Real-time freeway traffic state estimation based on extended Kalman filter: Adaptive capabilities and real data testing

This paper reports on real data testing of a real-time freeway traffic state estimator, with a particular focus on its adaptive capabilities. The pursued general approach to the real-time adaptive estimation of complete traffic state in freeway stretches or networks is based on stochastic macroscopic traffic flow modeling and extended Kalman filtering. One major innovative feature of the traffic state estimator is the online joint estimation of important model parameters (free speed, critical density, and capacity) and traffic flow variables (flows, mean speeds, and densities), which leads to three significant advantages of the estimator: (1) avoidance of prior model calibration; (2) automatic adaptation to changing external conditions (e.g. weather and lighting conditions, traffic composition, control measures); (3) enabling of incident alarms. These three advantages are demonstrated via suitable real data testing. The achieved testing results are satisfactory and promising for subsequent applications.     

Assessing the technical efficiency, service effectiveness, and technical effectiveness of the world’s railways through NDEA analysis

This paper presents an approach to include both the unstorable feature of transportation service and the technological differences within railway companies in efficiency and effectiveness measurements. We explore efficiency and effectiveness for a group of 40 global railways in the year 2002, using traditional data development analysis (TDEA) and network data development analysis (NDEA). Comparing the results obtained from the NDEA model with those from the TDEA indicate that performance measures are quite different in terms of the magnitude, and even using different DEA type models to evaluate railway system performance does not distort the ranking of their performance. We also analyze the inter-related effects among three performance measures, finding that transportation service characteristics have positive effects on the evaluation of performance. Generally speaking, the NDEA model provides deeper insight regarding the sources of inefficiency and process-specific guidance to railway managers so as to help them improve their railway’s performance.     

Joint distortion model for progressive image transmission using error correcting arithmetic codes

A novel joint source channel distortion model was proposed, which can essentially estimate the average distortion in progressive image transmission. To improve the precision of the model, the redundancy generated by a forbidden symbol in the arithmetic codes is used to distinguish the quantization distortion and the channel distortion, all the coefficients from the first error one to the end of the sequence are set to be a value within the variance range of the coefficients instead of zero, then the error propagation coming from the entropy coding can be essentially estimated, which is disregarded in the most conventional joint source channel coding （JSCC） systems. The precision of the model in terms of average peak-signal-to-noise has been improved about 0.5 dB compared to classical works. An efficient unequal error protection system based on the model is developed, and can be used in the wireless communication systems.     

A total generalized optimal velocity model and its numerical tests

A car-following model named total generalized optimal velocity model （TGOVM） was developed with a consideration of an arbitrary number of preceding vehicles before current one based on analyzing the previous models such as optimal velocity model （OVM）, generalized OVM （GOVM） and improved GOVM （IGOVM）. This model describes the physical phenomena of traffic flow more exactly and realistically than previous models. Also the performance of this model was checked out by simulating the acceleration and deceleration process for a small delay time. On a single circular lane, the evolution of the traffic congestion was studied for a different number of headways and relative velocities of the preceding vehicles being taken into account. The simulation results show that TGOVM is reasonable and correct.     

基于逆向重力模型的枢纽机场旅客吞吐量估计方法

为了利用航空OD客流数据精确估计机场旅客吞吐量,描述了全连通线性航线网络和枢纽辐射航线网络,根据枢纽机场之间的OD客流矩阵,建立了逆向重力模型标准代数算法和基于哈密顿图原理的简化代数算法,分析了在不同距离修正指数下,算法的拟合与估计精度。分析结果表明:简化代数算法与模型标准代数算法最优吞吐量回归直线的可决系数都为0.84,斜率分别为0.91和0.87,比较接近。可见算法的拟合效果优良,估计精度高,且简化代数算法需要的数据少,尤其适合大规模OD矩阵分析。     

路段平均行程时间估计方法

为了有效利用线圈检测数据,精确估计路段平均行程时间,提出了一种路段平均行程时间估计方法。将路段平均行程时间分为平均行驶时间、平均排队时间和平均通过路口时间三部分。考虑线圈埋设的特点,通过估计平均行驶速度得到平均行驶时间。用分段时齐Poisson过程描述车辆驶入路段过程和驶离过程,用Markov排队模型描述车辆排队过程,用生灭过程描述排队车辆数,得到车辆排队模型,计算了路段有、无初始排队的平均排队时间。基于选取与路口相关的饱和流率和平均车长,计算了平均通过路口时间。计算结果表明:平均行程时间估计值与实测值的误差小于12%,说明路段平均行程时间估计方法可行。     

内河航道横流对船舶航行的影响

为了使船舶能安全通过航道内的横流区域,利用水槽进行遥控自航船模试验,提出了内河航道横流对船舶航行横漂速度、漂角、航迹带宽度和漂距影响的经验公式,分析了Ⅳ与Ⅴ级航道横向流速的限值范围。分析结果表明:横流对船舶航行的影响程度主要与对岸航速成反比,与横流的大小及区域长度成正比,与船型大小(航道等级)成反比,同时与驾驶员的航行经验和初始船位有关;在限制航路航行方式过程中,Ⅳ与Ⅴ级航道对岸航速为2、3、4m·s-1时,可克服的一个船长内横流限值为0.48、0.58、0.70m·s-1。     

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简单输入输出模型与冲击波分析是研究交通瓶颈问题的两种常用方法,本文着重分析两者的一致性。在数学推导中考虑到达需求与流出率的变化时,两者对于排队和延误的预测结果是一致的。在不同的交通和边界条件下,两者在拥堵形成至消散的任意时刻所得排队长度,拥堵时间等结果均是一致的。以往认为两种方法不一致的研究忽略了一些与背景交通密切相关的基本因素。实例分析说明正是这些基本因素使得这两种分析方法在不同流量－密度关系下都具有一致性。     

Travel Behavior Analysis of the Females in Beijing

In urban life, compared with the same age group of male contrast, the statistical indicators of female travel behavior show significant differences. According to the sample data of Beijing 2005 travel survey, the paper analyzes the female travel behavior in the travel rate, travel consumption, trip purpose, and travel mode. Furthermore, the paper introduces the concept of the trip chain, to construct a female morning commuter trip chain choice behavior model with noncollection theories and methods, to analyze 10 factors that influence a female individual's choice of a trip chain from the source. Subsequently, model parameters are estimated, to calculate the incidents that can help to quantitatively understand the impact of each factor on a female's choice of the trip chain. The results show that the travel rate of elderly women is far lower than that of elderly men. Female travel proportion in shopping and social activities is obviously higher than that of male travelers, and factors related to the structure of families create important constraints in their average travel time consumption. The main travel mode of the female is walking, which is far more than that of a male. Age, whether they hold licenses, monthly income, and transport ownership are dominant factors for the female's choice of the trip chain.     

基于约束卡尔曼滤波的短时交通流量组合预测模型

为了克服单一的交通流预测模型性能不稳定的问题,提出了基于约束卡尔曼滤波的短时交通流量组合预测模型。约束卡尔曼滤波组合预测模型以各单一预测模型的权重为状态变量,交通流量为观测变量,预测结果是单一预测模型的加权和,加权系数由约束卡尔曼滤波方程递推动态确定,最后通过广深高速公路上采集的交通流量数据对算法进行了验证。结果表明,在不同预测步长情况下,约束卡尔曼滤波组合预测模型要优于最佳的单一预测模型或与其持平,并且不受某一较差的预测模型影响,具有较高的鲁棒性。