Equilibrium analysis of mixed passengers in urban railway network

A model is proposed to describe the passengers’route choice behaviors in urban railway traffic with stochastic link capacity degradation by considering two types of demand,sensitive and insensitive passenger.The insensitive passengers choose their route without paying much attention to congestion.To the contrary,sensitive passengers who consider route congestion choose travel route based on generalized cost.An equilibrium state is given by variational inequalities in terms of travel generalized cost,which is represented by the combinations of mean and variance of total travel time.The diagonalization algorithm is given to solve this programming.Results show that insensitive passengers have large effects on the path choice than sensitive ones,especially for the larger demand.     

Traffic jam in signalized road network简

Traffic jam in large signalized road network presents a complex nature.In order to reveal the jam characteristics,two indexes,SVS（speed of virtual signal） and VOS（velocity of spillover）,were proposed respectively.SVS described the propagation of queue within a link while VOS reflected the spillover velocity of vehicle queue.Based on the two indexes,network jam simulation was carried out on a regular signalized road network.The simulation results show that：1） The propagation of traffic congestion on a signalized road network can be classified into two stages：virtual split driven stage and flow rate driven stage.The former stage is characterized by decreasing virtual split while the latter only depends on flow rate; 2） The jam propagation rate and direction are dependent on traffic demand distribution and other network parameters.The direction with higher demand gets more chance to be jammed.Our findings can serve as the basis of the prevention of the formation and propagation of network traffic jam.     

Development of control strategy of variable speed limits for improving traffic operations at freeway bottlenecks

A control strategy of variable speed limits （VSL） was developed to reduce the travel time at freeway recurrent bottleneck areas. The proposed control strategy particularly focused on preventing the capacity drop and increasing the discharge flow. A cell transmission model （CTM） was developed to evaluate the effects of the proposed VSL control strategy on the traffic operations. The results show that the total travel time is reduced by 25.5% and the delay is reduced by 56.1%. The average travel speed is increased by 34.3% and the queue length is reduced by 31.0%. The traffic operation is improved by the proposed VSL control strategy. The way to use the proposed VSL control strategy in different types of freeway bottlenecks was also discussed by considering different traffic flow characteristics. It is concluded that the VSL control strategy is effective for merge bottlenecks but is less effective for diverge bottlenecks.     

Ants-Based On-Demand Routing Algorithm for Mobile Ad Hoc Networks

An ants-based on-demand routing algorithm （AORA） specialized for mobile ad hoc networks is proposed. AORA measures the network＇s traffic information including delivery time, route energy etc. by the continuous delivery of data packets, then calculates the compositive parameter for each route which can be seen as the stigmity and uses it to choose the comparatively optimal route in real time. To adjust the weight of each traffic information, the algorithm can meet the different demand of the network＇s user. Multipath source self repair routing （MSSRR） algorithm and dynamic source routing （DSR） can be seen as the special samples of AORA. The routing overhead is not increased in this algorithm. By using simulation, it can be seen that the performance of AORA is better than that of DSR in all scenarios obviously, especially the delivery fraction is increased by more than 100 96.     

Reliability-based congestion pricing model under endogenous equilibrated market penetration and compliance rate of ATIS

A reliability-based stochastic system optimum congestion pricing(SSOCP) model with endogenous market penetration and compliance rate in an advanced traveler information systems(ATIS) environment was proposed. All travelers were divided into two classes. The first guided travelers were referred to as the equipped travelers who follow ATIS advice, while the second unguided travelers were referred to as the unequipped travelers and the equipped travelers who do not follow the ATIS advice(also referred to as non-complied travelers). Travelers were assumed to take travel time, congestion pricing, and travel time reliability into account when making travel route choice decisions. In order to arrive at on time, travelers needed to allow for a safety margin to their trip.The market penetration of ATIS was determined by a continuous increasing function of the information benefit, and the ATIS compliance rate of equipped travelers was given as the probability of the actually experienced travel costs of guided travelers less than or equal to those of unguided travelers. The analysis results could enhance our understanding of the effect of travel demand level and travel time reliability confidence level on the ATIS market penetration and compliance rate; and the effect of travel time perception variation of guided and unguided travelers on the mean travel cost savings(MTCS) of the equipped travelers, the ATIS market penetration, compliance rate, and the total network effective travel time(TNETT).     

Joint analysis of urban shopping destination and travel mode choice accounting for potential spatial correlation betweenalternatives

In recent years, there have been important developments in the joint analysis of the travel behavior based on discrete choice models as well as in the formulation of increasingly flexible closed-form models belonging to the generalized extreme value class. The objective of this work is to describe the simultaneous choice of shopping destination and travel-to-shop mode in downtown area by making use of the cross-nested logit （CNL） structure that allows for potential spatial correlation. The analysis uses data collected in the downtown areas of Maryland-Washington, D.C. region for shopping trips, considering household, individual, land use, and travel-related characteristics. The estimation results show that the dissimilarity parameter in the CNL model is 0.37 and significant at the 95% level, indicating that the alternatives have high spatial correlation for the short shopping distance. The results of analysis reveal detailed significant influences on travel behavior of joint choice shopping destination and travel mode. Moreover, a Monte Carlo simulation for a group of scenarios arising from transportation policies and parking fees in downtown area, was undertaken to examine the impact of a change in car travel cost on the shopping destination and travel mode switching. These findings have important implications for transportation demand management and urban planning.     

Modified stochastic user-equilibrium assignment algorithm for urban rail transit under network operation

Based on the framework of method of successive averages(MSA), a modified stochastic user-equilibrium assignment algorithm was proposed, which can be used to calculate the passenger flow distribution of urban rail transit(URT) under network operation. In order to describe the congestion’s impact to passengers’ route choices, a generalized cost function with in-vehicle congestion was set up. Building on the k-th shortest path algorithm, a method for generating choice set with time constraint was embedded, considering the characteristics of network operation. A simple but efficient route choice model, which was derived from travel surveys for URT passengers in China, was introduced to perform the stochastic network loading at each iteration in the algorithm. Initial tests on the URT network in Shanghai City show that the methodology, with rational calculation time, promises to compute more precisely the passenger flow distribution of URT under network operation, compared with those practical algorithms used in today’s China.     

Analyzing influence of bicycles on traffic flow using microscopic simulation approach

Mixed traffic consisting of cars and bicycles is a typical pattern of urban traffic in China.To study the impact of bicycles on traffic performance,a microscopic simulating model based on the principle of cautious driving and collision free was proposed.The interaction between cars and bicycles were described by lateral friction and overlapping driving.The dynamical features of speed and time-headway were investigated by numerical simulations.The results show that bicycles have a significant impact on travel speed and time-headway.The effect of bicycles can cause different results in the free flow phase and congestion phase respectively.The results also indicate the necessity to mitigate the interaction between motorized vehicles and non-motorized vehicles.     

Alpha-reliable combined mean traffic equilibrium model with stochastic travel times

Based on the reliability budget and percentile travel time （PTT） concept, a new travel time index named combined mean travel time （CMTT） under stochastic traffic network was proposed. CMTT here was defined as the convex combination of the conditional expectations of PTT-below and PTT-excess travel times. The former was designed as a risk-optimistic travel time index, and the latter was a risk-pessimistic one. Hence, CMTT was able to describe various routing risk-attitudes. The central idea of CMTT was comprehensively illustrated and the difference among the existing travel time indices was analyzed. The Wardropian combined mean traffic equilibrium （CMTE） model was formulated as a variational inequality and solved via an alternating direction algorithm nesting extra-gradient projection process. Some mathematical properties of CMTT and CMTE model were rigorously proved. Finally, a numerical example was performed to characterize the CMTE network. It is founded that that risk-pessimism is of more benefit to a modest （or low） congestion and risk network, however, it changes to be risk-optimism for a high congestion and risk network.     

Evolvement regularity of signal control parameters of urban road in cold region

In snow-icy road environment, the survey data indicate that the largest decrease in traffic flow running characters occurs when snow and ice begin to accumulate on the road surface. Saturation flow is decreased by 16%, speed is decreased by 30%, and start-up lost time is increased by 27%. Based on the signal control theory of HCM and Webster, the character values of traffic flow in different urban road environments were investigated, and the evolvement regularity of signal control parameters such as cycle, split, green time, offset, yellow time and red time in snow-icy road environment was analyzed. The impact factors and the changes in the scope of signal control parameters were achieved. Simulation results and practical application show that the signal control plan of road environment without snow and ice will increase the vehicle delay, stop length and traffic congestion in snow-icy road environment. Thus, the traffic signal control system should address a suitable signal control plan based on different road environments.     

考虑交通诱导下新进出行者的网络交通流演化模型

研究了城市网络交通流的动态演化行为.在网络交通流的演化过程中,出行者根据路网状况不断调整自己的出行路径,假设OD对出行需求和路径流量受到OD对出行成本的影响,考虑在交通诱导下新进出行者的路径选择方式,以Logit分配模型表示新进出行者选择出行路径的比例,提出一个改进的交通流演化模型,并分析了该模型及其零点的一些特性,它能更好地反映现实中交通流演化结果.数值实验结果表明,模型可近似描述交通流演化到用户均衡态的过程,交通流能够收敛到均衡状态.     

Real-time routing control design for traffic networks with multi-route choices

This work considers those road networks in which there are multi-route choices for bifurcation-destination(or origin-destination) pairs, and designs a real-time variable message sign(VMS)-based routing control strategy in the model predictive control(MPC) framework. The VMS route recommendation provided by the traffic management authority is directly considered as the control variable, and the routing control model is established, in which a multi-dimensional control vector is introduced to describe the influence of route recommendations on flow distribution. In the MPC framework, a system optimum routing strategy with the constraints regarding drivers' acceptability with recommended routes is designed, which can not only meet the traffic management authority's control requirement but also improve drivers' satisfaction with the route guidance system. The simulation carried out shows that the proposed routing control can effectively mitigate traffic congestion, reduces followers' time delay, and improves drivers' satisfaction with routing control in road networks.     

有限理性视野下拥挤收费对交通流逐日演化规律影响

为了解决拥挤收费政策在不同理性程度群体构成的交通流中的实施效果问题,在逐日路径演化模型的基础上引入拥挤收费政策,建立新的模型以研究拥挤收费条件下出行者逐日路径选择行为.并以一个由2条路径构成的路网为例,探讨了有限理性视野下拥挤收费政策对网络交通流逐日动态演化过程的影响.通过数值实验,分析了拥挤收费条件下网络交通流的演化特征,发现拥挤收费对网络交通流演化的最终状态以及系统平均走行时间有一定的影响;出行者的时间价值、理性程度会影响拥挤收费政策的实施效果.     

基于元胞传输模型的区域疏散动态交通分配

为制定合理、高效的灾害条件下区域疏散交通管理与规划方案,针对道路交通应急区域疏散的动态交通分配问题进行研究.首先,采用元胞传输理论和单终点疏散方法,建立了元胞-连接桥疏散路网模型,进而以系统疏散出行时间最短为目标函数,以元胞流量守恒和流量传播等为约束条件,构建了区域疏散动态交通分配线性规划模型.对该模型的求解可以得到系统最优疏散出行时间、疏散清空时间、分阶段疏散优先权分配方案、交叉口车流诱导方案以及疏散者终点选择和路径选择最优方案.案例分析的结果表明,该模型即能够满足大规模疏散路网建模的需求,同时又能恰当地反映疏散交通流的动态特性.     

城市交通微循环系统优化设计方法

为充分利用城市交通微循环道路资源以有效缓解路网交通拥挤,在分析交通微循环系统特征的基础上,设计了完整的城市交通微循环系统优化方法.以缓解区域路网交通拥挤为优化目标,依据交通流特征与交通需求定位城市主干道路网的拥挤路段,然后建立微循环绕行路线的搜索模型,能够确定需进行道路条件与交通组织优化的微循环路段,并生成静态交通标志与可变信息板的布设地点.以曲靖市中心城区交通微循环系统优化为实例,验证了所提出优化方法的有效性.     

基于出行计划数据的最优路径规划方法

现有基于交通流预测的路径规划方法大多使用历史或实时交通流数据,预测时效性有待提升. 针对上述问题,提出基于出行计划数据的路径规划方法（RPTP）. 该方法能主动捕捉出行者的未来交通需求,为车辆提供更合理的出行路线.基于出行计划的思想,设计基于出行计划数据的路径规划整体框架;构建基于出行计划路线数据的未来时段路网密度估计算法;采用空间堆叠的方式融合未来多时段路网密度,以此为依据改进D*Lite算法的启发函数. 采用SUMO平台仿真验证,与静态路径规划方法（SPP）和滚动路径规划方法（RPP）进行对比分析.结果显示,在相同环境下RPTP方法能提高车辆的通行效率,缓解路网拥堵,有效验证了RPTP方法的优越性.     

拥挤条件下可变信息板交通诱导信息对驾驶行为的影响

运用模拟的方法,研究了在拥挤条件下VMS交通诱导信息对驾驶行为的影响,得出如下结论:①VMS交通诱导信息的提供位置对交通信息的作用有很大的影响。如果交通诱导信息被合理地提供给驾驶员,路网交通的运行状况将有较大改善,其中延误减少23.7%,停车时间减少31.8%,停车次数减少38.7%;②路网交通运行状况的改善取决于所推荐的替代路径的质量。如果替代路径的质量较差,拥挤现象不但不能得到缓解而且会进一步恶化,并且在替代路径上会形成新的拥挤;③左转次数和左转通行能力是决定替代路径质量的两个关键因素。无论是以出行时间还是出行距离为依据选择替代路径,都应该考虑左转次数及左转通行能力的影响。     

基于阻塞概率分析的车辆自动导航路线优选模型

根据交通供需随机性分析,借鉴网络可靠性分析方法,提出了概率型指标——畅通可靠度的概念和计算方法,通过该指标可分析拥挤路网阻塞现象发生的可能性。同时,以路网阻塞概率分析为基础,在没有实时交通数据采集的条件下,利用统计资料及经验信息,综合考虑绕行距离,建立了基于阻塞概率分析的车辆自动导航路径优选模型。该模型可为出行者提供更接近实际情况的满意的路径及出行信息,减少用户决策的盲目性。     

基于Mixed logit模型的拥挤收费下交通方式分担率预测

分析了传统非集计模型存在的缺陷,提出利用mixed logit模型研究拥挤收费下交通方式分担率变化的思路。结合实际居民出行数据建立了基于mixed logit的交通方式选择模型,利用SAS软件进行蒙特卡罗模拟计算,标定了模型并进行了仿真分析。经验证,所建模型具有较高的命中率和可用性。加入拥挤收费影响因素进行敏感性分析,可得出不同拥挤收费费率下的交通方式分担率。应用该模型能为拥挤收费下的出行行为分析和交通影响研究以及其他交通需求管理政策的评价提供了方法。     

改进型CTM模型突发事件下的拥堵传播规律

通过引入元胞长度和元胞交通流密度2个参数,克服了原元胞传输模型(CTM)需要所有元胞统一长度的局限性.同时,结合传统的基本图方法和三相交通流理论,构建了考虑迟滞现象的MCTM模型,并研究了突发事件下快速路通行能力下降导致交通拥堵的形成及消散过程.仿真结果表明:模型能恰当反映城市快速路突发事件下的交通拥堵演化特点.