基于Q-learning 的定制公交跨区域路径规划研究

考虑城市大客流通勤者跨区域出行需求,结合城市公交线网中乘客出行密集、客流走向规律等特点,提出一种跨区域定制公交的搭乘方案. 通过改进的Q-learning 模型对公交线路进行优化,为城市通勤者提供更加便捷和高效的出行服务. 通过综合路段拥堵状态、乘客需求及居民小区位置,设定了Q-learning 强化学习的奖惩函数,提升定制公交区域路径的直线系数、满载率、通行时间. 结果表明,所提出的改进方法能够降低通勤者跨区域通行的旅行时间,有效提高髙峰时段定制公交线网的通行效率.     

交通大数据视角看广佛同城

广佛同城发展由来已久,是中国城市群中同城化程度最高的区域。简要分析广佛同城的交通基础设施发展演变历程,并基于模糊大数据(手机信令数据)和准确大数据(运行监测数据)对广佛通勤交通特征进行分析。结合手机信令数据对广州南站的客流组成及空间分布进行研究,对广州南站选址偏远问题进行解析。结果表明:广佛同城具有双向对等性的联系;地铁在同城化推进过程中起到重要的促进作用,拓展同城化活动范围;广州市机动车交通需求管理政策不够系统,非广佛车牌在通勤小汽车中比例超过40%,需要引起足够的关注;广州南站服务的客流中广州客流与佛山客流比为7:3,与对应的常住人口规模比例相当,初步实现了交通战略规划提出的共享理念。     

实业家与慈善事业的结合——近代江苏实业家与晚清"义赈"的兴起

晚清时期的民间慈善事业在光绪初年时已发生一些新的变化,具体表现为江苏实业家成立新式慈善机构、改变传统赈灾观念、从事募捐善款、制定高效的放赈方式。实业家积极投身于大规模的民间赈灾活动,有力的促进了晚清时期“义赈”活动的兴起。     

基于出行时长的大型活动停车换乘选择行为研究

以大型活动期间来自外省市的小汽车出行者为研究对象,对不同出行时长的停车换乘选择行为进行调查和研究。结果表明当日往返者和停留多日者对停车换乘的需求特征与选择行为存在差异：停车供应限制政策对前者利用小汽车出行的选择行为影响较大,对后者的影响较小;前者强调换乘公共交通的直达性和便捷性,对时间要求较高,后者则重视交通方式的灵活性。针对停留多日者的相关设施及政策还须统筹考虑全程出行链的需求,提出在郊区新城结合住宿情况设置停车换乘系统。     

Strava Metro data for bicycle monitoring: a literature review

ABSTRACT

Monitoring bicycle trips is no longer limited to traditional sources, such as travel surveys and counts. Strava, a popular fitness tracker, continuously collects human movement trajectories, and its commercial data service, Strava Metro, has enriched bicycle research opportunities over the last five years. Accrued knowledge from colleagues who have already utilised Strava Metro data can be valuable for those seeking expanded monitoring options. To convey such knowledge, this paper synthesises a data overview, extensive literature review on how the data have been applied to deal with drivers’ bicycle-related issues, and implications for future work. The review results indicate that Strava Metro data have the potential—although finite—to be used to identify various travel patterns, estimate travel demand, analyse route choice, control for exposure in crash models, and assess air pollution exposure. However, several challenges, such as the under-representativeness of the general population, bias towards and away from certain groups, and lack of demographic and trip details at the individual level, prevent researchers from depending entirely on the new data source. Cross-use with other sources and validation of reliability with official data could enhance the potentiality.     

Estimation of delay variability at signalized intersections for urban arterial performance evaluation

Urban arterial performance evaluation has been broadly studied, with the major focus on average travel time estimation. However, in view of the stochastic nature of interrupted flow, the ability to capture the characteristics of travel time variability has become a critical step in determining arterial level of service (LOS). This article first presents a stochastic approach that integrates classic cumulative curves and probability theories in order to investigate delay variability at signalized intersections, as a dominant part of the link travel time variability. This serves as a basis for arterial travel time estimation, which can be obtained through a convolution of individual link travel time distributions. The proposed approach is then applied in the estimation of travel time along one arterial in Shanghai, China, with abundant automatic vehicle identification (AVI) data sources. The travel time variability is evaluated thoroughly at 30-min intervals, with promising results achieved in comparison to the field measurements. In addition, the estimated travel time distributions are utilized to illustrate the probability of multiple LOS ranges, namely, reliability LOS. The results provide insights into how we might achieve a more reliable and informative understanding of arterial performance.     

Plate scanning tools to obtain travel times in traffic networks

The management of vehicle travel times has been shown to be fundamental to traffic network analysis. To collect travel time measurement, some methods focus solely on isolated links or highway segments, and where two measurement points, at the beginning and at the end of a section, are deemed sufficient to evaluate users' travel time. However, in many cases, transport studies involve networks in which the problem is more complex. This article takes advantage of the plate scanning technique to propose an algorithm that minimizes the required number of registering devices and their location in order to identify vehicles candidates to compute the travel times of a given set of routes (or subroutes). The merits of the proposed method are explained using simple examples and are illustrated by its application to the real network of Ciudad Real.     

Subjective-utility travel time budget modeling in the stochastic traffic network assignment

ABSTRACT

In this article, we propose a new model called subjective-utility travel time budget (SU-TTB) model to capture travelers' risk-averse route choices. In the travel time budget (TTB) and mean-excess travel time (METT) model, a predefined confidence level is needed to capture the risk-aversion in route choice. Due to the day-to-day route travel time variations, the exact confidence level is hard to be predicted. With the SU-TTB model, we assume travelers' confidence level belongs to an interval that they may comply with in the route choice. The two main components of SU-TTB are the utility function and the TTB model. We can show that the SU-TTB can be reduced to the TTB and METT model with proper utility function for the confidence levels. We can also prove its equivalence with our recently proposed nonlinear-expectation route travel time (NERTT) model in some cases and give some new interpretation on the NERTT with this equivalence. Finally, we formulate the SU-TTB model as a variational inequality (VI) problem to model the risk-averse user equilibrium (RAUE), termed as generalized RAUE (GRAUE). The GRAUE is solved via a heuristic gradient projection algorithm, and the model and solution algorithm are demonstrated with the Braess's traffic network and the Nguyen and Dupuis's traffic network.     

Robust traffic assignment model: Formulation,solution algorithms and empirical application

ABSTRACT

The deterministic traffic assignment problem based on Wardrop's first criterion of traffic network utilization has been widely studied in the literature. However, the assumption of deterministic travel times in these models is restrictive, given the large degree of uncertainty prevalent in urban transportation networks. In this context, this paper proposes a robust traffic assignment model that generalizes Wardrop's principle of traffic network equilibrium to networks with stochastic and correlated link travel times and incorporates the aversion of commuters to unreliable routes.

The user response to travel time uncertainty is modeled using the robust cost (RC) measure (defined as a weighted combination of the mean and standard deviation of path travel time) and the corresponding robust user equilibrium (UE) conditions are defined. The robust traffic assignment problem (RTAP) is subsequently formulated as a Variational Inequality problem. To solve the RTAP, a Gradient Projection algorithm is proposed, which involves solving a series of minimum RC path sub-problems that are theoretically and practically harder than deterministic shortest path problems. In addition, an origin-based heuristic is proposed to enhance computational performance on large networks. Numerical experiments examine the computational performance and convergence characteristics of the exact algorithm and establish the accuracy and efficiency of the origin-based heuristic on various real-world networks. Finally, the proposed RTA model is applied to the Chennai road network using empirical data, and its benefits as a normative benchmark are quantified through comparisons against the standard UE and System Optimum (SO) models.     

深圳市交通需求管理政策的法治思考

深圳市制定和实施了若干小汽车交通需求管理政策,完善相关政策的法制保障成为政策实施的关键问题。首先结合深圳市交通需求管理实践经验,梳理小汽车增量调控、停车收费政策的制定与实施情况。指出交通需求管理政策的制定与实施面临经济杠杆存在法理争议、行政手段法律依据不足和程序合法性存疑等法治障碍。进而提出在国家层面构建交通管理法治体系、在地方层面完善法律法规以及规范交通需求管理政策出台程序等完善路径。