Priority Vehicles Research Articles

Implementation of Absolute Priority in a Predictive Traffic Actuation Schemes

Nowadays, the improvement of the emergency vehicles' priority is required to improve their response time. Presently, the emergency vehicles alert the road users using the sirens and lights, which might cause disturbances in the traffic or lead to accidents due to the unpredictability of the road users' behaviors. This paper introduces the priority indicator, which calculates the priority of several emergency vehicles as they approach an intersection and sort them in a way that allows granting priority to each one without causing delays neither for the emergency nor for the normal vehicles. The priority indicator is then introduced in a predictive traffic actuation program (DIRECTOR) that adjusts the signal timing in a dynamic way. Thus, this research aims to create a generalized priority form that simplifies granting the priority for emergency vehicles in a harmonized way in all over the Netherlands, making sure that it takes into consideration the several conditions of the intersection.

Density Cum Priority based Adaptive Traffic Light Control System

Advancement of technology and increase in population density expands the quantity of vehicles out. This in turn increases the traffic density, which necessitates the well developed traffic controller. This paper explains a microcontroller based traffic control system. To explain about the system a four way junction is considered. In addition to the normal traffic control system, two special cases are also handled in this system. The developed system is dealing problem of highly dense lane.IR sensors are used to detect the density of the vehicles. This system also help to avoid the unnecessary delay for the priority vehicles. RFID technique is used to identify the priority vehicles. An IOT WIFI module is used in this system to display the traffic signal status and to store the traffic data. This traffic data can be processed in future to design the improved adaptive control system

A 3-stage fuzzy-decision tree model for traffic signal optimization in urban city via a SDN based VANET architecture

One of the main challenges for developed cities is vehicle traffic and its management. Because of physical structures and cross roads of urban intersections, traffic flows may cause time delay, congestion, traffic accidents and more fuel/time consumption. For these reasons, there are many studies on traffic management systems which are a part of smart city applications in both literature and practice. In recent years, it seems that VANET (Vehicular Ad Hoc Networks) architecture has been preferred in these studies, which enables vehicles to easily communicate with each other or devices on the edge of the road and also to transfer the related traffic data to the center. On the other hand, there are many studies on a new network paradigm called SDN (Software Defined Networks) that solves problems such as performance, programmability, scalability, security and management difficulties in today’s traditional networks. Depending on all this, in this study, we will present an architectural proposal about how to use SDN and VANET network paradigms together in traffic management systems in order to use both existing intersection management system modules more adaptively and future traffic based services to be added in desired service quality without changing the communication infrastructure. Also in this study, a 3-stage fuzzy-decision tree model was proposed for traffic signaling which is the most important problems of urban traffic by focusing environmental factors (accident situation, priority vehicle transition etc.) and activity information (road construction, meeting, train and bus schedule etc. ) not only vehicle density unlike other signaling studies in literature. The proposed model also generates/sends a dynamic flow input to SDN agent vehicles and SDN agent RSU (Road Side Unit) in intersection for making VANET routing protocols (AODV-ad hoc on-demand distance vector, DSDV-destination-sequenced distance vector) selection automatically according to traffic incident and density. In order to measure the functionality of the SDN based VANET architecture and 3 stage fuzzy-decision tree model on it for the transmission infrastructure of the traffic management, performance tests were performed on different traffic and network scenarios on Adapazarı City Centre Model. SDN based VANET architecture was compared with traditional systems according to transmission infrastructure and also proposed 3-stage fuzzy-decision model was compared with signaling techiques in literature such as fixed-time signaling, Webster equation, ant colony algorithm and particle swarm optimization under same traffic and network scenarios. The results obtained from performance tests shows that the proposed 3-stage fuzzy-decision model has %15-17 better performance than fixed-time signaling and webster equation and also %9-11 better performance that particle swarm and ant colony optimizations in low density traffic scenarios. In high density and dynamic traffic scenarios these rates reach %20-22 compared to fixed-time signaling and webster equation and %14-15 compared to particle swarm and ant colony optimizations. In addition in this study, proposed SDN based VANET architecture was compared to traditional VANET ITS architectures within the same traffic and network scenarios. According to obtained results, it is shown that the proposed SDN based VANET has %30-40 better performance than traditional systems in end-end delay, throughput and packet loss rate criteria.

Tradable mobility permit with Bitcoin and Ethereum – A Blockchain application in transportation

Blockchain and its underlying technology have intrigued researchers with its promising applications and implications as “the second internet”. There is a wide range of Blockchain applications in transportation and logistics. In this paper, we present the basic principle of cryptocurrencies and Blockchain as well as Ethereum. This is followed by the potential applications of Blockchain in transportation, logistics, and supply chain industries in which the concept of a tradable mobility permit (TMP) to combat traffic congestion is formulated and numerically tested. We then discuss the deployment of the TMP scheme based on a Blockchain platform and its by-products such as dynamic toll pricing, priority for emergency vehicles, heavy truck platooning, as well as connected vehicles.

Effect Analysis on Emergency Vehicle Priority System for Securing Golden Time: Targeting on Cheongju City

Effect Analysis on Emergency Vehicle Priority System for Securing Golden Time: Targeting on Cheongju City

Single-Lane Roundabout Manager under Fully Automated Vehicle Environment

In the advent of new automation and communication technologies, the introduction of connected and autonomous vehicles (CAVs) can make efficient use of the space on our road networks. Since roundabouts suffer from lower efficiencies when traffic flows are unbalanced and unfamiliar drivers are present, CAVs have the potential to improve traffic operations, reducing lost time and inefficiency in gap-usage. The aim of this research is to take advantage of those recently available technologies to design a traffic management system for roundabouts. Such a system can provide CAVs with optimal trajectories to negotiate the roundabout, maximizing throughput and minimizing control delay. The rule-based Roundabout Manager algorithm developed considers the roundabout as a whole system, assessing the priority of incoming vehicles on a first-come-first-served scheduling to solve conflicts. The management system takes into consideration the geometry of the roundabout, including the flared entries and exits and the location of conflict sections based on merging trajectories of vehicles in negotiating the roundabout. To illustrate the operation of the algorithm, a total of 15 undersaturated demand scenarios with 10 replications per scenario were simulated. From the results, it can be concluded that the system can reduce control delay for medium demand scenarios, maximizing the throughput for all demand scenarios. The Roundabout Manager can work in real time providing optimized trajectories in less than 0.02 s at any traffic flow rate simulated.

Context-aware negotiation, reputation and priority traffic light management protocols for VANET-based smart cities

The traditional transportation system is based on a fixed-timed strategy to control the traffic congestion on urban roads. However, the increase of vehicle density in a smart city implies the variation and the conflict on the demand pattern of the drivers. The smart city development requires to create an efficient control plan for an intelligent traffic management system. In this paper, we aim to reduce the congestion at signalized intersections, and satisfy the needs of drivers according to their degree of displacement urgency. We use two optimization methods, namely the synchronization and the genetic algorithm ($$\hbox {GA}$$), where we develop three scheduling protocols. The first is the intelligent context-aware negotiation protocol ($$\hbox {ICANP}$$). This protocol allows the negotiating vehicles to cross the intersection. It enables each traffic light at the signalized intersection to negotiate the green time assigned to its phase. $$\hbox {ICANP}$$ uses $$\hbox {GA}$$ to optimize the crossing time in order to minimize the total waiting time of negotiating vehicles. Moreover, we introduce a negotiation protocol based on reputation, which minimises the congestion effect from incoming dishonest drivers. Finally, we propose an intelligent context-aware priority protocol ($$\hbox {ICAPP}$$), that considers the existence of priority vehicles. Upon arrival of at least one priority vehicle at the signalized intersection, $$\hbox {ICAPP}$$ interrupts the green time of negotiating vehicles. A series of simulation showed that the proposed protocols reduce the total waiting time and the emissions of $$\hbox {CO}_{2}$$ of vehicles at signalized intersection, in comparison with circular, $$\hbox {ITLC}$$ and $$\hbox {CATLS}$$ scheduling algorithms. Furthermore, formal complexity analysis and performance evaluation show the effectivity of our protocols.

A priority multi-channel coordination MAC protocol in roadside unit-assisted vehicular networks

This paper presents a priority-based RSU assisted multi-channel coordination MAC protocol (PRAMC) for vehicular ad hoc network (VANET). The paper provides the priority for vehicles in the RSU polling list in order to poll vehicles according to their priorities. So, vehicles can transmit the high priority and important messages before low priority ones. A vehicle includes its priority with the association request frame. After RSU receives the association request, it adds the vehicle to a polling list according to its priority. RSU in this situation is responsible for control and safety messages broadcasted and non-safety application. The proposed protocol in this paper is an enhancement to the previous RAMC MAC protocol where no priority messages were considered. Our simulation results show high throughput for non-safety applications as compared to previous works. In addition, the results achieve high delivery ratios for different priorities of emergency warning messages (EWMs) and status safety messages in different traffic densities.

Dynamic Traffic Light Timing Control System using Fuzzy TOPSIS Algorithm

Intelligent Traffic Light System with Dynamic timing control employs sensor and algorithm that has been design to solve the original problem of ordinary traffic light which is applied static timing for vehicle traffic flow control. Therefore to build a dynamic traffic light timing control system an algorithm and a sensor is a must. In this paper we proposed a Fuzzy TOPSIS algorithm to be used for traffic light timing control system based on real time quantity vehicle and vehicle classification. Using Fuzzy TOPSIS algorithm we can sets priority vehicle based on its parameter (in this paper we set to vehicle length). We can determine that the trailer truck gets more prioritize based on its length, the second priority would be bus, and the third one was car. Also using its coefficient we found the timing for each vehicle. For every trailer truck the timing would be 2.771552 seconds, for every bus the timing would be 2.581965 seconds and for every car would be 1.862602 second.

Smart Traffic Light based on IoT and mBaaS using High Priority Vehicles Method

Smart Traffic Light based on IoT and mBaaS using High Priority Vehicles Method

Smart Traffic Light based on IoT and mBaaS using High Priority Vehicles Method

Smart Traffic Light based on IoT and mBaaS using High Priority Vehicles Method

The Traffic Simulation of Regulated Road Network Using Navigation Systems

The paper presents the results of comparative studies of the selection of micromodels of traffic simulation on a regulated network. The accuracy of the calculated values of vehicle speed obtained from the models of catastrophe theory is shown. Based on model studies it was found that, depending on frequency of buses the optimal distance to the stop line changes, from which it is efficient to make decision on priority intersection. The paper estimates the probability of traffic light options with different volume of priority vehicles.

COMFORT CHARACTER OF LANDSCAPE FEATURES OF TRADITIONAL STREETS IN AMMAN, JORDAN

Fast expanding of urban development changes the street function and gives priority for vehicles, which effects the urban fabric and cultural life of the city. It makes walking in the street difficult and uncomfortable. Hence, this research aims to explore the influence of landscape features towards comfort character of traditional streets in Amman, Jordan. The case study was Rainbow Street in Amman, the capital city in Jordan. Mixed-method approach was used in this study, which involved direct observation (visual and behavioural) and user perception (survey and in-depth interviews) techniques. The data was analysed through thematic analyses for qualitative data and descriptive statistics for quantitative data. The results show that landscape features that contribute towards comfort character could be divided into two main categories, namely, pedestrian amenities and sidewalk. This should be taken into consideration in the design of the existing and future streets in Jordan.

COMFORT CHARACTER OF LANDSCAPE FEATURES OF TRADITIONAL STREETS IN AMMAN, JORDAN

Fast expanding of urban development changes the street function and gives priority for vehicles, which effects the urban fabric and cultural life of the city. It makes walking in the street difficult and uncomfortable. Hence, this research aims to explore the influence of landscape features towards comfort character of traditional streets in Amman, Jordan. The case study was Rainbow Street in Amman, the capital city in Jordan. Mixed-method approach was used in this study, which involved direct observation (visual and behavioural) and user perception (survey and in-depth interviews) techniques. The data was analysed through thematic analyses for qualitative data and descriptive statistics for quantitative data. The results show that landscape features that contribute towards comfort character could be divided into two main categories, namely, pedestrian amenities and sidewalk. This should be taken into consideration in the design of the existing and future streets in Jordan.

Optimising the public transport priority at road intersections

A lot of effort is put into improving the efficiency of transportation and the optimisation of the current traffic situations. Nevertheless, this will not be sufficient to deal with the increasing number of road users. Public transportation is an appealing economical solution, although its quality is dependent on the efficiency of traffic lights and congestions. The aim of this study is to investigate the impact of public transport (PT) priority on the performance of a single road intersection with two two-way crossing streets and a dedicated tram line. In this perspective, the authors set up a microscopic simulation experiment to evaluate different PT priorities. The study is applied to a road intersection in Ghent (Belgium) and all relevant inputs are based on real-life data. Overall, the total travel time of all actors advocate for traffic light control regulations that accommodate regular road users at the expense of PT and contradict the current priority settings of the signal control system. However, the passenger-dependent travel times give a slightly nuanced view advocating a delayed priority or even no priority for PT vehicles only during the evening peak.

IoT ENABLED TRAFFIC CONTROL MODEL USING RASPBERRY PI

In this paper a new methodology is described to efficiently handle and managed traffic in a highly populated and congested area. The traffic management system’s framework make use of an essential technology required which is IoT .It also has other important parts such as an autonomous activity controller raspberry-pi, pi-camera, RFID ,IR sensors .To further help to navigate the traffic the proposed framework uses decisive algorithm and round-robin algorithm to find the Optimum path through traffic. Raspberry pi is used to manage all components collectively and individually. Total traffic in a region is determined by the help of IR sensors which uses RFID to distinguish high priority vehicles such as ambulance and VIPS from day to day traffic. There is an additional benefit of using RFID it can be used to locate the robbed or snatched vehicles. The proposed framework has two major parts i.e autonomous and manual. The algorithm used to navigate traffic play a vital part in making the proposed framework work efficiently.

Microscopic Simulation and Optimization of Signal Timing based on Multi-Agent: A Case Study of the Intersection in Tianjin

The purpose of this paper is to optimize the signal timing through multi-agent simulation technology. Firstly, a conceptual model of the actual intersection is described. Secondly, the social dynamics model of the vehicle and pedestrian evolution rules are established from the micro perspective, which is simulated respectively by Anylogic and Synchro on this basis. Finally, the signal timing strategies for the different vehicle priorities are discovered through the heuristic algorithm. The case study shows that: ①The actual signal timing is not reasonable. ②The optimization strategies of signal timing can improve traffic efficiency. ③By comparing the signal timing strategies of different vehicle priority, the study shows that the Anylogic is more superior to the Synchro, which provides a new way to solve the traffic congestion.

A New Cell Transmission Model with Priority Vehicles and Special Lanes

Abstract Daganzo (1997) proposed a kinematic wave model of a traffic system with priority vehicles and special lanes, where the priority vehicles can use both regular and special lanes, but the regular vehicles can only use the regular lanes. Further in Daganzo et al. (1997), the Incremental Transfer (IT) principle was applied to devise a Cell Transmission Model to numerically solve the model. In this paper we first derive the fundamental diagram of a traffic system with priority vehicles and special lanes based on Wardrop’s user equilibrium principle and then show after transforming the variables that there exist two auxiliary Lighthill-Whitham-Richards model, which can be used to define the demand and supply functions. We present a new junction flux function for the Cell Transmission Model, which is simpler than the IT principle, and more importantly, is a lane-based formulation. Comparing the proposed fluxes with the Godunov (or IT principle) ones analytically, we identify the cases that they are different. Nevertheless, with numerical experiments, we demonstrate that they are consistent in all the cases in the sense that the stationary states of both models are identical. Finally, we show numerical examples that demonstrate the IT principle is not invariant by using a non-triangular fundamental diagram.

EVP-STC: Emergency Vehicle Priority and Self-Organising Traffic Control at Intersections Using Internet-of-Things Platform

This paper presents an Internet-of-Things-based platform for emergency vehicle priority and self-organised traffic control (EVP-STC) management at intersections. With the increasing number of automobiles, traffic jams in urban areas are becoming a critical issue. Traffic jams, especially those at intersections, not only increase delays for drivers but also increase fuel consumption and air pollution. We propose a novel platform and protocol called EVP-STC that contains three main systems. The first system, called the intersection controller, is installed at traffic lights and collects emergency vehicle position information and vehicle density data at each road segment approaching an intersection. The intersection controller then adjusts the timings of traffic lights based on detected real-time traffic. The second system is installed at each road segment and contains force resistive sensors to detect vehicles. It transmits the detected information to the intersection controller via ZigBee. The third system is installed in emergency vehicles and provides GPS coordinates to the intersection controller to avoid any waiting time for emergency vehicles at intersections. Simulation results demonstrate the effectiveness of the proposed platform, which minimises total delays, lane opening times, and waiting times for emergency vehicles.

Closed-form multiclass cell transmission model enhanced with overtaking, lane-changing, and first-in first-out properties

A novel multiclass macroscopic model is proposed in this article. In order to enhance first-in, first-out property (FIFO) and transmission function in the multiclass traffic modeling, a new multiclass cell transmission model with FIFO property (herein called FM-CTM) is extended from its prior multiclass cell transmission model (M-CTM). Also, to enhance its analytical compactness and resultant computational convenience, FM-CTM is formulated in this paper asa set of closed-form matrix equations. The objective is to improve the accuracy of traffic state estimation by enforcing FIFO property when a fast vehicle cannot overtake a slow vehicle due to a limitation of a single-lane road. Moreover, the proposed model takes into account a different priority for vehicles of each class to move forward through congested road conditions, and that makes the flow calculation independent from their free-flow speeds. Some hypothetical and real-world freeway networks with a constant or varying number of lanes are selected to verify FM-CTM by comparing with M-CTM and the conventional CTM. Observed densities of VISSIM and real-world dataset of I-80 are selected to compare with the simulated densities from the three CTMs. The numerical results show that FM-CTM outperforms the other two models by 15% of accuracy measures in most cases. Therefore, the proposed model is expected to be well applicable to the road network with a mixed traffic and varying number of lanes.