Travel Delay Research Articles

A single-layer approach for joint optimization of traffic signals and cooperative vehicle trajectories at isolated intersections

A joint control approach that simultaneously optimizes traffic signals and trajectories of cooperative (automated) vehicle platooning at urban intersections is presented in this paper. In the proposed approach, the signal phase lengths and the accelerations of the controlled platoons are optimized to maximize comfort and minimize travel delay within the signal cycle, subject to motion constraints on speeds, accelerations and safe following gaps. The red phases are initially considered as logic constraints, and then recast as several linear constraints to enable efficient solutions. The proposed approach is solved by mixed integer linear programming (MILP) techniques after linearization of the objective function. The generated outputs of the MILP problem are the optimal signal timings and the optimal accelerations of all vehicles. This joint control approach is flexible in incorporating multiple platoons and traffic movements under different traffic demand levels and it does not require prespecified terminal conditions on position and speed at the signal cycle tail. The performance of the proposed control approach is verified by simulation at a standard four-arm intersection under the balanced and unbalanced vehicle arrival rates from different arms, taking the released traffic movement numbers, turning proportions, signal cycle lengths and the controlled vehicle numbers into account. The simulation results demonstrate the platoon performance of the joint controller (such as split, merge, acceleration and deceleration maneuvers) under the optimal signals. Based on the simulation results, the optimal patterns of trajectories and signals are explored, which provide insights into the optimal traffic control actions at intersections in a cooperative vehicle environment. Furthermore, the computational performance of the proposed control approach is analyzed, and the benefits of the proposed approach on the average travel delay, throughput, fuel consumption, and emission are proved by comparing with the two-layer approaches using the car following model, the signal optimization models, and the state-of-the-art approach.

PENGARUH KEEFEKTIFAN TRAFFIC LIGHT PADA SIMPANG BERSINYAL SIMPANG SURABAYA

Banda Aceh has unavoidable transportation problems, such as congestion on a number of roads. One of the areas with a fairly high level of congestion and becoming the center of attention is the Simpang Surabaya area, so the Aceh Government decided to build a traffic light at the Simpang Surabaya to prevent congestion and travel delays. The purpose of this study was to review the effectiveness after the presence of a traffic light which includes the performance of the road network and to determine the vehicle speed profile at the crossroads under review. The method used is the 1997 Indonesian Road Capacity Manual. The results obtained are the highest vehicle volume occurs on Monday at the peak hour of the highest vehicle at 07.00 - 08.00 WIB and 08.00 - 09.00 WIB on T. Hasan Dek road at 14976 Kend/hour . The results of calculations using the 1997 MKJI method obtained a total cycle time of 134 seconds and a yellow time of 3 seconds consisting of the T. Hasan Dek road with a red time of 44 seconds, and a green time of 90 seconds, while on the M. Hasan road for a red time of 83 seconds. , and the green time is 50 seconds. On the T. Imuem Lueng Bata road, the red light setting is 99 seconds and the green light is 35 seconds, and on the T. Chik Ditiro road, the red light is 110 seconds and the green time is 24 seconds. Keywords : Performance of Signalized Intersection, MKJI 1997

An optimal control-based vehicle speed guidance strategy to improve traffic safety and efficiency against freeway jam waves

Freeway jam waves create many problems, including capacity reduction, travel delays, and safety risks. The development of cooperative vehicle infrastructure system (CVIS) has prompted numerous new strategies, which can resolve jam waves by implementing microscopic car-following control actions to individual vehicles. However, most of those strategies aimed at eliminating freeway jam waves without considering the safety risks induced by the car-following control. This paper proposes an optimal control-based vehicle speed guidance strategy to improve both traffic efficiency and safety against jam waves. The optimal controller is developed based on a discrete first-order traffic flow model formulated in Lagrangian coordinates. The optimization of vehicles’ driving speed is formulated as a linear programming problem, where the constraints concerning threshold safety measures are imposed. The proposed vehicle speed guidance strategy is tested using a modified Intelligent Driving Model (IDM+), which represents real traffic dynamics in CVIS environment. The proposed speed guidance strategy is compared with a state-of-the-art jam-absorption driving strategy, which also aimed to eliminate freeway jam waves. Simulation results show that the proposed strategy outperforms that strategy in terms of both total time spent saving and surrogate safety measures’ reduction. The time exposed time-to-collision (TET) is reduced by 31%, and the time integrated time-to-collision (TIT) is reduced by 9.5% on average. Furthermore, the computation time of the linear optimization is only a few seconds, which is fast enough for the online application of the proposed strategy.

Bi-Level Coordinated Merging of Connected and Automated Vehicles at Roundabouts.

Traditional uncoordinated traffic flows in a roundabout can lead to severe traffic congestion, travel delay, and the increased fuel consumption of vehicles. An interesting way to mitigate this would be through cooperative control of connected and automated vehicles (CAVs). In this paper, we propose a novel solution, which is a roundabout control system (RCS), for CAVs to attain smooth and safe traffic flows. The RCS is essentially a bi-level framework, consisting of higher and lower levels of control, where in the higher level, vehicles in the entry lane approaching the roundabout will be made to form clusters based on traffic flow volume, and in the lower level, the vehicles’ optimal sequences and roundabout merging times are calculated by solving a combinatorial optimization problem using a receding horizon control (RHC) approach. The proposed RCS aims to minimize the total time taken for all approaching vehicles to enter the roundabout, whilst minimally affecting the movement of circulating vehicles. Our developed strategy ensures fast optimization, and can be implemented in real-time. Using microscopic simulations, we demonstrate the effectiveness of the RCS, and compare it to the current traditional roundabout system (TRS) for various traffic flow scenarios. From the results, we can conclude that the proposed RCS produces significant improvement in traffic flow performance, in particular for the average velocity, average fuel consumption, and average travel time in the roundabout.

A Trajectory Optimization Strategy for Connected and Automated Vehicles at Junction of Freeway and Urban Road

The phenomenon of stop-and-go traffic and its environmental impact has become a crucial issue that needs to be tackled, in terms of the junctions between freeway and urban road networks, which consist of freeway off-ramps, downstream intersections, and the junction section. The development of Connected and Automated Vehicles (CAVs) has provided promising solutions to tackle the difficulties that arise along intersections and freeway off-ramps separately. However, several problems still exist that need to be handled in terms of junction structure, including vehicle merging trajectory optimization, vehicle crossing trajectory optimization, and heterogeneous decision-making. In this paper, a two-stage CAV trajectory optimization strategy is presented to improve fuel economy and to reduce delays through a joint framework. The first stage considers an approach to determine travel time considering the different topological structures of each subarea to ensure maximum capacity. In the second stage, Pontryagin’s Minimum Principle (PMP) is employed to construct Hamiltonian equations to smooth vehicle trajectory under the requirements of vehicle dynamics and safety. Targeted methods are devised to avoid driving backwards and to ensure an optimal vehicle gap, which make up for the shortcomings of the PMP theory. Finally, simulation experiments are designed to verify the effectiveness of the proposed strategy. The evaluation results show that our strategy could effectively militate travel delays and fuel consumption.

Identification of Factors to Improve Public Transit Services (A Case Study of Prithvi Chowk to Talchowk Section of Prithivi Highway)

This research presents studies on a segment of highway to determine the quantitative factors that inuence transit services. Travel time and delay study is one of the method to determine quantitative factors. Tour time is described as the average period of time required to journey from one region to some other. Total departure time consists of gadgets which include total working time, places and general delay time. The examine section was done in Prithvi chowk to Tal chowk of Prithvi Highway which is turned to be 12.5 km long. Additionally, it has been found that the principle variables affecting travel time are: postpone time because of forestall selecting and choosing up passengers, bus model and bus size.32 trips public transport carrier and a 10 trips non-public automobile journey have been held during peak hours. Models are developed the use of SPSS software to become aware of the relationship between the causes of delays and the overall-time delays. Travel time and learning delays can help reduce the number of private vehicles operating and increase the number of public vehicles in order to reduce congestion and improve the e efficiency of the public transport system. It turned into determined that there was a full-size distinction in tour time among the use of the public transit services and the car.

Bi-level optimization of long-term highway work zone scheduling considering elastic demand

Purpose More and more work zone projects come with the needs of new construction and regular maintenance-related investments in transportation. Work zone projects can have many significant impacts socially, economically and environmentally. Minimizing the total impacts of work zone projects by optimizing relevant schedules is extremely important. This study aims to analyze the impacts of scheduling long-term work zone activities. Design/methodology/approach Optimal scheduling of the starting dates of each work zone project is determined by developing and solving using a bi-level genetic algorithm (GA)–based optimization model. The upper level sub-model is to minimize the total travel delay caused by work zone projects over the entire planning horizon, whereas the lower level sub-model is a traffic assignment problem under user equilibrium condition with elastic demand. Findings Sioux Falls network is used to develop and test the proposed GA-based model. The average and minimum total travel delays (TTDs) over generations of the proposed GA algorithm decrease very rapidly during the first 20 generations of the GA algorithm; after the 20th generations, the solutions gradually level off with a certain level of variations in the average TTD, showing the capability of the proposed method of solving the multiple work zone starting date optimization problem. Originality/value The proposed model can effectively identify the near-optimal solution to the long-term work zone scheduling problem with elastic demand. Sensitivity analysis of the impact of the elastic demand parameter is also conducted to show the importance of considering the impact of elastic demand parameter.

Travel Hopping Enabled Resource Allocation (THEResA) and delay tolerant networking through the use of UAVs in railroad networks

This paper investigates the use of unmanned aerial vehicles (UAVs)/drones for providing high data rates to mobile relays (MRs) placed on top of high speed train wagons, thus introducing the concept of Travel Hopping Enabled Resource Allocation (THEResA). The objective is to provide high data rate connectivity to train passengers in 5G+/6G networks. With the drone flying at the same train speed, highly directive beams can be formed and steered between the drone and each of the MRs. The simulation results in the paper show that this leads to high data rate connectivity, which will be reflected in the indoor links between the MRs and the train passengers inside the wagons. The drones maintain the connectivity to the cellular infrastructure by using high speed links with the cellular base stations (BSs) deployed along the rail track, e.g., through free space optics (FSO). The drones use the BS sites for recharging and resuming their operation. Therefore, a separate set of drones, or the same drones when they are not flying over trains, can be used to provide connectivity to remote rural areas. In fact, high speed trains might travel through rural areas with low population density. Although it is practical to lay fiber optic cables along the rail track, villages and small rural population agglomerations far from the railroad might not have access to the internet backhaul. UAVs can provide this connectivity in a delay tolerant fashion, by heading from the BSs/train station sites towards remote areas, collecting/transferring data from/to these areas, then returning to the sites along the rail track to recharge their batteries. This paper presents an analysis that shows the feasibility of this approach.

Who’s more angry? Comparing driver anger and aggression within work and personal driving contexts

Anger and driver aggression increase crash risk. However, how these manifest according to the purpose of the journey (work vs personal) and the unique relationships between sources of anger and aggressive expressions of that anger is under-researched. The current study examined the relationships between different types of anger and aggression, recent crashes and infringements between drivers who drive mainly for work with those who drive mainly for personal reasons.Participants (N = 630) completed an online questionnaire reporting their driving anger tendencies across situations of travel delays, danger and hostility from others, frequency of aggressive driving (using the vehicle, verbal or physical) and crash and infringements in the previous year. Drivers were classified as work or personal drivers based on the percentage of the time they drove for each reason. Relationships between anger sources and aggression types were examined using Structural Equation Modelling, comparing models between the two groups. The relationships between aggression and safety outcomes were explored using Mann-Whitney U tests.The relationships between anger and aggression were similar across work and personal drivers. However, some group differences in the situations that contributed to anger and aggression were identified. Aggression was more frequent for drivers who drove mainly for work and had received a traffic violation, compared to those who had not received a traffic violation.These findings can inform the development of targeted interventions to manage the triggers of anger and aggression. Interventions are likely to impact work and personal drivers; thus, could target employers and road transport authorities.

Optimizing coordinated vehicle platooning: An analytical approach based on stochastic dynamic programming

Platooning connected and autonomous vehicles (CAVs) can improve traffic and fuel efficiency. However, scalable platooning operations require junction-level coordination, which has not been well studied. In this paper, we study the coordination of vehicle platooning at highway junctions. We consider a setting where CAVs randomly arrive at a highway junction according to a general renewal process. When a CAV approaches the junction, a system operator determines whether the CAV will merge into the platoon ahead according to the positions and speeds of the CAV and the platoon. We formulate a Markov decision process to minimize the discounted cumulative travel cost, i.e., fuel consumption plus travel delay, over an infinite time horizon. We show that the optimal policy is threshold-based: the CAV will merge with the platoon if and only if the difference between the CAV’s and the platoon’s predicted times of arrival at the junction is less than a constant threshold. We also propose two ready-to-implement algorithms to derive the optimal policy. Comparison with the classical value iteration algorithm implies that our approach explicitly incorporating the characteristics of the optimal policy is significantly more efficient in terms of computation. Importantly, we show that the optimal policy under Poisson arrivals can be obtained by solving a system of integral equations. We also validate our results in simulation with a Real-time Strategy (RTS) using real traffic data. The simulation results indicate that the proposed method yields better performance compared with the conventional method.

Contract bundling considerations in urban road project scheduling

AbstractRoad project scheduling and contract bundling are two separate concepts that profoundly influence project delivery consequences to key stakeholders. Therefore, agencies espouse initiatives for contract bundling (to reduce project costs) and project scheduling (to reduce user delay costs). Bundling combined with scheduling could potentially yield benefits to both the agency and urban road users. This paper investigates the overall benefits (to the two stakeholders) of optimal schedules with bundling considerations, compared to the optimal schedules for unbundled contracts. The agency's objective is to make scheduling‐with‐bundling decisions that minimize system‐wide travel time and project costs, and the users’ objective is to minimize their travel times in the network with work zones. The problem is solved using the non‐dominated sorting genetic algorithm. The numerical experiments suggest that with well‐designed bundling, optimal scheduling can significantly reduce not only the project cost but also the total system cost (project and travel delay).

Flood impacts on urban transit and accessibility—A case study of Kinshasa

• Transit system was surveyed under dry & flooded conditions to document transport disruptions. • Floods impact public transit headways, itineraries and vehicle travel speeds in Kinshasa. • Commuting delays vary spatially and impact some economically disadvantaged households more. • Criticality analyses based on observed travel paths show priorities for resilience upgrades. • Estimated daily commuting delays due to floods cause daily city-wide losses over US$ 1.2 M. Transportation networks underpin socioeconomic development by enabling the movement of goods and people. However, despite their frequency, little is known about how floods disrupt transportation systems in developing country cities. We collect an innovative dual-condition transit feed specification dataset, and combine it with a travel survey and high-resolution flood maps to examine how regular floods in Kinshasa impact transport services, job accessibility, and the associated economic opportunity costs from travel delays. Our results show that flood disruptions cause increases in public transit headways, transit rerouting, decreases in travel speeds, which translate into travel delays and loss of job accessibility. This induces substantial economic costs to local commuters – about $1.2 million daily – and hinders the establishment of an integrated citywide labor market. In addition, we reveal sizeable socio-spatial heterogeneities, with clusters of low-income residents incurring a large share of the travel delays and identify critical network segments that should be prioritized for resilience interventions.

Variable Speed Limit Strategies Based on the Macro Hierarchical Control Traffic Flow Model

The superior traffic control system can promote the efficiency of mainstream expressway. As the effective method to smooth traffic system, the variable speed limits (VSL) strategies are discussed in an expressway traffic network. The dynamic OD estimation model is used to produce the real traffic information, which is loaded to the traffic network. Then, the prediction information of traffic variables and the VSL strategy are introduced to macro hierarchical control traffic flow model. A solution algorithm is further developed to find the optimal parameters of VSL by minimizing the total travel time and delay. The simulation results show that the proposed strategy perfects well, the traffic congestion is effectively alleviated, and the traffic efficiency of the road section is significantly improved. This framework can be adopted by transit managers for traffic efficiency.

Toxicological impacts of roadway deicers on aquatic resources and human health: A review

During winter, snow and ice on roads in regions with cold weather can increase traffic crashes and casualties, resulting in travel delays and financial burdens to society. Anti-icing or deicing the roads can serve a cost-effective method to significantly reduce such risks. Although traditionally the main priorities of winter road maintenance (WRM) have been level of service, cost-effectiveness, and corrosion reduction, it is increasingly clear that understanding the environmental impacts of deicers is vital. One of the most important problems in this regard is environmental contamination caused by cumulative use of deicers, which has many detrimental effects on the aquatic systems. Among the deicers, the chloride-based ones raise the most toxicological concerns because they are highly soluble, can migrate quickly in the environment and have cumulative effects over time. In this review, we summarize and organize existing data, including the latest findings about the adverse effects of deicers on surface water and groundwater, aquatic species, and human health, and identify future research priorities. In addition, the data provided can be used to develop a framework for quantifying some of the variables that stakeholders and agencies use when preparing guidelines and standards for WRM programs. PRACTITIONER POINTS: Pollution from the increasing use of roadway deicers may have detrimental effects on the environment. Of particular concern are the acute and cumulative risks that chloride salts pose to aquatic species. Chloride salts are water-soluble, very difficult to remove, highly mobile, and non-degradable. Deicers cause water stratification, change the chemicophysical properties of water, and affect aquatic species and human health. Current guidelines may not be appropriate for environmental protection and need to be revised.

Cooperative Lane-change on the Main-line of Highway in a Connected Vehicle Environment

The main-line lane-change (LC) and ramp LC are critical factors which decrease the mobility and safety of the transportation system. Connected Vehicle Technologies (CVTs) bring promising foundations for both types of LC to improve the traffic efficiency and reduce the crash risks by using real-time communication and systematic operation. Based on an 5G communication architecture, this paper proposes a novel CVT-based cooperative LC method which can be used for advanced traffic management to enhance the transport service. In the proposed approach, several Roadside Units (RSUs) are set up on the main-line of a highway to communicate with and manage connected client vehicles (CVs) for traffic flow smoothing. A mathematical model is developed to address the systematic maneuver of vehicles’ LC in the connected vehicle environment (CVE), and its solution algorithm is also proposed. In order to assess the proposed method, a simulation test-bed is developed using VISSIM COM, and a typical highway network is employed as the study case. The simulation results illustrate that the proposed method can increase 20.7% of traffic capacity in a two-lane highway. And when it is applied in dense traffic environment, it can reduce more than 90% of travel delay, more than 75% of maximum queue length, and more than 10% of fuel consumption and gas emission. Moreover, sensitivity analysis shows that the market penetration of CVT is a key factor that affects the result of CVT-based cooperative LC.

Reservation-based Dedicated Lane Method for Mixed Autonomous and Human-operated Vehicles at Intersections

This paper develops a reservation-based dedicated lane (RDL) mechanism for mixed autonomous and human-operated vehicles at intersections in connected vehicle environment. The RDL mechanism is proposed to coordinate hybrid transport at intersections under the condition of dedicated land, improve the capacity of intersections, reduce delay and the number of stops. The overall RDL architecture consists of two essential sub-modules: a connected and autonomous vehicles (CAVs) speed guidance application, a signal-control application for human-operated vehicles (HVs). Thus, the proposed RDL strategy enables HV/CAV/signal cooperation in a connected vehicle environment. A set-projection algorithm and a three-segment linear speed profile are employed to control the trajectories of the CAV. The performance of the proposed method is evaluated by simulating various traffic conditions on an actual urban network. The simulation evaluation results show that, compared with the traditional signal control method, the model can significantly reduce the travel delay. The simulation experiments indicate that the penetration rate of CAV reaches 30%-40%, and proposed method can achieve considerable results.

Impacts of Automated Mobility-on-Demand on traffic dynamics, energy and emissions: A case study of Singapore

Technological advancements have focused increasing attention on Automated Mobility-on-Demand (AMOD) as a promising solution that may improve future urban mobility. During the last decade, extensive research has been conducted on the design and evaluation of AMOD systems using simulation models. This paper adds to this growing body of literature by investigating the network impacts of AMOD through high-fidelity activity- and agent-based traffic simulation, including detailed models of AMOD fleet operations. Through scenario simulations of the entire island of Singapore, we explore network traffic dynamics by employing the concept of the Macroscopic Fundamental Diagram (MFD). Taking into account the spatial variability of density, we are able to capture the hysteresis loops, which inevitably form in a network of this size. Model estimation results at both the vehicle and passenger flow level are documented. Environmental impacts including energy and emissions are also discussed. Findings from the case study of Singapore suggest that the introduction of AMOD may bring about significant impacts on network performance in terms of increased VKT, additional travel delay and energy consumption, while reducing vehicle emissions, with respect to the baseline. Despite the increase in network congestion, production of passenger flows remains relatively unchanged.

Jam-Absorption Driving Strategy for Improving Safety Near Oscillations in a Connected Vehicle Environment Considering Consequential Jams

This article proposes an optimal jam-absorption driving (JAD) strategy, which not only prevents the occurring traffic oscillation but also avoids the consequential jam caused by the JAD vehicle. We first conducted a theoretical analysis to estimate the relationship between velocity and space headway within kinematic waves. Then an optimization function was formed to minimize the system travel delay. A procedure for specifying the absorbing vehicle was proposed. The performance of the JAD strategy was validated in a simulation model developed for the connected and automated driving environment. The results showed that by reaching a balance between the space headways in the “slow in” and “fast out” JAD execution stages, our optimal JAD strategy can successfully eliminate the oscillation without causing consequential jams. The collision risks measured by surrogate safety measures were reduced by 14.63% to 44.22% during the oscillation. Our strategies outperformed some previous ones in the same traffic condition. The proposed JAD strategy can effectively improve the safety situation on the freeway by eliminating traffic oscillations.

Decision attributes for disaster recovery planning of transportation networks; A case study

This paper implements a structured framework to suggest decision attributes of transportation network disaster recovery planning. For this purpose, we collected 57 decision attributes from the relevant literature and experts’ opinions. Following a framework with three sequential evaluation stages, decision-makers systematically assessed the attributes based on each evaluation stage’s specific criteria. Thereafter, we aggregated the decision-makers’ input values using a combination of compensatory and non-compensatory Multi-Attribute Decision-Making techniques. Results offer a ranked list of attributes and a recommended set of attributes for Tehran’s road network as our case study. The findings suggest six attributes to be included in road network disaster recovery planning as 1) access level to service-providing nodes, 2) integration of link travel delay and traffic flow, 3) travel time improvement per recovery duration, 4) travel time improvement per resources, 5) centrality measures, and 6) link capacity. However, the recommended attributes are valid only when they remain as a set. Results contribute to the existing knowledge about concerns and values in the reconstruction and recovery of transportation networks after disasters. Transportation network planners and disaster managers can use the recommended attributes as key factors for post-disaster decision support systems or for evaluating available disaster resiliency plans. Additionally, future research can adopt this research outcome as an input for the problem-structuring phase of disaster recovery models.

Travel Time Prediction Models for Major Arterial Road in Baghdad City using Manufactured GPS device

Travel time on arterials can be rotten into two components, free flow travel time and delay. That’s where the difference between the observed travel time and travel time of free flow, the delay can be calculated. Which is one of the most important roadways Metrics for Traffic. Estimation of travel time and measurement of reliability are critical issues for improving the efficiency of traffic network operations and safety. The purpose of this review is to estimate overall travel time and to analyse the collected data and also to estimate the travel time through predicting model for total delay of signalized intersections. In addition, utilizing a more convenient method and tools to reflect and to achieve a more practical model of delay time for the selected urban arterial in Baghdad city. Global Positioning System (GPS) receivers have an ability to reliably measure intersection delay in terms of (deceleration delay, stopped delay, and acceleration delay). In addition to measuring the travel time for each link along the streets specified for this study (Al-Karada Kharidge street). 50 test runs were collected from GPS-equipped instrumented vehicle at off peak and peak hours of the day for each direction for selected street in this study. So, the required data collection period for two months was from December 2019 to February 2020 were identified to study the complete travel time variations and travel delay times for each link and each intersection along the identified arterial street. The field data were collected for the selected of Al-Karada Kharidge street the Baghdad University intersection to Mohamed al-Qasim intersection.