Study on the network acoustics environment effects of traffic management measures by a bilevel programming model

Variable speed limits in the link transmission model using an information propagation method

Assessment of the impact of speed limit reduction and traffic signal coordination on vehicle emissions using an integrated approach

In view of the fact that the road capacity drops obviously near the lane reduction bottleneck, we propose two traffic cellular automata models around the merging point under two different traffic management measures. One is the control scheme of first-arrive and first-in, the other is the periodic control scheme. Using the open boundary condition, the numerical simulations are performed. The flux, density distribution and the evolution time from congested state to free state under different entering probability, deceleration zone length and periods are obtained. The comparisons indicate that whether the traffic management measures are chosen properly or not is closely related to entering probability, deceleration zone length and period. These conclusions have a significant reference value for the reduction of traffic jams near the bottlenecks.

Passengers would like to choose the most suitable train based on their travel preferences, expenses, and train timetable in the high-speed railway corridor. Meanwhile, the railway department will constantly adjust the train timetable according to the distribution of passenger flows during a day to achieve the optimal operation cost and energy consumption saving plan. The question is how to meet the differential travel needs of passengers and achieve sustainable goals of service providers. Therefore, it is necessary to design a demand-oriented and environment-friendly high-speed railway timetable. This paper formulates the optimization of train timetable for a given high-speed railway corridor, which is based on the interests of both passengers and transportation department. In particular, a traveling time-space network with virtual departure arc is constructed to analyze generalized travel costs of passengers of each origin-destination (OD), and bilevel programming model is used to optimize the problem. The upper integer programming model regards the minimization of the operating cost, which is simplified to the minimum traveling time of total trains, as the goal. The lower level is a user equilibrium model which arranges each OD passenger flow to different trains. A general advanced metaheuristic algorithm embedded with the Frank–Wolfe method is designed to implement the bilevel programming model. Finally, a real-world numerical experiment is conducted to verify the effectiveness of both the model and the algorithm.

Purpose – Commonly shared logistics services help manufacturing companies to cut down redundant logistics investments while enhance the overall service quality. Such service-sharing mode has been naturally adopted by group companies to form the so-called headquarter-managed centralized distribution center (HQ-CDC). The HQ-CDC manages the common inventories for the group’s subsidiaries and provides shared storage services to the subsidiaries through appropriate sizing, pricing and common replenishment. Apart from seeking a global optimal solution for the whole group, the purpose of this paper is to investigate balanced solutions between the HQ-CDC and the subsidiaries. Design/methodology/approach – Two decision models are formulated. Integrated model where the group company makes all-in-one decision to determine the space allocation, price setting and the material replenishment on behalf of HQ-CDC and subsidiaries. Bilevel programming model where HQ-CDC and subsidiaries make decisions sequentially to draw a balance between their local objectives. From the perspective of result analysis, the integrated model will develop a managerial benchmark which minimizes the group company’s total cost, while the bilevel programming model could be used to measure the interactive effects between local objectives as well as their final effect on the total objective. Findings – Through comparing the numerical results of the two models, two major findings are obtained. First, the HQ-CDC’s profit is noticeably improved in the bilevel programming model as compared to the integrated model. However, the improvement of HQ-CDC’s profit triggers the cost increasing of subsidiaries. Second, the analyses of different sizing and pricing policies reveal that the implementation of the leased space leads to a more flexible space utilization in the HQ-CDC and the reduced group company’s total cost especially in face of large demand and high demand fluctuation. Research limitations/implications – Several classical game-based decision models are to be introduced to examine the more complex relationships between the HQ-CDC and the subsidiaries, such as Nash Game model or Stackelberg Game model, and more complete and meaningful managerial implications may be found through result comparison with the integrated model. The analytical solutions may be developed to achieve more accurate results, but the mathematical models may have to be with easier structure or tighter assumptions. Practical implications – The group company should take a comprehensive consideration on both cost and profit before choosing the decision framework and the coordination strategy. HQ-CDC prefers a more flexible space usage strategy to avoid idle space and to increase the space utilization. The subsidiaries with high demand uncertainties should burden a part of cost to induce the subsidiaries with steady demands to coordinate. Tanshipments should be encouraged in HQ-CDC to reduce the aggregate inventory level as well as to maintain the customer service level. Social implications – The proposed decision frameworks and warehousing policies provide guidance for the managers in group companies to choose the proper policy and for the subsidiaries to better coordinate. Originality/value – This research studies the services sharing on the warehouse sizing, pricing and common replenishment in a HQ-CDC. The interactive decisions between the HQ-CDC and the subsidiaries are formulated in a bilevel programming model and then analyzed under various practical scenarios.

As the poor applicability of rail transit and elevated road limited by economy, population and many other factors, the waste of road resources caused by bus lane, maximizing application of available road resources and bus facilities, reducing the environmental pollution is the critical issue faced by current situation of urban transportation development in China. Guided by Bus Priority Oriented, utilized comprehensive techniques, such as ABC classification, bi-level programming model, sensitivity analysis, this paper constructed a theoretical frame of elastic equilibrium based on system optimization. Taking time and environment as optimized objectives, This paper established the Bi-Level multiobjective programming model based on travel time, and programmed with MATLAB for the calculation. Finally, the case study is illustrated. the software VISSIM was adopted to realize the simulation of the volume before and after the implementation of elastic plan in urban areas of PingDingshan. The simulation results showed the validity and feasibility of the modeling and simulation of Bus Priority Oriented urban road network elastic equilibrium.

With the accelerating economic development and increasing urban motorization, traffic congestion is seen everywhere. The issue of vehicular exhaust emissions which leads the vehicles to accelerate and decelerate frequently as well as stay in idle state for a long time, is particularly serious. In order to reduce carbon emissions and improve road network efficiency, a bi-level programming model considering carbon emissions under the action of route guidance information is set up. The decision maker aims at reducing carbon emissions and optimizing road network efficiency. It makes road traffic capacity as a constraint condition by means of providing different types of information in its upper model. The route choice behavior of a driver is described by the user equilibrium in its lower model. The bi-level programming model of the network was analyzed and solved by a heuristic algorithm. In the end, a simple numerical example is presented in order to validate the feasibility of the model and the algorithm. On the basis of analyzing the influence of vehicle carbon emissions and road network efficiency under the route guidance information, vehicular exhaust emissions control strategies are presented.

Improving traffic management through consideration of uncertainty and stochastics in traffic flow

Network Impact of Dynamic Traffic Management Measures

Optimization of Two-Stage Port Logistics Network of Dynamic Hinterland Based on Bi-level Programming Model

In order to solve the problem of vehicle speed planning that meets the constraints of safety and efficiency in complex road environments (large curvature and low adhesion), a differential equation planning method based on vehicle dynamics analysis is proposed. First, the structural parameter expression of the limit speed that meets the lateral tire force constraint during steady-state steering is derived. Secondly, the tire force execution space of the front and rear wheels is combined into an FF diagram, and an implicit differential equation that considers load transfer and driving mode factors is obtained. The differential equation is solved to obtain the limit speed along the path, and a limit speed calculation method for discrete path information is given. Finally, a lateral and longitudinal collaborative model predictive controller is designed, and a CarSim and Simulink joint simulation platform is built. Trajectory tracking simulation experiments are carried out on both continuous and discrete information paths with the planned limit speed. The results show that the limit speed planning method proposed in this paper can complete the trajectory tracking task in complex road environments as quickly as possible while controlling the tire force within the range of the stable friction circle.

The impact of speed limits on traffic equilibrium and system performance in networks

High-density interchange groups (HDIG) have become an increasingly common feature in urban transport infrastructure, but the reduction of the spacing between interchanges has led to poor weaving environments and disorganized traffic flows. However, this safety issue has not yet attracted much attention. This study aims to investigate the effects of interchange spacing, driving conditions, and driver heterogeneity on the speed control behavior of drivers in HDIGs. A naturalistic driving test was carried out at an HDIG in Chongqing, China, where real-vehicle operating data were collected from 37 drivers, and the effects of their interactions with driving conditions, driver gender, and driving style on vehicle longitudinal speed and acceleration were discussed separately, using the spacing of the interchanges as the key factor. The drivers’ speed control patterns varied under different interchange spacing, especially under ramp-to-mainline conditions, where vehicle travel speed and driving stability were more significantly affected by interchange spacing and driver heterogeneity. In addition, the driving behaviors of drivers of different genders and styles were found to differ to some extent, and the driving conditions affected the significance of the differences. This study reveals the effects of interchange spacing, driving conditions, and driver heterogeneity on speed control behavior in HDIGs, discusses further the possible reasons for the differences in driving behavior, and proposes targeted improvement measures. Moreover, this study provides theoretical support for the development of design specifications for HDIGs in urban and traffic safety management measures to reduce the number of traffic accidents at the interchange.

Traditionally, traffic problems are treated in isolation in terms of location of the problem and the kind of problem. However, there is a strong correlation between these problems, so clearly solving a traffic problem at one location may result in other problems at other locations. Congestion problems on the main network can, for example, lead to “rat-running” (through-traffic using the secondary road network avoiding these congestion problems) causing liveability problems. Therefore, measures to alleviate traffic problems are nowadays increasingly focussed on the network level. In addition, solutions are sought for the optimization of traffic systems and less emphasis is placed on expanding the infrastructure of the system mainly because of financial considerations and space limitations. This optimization can be achieved using traffic management measures. Traditionally, this type of optimization is focussed on improving accessibility, given particular boundary conditions for traffic safety and liveability (set by law).

PurposeIn order to explore the effect of curb parking on dynamic traffic and formulate some reasonable and effective traffic management measures, the effects on capacity and traffic safety are studied.MethodsFour road segments with curb parking were selected as the investigation location. Several traffic characteristics and parameters were then investigated and counted, including traffic flow volume, speed, headway and traffic conflict. Based on a reduction of lane effective width and the Gap Acceptance Theory, two effect models describing curb parking and road capacity were constructed. Considering the factors involved in motor vehicle conflicts (such as non-motor vehicle lane distribution and stopping sight distance), the effects of curb parking on both motor vehicle and non-motor vehicle traffic safety was analyzed, as well as pedestrian crossing safety. This case study analyzes both the capacity and traffic safety of all four investigation segments.ResultsResults show that the lane effective width of road segment with curb parking significantly influences the road capacity and impacts the traffic flow volumes of the parking lane and its adjacent lane.ConclusionsCurb parking significantly effects traffic operation safety; however, it can be improved by implementing traffic safety management measures.