Lane Allocation Research Articles

IOT BASED MOVABLE ROAD DIVIDING SYSTEM

Road dividers conventionally serve the purpose of segregating traffic on roads into lanes for ongoing and incoming vehicles, facilitating smooth traffic flow. Typically, an equal number of lanes are designated for each direction of traffic. However, static road dividers present a limitation as they do not adapt to varying traffic demands. Our objective is to devise an automated road divider system capable of dynamically adjusting lane allocation, thereby accommodating the prevailing traffic patterns. The potential benefits of such a system include significant savings in time and fuel consumption, particularly by reallocating lanes to the direction experiencing higher traffic volume. This innovation promises to alleviate traffic congestion effectively and enhance traffic management strategies.

Optimal lane allocation strategy for shared autonomous vehicles mixed with regular vehicles

Autonomous driving technology has the potential to alter the way we travel and is rapidly evolving. Sharing rides in autonomous vehicles may become a popular mode of public transportation in the future. One strategy to enhance operational efficiency is to deploy designated autonomous vehicle (AV) lanes for shared autonomous vehicles (SAVs). This study investigated optimal allocation for dedicated AV lanes considering mixed SAVs and regular vehicles (RVs) flows. First, the standard bottleneck model for morning rush hour was extended to account for both ridesharing and automation, and user equilibrium (UE) solutions were obtained by assuming dedicated AV lanes co-exist with general-purpose (GP) lanes. The equilibrium capacity allocation for dedicated AV lanes was determined for multi-modal traffic scenarios. The study found that commuters may prefer to use SAVs because SAVs were more cost-effective and time-saving. Furthermore, analysis of the fixed payment for ridesharing in SAVs revealed that the system performance could be negatively impacted by high fixed payments. The study proposed an enumeration algorithm for developing lane strategies for discrete lane settings. It was found that the deployment of dedicated AV lanes should be matched to the penetration rate of SAVs and different management objectives, following a gradual rather than a radical process. Finally, a sensitivity analysis was performed considering the value of travel time for SAVs and the bottleneck capacity of a dedicated AV lane. This work provides a new solution to AV lane capacity allocation and offers theoretical support for managers to deploy dedicated AV lane allocation.

СРАВНЕНИЕ ГОРОДСКОГО ПАССАЖИРСКОГО ТРАНСПОРТА МЕГАПОЛИСОВ НА ОСНОВЕ ПОКАЗАТЕЛЕЙ РАЗЛИЧНЫХ ЛЕТ И СПОСОБЫ ВЫХОДА ИЗ КРИЗИСА

. Various indicators of the transport systems of megalopolises – St. Petersburg and Moscow – are considered. The shortcomings of the existing transport system of St. Petersburg are revealed. The existing program for the development of the electric transport carrier St. Petersburg State Unitary Enterprise «Gorelektrotrans» was also studied. A step-by-step plan for overcoming the crisis based on various methods and practices is proposed: the separation of tram lines and the allocation of lanes for wheeled transport will increase the safety and average speed of transport, the use of the author's corridor-junction method of forming a route network to increase the availability of public transport and reduce individual mobility. The use of the expected results is planned to be expanded in the direction of the development of St. Petersburg, in the future - cities and megacities with negative indicators of the transport system.

A Dynamic CAV-Dedicated Lane Allocation Method With the Joint Optimization of Signal Timing Parameters and Smooth Trajectory in a Mixed Traffic Environment

Owing to the difference in utilization efficiency of road between a connected-automated vehicle (CAV) and connected human-driven vehicle (CHV), caused by trajectory controllability, the optimization methods reported in literature for the mixed traffic of CAVs and CHVs at signalized intersections do not consider the dynamic adjustment of the approach lane utilization due to variations in the CAV penetration rate and traffic demand. Accordingly, a dynamic CAV-dedicated lane allocation method with the joint optimization of signal timing parameters and smooth trajectory is proposed to avoid using transitional or inefficient CAV-dedicated lanes and improve the performance of the intersections. In addition, a CAV trajectory control model for the CAV-dedicated lane is built to avoid the start-up loss time and maximize the utilization of green time. The delay and stops are weighted to form an integrated performance index (PI), and a PI model is established to evaluate the proposed method. A simplified solution procedure is designed to solve the joint optimization problem. The simulation results show that the proposed method in this paper can reduce the average PI per vehicle at intersections by 15.7% or more compared with that of a fully actuated signal control scheme, which indicates that it is necessary to drive the CAVs in one or more CAV-dedicated lanes when the CAV penetration rate exceeds a certain threshold. Compared with the existing signal and trajectory control approaches, the proposed method is more suitable for multi-lane signalized intersection with high saturation and high CAV penetration rate.

Managing connected and automated vehicles with flexible routing at “lane-allocation-free” intersections

With the development of internet of vehicles and automated driving, individual-based trajectory control at intersections becomes possible. Trajectory planning and coordination for connected and automated vehicles (CAVs) have been studied at isolated “signal-free” intersections and in “signal-free” corridors under the fully CAV environment in the literature. Most existing studies are based on the definition of approaching and exit lanes. The route a vehicle takes to pass through an intersection is determined by its movement. That is, only the origin and destination arms are included. This study proposes a mixed-integer linear programming (MILP) model to optimize vehicle trajectories at an isolated “signal-free” intersection without lane allocation, denoted as “lane-allocation-free” (LAF) control. Each lane can be used as both approaching and exit lanes for all vehicle movements including left-turn, through, and right-turn. A vehicle can take a flexible route by way of multiple arms to pass through the intersection. In this way, the spatial–temporal resources are expected to be fully utilized. The interactions between vehicle trajectories are modeled explicitly at the microscopic level. Vehicle routes and trajectories (i.e., car-following and lane-changing behaviors) at the intersection are optimized in one unified framework for system optimality in terms of total vehicle delay. Considering varying traffic conditions, the planning horizon is adaptively adjusted in the implementation of the proposed model to make a balance between solution feasibility and computational burden. Numerical studies validate the advantages of the LAF control in terms of both vehicle delay and throughput with different demand structures and temporal safety gaps.

Exclusive Bus Lane Allocation Considering Multimodal Traffic Equity Based on Bi-Level Programming

To ensure the equity of exclusive bus lane (EBL) allocation under multimodal traffic conditions, a bi-level programming model is first constructed. The upper-level model is the minimum total system cost considering the Gini coefficient and the lower-level model constructed a stochastic user equilibrium (SUE) model based on logit loading. Secondly, a heuristic algorithm combining an improved genetic algorithm (GA) and a method of the successive average method (MSA) is designed. Finally, the Nguyen and Dupuis networks are used as examples to verify and analyze the effectiveness, superiority and sensitivity of the model and algorithm. The results show that the method can effectively obtain the optimal solution of the upper-level model as 15,004 RMB, the Gini coefficient is 0.31, and the equity is at a relatively reasonable level. Compared with the different allocation schemes, the proposed scheme has a higher bus sharing rate and lower Gini coefficient. At the same time, when the actual demand is twice the basic demand, the bus share rate is the largest, 65%, and the Gini coefficient is the smallest at 0.3. The bus share rate decreases with the increase in the proportion of high time value travelers, which fully verifies the sensitivity of the model to the type of traveler.

BUS LANE IMPLEMENTATION STRATEGY

This paper proposes a methodology for bus lane allocation including different strategies, dynamic bus lanes, and exclusive bus lanes. Choosing the right solution depends on many factors, such as traffic flow, passenger flow, and time losses. Analytical or simulation models can be used to evaluate the effectiveness of a separate bus lane. Analytical methods are simple to use and provide results in a short time. Simulation models, unlike analytical ones, require much more time and data to prepare but they are also much more detailed and accurate data. Therefore, analytical models may be particularly needed in the first stage of planning work during which potential sections for separated bus lanes are indicated. In this article, the author proposed an analytical model based on the 6th edition of the Highway Capacity Manual, which can be used to assess the implementation of separated bus lanes in different strategies. The final model developed was calibrated using traffic measurement results collected in a Polish city. As a result of the work, the author proposed the calculation procedure of the assumptions and diagrams, enabling the assessment of the selection of the appropriate solution.

Investigating the Effect of Network Traffic Signal Timing Strategy with Dynamic Variable Guidance Lanes

This paper aims to investigate the effect of network signal timing strategy with dynamic variable guidance lanes based on a two-step approach, where the first step is an interactive traffic signal optimization model for each single interaction (e.g., lane allocation plans, cycle length) in the network, and the second refers to network signal control (e.g., split, off-sets). The optimization problem in the first step is solved using the Non-dominated Sorting Genetic Algorithm (NSGA-ΙΙ), and the network signal control problem in the second step is solved through SYNCHRO. To verify the effect of dynamic variable guidance lanes and also the reliability and validity of the proposed approach, a numerical case study is carried out. The results show that the average vehicle delay in the entire road network was reduced by 25.06% after optimization using the proposed model. Moreover, the sensitivity of influencing factors of the proposed model is also analyzed. The results show that when the traffic flow is increased by 60% of the original traffic flow, the optimization effect of the model is more significant. However, when the lane capacity is more than 1300 pcu/h, the vehicle delay will increase slowly. To sum up, this method can improve the regional traffic efficiency of the traffic-stressed lanes and further promote the full utilization of space-time resources of the road network.

Investigation of Bus Special Lane Performance Using Statistical Analysis and Optimization of the Signalized Intersection Delay by Machine Learning Methods

Nowadays, the performance analysis and evaluation of public transportation systems have great importance in traffic engineering science. So far, the bus system has not been very effective in some cities in Iran, and many management approaches such as the allocation of special lanes and regular bus scheduling, which are needed to increase the efficiency of this system, have not been sufficiently considered. The purpose of the present study is to optimize the delay of the signalized intersection of bus lane and investigate the factors affecting the urban bus usage by citizens in public transportation of Rasht city and especially their satisfaction. Therefore, the intersection delay was optimized by gathering the traffic volume data in peak hour time of a signalized intersection along the bus lane and using machine learning methods. In addition, by collecting two different questionnaires, taking 84 samples (first questionnaire) and 374 samples (second questionnaire), the satisfaction of citizens and business people on the boundary of the bus lane was considered. The results indicated that about 95% of the businesses around this route believe that the construction of the bus lane led to a decrease in the income of more than 110 dollars per month. Further to this, despite the lack of facilities, poorly designed routes, and lack of the bus system fleet, the bus lane of Imam Khomeini had a high degree of satisfaction among the citizens. The result of various models showed that the adaptive network-based fuzzy inference system (ANFIS) had the highest R2 and the lowest amount of root mean square error (RMSE). In fact, this model had a better performance to predict and optimize the delay of signalized intersection than the fuzzy model. The optimum amount of intersection delay was determined as 56 seconds. With this value, the delay of bus movements in the bus lane had a higher possibility of being reduced.

Deploying dedicated lanes for connected and autonomous buses in urban transportation networks

To promote the ridership of connected and autonomous buses (CABs), this paper proposes to build CAB lanes in urban transportation networks. Three travel modes are considered: CAB, connected and autonomous passenger vehicle (CAV) and human-driven passenger vehicle (HV). To better utilise the capacities of CAB lanes, CAVs are granted limited access while maintaining good levels of services on these lanes. Analyses show that deploying CAB lanes may substantially increase the ridership of CABs and increase total social benefit, and allowing limited CAV access can further improve the overall system performance. The CAB lane allocation problem is formulated into a mixed-integer nonlinear programme. Numerical tests are performed to demonstrate the approach.

Managing Evacuation of Mixed Traffic Flow: Fleet Configuration, Lane Allocation, Lane Reversal, and Cross Elimination

Managing Evacuation of Mixed Traffic Flow: Fleet Configuration, Lane Allocation, Lane Reversal, and Cross Elimination

Lane-based multi-class vehicle collaborative evacuation management

Mixed traffic evacuation management is recognized as a critical and challenging task. This paper develops a bi-level model to address the multi-class vehicle collaborative evacuation problem. The upper-level program is a mixed-integer nonlinear programming (MINLP) model to determine the optimal lane allocation scheme according to the fleet size. The lower-level program is formulated as multiple independent system optimal dynamic traffic assignment (SO-DTA) problems to load mixed traffic flow. A two-layer solution method integrating branch-and-bound algorithm is developed to solve the model. Finally, the optimization model is applied in a small network and a real-world network. Results demonstrate that (1) the evacuation performance of multi-class vehicle collaboration is better than that of single-class vehicles under the medium demand levels; (2) the proposed model realizes the coupling among evacuation demand, fleet size, and road network capacity; (3) the shortest path should first be allocated to the bus during a mass evacuation.

Dynamic Allocation Model for Reversible Lanes in the Intelligent Vehicle Infrastructure Cooperative System

The real-time dynamic control of reversible lanes is an effective measure to alleviate the traffic congestion caused by the directional imbalance of the traffic flow and improve the utilization rate of urban road resources. This paper proposes a dynamic allocation model for reversible lanes for road sections and intersections in the intelligent vehicle infrastructure cooperative system (IVICS). The dynamic lane allocation model for the road sections is constructed based on the Bureau of Public Road (BPR) function, in which the 24 hours of the day are divided into stages, the traffic volume and road impedance of each stage are obtained, and their product is integrated over time. Finally, the plan with the least delay in each stage is selected as the optimal solution. The dynamic lane control model for intersections is built according to the Highway Capacity Manual 2000 (HCM2000) delay model. With the minimum average delay of vehicles at the intersection as the objective function, the average delay of different lane combinations under different traffic conditions is analyzed to find the optimal combination of reversible lanes and ordinary lanes. The model is verified by case analysis and MATLAB calculations. The results show that the reversible lane dynamic control model can effectively allocate road resources and reduce driving delays.

Methodology of assessing the regulated crossing throughput with a dedicated lane for ground public transport based on a probabilistic model

One of the problems of traffic management in the allocation of lanes for ground public transport (GPT) is the organization of the right turn at regulated and unregulated intersections. High traffic intensity at a regulated intersection on the main carriageway and a significant proportion of right-turn traffic leads to numerous violations of the rules of passage when making a right turn. A method for assessing the throughput of a controlled intersection with a dedicated lane before joining is presented on the basis of a deterministic stochastic model.

Allocating exclusive and intermittent transit lanes in dynamic traffic networks with connected and automated vehicles

Exclusive bus lanes (XBLs) have been widely discussed and implemented worldwide in recent years. An improved and more flexible transit lane management strategy—intermittent bus lanes (IBLs)—prove to be potentially more efficient and car-friendly than XBLs. The common benefit of XBLs and IBLs arises from the fact that they separate the bus and car traffic and hence eliminate the impacts of slowly moving buses on the car traffic. Compared to XBLs, the application of IBLs has not been broadly adopted in the real world so far except very few cases, because managing an urban IBL segment or area typically involves extra traffic signals and message signs and the switch between its regular and protected statuses could potentially cause unexpected traffic chaos and safety issues. The recent emergence of connected and automated vehicle (CAV) technologies, however, favors relieving these concerns and bring the dawn to a future application of this theoretically sound traffic control strategy. This paper is dedicated to evaluating the network performance of XBLs and IBLs and optimizing the networkwide configurations of these two strategies for future urban traffic networks where CAVs prevail. For this purpose, we formulate a system-optimal dynamic traffic assignment (SO-DTA) problem with car-exclusive lane segments, on the basis of a cell transmission model for separate car and bus traffic (CTM-SCB). By limiting its applicable context to morning commute networks and emergency evacuation networks, this model is set with only one real or virtual destination, which greatly eases its modeling and solution complexity. On the basis of the single-destination SO-DTA model, an XBL-based network design problem and an IBL-based network design problem are then both formulated into mixed integer programming models and solved by a discrete optimization solver, where the former problem statically configures bus lanes while the later one allows a dynamic allocation of bus lanes. Insightful findings obtained by applying the models and solver to a synthetic corridor network and a real commute network illustrate the great promise of these two lane-based strategies in mixed car and bus traffic management.

Modeling and optimization of dedicated bus lanes space allocation in large networks with dynamic congestion

Dedicated bus lanes provide a low cost and easily implementable strategy to improve transit service by minimizing congestion-related delays. Identifying the best spatial distribution of bus-only lanes in order to maximize traffic performance of an urban network while balancing the trade-off between bus priority and regular traffic disturbance is a challenging task. This paper studies the problem of optimal dedicated bus lane allocation and proposes a modeling framework based on a link-level dynamic traffic modeling paradigm, which is compatible with the dynamic characteristics of congestion propagation that can be correlated with bus lane relative positions. The problem is formulated as a non-linear combinatorial optimization problem with binary variables. An algorithmic scheme based on a problem-specific heuristic and Large Neighborhood Search metaheuristic, potentially combined with a network decomposition technique and a performance-based learning process for increased efficiency, is proposed for deriving good quality solutions for large-scale network instances. Numerical application results for a real city center demonstrate the efficiency of the proposed framework in finding effective bus lane network configurations; when compared to the initial network state they exhibit the potential of bus lanes to improve travel time for car and bus users.

Lane Allocation Optimization in Container Seaport Gate System Considering Carbon Emissions

Long queues of arrival trucks are a common problem in seaports, and thus, carbon emissions generated from trucks in the queue cause environmental pollution. In order to relieve gate congestion and reduce carbon emissions, this paper proposes a lane allocation framework combining the truck appointment system (TAS) for four types of trucks. Based on the distribution of arrival times obtained from the TAS, lane allocation decisions in each appointment period are determined in order to minimize the total cost, including the operation cost and carbon emissions cost. The resultant optimization model is a non-linear fractional integer program. This model was firstly transformed to an equivalent integer program with bilinear constraints. Then, an improved branch-and-bound algorithm was designed, which includes further transforming the program into a linear program using the McCormick approximation method and iteratively generating a tighter outer approximation along the branch-and-bound procedure. Numerical studies confirmed the validity of the proposed model and algorithm, while demonstrating that the lane allocation decisions could significantly reduce carbon emissions and operation costs.

Ensuring priority of public urban passenger transport on urban road network

Recently, in large and medium-sized cities, the increase in a load of highways is aggravated by the growth of motorization and the lack of development of the road network. An increase in the traffic intensity of vehicles to a critical level leads to an excess of the throughput of highways. The consequence is an increase in the level of road traffic delay. One of the most vulnerable groups is public urban mass passenger transport. This article discusses the methodology for determining the need to allocate a separate lane for the movement of public urban passenger transport on a given section of the road network. The purpose of this work is to identify patterns between the parameters of traffic flows and the parameters of the transportation program for public urban passenger transport, based on which criteria will be formulated for the need to allocate a separate lane for the movement of urban land transport on each separate section of the route network. For quality improvement of passenger transportation, a mathematical model has been developed, which is based on such indicators as the level of traffic delay and the share of the passenger flow in the total flow of traffic participants. Necessary conditions have been formulated, the strict implementation of which determines the need to ensure the priority of urban mass public transport on the considered section of the city’s road network. The resulting dependencies allow determining the need to ensure the priority of urban transport. The proposed model makes it possible to determine the rationality of the allocation of individual lanes, traffic for public transport following the level of traffic in the city’s road network. This study can become the basis for an algorithm for the operation of interactive signs that regulate traffic on a given stretch of the city’s road network.

BEHT: Blockchain-Based Efficient Highway Toll Paradigm for Opportunistic Autonomous Vehicle Platoon

Autonomous vehicle platoon is a promising paradigm towards traffic congestion problems in the intelligent transportation system. However, under certain circumstances, the advantage of the platoon cannot be fully developed. In this paper, we focus on the highway Electronic Toll Collection (ETC) charging problem. We try to let the opportunistic platoon pass the ETC as a whole. There are three main issues in this scenario. Firstly, the opportunistic platoon is temporarily composed; vehicles do not trust each other. Secondly, single vehicle may try to escape from the ETC charging by following the platoon. Finally, platoon members may collude with each other and try to underreport the number of vehicles in the platoon so as to evade payment. To solve these challenges, we propose a blockchain-based efficient highway toll paradigm for the opportunistic platoon. The driving history, credential information of every registered vehicle, is recorded and verified from the blockchain. A roadside unit (RSU) is adopted to distinguish the single vehicle from the platoon and in charge of lane allocation. Additionally, an aggregate signature is introduced to accelerate the authentication procedure in the RSU. We analyse the potential security threats in this scenario. The experimental result indicates that our scheme is efficient and practical.

ENSURING PRIORITY FOR PUBLIC URBAN PASSENGER TRANSPORT ON URBAN STREETS AND ROAD NETWORK

Introduction.Recently, in large and medium-sized cities, the increase in traffic has been exacerbated by the growth of motorization and the lack of development of the road network. Increasing vehicle traffic to a critical level leads to overcapacity of the arteries and, as a consequence, increases the level of delay. Public urban mass passenger transport is one of the most vulnerable groups in this regard. In order to unload the city’s street network, it is necessary to reduce the level of road traffic. One of the effective measures to deal with this problem is to increase the attractiveness of urban mass passenger transport, i.e. to ensure an adequate level of service for passengers including high speed, which can be increased by giving priority to bus traffic. One of the prospects for prioritizing public urban transport is the development of individual lanes or streets for urban rolling stock only. Due to the lack of criteria for the allocation of separate lanes for urban rolling stock, they have begun to appear in the vast majority on the main streets of the city. There are a large number of urban highways used for the operation of only one public transport route with dedicated lanes on them. The need for such arrangements is questionable. It is therefore necessary to formulate the criteria that justify the need for a separate urban passenger lane on a given stretch of the city network. Thus, the purpose of this work is to identify patterns between traffic parameters and the parameters of the urban public passenger transport programme, which will determine the criteria for the need for a separate lane for urban land transport on each individual stretch of the network.Materials and methods.This article deals with the method of determining the need for a separate lane for public urban passenger transport on a given stretch of the road network. In order to improve the quality of the transport of passengers, a mathematical model has been developed, based on such indicators as the level of traffic delay and the share of passenger traffic in the total flow of participants. Results. The necessary conditions have been laid down the strict implementation of which determines the need to ensure the priority of urban mass public passenger transport on the section of the city’s street network under consideration.Discussion and conclusion.The dependencies obtained make it possible to identify the need to ensure the priority of urban transport.