A new cellular automata model of traffic flow with negative exponential weighted look-ahead potential

With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver's random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations.     

Traffic-Aware Green Cognitive Radio

Cognitive Radio Network (CRN) has emerged as an effective solution to the spectrum under-utilization problem, by providing secondary users (SUs) an opportunistic access to the unoccupied frequency bands of primary users (PUs). Most of the current research on CRN are based on the assumption that the SU always has a large amount of data to transmit. This leads to the objective of SU throughput maximization with a constraint on the allowable interference to the PU. However, in many of the practical scenarios, the data arrival process of the SU closely follows an ON–OFF traffic model, and thus the usual throughput optimization framework may no longer be suitable. In this paper, we propose an intelligent data scheduling strategy which minimizes the average transmission power of the SU while maintaining the transmission delay to be sufficiently small. The data scheduling problem has been formulated as a finite horizon Markov Decision Process (MDP) with an appropriate cost function. Dynamic programming approach has been adopted to arrive at an optimal solution. Our findings show that the average transmitted power for our proposed approach can be as small as 36.5% of the power required for usual throughput maximization technique with insignificant increase in average delay.     

巡游出租车运价动态调整系统动力学模型

合理的巡游出租车运价体系是缓解行业矛盾和促进行业良性发展的重要保障.为了充分体现运价在供需调节中的杠杆作用,运用系统动力学构建了巡游出租车运价动态调整模型.以宁波市巡游车和网约车运营数据对模型参数进行标定,验证了模型的有效性;以市场供需平衡为目标,分别模拟了高峰、低峰不同需求水平下动态加价、减价对市场供需平衡状态的影响分析以及不同网约车吸引度水平下巡游出租车运价动态调整策略.模型结果表明:(1)当运价增加0.6元km~(-1)时,可使高峰时段供需接近平衡状态,有效地抑制了高峰需求水平,且保证了巡游车运营总体收益增加;(2)当巡游车和网约车市场业务量之比约为10:4.5和10:8时,巡游车加价分别为0.6和-0.4元km~(-1),当巡游车处于竞争优势时,适度加价可期获得更大收益;处于劣势时,适度降价以提高自身竞争能力.     

Routing strategies in traffic network and phase transition in network traffic flow

The dynamics of information traffic over scale-free networks has been investigated systematically. A series of routing strategies of data packets have been proposed, including the local routing strategy, the next-nearest-neighbour routing strategy, and the mixed routing strategy based on local static and dynamic information. The capacity of the network can be quantified by the phase transition from free flow state to congestion state. The optimal parameter values of each model leading to the highest efficiency of scale-free networked traffic systems have been found. Moreover, we have found hysteretic loop in networked traffic systems with finite packets delivering ability. Such hysteretic loop indicates the existence of the bi-stable state in the traffic dynamics over scale-free networks.      

An asymmetric full velocity difference car-following model

This paper presents a car-following model that considers the asymmetric characteristic of the velocity differences of the vehicles in a traffic stream. The problems of the prevalent general force (GF) model and the full velocity difference (FVD) model were solved. Furthermore, the optimal velocity (OV) model, the GF model, and the FVD model are proved to be the special cases of the proposed asymmetric full velocity difference (AFVD) model. The mathematical model is presented, followed by simulation analysis which demonstrates the properties of the AFVD model.     

A dynamic model for traffic network flow

Concerning the link properties in traffic networks, we introduce a dynamic equation of road flow into each link, and thereby propose a dynamic model for network flow. Using this model, we investigate the evolutions of inflow, outflow and flow on each link caused by a small perturbation of the network inflow under different route choice rules. Numerical results show that the dynamic model can reasonably capture the basic characteristics of network flow.     

Development of a highway traffic noise prediction model that considers various road surface types

A highway traffic noise prediction model has been developed for environmental assessment in South Korea. The model is based on an outdoor sound propagation method and is fully compliant with ISO 9613 and the sound power level (PWL) estimation for a road segment, as suggested in the ASJ Model-1998 that is based on PWLs. Due to that model’s selection of two pavement types, such as asphalt or concrete pavement, an unacceptable traffic noise prediction is made in cases where the road surface is different from that on which the model is based. In order to address this problem, several road surface types are categorized, and the PWL of each surface type is determined and modeled by measuring the noise levels obtained from newly developed methods. An evaluation of the traffic noise prediction model using field measurements finds good agreement between predicted and measured noise levels.     

AN IDEA OF IMPROVING INNER WHEEL DIFFERENCE PROBLEM OF SEMI-TRAILER TRUCK

基于降低货车内轮差安全隐患的考虑,根据已有的研究成果对半挂车内轮差问题改善方向提出设想,基于刚体运动学原理提出具体改进方案,导出转弯时半挂车运动轨迹方程,运用Matlab软件从理论上进行了验证。     

A genetic resampling particle filter for freeway traffic-state estimation

On-line estimation of the state of traffic based on data sampled by electronic detectors is important for intelligent traffic management and control.Because a nonlinear feature exists in the traffic state,and because particle filters have good characteristics when it comes to solving the nonlinear problem,a genetic resampling particle filter is proposed to estimate the state of freeway traffic.In this paper,a freeway section of the northern third ring road in the city of Beijing in China is considered as the experimental object.By analysing the traffic-state characteristics of the freeway,the traffic is modeled based on the second-order validated macroscopic traffic flow model.In order to solve the particle degeneration issue in the performance of the particle filter,a genetic mechanism is introduced into the resampling process.The realization of a genetic particle filter for freeway traffic-state estimation is discussed in detail,and the filter estimation performance is validated and evaluated by the achieved experimental data.     

Solitary wave solution to Aw-Rascle viscous model of traffic flow

A traveling wave solution to the Aw-Rascle traffic flow model that includes the relaxation and diffusion terms is investigated. The model can be approximated by the well-known Kortweg-de Vries (KdV) equation. A numerical simulation is conducted by the first-order accurate Lax-Friedrichs scheme, which is known for its ability to capture the entropy solution to hyperbolic conservation laws. Periodic boundary conditions are applied to simulate a lengthy propagation, where the profile of the derived KdV solution is taken as the initial condition to observe the change of the profile. The simulation shows good agreement between the approximated KdV solution and the numerical solution.