Route swapping in dynamic traffic networks

A dynamic traffic assignment (DTA) model typically consists of a traffic performance model and a route choice model. The traffic performance model describes how traffic propagates (over time) along routes connecting origin-destination (OD) pairs, examples being the cell transmission model, the vertical queueing model and the travel time model. This is implemented in a dynamic network loading (DNL) algorithm, which uses the given route inflows to compute the link inflows (and hence link costs), which are then used to compute the route travel times (and hence route costs). A route swap process specifies the route inflows for tomorrow (at the next iteration) based on the route inflows today (at the current iteration). A dynamic user equilibrium (DUE), where each traveller on the network cannot reduce his or her cost of travel by switching to another route, can be sought by iterating between the DNL algorithm and the route swap process. The route swap process itself takes up very little computational time (although route set generation can be very computationally intensive for large networks). However, the choice of route swap process dramatically affects convergence and the speed of convergence. The paper details several route swap processes and considers whether they lead to a convergent system, assuming that the route cost vector is a monotone function of the route inflow vector.     

Cognitive cost in route choice with real-time information: An exploratory analysis

Real-time traffic information is increasingly available to support route choice decisions by reducing the travel time uncertainty. However it is likely that a traveler cannot assess all available information on all alternative routes due to time constraints and limited cognitive capacity. This paper presents a model that is consistent with a general network topology and can potentially be estimated based on revealed preference data. It explicitly takes into account the information acquisition and the subsequent path choice. The decision to acquire information is assumed to be based on the cognitive cost involved in the search and the expected benefit defined as the expected increase in utility after the search. A latent class model is proposed, where the decision to search or not to search and the depth of the search are latent and only the final path choices are observed. A synthetic data set is used for the purpose of validation and ease of illustration. The data are generated from the postulated cognitive-cost model, and estimation results show that the true values of the parameters can be recovered with enough variability in the data. Two other models with simplifying assumptions of no information and full information are also estimated with the same set of data with significantly biased path choice utility parameters. Prediction results show that a smaller cognitive cost encourages information search on risky and fast routes and thus higher shares on those routes. As a result, the expected average travel time decreases and the variability increases. The no-information and full-information models are extreme cases of the more general cognitive-cost model in some cases, but not generally so, and thus the increasing ease of information acquisition does not necessarily warrant a full-information model.     

The effects of social networks on choice set dynamics: Results of numerical simulations using an agent-based approach

Activity-based analysis has slowly shifted gear from the analysis of daily activity patterns to the analysis and modeling of dynamic activity-travel patterns. In this paper, we address one type of dynamics: the formation and adaptation of location choice sets under influence of dyad relationships within social networks. It extends the dynamic model developed in earlier work, which simulates habitual behavior versus exploitation and exploration as a function of discrepancies between dynamic, context-dependent aspiration levels and expected outcomes. Principles of social comparison and knowledge transfer are used in modeling the impact of social networks through information exchange, adaptations of spatial choice sets and formation of common aspiration levels. We demonstrate model properties using numerical simulation with a case study of shopping activities.     

Mode choice models' ability to express intention to change travel behaviour considering non-compensatory rules and latent variables

Disaggregate behaviour choice models have been improved in many aspects, but they are rarely evaluated from the viewpoint of their ability to express intention to change travel behaviour. This study compared various models, including objective and latent models and compensatory and non-compensatory decision-making models. Latent models contain latent factors calculated using the LISREL (linear structural relations) model. Non-compensatory models are based on a lexicographic-semiorder heuristic. This paper proposes ‘probability increment’ and ‘joint probability increment’ as indicators for evaluating the ability of these models to express intention to change travel behaviour. The application to commuting travel data in the Chukyo metropolitan area in Japan showed that the appropriate non-compensatory and latent models outperform other models.     

Experimental Study of Effects of Travel Time Distribution Information on Dynamic Route Choice Behavior

This study focuses on the possibility that providing travelers with information on travel time distribution, along with the existing travel time information, might affect their decision making and enhance traffic control. As an initial step to confirm the effectiveness of travel time distribution information, we use a laboratory experiment to obtain panel data of route choices when information is provided. The rationality of the behavior of the respondents and the characteristics of the route choice are first analyzed by aggregation analysis and then statistically examined by specifying a mixed logit route choice model. As a result, it is revealed that both travel time information and maximum travel time information significantly affect route choice behavior when a penalty is imposed for late arrival.     

北京地铁五号线天坛东门站施工监测技术及受力特性研究

通过对天坛东门站施工过程中围岩变形、压力和结构内力进行系统监测,对中洞法施工过程中的围岩及车站结构的受力特点进行了分析;提出了一套适合大跨度浅埋车站的施工监控技术,在天坛东门站的复杂施工过程中得到了成功应用。文章对中洞法施工方案的合理性及施工中的安全性进行了论证,并为中洞法施工总结出了可供推广的经验。     

生态影响综合评价方法在公路选线中的应用

针对高速公路建设项目的特点,从指标选取入手,采取定量分析的手段,对比研究了两条线路工程建设对生态环境的影响程度。结果表明,用植被覆盖率、生物量、滞洪能力、土壤变化、农田占用、水土流失量等6项指标来定量分析生态影响程度效果较好,采用综合生态影响评价指数法确定线路的舍取是可行的。     

基于需求划分的带软时间窗的路径优化方法

针对带有时间窗约束的车辆路径问题(Vehicle Routing Problem With Time Windows,VRPTW)的NP特征,以非完全连通配送网络为研究对象,用带有软时间窗约束的整体配送费用最小为目标,提出了一种基于需求的城市动态划分方法,有效的减少了路径的组合规模,并且用遗传算法将其实现,通过改进的Dijkstra算法求取其基于动态划分的最优配送路径集,最后计算示例验证了本文方法的有效性。     

同三公路哈尔滨绕城高速公路西北半环路线方案分析

根据我省公路网建设和规划情况,就目前穿越哈尔滨市各条公路的现状,对同三公路哈尔滨市绕城高速公路西北半环路修建的必要性、意义进行了分析,同时提出了合理的路线方案。     

道路安全理念在山区公路设计中的应用

从道路安全的理念出发,探讨了山区公路基于道路安全理念的设计思路,并从运行速度、安全设施、隧道出入口等方面介绍了道路安全理念的应用。