi agent systems (MAS), i.e., an environment-centric coordination mechanism that is, in part, inspired by ant behavior. This paper mainly focus on provide the traffic forecast among the road network is very efficient to minimize the traffic.

A New Approach for Real-Time Traffic Delay Estimation Based on Cooperative Vehicle-Infrastructure Systems at the Signal Intersection

Confined by the real-time and accuracy of traditional traffic collecting parameters, the existing traffic delay estimation models are generally with poor performance in guiding practical applications. In the Cooperative Vehicle-Infrastructure System, the real-time entire space-time driving state information of a single intelligent vehicle provides new data supporting for road traffic status evaluation. Fully extracting the value of this kind of new data, this paper proposes a new real-time traffic delay estimation method based on the Webster signalized intersection delay model. Taking each intelligent vehicle as a benchmark point, the vehicle arriving/leaving characteristics of the signalized intersection are spatially interpolated by the stopping state of a small amount of benchmark vehicles. In order to obtain the critical queuing dissipation point, the linear fitting method is used to forecast the critical stopping time and further the Markov model is used to estimate the number of queuing vehicles at the critical stopping time. Based on the real-time vehicle queuing characteristics, a new traffic delay estimation model is built according to the Webster estimation mechanism. The case study shows that, compared with the traditional Webster model, the proposed method can effectively improve the traffic delay estimating accuracy.

Link Transmission Model-Based Linear Programming Formulation for Network Design

This article presents a linear programming formulation to solve the network design problem using the link transmission model (LTM) as the underlying traffic flow model. The original LTM was adapted by incorporating link-sending and receiving flows using linear inequalities. Furthermore, route choice was relaxed, and transfer flow variables were used to model vehicles’ routing decisions within the network. The objective function of the linear program aimed to minimize the total difference between the cumulative vehicle numbers (CVN) at the upstream and at the downstream boundaries of each link subject to flow-conservation and budget constraints. CVN were represented using transfer flows from connected links. The resulting formulation is a linear program that represents a dynamic system optimum traffic flow pattern, embedding the LTM’s network loading procedure. In contrast to the single-destination system optimum dynamic traffic assignment, based on the cell transmission model, the proposed formulation requires considerably fewer decision variables, thus potentially providing a more scalable approach. The proposed formulation was implemented on an example network to illustrate the behavior of the model, and was compared with the cell-based formulation. We show that the model describes free-flow and congested traffic flow states accurately in terms of shock-wave propagation, queuing of vehicles, and optimal total system travel time.

V2I 통신 기반의 효과적인 차량 대기행렬 길이 추정 기법

V2I 통신 기반의 효과적인 차량 대기행렬 길이 추정 기법

Hybrid model predictive control based dynamic pricing of managed lanes with multiple accesses

We propose a hybrid model predictive control (MPC) based dynamic tolling strategy for high-occupancy toll (HOT) lanes with multiple accesses. This approach preplans and coordinates the prices for different OD pairs and enables adaptive utilization of HOT lanes by considering available demand information and boundary conditions. It also addresses such practical issues as prevention of recurrent congestion in HOT lanes, ensuring no higher toll for a closer toll exit and fairness among different OD groups at each toll entry, as well as the fact that high occupancy vehicles (HOVs) have free access to the HOT lanes. Taking the inflows at each toll entry as the control, traffic densities and vehicle queue length as observed system states, and boundary traffic as predicted exogenous input, we formulate a discrete-time piecewise affine traffic model. Optimal tolls are then derived from a one-to-one mapping based on the optimal toll entry flows. By properly formulating the constraints, we show that the MPC problem at each stage is a mixed-integer linear program and admits an explicit control law derived by multi-parametric programing techniques. A numerical experiment is presented for a representative freeway segment to validate the effectiveness of the proposed approach. The results show that our control model can react to demand and boundary condition changes by adjusting and coordinating tolls smoothly at adjacent toll entries and drive the system to a new equilibrium that minimizes the total person delay. Under the optimal prediction horizon, the on-line computational cost of the proposed control model is only about 4% and 8% of the modeling cycle of 30 s, respectively, for two typical traffic scenarios, which implies a potential of real-time implementation.

Vehicle Accident Report Application for Solving Traffic Problems and Reduce the Ratio of Pollution using Case Study: Kuwait City

<span lang="EN-US">Minor traffic accidents have become a major problem facing the road users in the recent years, according to the statistics from the Ministry of Interior (MOI) in Kuwait there were recorded 80,388 accidents by the year 2014. Accidents not only affect the mobility but also contribute to air pollution and slow down economic growth. These effects are the result of the seriously extended trips travel time due to accumulated vehicles queue. In some accidents cases, the lost time waiting for the arrival of the traffic officers and filling up the accident report could take up to 45 minutes. The new idea of Vehicle Accident Report application (I-VAR) concept developed by the research team would reduce the waiting time up to 3 minutes (93% savings), which would increase the level of service of the segment of a roadway. In addition, the study will be discussed four major situations on some of the busiest roads in Kuwait. Specifically, gas emissions and cost estimation. Improve the pollution obviously, by using the (I-VAR) application for the minor accidents there is an amount of 360,776,460 K.D would be saved yearly from the Kuwait government funds. It is a consequence of the huge savings in alleviating traffic congestion and generally produces more saver and efficient travel conditions.</span>

Reducing a congestion with introduce the greedy algorithm on traffic light control

The density of vehicles causes congestion seen at every junction in the city of jakarta due to the static or manual traffic timing lamp system consequently the length of the queue at the junction is uncertain. The research has been aimed at designing a sensor based traffic system based on the queue length detection of the vehicle to optimize the duration of the green light. In detecting the length of the queue of vehicles using infrared sensor assistance placed in each intersection path, then apply Greedy algorithm to help accelerate the movement of green light duration for the path that requires, while to apply the traffic lights regulation program based on greedy algorithm which is then stored on microcontroller with Arduino Mega 2560 type. Where a developed system implements the greedy algorithm with the help of the infrared sensor it will extend the duration of the green light on the long vehicle queue and accelerate the duration of the green light at the intersection that has the queue not too dense. Furthermore, the design is made to form an artificial form of the actual situation of the scale model or simple simulator (next we just called as scale model of simulator) of the intersection then tested. Sensors used are infrared sensors, where the placement of sensors in each intersection on the scale model is placed within 10 cm of each sensor and serves as a queue detector. From the results of the test process on the scale model with a longer queue obtained longer green light time so it will fix the problem of long queue of vehicles. Using greedy algorithms can add long green lights for 2 seconds on tracks that have long queues at least three sensor levels and accelerate time at other intersections that have longer queue sensor levels less than level three.

Traffic signal fuzzy control algorithm for urban intersection based on vehicle-road cooperative environment

Traditionally, when using simple fuzzy control algorithm to control traffic signals at urban intersections, phase sequence optimization control is not carried out in view of vehicle-road coordination environment, and traffic lights cannot be reasonably arranged, resulting in a long queue of vehicles at intersections, resulting in traffic congestion. Therefore, a fuzzy control algorithm of urban intersection traffic signal is proposed under the vehicle-road cooperative environment. Based on the traffic signal model under the vehicle-road cooperative environment, the fuzzy control algorithm based on phase sequence optimization is obtained by combining the fuzzy control algorithm with the phase sequence optimization algorithm, and the fuzzy control algorithm steps are controlled reasonably according to the phase sequence optimization. The experimental results show that the average waiting time of vehicles controlled by the proposed algorithm is only 21s and 23s in the afternoon rush hours, which is an effective traffic signal control algorithm for urban intersections.

Modelling the loss of time caused by traffic incidents on motorways

For each road incident important factors like location, capacity reduction, traffic management, duration of road incidents and amount of traffic should be defined. All performer operations and effects of incidents affect the capacity of the road, average speed, time loss, vehicle queues and traffic jams. In the article road incidents were divided into planned and unexpected. Statistical analysis prepared using the database of traffic events which occurred on highways and expressways in Pomeranian Voivodeship is presented considering location of incidents on each road, frequency and duration of incidents and duration of rescue operation. Furthermore, the cases used to calibrate the model are characterised. Subsequently, the method of estimation of time loss resulting from incidents is presented. Within the methodology, mathematical and simulation models are distinguished. The tools for dynamic traffic modelling are also presented. In the last part of the article, the method of calculation value of time loss is presented.

Dynamic Contention Window based Safety-Application Model for Vehicular Ad-hoc Networks

The paper proposes a dynamic contention window based safety-application model to provide service to the Event Driven Messages (EDMs) over the beacon messages by varying the Contention Window (CW) size dynamically. This is done to ensure timely distribution of EDM as these messages are most critical messages and require immediate transmission in order to maintain the essence of the network. For prioritization, whenever the vehicular network detects an EDM, the system holds all the beacon messages, prioritizing EDMs and reduces the CW size by a pre-defined factor. This factor is continuously increased if consecutive EDMs are received at the vehicles queue. Consequently, for broadcasting beacons in the absence of EDM, the proposed model first evaluates backlogged packets, which is estimated by using round trip time and varies the size of CW accordingly. This is done to maintain the network performance even in the absence of EDM. The model is validated against the simulation result. It can be evident from the simulation results that our model provides smallest CW without degrading the performance of the network in terms of collision probability.

Traffic queue modeling using arena simulation software (a case study of Mergan 4-Way intersection in Malang City)

Currently Mergan 4-way intersection is one of intersection that have most traffic dense in Malang City, East Java - Indonesia. This research implement simulation method in order to give several solution option to manage the traffic queue in Mergan 4-way intersection. Simulation method is conducted with several phase, from problem identification up to verification and validation also scenario simulation. Arena Simulation software v.14 is chosen as the tool to modeling the traffic queue line. The research outcome give several solution through Traffic Light 2 simulation scenario. With this simulation scenario, the traffic flow system simulation can be run with fewer queues of vehicles.

Model petri net of adaptive traffic lights and its collaboration with a special event

Traffic lights have an important role as the system control of vehicles flow on the urban network. Commonly, most countries still using fixed time strategy. Our research proposes the adaptive traffic lights model to response the traffic demand. It uses basic Petri net as a general modeling framework. Foractuating method of minimum and maximum green signal time interval, the green traffic lights have three-time extension units. Next, we collaborate on a case of the existence of railways that crosses on the southern arm of an intersection. We introduce both of collaboration model design of traffic lights and the railway's gate which always closes while a train passing. Verification and validation of the model are based on the simulation result of vehicles queue. The collaboration model design of traffic lights has excellent performance, and it can resolve the congestion problem better than conventional schedule.

Optimal Signal Timing for Multi-Phase Intersections

We present an optimal signal timing policy for multi-phase intersections. The policy is optimal in the sense of minimizing the increase in the number of queuing vehicles, i.e. maximizing throughput, within one signal cycle. By introducing weights in the optimality criterion, our solution also accommodates the setting of prioritized traffic, in which it is more important for certain classes of traffic to wait for a shorter time. The proposed signal timing policy is simple to compute and implement. In particular, we show that the proposed strategy can be computed as a solution to a linear programming problem. Additionally, upon parametrizing the proposed policy with respect to the vehicle queue lengths, we analyze some aspects of the multi-cycle behavior of the closed-loop system generated by the policy, most notably convergence of the queue lengths over time. Finally, we illustrate the proposed control law with two numerical examples, one of which is based on real data collected from an existing complex multi-phase intersection.

АНАЛИЗ ИЗМЕНЕНИЯ ДЛИНЫ ОЧЕРЕДИ АВТОМОБИЛЕЙ ПЕРЕД РЕГУЛИРУЕМЫМ ПЕРЕКРЕСТКОМ ПРИ ПЕРЕГРУЗКЕ

АНАЛИЗ ИЗМЕНЕНИЯ ДЛИНЫ ОЧЕРЕДИ АВТОМОБИЛЕЙ ПЕРЕД РЕГУЛИРУЕМЫМ ПЕРЕКРЕСТКОМ ПРИ ПЕРЕГРУЗКЕ

Analysis of signalized intersection performance using IHCM 1997 method and PTV Vistro software

Brigjend Slamet Riyadi road is the main city road serving the traffic of Surakarta City. It is located in the Central Business District so that many vehicles pass through this road. The relatively high traffic volume in Brigjend Slamet Riyadi affects the signalized intersections performance along this road. This study analyses the performance of signalized intersections along the Brigjend Slamet Riyadi road by using the IHCM 1997 method and PTV Vistro software. The IHCM 1997 method is a traffic modelling method based on empirical Indonesian traffic conditions. PTV Vistro is traffic modelling software based on empirical United States America traffic conditions. Analysis of the signalized intersections performance results using both approaches is compared with the field data. Calibration and validation of models is carried out to see the similarity of traffic performance results between models with field data. In general, the IHCM 1997 method produces vehicle queue length closer to field data than the PTV Vistro software. The IHCM 1997 method tends to produce lower degree of saturation, vehicle delay and level of service than the PTV Vistro software.