Vehicle Arrival Rate Research Articles

Space-time graph path planner for unsignalized intersection management with a V2V agent coordination architecture

Reducing traffic congestion and increasing passenger safety are important objectives for emerging automated transportation systems. Autonomous intersection management systems (AIMS) enable large scale optimization of vehicle trajectories with connected and autonomous vehicles (CAVs). We propose a novel approach for computing the fastest waypoint trajectory in intersections using graph search in a discretized space-time graph that produces collision-free paths with variable vehicle speeds that comply with traffic rules and vehicle dynamical constraints. To assist our planner algorithm in decentralized scenarios, we also propose a multi-agent protocol architecture for vehicle coordination for trajectory planning using a vehicle-to-vehicle (V2V) network. The trajectories generated allow a much higher evacuation rate and congestion threshold, with lower O(N) algorithm runtime compared to the state of the art conflict detection graph platoon path planning method, even for large scenarios with vehicle arrival rate of 1/s and thousands of vehicles.

Driver–passenger guidance model for Chinese freeway service areas based on path selection and parking delay

The driver–passenger guidance model proposed in this article is designed for large-scale freeway service areas that integrate various services such as shopping, leisure and catering. The model focuses on analyzing the impact of perceived travel distance and parking delay on path selection and parking space selection to optimize passenger flow efficiency. A perceived travel distance function is used to construct a pedestrian path selection model whose parameters are calibrated by a stated preference survey. An optimal parking space selection model is established based on the analytic hierarchy process-technique for order of preference based on similarity to the ideal solution method and considers parking distance, outdoor walking distance, indoor perceived travel distance after parking, and the impact of pedestrian crossings on parking delays. The model also calculates the vehicle arrival rate with parking time and the critical gap to ensure pedestrian safety. A parking delay calculation model is established based on the acceptable gap theory. The model is verified using the Yihezhuang service area of the Xiongan freeway as an example. The results show that the pedestrian path selection model improves passenger flow balance and reduces the variance in road passenger flow by 12% and per capita travel time by 9%. The proposed parking delay calculation model reduces parking delays by 30 s compared to models that do not consider pedestrian crossings, indicating its smoothness and convenience.

Road Safety Criteria for Mid-Block Pedestrian Crossing Facility and Application of ITS Technologies

This paper describes an attempt made to evaluate the pedestrian's road crossing facility at midblock to relate with pedestrian road crossing behaviour and identify the variables influencing pedestrian road crossing decisions. The decision of pedestrians on road crossing depends on many other elements like yielding behaviour of a driver, vehicle speed, roadway width, traffic volume etc. Pedestrians road crossing data collected through videographic survey at Kozhikode city, Kerala, India were used to evaluate the pedestrian crossing facility. Regression model has been developed considering the pedestrian waiting time as dependent variable and vehicle speed and volume as independent variable. Further, a computational tool is developed to derive suitable criteria for regulating the number of pedestrian phases based on the percentage of vehicles in the queue formation for varying levels of interruptions and vehicle arrival rate. The criteria has been derived such that the negative force exerted by vehicles and drivers during pedestrian road crossing to a minimum level, through the implementation of signal control using Intelligent Transport System (ITS) technologies. Further, the queuing analysis results helps to identify the criteria for proposing grade-separated crossing based on the threshold value of the percentage of vehicles in the queue formation. From the queuing analysis, it was found that, the percentage of vehicle in queue has been increased from 19.44% to 38.89% for the arrival rate of 1200v/h when the number of pedestrian interruptions per hour is increased from 20 to 40. Also, it is observed that when the arrival rate increases from 1200 to 1800 v/h the percentage of vehicle in queue increases 19.44% to 77.78% for 20 number of pedestrian interruptions. The prediction tool developed may help the transportation policymakers and highway officials to evaluate the field conditions and to identify suitable control measures for the pedestrian facility with improved pedestrian safety and vehicular traffic efficiency.

Queue Length Estimation Based on Probe Vehicle Data at Signalized Intersections

Queue length is one of the important indexes to evaluate the operation efficiency of signalized intersection and also the key parameter of intersection signal control optimization. Traditional queue length estimation models are mostly based on fixed detection equipment, and the models assumptions are too harsh; there are certain limitations. Based on the probe vehicle data, this paper establishes a model of queue length estimation for signalized intersection based on shockwave theory. First, based on the speed and location data of the probe vehicle, the vehicle density is calculated to estimate the intersection stop line. A real-time calculation method of vehicle arrival rate is proposed to improve the applicability of the model. Then, based on the shockwave theory, the meeting time of the queue forming wave and the queue discharging wave are calculated after the green light is on. Finally, the queue length is summed in sections, including the distance between the last queued probe vehicle and the stop line during the red light period, the length of the subsequent vehicles arriving during the residual red light time, and the newly increased queue length within the queue discharging time. This paper uses the VISSIM software to simulate the actual intersection. The simulation results show that when the penetration of probe vehicle is 50%, 25%, and 10%, their corresponding mean absolute relative error are 11.27%, 27.77%, and 39.12%, respectively. It can be seen that with the increase of penetration, the error gradually decreases. The average absolute relative error is within the acceptable range. After analyzing the existing similar methods, although the accuracy of the method proposed in this paper does not reach the highest level, it has the advantages of simple operation, less computation, and good real-time computation. Relevant research results can provide support for traffic control at signalized intersections.

Estimation of Road Traffic State at a Multilanes Controlled Junction

We present in this paper a method for the estimation of traffic state at road junctions controlled with traffic lights. We assume mixed traffic where a proportion of vehicles are equipped with communication resources. The estimation of road traffic state uses information given by communicating vehicles. The method we propose is built upon a previously published method which was applied to estimate the traffic in the case where roads are composed of two lanes. In this paper, we consider the case where roads are composed of three lanes and we show that this solution can address the general case, where roads are composed of any number of lanes. We assume the geometry of the road junction is known, as well as its connections between incoming and outgoing lanes and roads. Using the location data provided by the communicating vehicles, first, we estimate some primary parameters including the penetration ratio of the probe vehicles, as well as the arrival rates of vehicles (equipped and non-equipped) per lane by introducing the assignment onto the lanes. Second, we give estimations of the queue length of the 3-lanes road, without and with the additional information provided by the location of the communicating vehicles in the queue. We illustrate and discuss the proposed model with numerical simulations.

A stochastic model for estimating electric vehicle arrival at multi-charger forecourts

Many countries are observing significant growth rates in electric vehicle (EV) uptake, often backed by financial incentives or regulation and legislation. The availability of large multi-charger sites for rapid EV charging with an experience similar to conventional refuelling stations lowers the barrier to acceptance for drivers considering the switch to using an EV. The question arises about how to size such a facility at the design and planning stage, as well as accommodating growth in the number of EVs in daily use. One of the important factors is the vehicle arrival rate and the corresponding power and energy demand. EV charging is a function of several parameters, all of which are stochastic in nature, such as the vehicle daily travelled distance, charging start time and the required energy. To account for uncertainty in the parameters, a stochastic model has been designed to simulate realistic vehicle arrival rates. The model accounts for EVs coming from the site catchment area and opportunistic charging from passing traffic travelling on the major roads adjacent to the site, the seasonality of parameters, and charging at places other than the site (competitive charging). The model produced plausible EV arrival patterns for both local and passing traffic, and reproduced the characteristic power demand at the case study site. All estimates incorporate uncertainty, reflecting realistic variability of the important parameters. The model in independent of location, uses open-source data, and is structured flexibly, making it adaptable to new sites as part of the technical and business planning process.

An effective hybrid V2V/V2I transmission latency method based on LSTM neural network

We propose an effective hybrid vehicle-to-vehicle/vehicle-to-infrastructure (V2V/V2I) transmission latency method based on a long short-term memory (LSTM) neural network to address transmission latency in the internet of vehicles. First, a traffic model is established, and the LSTM artificial neural network is used to predict the vehicle arrival rate in the road section. Second, the vehicle arrival rate function is used to construct an objective function, i.e., the problem of minimizing system transmission the overall latency. The hybrid V2V/V2I transmission method determines the communication transmission mode of the vehicles to minimize transmission latency. The simulation results show that the overall transmission latency is substantially lower for the hybrid V2V/V2I transmission method than the pure V2I transmission method with the transmission packet size and vehicle speed varying.

Urban Traffic Signals Timing at Four-Phase Signalized Intersection Based on Optimized Two-Stage Fuzzy Control Scheme

This paper proposes a signal timing scheme through a two-stage fuzzy logic controller. The controller first determines the signal phase and then adjusts the green time. At the first stage, the adaptive membership function of vehicle arrival rate is improved to adapt to the changing traffic flow. In addition to arrival rate and queue vehicles, a specific phase order rule is considered to avoid disordered phase selection in fuzzy control. At the second stage, the green time detection module decides whether to extend the current green time or switch phases every few seconds and the vehicle arrival rate is not required as the input to controller in real-time detection. Differential evolution algorithm with low space complexity and fast convergence is applied to optimize the fuzzy rules for avoiding artificial uncertainty. Simulation experiments are designed to compare traditional fuzzy controller, fixed-time controller, and fuzzy controller without flow prediction. Results show that the current proposed method in this paper can reduce vehicle delay significantly.

Correction to “Queuing Analysis-Based PEV Load Modeling Considering Battery Charging Behavior and Their Impact on Distribution System Operation” [Jan 18 261-273

This paper presents a queuing analysis-based method for modeling the 24-h charging load profile of a plug-in electric vehicle (PEV) charging station. The queuing model considers the arrival of PEVs as a non-homogeneous Poisson process with different arrival rates over the day. The first PEV charging load profile assumes customer convenience as the factor that influences the hourly arrival rate of vehicles at the station, while the second profile is developed assuming that customers would respond to PEV charging prices and arrival rates are accordingly affected. One of the main contributions of this paper is to model the PEV service time considering different factors such as the state-of-charge of the vehicle battery, as well as the effect of the battery charging behavior. The impact of PEV load models on distribution systems is studied for a deterministic case, and the impact of uncertainties is examined and compared using the stochastic optimal power flow and the model predictive control approaches.

A study on modeling vehicles mobility with MLC for enhancing vehicle-to-vehicle connectivity in VANET

In Vehicular ad hoc networks (VANETs), vehicle-to-vehicle (V2V) is a significant mode of communication in which vehicles communicate with other moving vehicles with the aid of wireless transceivers. Due to the rapid mobility of vehicles, network connectivity over VANETs is frequently unstable, especially in sparse highways. This paper analyzes V2V connectivity dynamics by designing the microscopic mobility and lane changing decision model using an adaptive cursive control mechanism and recurrent neural network. Extensive simulators like SUMO and NS2 analyze the validity of this proposed model. The proposed analytical model provides a framework for examining the impact of mobility dependent metrics such as vehicle velocity, acceleration/deceleration, safety gap, vehicle arrival rate, vehicle density and network metric data delivery rate for characterizing the VANET connectivity of the proposed network. The simulation results synchronized those of the proposed model, which illustrated that the developed analytical model of this work is effective.

Fatigue life estimation of continuous girder bridges based on the sequence of loading

A need exists to determine the fatigue life of multi-span continuous bridges in the design stage. It is difficult to conduct a full-scale fatigue test of a bridge, hence the simulation of bridge-vehicle interaction dynamics is important to estimate the fatigue life of bridges. The vehicles entering the bridge are random in nature. In the present study, the arrival time of the vehicles is considered a random variable following Poisson process to simulate the actual traffic. The bridge-vehicle coupled system equations have been derived wherein the vehicle arrival rate appears as random variable casting difficulty in obtaining a direct solution. The solution approach has been devised using Orthogonal Polynomial Expansion method. Response statistics so obtained for a multi-span continuous bridge has been used in fatigue life estimation involving crack initiation phase and crack propagation phase modifying conventional linear damage rule. The sequence of loading is also considered in the modified fatigue formulation. The effect of the vehicle speed, road surface irregularity and the arrival rate of the vehicle on fatigue life estimation of the bridge have been studied.

Cooperative U-Turn Merging Behaviors and Their Impacts on Road Traffic in CVIS Environment

U-turn behavior of vehicle is one of the main causes of urban traffic congestion and accidents. A collaborative U-turn merging control algorithm is studied with collision avoidance and delay minimization for vehicles under Cooperative Vehicle Infrastructure System (CVIS) environment. Two control strategies, zip merging and platoon merging control, are proposed. The applicability of these two strategies is compared from the perspective of efficiency and driving comfort. The cellular automaton simulation system composed of a two-way four-lane traffic flow with a U-turn facility in middle of road is established with cooperative control algorithm imbedded. The influence of cooperative U-turn merging behaviors on traffic performance is evaluated by analyzing the arrival rates of main lane and U-turn vehicles and their relationship between one another. The simulation results show that the arrival rate of vehicles on target lane has a great impact on traffic delay. The cooperative control can improve the traffic flow only in the condition that the arrival rate of vehicles on target lane is less than 0.7. It provides some practical references for transportation agencies to meet efficiency requirements of the U-turn section when they apply cooperative control strategy.

Traffic Light Regulatory System Based on Fuzzy Algorithm Using Microcontroller

Basically, control system for traffic lights only perform control based on a fixed time. In fact, the arrival rate of vehicles at the intersection of the road is not always the same so of course congestion at the crossroads can not be controlled. This study presents a simulation control system which can perform automatic traffic light control based on vehicle arrival rate. In this control, the duration of the flame is not constant but follows the arrival rate of vehicles. The method used to control the flame duration is fuzzy logic algorithm with the Mamdani fuzzy reasoning using Matlab software. Test results based on the simulation of fuzzy logic in fuzzy MatLab toolbox show that the fuzzy logic algorithm can be used to meet the goal of optimal traffic control, the duration of a given time based on the arrival rate of vehicles. The higher rate of arrival of the vehicle, the longer the duration of a given time, and the lower rate of the arrival of the vehicle, the more briefly given time duration.

Connectivity Analysis of Vehicles in Highway with One Entry/Exit and One RSU

In this paper, we consider a unidirectional highway road with one entry/exit uniformly distributed on the road interval. One road side unit (RSU) is located on the position of the entry/exit. We build an analytical model to study the network connectivity problem. In building the analytical model, we take into account several parameters, such as vehicle arrival rate, vehicle moving speed, vehicle communication radius, RSU communication radius, highway road length and the probability of vehicles driving through the entry/exit. The analytical model is verified by using simulation tools.

Arterial Control Against Lane Occupancy Accidents Based on Discrete Traffic Flow Model

Due to oversaturated traffic condition, few models are capable of describing the complexity and control strategies are difficult to design. This article proposes an arterial coordination control for unsaturated and oversaturated traffic condition via discretization analysis model. The Robertson discrete formula is introduced to describe the discrete relationship between the upstream and downstream flow. The downstream vehicle arrival rate satisfies the cyclical relationship when the turning traffic flow is low. On this basis, the traffic parameters of the upstream and downstream can be calculated by the ‘look-up table’ method instead of the ‘recursion’ method in using the periodic array to save the intermediate variables in the model. As a result, the computation time significantly decreases. For unsaturated situation, delays are accumulated in each time period and reduced through adjusting offsets. For oversaturated traffic condition caused by lane occupancy accidents, green time is optimized by genetic algorithm after the road capacity decline is estimated. Simulation experimental results verify the effectiveness of the control strategies and the practicability of the proposed model.

A Distributed Control Method for Urban Networks Using Multi-Agent Reinforcement Learning Based on Regional Mixed Strategy Nash-Equilibrium

Urban network traffic congestion can be caused by disturbances, such as fluctuation and disequilibrium of traffic demand. This paper designs a distributed control method for preventing disturbance-based urban network traffic congestion by integrating Multi-Agent Reinforcement Learning (MARL) and regional Mixed Strategy Nash-Equilibrium (MSNE). To enhance the disturbance-rejection performance of Urban Network Traffic Control (UNTC), a regional MSNE concept is integrated, which models the competitive relationship between each agent and its neighboring agents in order to improve the decision-making process of MARL. The learning rate is enhanced with a self-adaptive ability to avoid a local optimal dilemma; Jensen-Shannon (JS) divergence is utilized to define the learning rate of the modified MARL. A two-way rectangular grid network with nine intersections is modeled via a Cell Transmission Model (CTM). A probability distribution mechanism, which can update the turn ratio of each approach dynamically and discretely, is established to represent the segmented route-decision process of the vehicles. The effectiveness of the proposed control method is evaluated through simulations in the grid network. The results show the influence of major disturbances, such as fluctuation of vehicle arrival rate, fluctuation of traffic demand (e.g. a rapidly rising flow and extreme changes in origin-destination distribution), and disequilibrium of traffic demand (e.g. different arrival flows at each boundary of the urban network), on the performance of the suggested control method. The results can be used to improve the state of the art in order to reduce urban network traffic congestion due to these disturbances.

RE-EVALUASI PENERAPAN SISTEM PENGUMPULAN TOL ELEKTRONIS DI INDONESIA

Pada tahun 2007 untuk pertama kalinya diterapkan sistem pengumpulan tol elektronis untuk mengatasi permasalahan antrian panjang pada gerbang tol, akan tetapi penerapannya hanya terbatas pada beberapa ruas tol saja yang ada di Indonesia. Setelah itu tahun 2017 Menteri Pekerjaan Umum dan Perumahan Rakyat mengeluarkan peraturan Nomor 16/PRT/M/2017 tentang Transaksi Tol Nontunai di Jalan Tol, tanggal 31 Oktober 2017 untuk menerapkan sistem pengumpulan tol elektronis di seluruh gerbang tol di Indonesia. Untuk itu perlu dilakukan evaluasi terhadap penerapan sistem transaksi elektronis yang telah diterapkan saat ini. Dari analisis didapatkan dengan sistem elektronis ini waktu transaksi rata-rata untuk GTO 3 detik dan GSO 3,6 detik sehingga memenuhi SPM Jalan Tol yaitu kurang dari 5 detik. Untuk hasil perhitungan kapasitas, gardu nirsentuh memiliki kapasitas yang paling besar dibandingkan GTO dan GSO. Serta untuk analisis antrian dengan kapasitas gardu yang lebih besar dibandingkan dengan tingkat kedatangan kendaraan pada seluruh tipe gardu maka tidak terjadi antrian di gardu. Disisi lain dengan diterapkannya sistem pengumpulan tol elektronis saat ini 86% responden merasa puas dan ada beberapa keuntungan yang didapatkan oleh operator tol seperti menurunnya biaya operasi gardu. Kedepannya BUJT telah melakukan persiapan untuk penerapan transaksi berbasis nirsentuh dengan melakukan koordinasi antar operator tol mengenai sistem dan proses teknologi yang akan diterapkan.

Estimation and Analysis of Vehicle Exhaust Emissions at Signalized Intersections Using a Car-Following Model

A signalized intersection is a high fuel consumption and high emission node of a traffic network. It is necessary to study the emission characteristics of vehicles at signalized intersections in order to reduce vehicle emissions. In this study, the combination of a car-following model and the vehicle specific power emission model was used to estimate the vehicle emissions, including the CO2, CO, HC, and nitric oxide (NOX) emissions, at unsaturated signalized intersections. The results of simulations show that, under the influence of the signal light, the substantial changes in a vehicle’s trajectory increase the CO2, CO, HC, and NOX emissions. The CO2, CO, HC, and NOX emissions from vehicles at signalized intersections were further analyzed in terms of signal timing, vehicle arrival rate, traffic interference, and road section speed. The results show that an increase in the signal cycle, the vehicle arrival rate, and the traffic interference amplitude result in increases in the CO2, CO, HC, and NOX emissions per vehicle at the intersection inbound approach, and an increase in the green signal ratio and the vehicle road section speed within a specified range has a positive significance for reducing the CO2, CO, HC, and NOX emissions of vehicles in the study range. The proposed method can be flexibly applied to the analysis of vehicle emissions at unsaturated signalized intersections. The obtained results provide a reference for the control and management of signalized intersections.

Vehicular Ad Hoc Network (VANET) Connectivity Analysis of a Highway Toll Plaza

The aim of this paper was to study issues of network connectivity in vehicular ad hoc networks (VANETs) to avoid traffic congestion at a toll plaza. An analytical model was developed for highway scenarios where the traffic congestion could have the vehicles reduce their speed instead of blocking the flow of traffic. In this model, nearby vehicles must be informed when traffic congestion occurs before reaching the toll plaza so they can reduce their speed in order to avoid traffic congestion. Once they have crossed the toll plaza they can travel on at their normal speed. The road was divided into two or three sub-segments to help analyze the performance of connectivity. The proposed analytical model considered various parameters that might disturb the connectivity probability, including traveling speed, communication range of vehicles, vehicle arrival rate, and road length. The simulation results matched those of the analytical model, which showed the analytical model developed in this paper is effective.

Connectivity Analysis of a Highway With One Entry/Exit and Multiple Roadside Units

This paper studies the connectivity problem of vehicles moving on a highway road and considers a one-way road scenario where there exist one entry and exit, and multiple roadside units (RSUs) equidistantly deployed along the road. A connectivity analytical model is derived for analyzing the connectivity probability, taking into account the existence of the entry and exit and the deployment of multiple RSUs. In the considered road scenario, the entry and exit is uniformly distributed on the highway road. At the entry and exit, a vehicle may enter or exit from the road, or drive through the entry and exit with a certain probability. In deriving the connectivity analytical model, the highway road is divided into several segments and the connectivity probability of each segment is derived based on probability distribution theory. The connectivity probability of the highway road is then derived based on the connectivity probability on each sub-segment. Moreover, several parameters that may affect the connectivity of the road are taken into account, including a vehicle's arrival rate and moving speed, the number of RSUs deployed on the road, and a vehicle's driving-through probability at the entry and exit. The derived analytical model is justified based on simulation results. It can be used to investigate the effects of major parameters on the connectivity probability of a highway road, which is useful for the deployment of RSUs in such scenarios.