Vehicle Delay Research Articles

Based on MOPSO Algorithm of Real-Time Traffic Signal Optimization Control for Intelligent Transportation Intersections

In order to improve the traffic efficiency of intersections, this paper establishes a multi-objective optimization model with the minimum real-time delay time and maximum capacity as the optimization objectives by applying multi-objective particle swarm optimization algorithm, and simulates the actual intersections. By optimizing the multi-objective model, a set of Pareto optimal solution sets can be obtained, and the optimal timing scheme can be determined by using multi-attribute decision-making algorithm and real-time update of signal timing configuration parameters to achieve dynamic optimization of signal timing. The simulation model of city road intersection is established by SUMO software. By using multi-objective particle swarm optimization algorithm to optimize the intersection simulation model, the traffic capacity of the simulated intersection has been greatly improved, with the average traffic capacity increasing by about 3.69% and the average vehicle delay time decreasing by about 21.35%.

A nearly throughput-maximum knotted intersection design and control for connected and automated vehicles

Traffic at urban intersections constitute a series of complex conflicting vehicular movements and contribute greatly to the problems of traffic congestion and air pollution. The emerging of connected and automated vehicle (CAV) technologies inspires innovative ideas in traffic management at intersections; it not only enables new control paradigms, but also allows for possibilities to revolutionize the geometric layouts of intersections. This study proposes a novel intersection design called knotted intersection (KI), to resolve the complexity of conflicting relations at intersections in a full CAV environment. This new design is associated with a set of neat control rules for vehicles to realize the smooth traffic operation at these intersections. The design problem of intersection geometry and control strategy is optimized jointly and formulated as a mixed-integer linear program (MILP), and some basic theoretical properties of KI design are derived, including nearly throughput-maximizing property and bounded within-intersection delay of vehicles. Furthermore, the KI design is then extended to a road network composed of multiple intersections to improve the overall efficiency. The optimal design of multiple knotted intersections (MKI) is developed to coordinate the traffic organization methods among intersections and a two-level solution method is proposed to solve the optimization efficiently. Numerical and simulation experiments are conducted at both the intersection level and network level under various cases, and the results validate the superior performance of the proposed methods compared to classical traffic signal control (TSC) strategies.

Are facilities to support alternative modes effective in reducing congestion?: Modeling the effect of heterogeneous traffic conditions on vehicle delay at intersections

Multimodal facilities are being built in a majority of urban areas to accommodate both motorized and non-motorized traffic. The resulting transportation system is susceptible to complex interactions between different modes and users. These complex interactions are hard to quantify and capture on a regular basis. There is a need to rely on a microsimulation platform to replicate such real-world scenarios and forecast future conditions. This study focuses on assessing the effect of heterogeneous traffic conditions involving multiple modes like light rail transit (LRT), walking, bicycling, and motorized traffic on vehicle delay at intersections using Vissim traffic simulation software. A 2.5-mile urban arterial corridor comprising of seven at-grade and two grade-separated signalized intersections along US-29 route in the city of Charlotte, NC, USA was chosen for analysis and modeling. Base simulation model was developed by replicating the traffic scenario for the year 2018 (without LRT and non-motorized traffic). External controllers like VisVAP and Viswalk were used to assign signal priority and model heterogenous traffic conditions. The vehicle operational performance of the corridor improved along the major street after the addition of the LRT. An increase in vehicle delay on the major street was observed with an increase in the non-motorized traffic. Contrarily, the operational performance of the cross-streets at at-grade intersections did not see any significant change due to the addition of non-motorized traffic. The proposed framework assists planners to assess the impact of adding a new transit system like LRT and associated non-motorized traffic on the urban corridor.

Research on Dynamic Modeling Measurement and Control of Cable Traction Devices for Electro-Optical Unmanned Systems

In order to realize the high-precision variable direction cable control of the electro-optical unmanned system in non-electromagnetic remote control, a cable traction device measurement and control with characteristics of variable direction traction, rapid installation, and lightweight portability were proposed. Fan-shaped connect rod mechanism and U-shaped groove fixed pulley group were added to it, which can realize multi-direction traction without derailment on the basis of the cable limit and alleviate the cable fracture caused by mechanical wear. Introducing Euler transformation and analyzing the dynamics of the cable, the whole operation process, and the tension detection model was established. A Kalman Filter traction planning method was proposed to solve the problems of inertia delay and emergency stop of the unmanned vehicles after a sudden direction change. In order to verify the effectiveness, an experimental platform for the cable traction system of a 50kg wheeled and 150kg tracked unmanned system was built for simulation and experimental testing. The results show that the cable system has good dynamic variable traction, which can meet the multi-terrain control ability of an electro-optical unmanned system in a complex field environment.

Intelligent vehicle pedestrian light (IVPL): A deep reinforcement learning approach for traffic signal control

Deep reinforcement learning (RL) has been widely studied in traffic signal control. Despite the promising results that indicate the superiority of deep RL in terms of the quality of solution and optimality over fixed time signal control, the real-world multi-modal traffic flows, especially pedestrians, are not properly considered nor sufficiently investigated. This study presents a novel deep RL-based adaptive traffic signal model to control the vehicles and pedestrian flows by allocating an equitable green time to each, aiming at minimizing “total user delays” as opposed to “total vehicle delays” dominantly being used in the literature. Our proposed intelligent vehicle pedestrian light (IVPL) method can perform in the absence or presence of pedestrians, especially when there is jaywalking at the intersection, interrupting vehicle flows. To this end, an extended reward function is designed to capture delays due to vehicle-to-vehicle, vehicle-to-pedestrian, and pedestrian-to-pedestrian interactions, as well as red-light delays for vehicles and pedestrians. To evaluate the performance of IVPL, a microsimulation model of an intersection in city of Melbourne is used as a case-study. The real traffic signal parameters of an existing operation system (SCATS) are employed, and the simulation is calibrated using video-based camera data and loop detectors data collected at intersection. The experimental results demonstrate the superiority of the proposed model over fully actuated traffic signal, not only in terms of the quality of optimal solution, but also considering the fact that the proposed model can minimize the “total user delays”.

A Two-Stage Optimization Method for Schedule and Trajectory of CAVs at an Isolated Autonomous Intersection

Autonomous intersection management has become a state-of-the-art control strategy customized for connected and autonomous vehicles. Combining the advantages of tile-based and conflict point-based approaches, this paper proposes a two-stage optimization method based on a developed intersection modeling approach. The first stage is a timing schedule optimization model, assigning vehicle arrival times at an intersection. Based on the output of the first stage, the second stage is a trajectory optimization model, which gives the eco-driving strategies. Moreover, a rolling optimization with a variable cycle length is adopted to run the method continuously. Simulation results show that the proposed method outperforms the genetic algorithm-based method in terms of computation time, and can reduce vehicle delay and fuel consumption by 89.48% and 46.84%, respectively, under different traffic demands compared to the first-come-first-serve method. Furthermore, the performance of the proposed method under asymmetric traffic demand is discussed. Sensitivity analyses suggest that (1) a long cycle length benefits the proposed method within certain limits and (2) a proper deceleration within the intersection can balance traffic delay with fuel consumption. In addition, an additional model with a heuristic rule is compared with the original timing schedule optimization model. It is found that reducing binaries in the first stage can make a tradeoff between the quality of the solution and efficiency, which can be used in conjunction with long cycles.

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.

Space-Time Resource Integrated Optimization Method for Time-of-Day Division at Intersection Based on Multidimensional Traffic Flows

Based on the change trends of traffic flow in different controlled directions at an intersection, the space-time resource integrated optimization method for TOD (time-of-day) division based on multidimensional traffic-flow data is proposed in this paper. By analyzing the traffic-flow data of 8, 4, 2, and 1 dimensions commonly used at the intersection, the dynamic Fisher algorithm is used to complete the time segment division of the traffic-flow sequence of different dimensions. On this basis, the preliminary TOD division is completed, and the phase timing and lane-use assignment corresponding to the preliminary time periods are optimized. Then, the adjacent time periods are merged and tested to complete the final result of the TOD division. In order to verify the effectiveness of the proposed method, the schemes based on traffic-flow data of different dimensions are carried out by using the data at an actual intersection in Wuhu City, and the total and average vehicle delays of different schemes throughout the day are evaluated by VISSIM. The results show that the more dimensions of traffic flow data are adopted, the more refined the TOD division scheme is, and the less the total delay and average delay at intersections throughout the day are. In particular, the TOD division scheme after further optimizing the lane-use assignment can further reduce the total and average vehicle delay throughout the day. It shows that the method using multidimensional traffic-flow data at an intersection to carry out the integrated optimization of TOD division, lane-use assignment, and phase timing has good applicability.

RMS: A Delay Sensitive Road Monitoring System Using Edge Intelligence

Smart vehicles equipped with onboard sensors can detect the surrounding cars, cycles, pedestrians, and other objects in real time and can make control decisions to achieve road safety. The high dynamism of vehicular mobility switches base stations in their trajectory, and at an instant, one edge server services one base station only. So, making control decisions by processing and transmitting vehicular data in real time is challenging. In this article, we propose a road monitoring system (RMS) in which moving vehicles collect road data and offload collected data to the paired edge server. The edge devices and connected vehicular networks receive road-hindering alerts. It comes up with Road Ambient Intelligence that supports ubiquitous computing and generates context-aware alerts with low latency. It uses a deep learning model for the decision-making about road-hindering alerts and a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> -nearest neighbor algorithm to form clusters for the distribution of alert messages. For intense occurrences, the data are sent to the cloud server for further notifications to remote-control offices. The proposed study is compared with social vehicle route selection (SVRS) and delay tolerant processing (DTP) schemes. The performance analysis shows that rms presents 12%–44% better performance compared to the SVRS scheme and 15%–53% better compared to the DTP scheme in terms of delay. The energy requirement analysis shows that compared to SVRS, RMS involves 50% less energy when processed at edge clouds, and DTP involves 51%–65% more energy requirements compared to the RMS scheme.

Effect of Signal Coordination on the Traffic Operation of Urban Corridor

The severity of traffic congestion has increased in Baghdad city and influenced the public’s perception of the community. Extended travel time is experienced by users of the urban street system, so optimal traffic operation with a coordinated traffic signal system becomes necessary. Also, it is needed to alleviate congestion and progress traffic movement along the urban corridor. This study aims to evaluate and optimize traffic signal timing for selected intersections on Palestine arterial corridor and apply the coordinated signal system to reduce the users’ travel time on the selected urban corridor. Analyzing and evaluating congested signalized intersections using Synchro (ver.9) (Al-Nakhala intersection, Al-Sakhra intersection, and Beirut intersection) were performed. Also, their adopted strategies for improving traffic performance and reducing delays were provided. The overall assessment in terms of the level of service for the current traffic states is (LOS F) with an average control delay of (197.2, 166.8, and 262.3) sec/veh. for the Al-Nakhala, Al-Sakhra, and Beirut intersections respectively. The queue length appears after two cycles, becoming more severe congestion at intersections under oversaturated traffic conditions. The performance operation efficiency improved by reducing the control delay from (197.2 to 88) sec/veh, (166.8 to 46) sec/veh, and (262.3 to 76) sec/veh for the Al-Nakhala, Al-Sakhra, and Beirut intersections respectively. Even at high volume and oversaturated conditions, the blocked intersections were effectively alleviated. Finally, it was observed that the proposed signal coordination, built on standard actuated control significantly performed along the urban corridor, reducing vehicles’ delay. However, there are still concerns regarding the flow-to-capacity ratio (v/c ratio is still greater than 1), and the level of service is still in poor conditions (LOS E) for Beirut and (LOS F) for Al-Nakhala intersections. The application of signal coordination improved traffic progression by reducing travel time, and vehicle delay and alleviating blocked intersections.

Centrality-based lane interventions in road networks for improved level of service: the case of downtown Boise, Idaho

Recent advancements in network science showed that the topological credentials of the elements (i.e., links) in a network carry important implications. Likewise, roadway segments (i.e., links) in a road network should be assessed based on their network position along with traffic conditions at a given geographic scale. The goal of this study is to present a framework that can identify and select critical links in a road network based on their topological importance such as centrality, and the effects of systematic interventions conducted on such links in improving overall system performance (vehicle delay, travel time) to provide an adequate level of service (LOS). A real-world road network (Boise downtown) is investigated by applying lane interventions on roadways experiencing high congestion. Microscopic traffic simulation and analyses are conducted to estimate the traffic flow parameters hence the performance of the road segments. The findings of this study show that interventions applied to critical and congested road segments improve the serviceability from LOS F to LOS E as well as from LOS D to LOS C. Besides, reduced travel time and vehicular delay (after applying intervention on critical components) are also observed for high demand OD pairs of the road network. As such the proposed framework has the potential to incorporate the topological credentials with traffic flow parameters and improve the performance of the road network. This systematic approach will help traffic managers and practitioners to develop strategies that enhance road network performance.

ОЦІНЮВАННЯ ЕКОЛОГІЧНОГО РИЗИКУ ЗАБРУДНЕННЯ НАВКОЛИШНЬОГО СЕРЕДОВИЩА АВТОМОБІЛЬНИМ ТРАНСПОРТОМ

Assessment of the quality of traffic management and design solutions in the field of traffic management in cities, complex systems for organizing the movement of cities with a population of more than 100 thousand people residents, temporary schemes of organization for the period of overlapping of significant sections of the street network is combined with the need to take into account a large amount of data to resolve contradictions of uncertainty of an objective and subjective nature. Taking into account the variety of factos to assess the effectiveness of the organization and management of traffic is possible only for small sections of the street network using advanced information technologies to improve the quality of automated traffic management through the implementation of optimization principles. The effectiveness of traffic management can be assessed by many factors that depend on its management. As an objective function of traffic management, a number of authors suggest using the following values: the number of road accidents, socio-economic damages from road accidents, the amount of harmful substances, the total travel time along the route, the number of stops per trip, the skip rate, the average delay of the crew per cycle, the average downtime, connection speed, traffic intensity, etc. The proposed calculations of the amount of the total risk and the average length of a person's life, which use basic normative data, allow to give a quantitative assessment of the danger of atmospheric air pollution. In this regard, environmental risk can be applied as an objective function of traffic management. As can be seen from the above results, both the environmental risk, and the time the car travels from one point to another, and fuel consumption are determined depending on the delays of vehicles in front of regulated intersections. Therefore, it is advisable to recommend as a target function for optimizing traffic management the value of the total time of vehicle delays in front of intersections of the urban street network in one cycle of regulation.

Exit transit control at objects of traffic attraction as a mobility service

The modern development of transport and road engineering is aimed at the design of transport systems. The sustainable development of territories cannot be imagined without the appropriate transport information content, which includes the services of intelligent transport systems. Management of transport demand and mobility based on a service approach is the future of transport systems, affecting the quality of society development. A conscious perspective of intelligent transport systems (ITS) projects is the development of mobility services. One of them is providing road users with information that encourages them to take a certain action, resulting in a spatial or temporal redirection of traffic flows. A specialized ITS subsystem that controls traffic near objects of traffic attraction by informing about the place of comfortable waiting for the exit and the time of comfortable departure from this object is understood as a system of motivational control of exit transit. The system under consideration is formed in order to prevent a decrease in the capacity of the road in the area of operation of this object and is not intended to reduce the total intensity of the traffic flow at the exit from the object. It provides only a temporary redistribution of exit flows of road users from the object of traffic attraction and the coordination of the moments of these exits in accordance with the current (and predicted) load level of the main highway. Delays of vehicles and the value of unsatisfied demand are taken as performance indicators.

Leveraging Autonomous Vehicles to Tally Cooperative Driving Behavior

The number of Autonomous Vehicles (AVs) coexisting with conventional human-driven vehicles is expected to increase significantly in the coming years. This coexistence will last decades before full AV adoption is achieved worldwide. However, the cautious nature of AVs and the aggressive behavior of some human drivers could create unprecedentedly challenging scenarios for AVs, such as being stuck on merge lanes and blocked by human-driven vehicles. On the other hand, the cooperative behavior of other human drivers could assist AVs in avoiding deadlock situations. In this paper, we propose to leverage AVs to tally the cooperative driving behavior of human-driven vehicles. To this end, we model cooperative driving behavior in a “highway merge” scenario, which tends to be challenging for AVs. We vary the percentage of cooperative human-driven vehicles and estimate the percentage of AVs required to tally cooperative acts. Results show that when fifty percent of the human drivers cooperate, cooperation leads to statistically significant reductions of up to 68%, 46%, 38%, and 5% in stop delay, number of stops, vehicle delay, and travel time, respectively. Finally, we demonstrate that a 30% penetration of AVs is sufficient to tally up to 78% of cooperative behavior in highway scenarios. To promote cooperation across the population, our future work revolves around the construction of vehicular profiles based on their cooperative behavior. These profiles will be regularly updated and disseminated among AVs to aid their cooperative decisions toward human-driven vehicles in the upcoming interactions.

Optimal Traffic Signal Control of Isolated Oversaturated Intersections Using Predicted Demand

This paper tackles the optimal traffic signal control of isolated oversaturated intersections. An analytical signal control algorithm is proposed to find the global optimal signal timings with dynamic cycle lengths and phase splits to minimize the vehicle delay throughout the oversaturation period at a generic multi-phase junction. The traffic dynamics are modelled based on the kinematic wave theory and the predicted traffic flows. Moreover, spillback avoidance is incorporated during the queue formation oversaturated regime by adopting a mixed delay and probability of spillback objective function. Microsimulation experiments demonstrate the optimality, practicality, and robustness to system uncertainties of the proposed signal control method. The results pinpoint over 63%, 55%, and 40% reduction in total vehicle delay by implementing the proposed signal control respectively compared to an optimal fixed-time, actuated, and capacity-aware max pressure signal control methods.

Research on the Conflict Between Pedestrians and Right-turning Vehicles at Signal Intersections Based on Psychological Level

Urban roads play an important role in daily life, and signal intersections, as an important nodes of urban roads, are the main place of traffic conflict. During turns, there are frequent traffic conflicts between right-turning vehicles and pedestrians at specific stages. This conflict will lead to the acceleration, deceleration, and parking of right-turning vehicles and the delay of right-turning vehicles, which will affect the efficiency of the entire intersection and threaten the personal safety of pedestrians crossing the street. This paper adopts the combination of video and questionnaire survey, by observing the signal intersection pedestrian and right driver behavior, then the questionnaire, analyzing the psychological traffic participants, find out the real reason for the connection between the behavior and the psychological, microanalysis signal control road intersection right and pedestrian traffic conflict principle.

Increasing public transport system operation efficiency in the city of Košice - the case study

The paper deals with the urban public transport in the city of Košice and the proposed solution to traffic congestion, which causes delays for public transport vehicles. The biggest problem is the fact that the volume of cars used for individual transport is increasing in the city, and so the resulting congestions cause time losses for public transport vehicles. In the research, traffic data was collected to determine the one bus line experiencing the greatest travel time delays and the locations where the biggest time losses occurred were identified. In order to reduce these travel time delays, solutions and their application were proposed, which could reduce time losses and ensure high-quality urban public transport.

Safety and environmental benefits of intelligent speed bumps

Speed bumps are a common speeding prevention measure used to protect vulnerable road users, i.e. pedestrians and cyclists, near crosswalks in urban areas. They are also used to reduce traffic volumes, prevent overtaking, and allow a change in driving routine. However, conventional speed bumps have certain shortcomings, such as reduced driving comfort for all road users, potential vehicle damage and associated repair costs, delays for emergency vehicles and public transport vehicles, longer travel times and congestion, difficulties with snow removal in winter, the formation of ruts and potholes before or after such obstacles, and an increase in fuel consumption, traffic noise, and emissions of harmful gasses during braking and accelerating. Consequently, in recent years, intensive work has been done to solve the above problems by developing so-called intelligent speed bumps. Although evaluating the performance of these intelligent speed bumps in real-world environments is not yet widely available in scientific research, numerous patents have been filed in this field over the years. This paper provides an overview of several intelligent speed bumps that have been developed in recent years and discusses the results of investigations conducted on one such speed bump that is already widely used in practice.

Impact of autonomous vehicles on the performance of a signalized intersection under different mixed traffic conditions: A simulation-based investigation

Autonomous driving can overcome the limitations of stochastic human driving behavior. Therefore, implementing autonomous vehicles (AVs) could improve the efficiency of road networks. This study investigates the impacts of AV implementation on the performance of a signalized intersection considering a mixed traffic environment comprising regular vehicles (RVs) and AVs through microscopic traffic simulations. Accordingly, 24 scenarios with different AV implementation rates, AV driving models, and traffic volume conditions, were developed and evaluated using the Vissim simulation software. The results indicated that even partial AV implementation could improve the operational efficiency of a signalized intersection compared to full RV traffic. AV implementation reduced the vehicle delay, stopped delay, and queue length. The expected improvements are primarily based on the implementation rate, and are higher at higher rates (≥50%). The improvements are highest at moderate traffic volumes. Compared to the moderate level, partially replacing RVs with AVs at free-flow conditions does not significantly impact the performance of the intersection. Under congested conditions, the expected improvements from AV implementation are mitigated by the high traffic volumes. Considering the different AV models employed herein, the connected autonomous vehicle (CAV) model exhibited the best performance.

Analysis of the selected tram lines operation during the tram lines modernization project in the city of Košice - the case study

The sustainability of public passenger transport is a key aspect for ensuring efficient urban mobility. For this reason, transport systems need to be maintained at a level where they can deliver the required transport performance, quality and reasonable operating costs. Regular maintenance and modernization is a necessary condition for meeting these criteria. However, this process must be carried out in such a way that it does not significantly affect the quality of the transport services provided. The paper presents research aimed at analyzing the impact of the tram transport system reconstruction in Košice on the transport means capacity utilization and on the vehicles delay time monitoring. The research revealed the differences that existed before and during the reconstruction of the tram lines.