Traffic Intersection Research Articles

Signal Control Study of Oversaturated Heterogeneous Traffic Flow Based on a Variable Virtual Waiting Zone in Dedicated CAV Lanes

To meet the demand for cooperative signal control at oversaturated heterogeneous traffic flow intersections containing CAVs and HVs, cooperative control including dedicated CAV lanes has been explored to improve intersection safety capacity and reduce vehicle delays while avoiding uncertain HV driving behaviour. However, this approach does not fully exploit CAV network connectivity advantages and intersection spatial and temporal resources. Here, an oversaturated heterogeneous traffic flow signal control model based on a variable virtual waiting zone with a dedicated CAV lane is proposed. Within the model, CAVs going straight or left share a dedicated CAV lane, a CAV variable virtual waiting zone is within the intersection ahead of the dedicated CAV lane, and CAVs and HVs share the straight-through lane. The model framework has three layers. The upper layer optimizes the barrier time using a rolling time domain scheme. The middle layer optimizes the phase duration and variable virtual waiting zone switching time based on the fixed phase sequence, returning the vehicle delay to the upper optimization model. The lower layer performs CAV grouping and trajectory planning in the dedicated CAV lane based on signal timing and variable virtual waiting zone duration, returning the CAV delays to the middle level.

Characterization of organic contaminants associated with road dust of Delhi NCR, India.

Hydrophobic organic contaminated polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and CHNS (carbon, hydrogen, nitrogen and sulphur species) are explosively associated with road dust particles. A few organic contaminants are toxic in nature and have an unpleasant effect on human health. The International Agency for Research on Cancer (IARC), the US Department of Health and Human Services (HHS) and the United States-Environmental Protection Agency has considered several PAHs and PCBs as carcinogens for human beings. In the proposed study, the anthropogenic contaminants present in road dust were assessed in six representative diversified sites i.e. industrial, commercial, office, residential, construction and traffic intersection in Delhi NCR, India. Roadside dust samples were gathered in premonsoon, monsoon and postmonsoon seasons and characterized for PAHs, PCBs and CHNS. The concentration of total PAHs (16 Nos) and PCBs (6 Nos) of the selected sites ranged from 0.27µg/kg to 605.80µg/kg and 0.01µg/kg to 41.26µg/kg, respectively. The Fourier transform infrared spectroscopy-attenuated total reflectance study suggested that the presence of O = C = O, Si-O, carbonyl, acidic or aliphatic esters group were associated with road dust particles. Hydrogen and sulphur concentrations were not detected in the selected road dust samples. Carbon and nitrogen concentrations varied from 2.24% to 16.82% and 0.69% to 14.5%, respectively, seasonally. In the premonsoon season, road dust was distinguishably contaminated as compared to monsoon and postmonsoon season, whichmight be due to movement of contaminated road dust from adjacent locations. It was perceived that Delhi NCR organic contamination inroad dust was much below as compared to other countries. It may be concluded that due to the presence of significant amounts of carbon and nitrogen concentrations in the road dust, to a greater extent, road dust can be fertile and might be advantageous for green belt development to mitigate air pollution. The utilization of road dust will further bring down the burden of landfill sites and may lead towards sustainability.

Improving pedestrians’ navigation safety at night by enhancing legibility of foreground and background information on the display

Traffic intersections are dangerous areas for pedestrians at night, primarily when people use their mobile phones while walking; pedestrians’ line of sight switches between their phones and the environment, which causes inattentional blindness during emergencies. The salience of the foreground and background information is different by the lightness conditions; therefore, identifying the lightness level of the foreground and background is critical. In this study, the brightness of urban traffic intersection scenes in the nighttime was analyzed, and improved color tones of the navigation interface for enhancing information recognition were identified. Moreover, identify the balance of visual attention by adjusting lightness and color treatment between foreground and background information. A glance legibility experiment indicated that a warm color tone with contrast and gamma correction under a lighting value of 65 in the LAB color mode is the optimal recognition combination. The results of this study indicated that low gamma under high lighting effectively reduced glare-related distractions and resulted in the lowest error rate in background information recognition. This paper proposes increasing the visual attention of urban pedestrians during nighttime navigation through the balancing of the lighting of the foreground interface and the color treatment of the background. Navigating at nighttime can be safer when their attention toward the environment increases and decreases attention distraction.

A simulation model to study truck-allocation options

We present a discrete event simulator, TSJSim (Truck-Shovel JaamSim Simulator), for evaluating the stochastic and dynamic operational variables in a truck-shovel system. TSJSim offers four truck allocation strategies: Fixed truck assignment (FTA), Minimizing shovel production requirement (MSPR), Minimizing truck waiting time (MTWT), and Minimizing truck semi-cycle time (MTSCT) including the genetic algorithm (GA) optimization and the frozen dispatching algorithm (FDA) optimization rules. Multiple decision points along the haul routes for all the trucks close to the decision points were included in the model. The simulation results indicate that the trends associated with production tons and queuing time utilizing the four truck allocation strategies (MSPR, MTWT, FDA, and GA) all demonstrated similar patterns as the fleet size varied. As the system fleet size increased, the system production tons under these strategies at first increased significantly and then remained relatively constant; the queuing time relating to these strategies showed a positive relationship with the system fleet size. The bunching time decreased when the truck allocation strategies were applied in the model. In the simulated truck-shovel network system with multiple traffic intersections, by assigning the trucks at the intersections, both productivity and fleet utilization increased.

An Online Optimal Bus Signal Priority Strategy to Equalise Headway in Real-Time

Bus bunching is a severe problem that affects the service levels of public transport systems. Most of the previous studies in the field of Bus Signal Priority (BSP) and Transit Signal Priority (TSP) focus on reducing a bus delay at signalised intersections and ignore the importance of balancing the bus headways. However, since general BSP methods allocate uneven priorities for individual buses, the headways of bus sequences are prioritised or delayed randomly, increasing the likelihood of bus bunching. To address this problem and to improve the reliability of bus services, we propose an online optimisation model to determine the signal duration and splits for each traffic intersection and each signal cycle for bus priority. The proposed model is able to induce the signal timing back to a baseline when the BSP request frequency is low. Using the proposed model, a statistically significant reduction of 10.0% was achieved for bus headway deviation and 6.4% for passenger waiting times. The simulation-based evaluation results also indicate that the proposed model does not affect the efficiency of bus services and other vehicles significantly.

The impact of heavy metals that released from vehicles exhausts on some biochemical parameters in Eucalyptus and Ziziphus plants in street intersections of Baghdad city

The air pollution by vehicles exhaust is consider the most risk environmental problems, especially when precipitate on soil surface and transport to the plants and entering the food chain. so that, the current study was carried out to determine the impacts of air pollution on the plants growth in traffic intersections, the study was carried out in Baghdad city, identified two regions for each of the both sides of the Rusafa and Karkh by two main sites for each region, as well as, the secondary stations in each site. the heavy metals and total suspended particles concentrations were determined in the filter paper that suffer the pollution air for 30 min. in specific sites using sniffer device. The concentrations decrease of some pollutants was noticed more than to the national and global permitted limits and the summer was the highest season in pollution during study period. Eucalyptus and Ziziphus spina Christi plants was chosen to evaluating the impacts of pollution on the plants because its being of the most common and the evergreen trees in the Baghdad s' streets. Primary metabolites content in plants was measured as total chlorophyll recorded a height concentration in August(98.631mg/gm) in Eucalyptus leaves ,while the total protein content reached to maximum concentration (26.101 mg/gm) in both plants, either total carbohydrate content reached to (88ppm) in Eucalyptus leaves and (74.62ppm) in Ziziphus leaves and noticed that , the increase in concentration of pollutants affected on the protein and carbohydrate content. Seven phenolic compounds was diagnosed being one of the main secondary compounds of metabolism , the increase in total phenolic content was recorded in the region that have a high concentration of carbon dioxide was reach to (6699.88ppm) in Al-Mansour(3) samples compared to the control samples was(2388.87ppm). the heavy metals concentrations in the leaves of eucalyptus and ziziphus arranged from more to less as steady regime throughout the study period in the following order: iron > zinc > copper > lead .

Pollutant concentrations and exposure variability in four urban microenvironments of London

We compared various pollutant concentrations (PM1, PM2.5, PM10, PNC, BC) at four different urban microenvironments (MEs) in London (Indoor, IN; Traffic Intersection, TI; Park, PK; and Street Canyon, SC). The physico-chemical characteristics of particles were analysed, and the respiratory deposition doses (RDD) were estimated. Field measurements were conducted over a period of 121 days. The mean PM2.5 (PNC) concentrations were found to be 9.47 ± 7.05 (16366 ± 11815), 8.09 ± 4.57 (10951 ± 6445), 5.11 ± 2.96 (7717 ± 4576), 3.88 ± 3.06 (5672 ± 2934) μg m−3 (# cm−3) at TI, SC, PK and IN, respectively. PM2.5, PM10 and PNC exhibited a trend of TI > SC > PK > IN; higher concentrations for PM1 and BC were observed at IN than PK due to the emissions from printers, producing a trend of TI > SC > IN > PK. We observed 12%–30% higher fine PM concentrations at TI and SC sites during morning peak (07:00–09:30) than the evening peak hours (16:00–19:00); while IN showed a smaller variation in fine PM concentrations compared with outdoor TI, PK and SC sites owing to their prevalence in the IN for a longer time. Fine and ultrafine PM containing potentially toxic trace transition metals including Fe, Ti, Cr, Mn, Al and Mg were detected by high resolution electron microscopy at all sites. There was a similar relative abundance of different elements at the TI, IN and PK sites, which suggests a transport of PM between MEs. RDD for PM1 was highest (2.45 ± 2.27 μg h−1) at TI for females during running; PM2.5 and PM10 were highest at SC (11.23 ± 6.34 and 37.17 ± 20.82 μg h−1, respectively). The results show that the RDD variation between MEs does not follow the PM concentration trend. RDD at PK was found to be 39%–53% lower than TI and SC during running for all the PM fractions. Overall, the study findings show the air quality variation at different MEs and reveals the exposure inequalities around the city, which enable the management of personal exposure by selecting appropriate MEs for different activities.

Optimizing Traffic Light Green Duration under Stochastic Considerations

An optimization model for traffic light control in an urban network of intersections is derived. The model is based on store-and-forward analytic relations, which account for the length of the queue of waiting vehicles in front of the traffic light intersection. The model is complicated with probabilistic relations that formalize the requirements for maintaining short queues of vehicles. Probabilistic inequalities apply to each intersection of the city network. Approximations of probability inequalities are given in the article. Quadratic deterministic inequalities, which are part of the set of the traffic flow control optimization problem, are derived. Numerical simulations are performed, applying mean estimated data for real traffic in an urban area of Sofia. The model predictive approach is applied to traffic light optimization and control. Empirical results give advantages of the obtained model compared to the classical store-and-forward optimization model for the total number of vehicles waiting in the considered urban network.

Investigation of the discharge flow rate patterns at real-time traffic signal control intersections

This study investigates the effects of variable queue lengths and green times on discharge flow rates at real-time managed intersections in Mersin, Turkey. For this purpose, traffic flow data were collected at two different signalized intersections during morning peak hours for two days. The traffic data including the time headways, queue lengths for each cycle were derived from video records via MATLAB coding while the signal timing data were obtained from Mersin Metropolitan Municipality. The impact of variable queue lengths and green times on discharge flow rate were evaluated separately via analysis of variance (ANOVA) tests. The results indicated that time headways of the first vehicles in the queue were statistically larger than the time headways of the remaining vehicles in the queue (p-value<0.05). On the other hand, the time headways of the remaining vehicles in the queue were not found statistically different at 95 confidence level (p-value>0.05). Furthermore, the effect of the variable green time on discharge flow rate revealed that the significant difference was only observed for the first twelve seconds of the green time.

A Sensitivity-based Heuristic for Vehicle Priority Assignment at Intersections

This paper presents a sensitivity-based heuristic to address the dynamic priority assignment problem of connected and autonomous vehicle (CAV) and human-driven vehicle (HDV) at traffic intersections. We exploit sensitivity analysis tools to approximatively predict the CAV's performance violation as a function of the HDV states. Such predictions are then used to decide on a crossing order that preserves optimality and feasibility despite the behavior of the HDV. The proposed algorithm is compared with the baseline first-come, first-serve (FCFS) and mixed-integer nonlinear programming (MINLP) approaches. In the closed-loop simulation, we show that the heuristic is computationally much faster than MINLP and able to retain a close-to-optimal solution, which is far better than FCFS.

Analysis of stopping behaviour of cyclists at a traffic light-controlled intersection using trajectory data

Analysis of stopping behaviour of cyclists at a traffic light-controlled intersection using trajectory data

Impact of Delay and Queue on the Length of Left-Turn Storage at Palestine Intersections in Baghdad city, Iraq

At intersections, Left-turning vehicles seek to occupy the same physical space as close to the stop line as possible. These result in high conflicts, delays, and blockage of vehicles by turning vehicles and vice versa. The impact of the lengths of Left-turn lanes on intersection delays is considered to optimize the lengths of the Left-turn lanes. Data for traffic counts, queue lengths, and signal timing are collected from three intersections in Baghdad city in Iraq. The methodology involves the development of estimation models using traffic Simulation SIDRA INTERSECTION 8.0 and simulating various scenarios by varying traffic signal conditions to evaluate delays and queues caused by varying lengths of the Left-turn Lane. Optimal lengths are computed and compared to existing lengths in intersections. No differences in delay, queue, and lengths of the Left turn lane are found using t-test analysis for significance. Outputs from the three models were compared to the maximum observed in the field from the selected intersections. Data analysis involved determining the R2 and the standard error mean between the model output and the observed data. In general, SIDRA INTERSECTION 8.0 overestimated queue vehicles and length of storage for approaches with a high degree of saturation ratios and underestimated it for those with a high degree of saturation ratios.

Processing Traffic Jam in Al-Sadrain Intersection in the Holy City of Najaf

Modern metropolitan cities worldwide suffer from heavy congestion due to high daily commutes for various purposes. Intersections are the most congested component of the network and represent the sites of accidents. At the same time, the intersection (Al-Sadrien) in Al- Najaf Al-Ashraf city is regarded as one of the major important intersections. Typically, this intersection increases the volume of traffic during rush hours, which raises traffic congestion, Therefor, the problem with this article is that unclear how the distribution of the surrounding areas affects traffic accidents and junction congestion. Our hypothesis to solve the problem is that an important relationship must be clear between the intersection and its surrounding areas. In this study, analysis the current service of intersection as field survey adopting the analytical approach using simulation by HCS2010 and VISSIM software, based on GIS that showed: the eastern approach (coming from Al- Kufa) was (F) (3.18.97), the result of the western approach (coming from Najaf) (F) (3.45.49), and the result of the northern approach (coming from the College of Administration and Economics) (D) (1.38). 83) and the result of the southern approach (coming from Al- Rawan Street) (E) (1.14.13). When the times of delay to the level of service intersection, as adopted by the capacity of roads on the program (HCS 2010), amounted to more than (800) seconds/vehicle at peak times. So, the classification of service at this intersection is in level (E). Through the traffic intersection analysis, recommendations and proposals must be taken before any decisions regarding land use , which has effects on the city.

Traffic intersection crossing method for intelligent vehicles based on game theory

Traffic intersection crossing method for intelligent vehicles based on game theory

An IoT-Based Framework for Motion Planning of Connected Automated Vehicles at Signal-Free Traffic Intersections

An IoT-Based Framework for Motion Planning of Connected Automated Vehicles at Signal-Free Traffic Intersections

Fuzzy logic and deep Q learning based control for traffic lights

Traffic congestion is a major concern for many metropolises. Although it is difficult to regulate traffic flow because of numerous complexities and uncertainties, the traffic congestion problem must be mitigated in order to reduce the environmental problems related to traffic and the time lost on the roads in big cities. Intelligent traffic control methods, the use of which is increasing with the development of new methods, as opposed to conventional methods, and provide more efficient solutions, especially in traffic intersections with high traffic density. In this paper, we propose a new agent-based Fuzzy Logic assisted traffic light signal timing for traffic intersections. Deep Q-Learning algorithms and Fuzzy Logic Control (FLC) are used together in the proposed method. In this study, the proposed method and many traffic light control methods in the literature were simulated. In order to demonstrate the effectiveness of the proposed method, some of the important metrics of evaluation such as traffic congestion, air pollution, and waiting time were used in the assessment of the simulation results. In addition, with the proposed method, it has been shown that the stability and robustness of the system are increased.

Emissions Production by Exhaust Gases of a Road Vehicle's Starting Depending on a Road Gradient.

An increasing number of motor vehicles are connected with negative environmental impacts in relation to their operation. Among the main negative effects are exhaust gas emissions production. The annual increase in passenger cars and emissions from them deteriorates air quality daily. Traffic junctions also have a negative impact on increasing emissions production by exhaust gases. This situation may be caused by vehicle speed fluctuation, mainly when they get closer or leave. This study focuses on the emissions produced by exhaust gases after a road vehicle starts. The research was performed with a combustion engine vehicle on a route 30 m long. The vehicle was simulated in three different ways of starting (uphill, on ground level/plain and downhill). The values of carbon monoxide (CO), carbon dioxide (CO2), hydrocarbons (HC) and nitrogen oxides (NOX) were observed, as well as the vehicle's operation performance during start-ups. The research results showed that the lowest emissions production is when the vehicle is starting downhill. There, the emissions increased up to a distance of 9.7 m from the start. After reaching this distance, the emissions decreased and the vehicle speed continued to increase. While the vehicle started uphill, the emissions increased up to the distance of 16.8 m. After reaching this distance, the emissions began decreasing. Due to this fact, this type of testing is assessed as "the worst" from the emissions production point of view. The research demonstrates the relations between a road gradient representing starting on a plain surface and a vehicle's emissions produced by the exhaust gases. It is known that exhaust emissions are higher predominantly at junctions. They depend considerably on vehicle speed and driving continuity on a route. This research helps to quantify all the data and, thus, to provide a possibility of further solutions in the future as a tool for emissions reduction in cities and close to traffic intersections.

Urban traffic air pollution - case study City of Vranje, Serbia

The expansion of urban areas with unequal, rapidly growing population results in higher vehicle numbers in the cities. Traffic in the urban environment is one of the main concerns, since it is one of the most prominent sources of air pollution, connected to the mortality rate. Regarding the Sustainable Development Goals (SDG) and SDG 11, urban areas should meet environmental needs following the process of environmental transition. The Vranje city, Serbia follows the global trend of vehicle number increment. Regarding the specific geomorphological and climate conditions, it is of importance to emphasize the traffic air pollution control in the urban environment. Numerous studies found that vehicular exhaust emissions near traffic intersections are largely dependent on fleet speed, queuing time in idle mode with a red signal time, traffic-flow rate, ambient conditions, etc. Traffic management has the key role, especially regarding the intersection of traffic flows, since there are time losses on the intersections’ driveways that increase the energy consumption to overcome certain conflict flows. The scope of this study should point out the importance of traffic planning and management, especially at the traffic flows for reducing air pollution in the urban environment.

A Minimax Framework for Two-Agent Scheduling With Inertial Constraints

Autonomous agents are promising in applications such as intelligent transportation and smart manufacturing, and scheduling of agents has to take their inertial constraints into consideration. Most current researches require the obedience of all agents, which is hard to achieve in non-dedicated systems such as traffic intersections. In this article, we establish a minimax framework for the scheduling of two inertially constrained agents with no cooperation assumptions. Specifically, we first provide a unified and sufficient representation for various types of situation information, and define a state value function characterizing the agent's preference of states under a given situation. Then, the minimax control policy along with the calculation methods is proposed which optimizes the worst-case state value function at each step, and the safety guarantee of the policy is also presented. Furthermore, several generalizations are introduced on the applicable scenarios of the proposed framework. Numerical simulations show that the minimax control policy can reduce the largest scheduling cost by $13.4\%$ compared with queueing and following policies. Finally, the effects of decision period, observation period and inertial constraints are also numerically discussed.

A road network simplification algorithm that preserves topological properties

A road network can be represented as a weighted directed graph with the nodes being the traffic intersections, the edges being the road segments, and the weights being some attribute of a road segment. Such a representation enables researchers to analyze road networks in consistent and automatable ways from the perspectives of graph theory. For example, analysis of the graph along with the traffic demand pattern can identify critical road segments based on centrality measures. However, due to the complexity of real-world road networks and the computationally expensive algorithms, it is challenging to extend the such methods to a large-scale road network. In this paper, we present a simple yet efficient network simplification framework based on graph theory that sub-samples and simplifies the graph while preserving key topological characteristics in the original network. Our method iteratively identifies and removes network elements that do not contribute to transportation functionality, such as self-loops, dead-ends, and interstitial nodes that lies on the same road line. We applied this method to three small cities with distinct street patterns and one large city, and showed that topological characteristics in the original networks are preserved by comparing two distinct kinds of centrality distributions in the original and simplified networks.