Decomposing travel times measured by probe-based traffic monitoring systems to individual road segments

In probe-based traffic monitoring systems, traffic conditions can be inferred based on the position data of a set of periodically polled probe vehicles. In such systems, the two consecutive polled positions do not necessarily correspond to the end points of individual links. Obtaining estimates of travel time at the individual link level requires the total traversal time (which is equal to the polling interval duration) be decomposed. This paper presents an algorithm for solving the problem of decomposing the traversal time to times taken to traverse individual road segments on the route. The proposed algorithm assumes minimal information about the network, namely network topography (i.e. links and nodes) and the free flow speed of each link. Unlike existing deterministic methods, the proposed solution algorithm defines a likelihood function that is maximized to solve for the most likely travel time for each road segment on the traversed route. The proposed scheme is evaluated using simulated data and compared to a benchmark deterministic method. The evaluation results suggest that the proposed method outperforms the bench mark method and on average improves the accuracy of the estimated link travel times by up to 90%.     

广铁集团电话订票系统的设计与实现

在广铁集团电话订票系统是在广铁集团现有信息系统的基础上,借助铁路的数据传输网,实现基于电话语音、手机短信、互联网等多种接入模式的旅客实时信息服务系统.重点介绍系统的总体结构、自动语音流程、功能设计、关键技术和应用效果等.     

Analysis of taxi demand and supply in New York City: implications of recent taxi regulations

This paper investigates temporal and weather-related variation in taxi trips in New York City. A taxi trip data-set with 147 million records covering 10 months of activity is used. It is shown that there are substantial variations in ridership, taxi supply, trip distance, and pickup frequency for different time periods and weather conditions. These variations, in turn, cause variations in driver revenues which is one of the main measures of taxi supply–demand equilibrium. The findings are then used to discuss the anticipated impacts of two recently enacted taxi regulation changes: the first fare increase since 2006 and the E-Hail pilot program which allows taxi hailing with smart phone applications. The fare increase is estimated to cause varying levels of revenue increase for different time periods. E-Hail apps are not expected to offer considerable improvements at all times, but rather when both adequate taxi supply and demand occur simultaneously.     

融合手机信令数据的轨道交通出行分担率模型研究

交通行为模型广泛应用于城市出行需求分析等领域.传统行为模型的参数设置通常依赖经验判断,模型预测精度缺乏大样本验证手段.本文以重庆市解放碑-观音桥组团通道出行行为为研究对象,融合手机信令数据、AFC数据和问卷调查数据,构建随机参数分别为正态分布、均匀分布和γ分布的混合Logit模型,将手机信令数据与AFC数据分析结果作为...     

Effects of income inequality on evacuation,reentry and segregation after disasters

Large-scale disasters often trigger mass evacuation due to significant damages to urban systems. Understanding the evacuation and reentry (return) process of affected individuals is crucial for disaster management. Moreover, measuring the heterogeneity in the individuals' post-disaster behavior with respect to their socio-economic characteristics is essential for policy making. Recent studies have used large-scale location datasets collected from mobile devices to analyze post-disaster mobility patterns. Despite the availability of such data and the societal importance of the problem, no studies have focused on how income inequality affects the equity in post-disaster mobility. To overcome these research gaps, we overlay mobility data with income information from census to quantify the effects of income inequality on evacuation and reentry behavior after disasters, and the resulting spatial income segregation. Spatio-temporal analysis using location data of more than 1.7 million mobile phone users from Florida affected by Hurricane Irma reveal significant effects of income inequality on evacuation behavior. Evacuees with higher income were more likely to evacuate from affected areas and reach safer locations with less damage on housing and infrastructure. These differences were common among evacuees from both inside and outside mandatory evacuation zones. As a result of such effects of inequality, significant spatial income segregation was observed in the affected areas. Insights on the effects of income inequality on post-disaster mobility and spatial segregation could contribute to policies that better address social equity in pre-disaster preparation and post-disaster relief.     

Network Signal Setting Design: Meta-heuristic optimisation methods

This paper aims to investigate the application of meta-heuristic optimisation methods to Network Signal Setting Design. The adopted approaches are (i) three step optimisation, in which first the stage matrix (stage composition and sequence), the green timings at each single junction are optimised, then the node offsets are computed in three successive steps; (ii) two step optimisation, in which the stage matrix is defined at a first step, then the green timings and the node offsets are computed at a second step. In both approaches the stage matrix optimisation is carried out through explicit complete enumeration.In the first approach multi-criteria optimisation is followed for single junction signal setting design (green timings), whilst the coordination (node offsets) is approached through mono-criterion optimisation, as well as for the synchronisation (green timings and offsets) in the second approach.A new traffic flow model mixing CTM and PDM has been applied. This model allows to explicitly represent horizontal queuing phenomena as well as dispersion along a link. Some meta-heuristic algorithms (i.e. Genetic Algorithms, Hill Climbing and Simulated Annealing) are investigated in order to solve the two problems.The proposed strategies are applied to two different layouts (a two junction arterial vs. a four junction network) and their effectiveness is evaluated by comparing the obtained results with those from benchmark approaches implementing mono-criterion optimisation only.     

基于狄利克雷过程混合模型的城市活动聚类方法研究

手机信令数据不仅记录个体出行轨迹，也为分析城市活动空间分布特征提供了基础.本文提出一种基于狄利克雷混合模型的城市活动特征聚类方法，以手机信令提取居民出行OD为基础，将每个基站的到发出行量作为表征该基站所处空间位置的活动特征，研究特征的聚类方法.引入狄利克雷分布作为先验分布，由中餐馆模型推定特征聚类数量.与其他聚类方法相比，该方法最大的优点在于无需事先指定聚类数量，避免了传统聚类方法的缺陷.将本文方法应用到三亚市城市活动特征聚类当中，结果能够有效地反应不同城市功能组团的活动特征.     

A multiclass cell transmission model for shared human and autonomous vehicle roads

Autonomous vehicles have the potential to improve link and intersection traffic behavior. Computer reaction times may admit reduced following headways and increase capacity and backwards wave speed. The degree of these improvements will depend on the proportion of autonomous vehicles in the network. To model arbitrary shared road scenarios, we develop a multiclass cell transmission model that admits variations in capacity and backwards wave speed in response to class proportions within each cell. The multiclass cell transmission model is shown to be consistent with the hydrodynamic theory. This paper then develops a car following model incorporating driver reaction time to predict capacity and backwards wave speed for multiclass scenarios. For intersection modeling, we adapt the legacy early method for intelligent traffic management (Bento et al., 2013) to general simulation-based dynamic traffic assignment models. Empirical results on a city network show that intersection controls are a major bottleneck in the model, and that the legacy early method improves over traffic signals when the autonomous vehicle proportion is sufficiently high.     

Congestion mechanism and demand adjustment strategies for double-cell system with bottlenecks

In this paper, ramp systems on the Beijing 3rd ring road are described as double-cell ramp systems with a bottleneck. By analyzing empirical data for the Beijing 3rd ring road, we found that the initial states have an important impact on the final convergence states of the ramp systems. Then, we studied the dynamic process of the ramp systems, determined the congestion mechanism, and then designed a ramp control method based on the obtained mechanism. Under a feasible demand, double-cell ramp systems exhibit two typical cases, including an upstream-bottleneck system (in which the bottleneck cell is upstream) and a downstream-bottleneck system (in which the bottleneck cell is downstream). Then, a cell transmission model is used to analyze the dynamic evolution processes, starting from different initial states, and determine the congestion mechanism for each case. It is proven that the two systems have different possible equilibrium sets and congestion mechanisms. In an upstream-bottleneck system, the downstream always converges to the uncongested equilibrium, while the upstream bottleneck cell may experience congestion under certain initial states. In a downstream-bottleneck system, the congestion starts downstream, and then gradually propagates upstream. Furthermore, based on the different congestion mechanisms, two demand adjustment strategies are proposed, which redistribute the stationary feasible demand. The simulation results indicate that both systems can converge to uncongested equilibriums after demand adjustment. The ramp demand adjustment methods provide a scientific basis for urban traffic system management.     

A cell-based Merchant-Nemhauser model for the system optimum dynamic traffic assignment problem

A cell-based variant of the Merchant-Nemhauser (M-N) model is proposed for the system optimum (SO) dynamic traffic assignment (DTA) problem. Once linearized and augmented with additional constraints to capture cross-cell interactions, the model becomes a linear program that embeds a relaxed cell transmission model (CTM) to propagate traffic. As a result, we show that CTM-type traffic dynamics can be derived from the original M-N model, when the exit-flow function is properly selected and discretized. The proposed cell-based M-N model has a simple constraint structure and cell network representation because all intersections and cells are treated uniformly. Path marginal costs are defined using a recursive formula that involves a subset of multipliers from the linear program. This definition is then employed to interpret the necessary condition, which is a dynamic extension of the Wardrop’s second principle. An algorithm is presented to solve the flow holding back problem that is known to exist in many discrete SO-DTA models. A numerical experiment is conducted to verify the proposed model and algorithm.