Human-like autonomous car-following model with deep reinforcement learning

This study proposes a framework for human-like autonomous car-following planning based on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation environment where an RL agent learns from trial and error interactions based on a reward function that signals how much the agent deviates from the empirical data. Through these interactions, an optimal policy, or car-following model that maps in a human-like way from speed, relative speed between a lead and following vehicle, and inter-vehicle spacing to acceleration of a following vehicle is finally obtained. The model can be continuously updated when more data are fed in. Two thousand car-following periods extracted from the 2015 Shanghai Naturalistic Driving Study were used to train the model and compare its performance with that of traditional and recent data-driven car-following models. As shown by this study’s results, a deep deterministic policy gradient car-following model that uses disparity between simulated and observed speed as the reward function and considers a reaction delay of 1 s, denoted as DDPGvRT, can reproduce human-like car-following behavior with higher accuracy than traditional and recent data-driven car-following models. Specifically, the DDPGvRT model has a spacing validation error of 18% and speed validation error of 5%, which are less than those of other models, including the intelligent driver model, models based on locally weighted regression, and conventional neural network-based models. Moreover, the DDPGvRT demonstrates good capability of generalization to various driving situations and can adapt to different drivers by continuously learning. This study demonstrates that reinforcement learning methodology can offer insight into driver behavior and can contribute to the development of human-like autonomous driving algorithms and traffic-flow models.     

An ontology-based framework to support performance monitoring in public transport systems

Managers of public transport systems have been facing for years the strategic challenge of maintaining high quality of transport services to improve the mobility of citizens, while reducing costs and ensuring safety and low environmental impact. A well-established way to evaluate the performance achieved by the system or by specific activities is to monitor Key Performance Indicators (KPI). However, existing management systems, which refer to flexible yet large and complex data models, provide a limited support to define and select relevant KPIs for the objectives at hand, and even the identification of whether and how the data model is capable to achieve a certain informative need is a critical and time-consuming task. This work is aimed to propose a framework to ease the development of a monitoring system in the public transport domain. The approach is based on the ontological representation of all the knowledge regarding indicators and their formulas, business objectives, dimension analysis and their relation with the Transmodel, the European reference data model for public transport information systems. On its top, a reasoning framework provides logic functionalities to interactively support designers in a set of common design tasks: the choice of the most suitable indicators for the performance monitoring needs at hand, the definition of new indicators and the identification of the minimal set of Transmodel modules needed to calculate them. A case study is included to discuss these applications, while an evaluation shows the feasibility of the approach.     

新加坡公共交通发展经验及启示

通过实际考察和走访咨询,系统地总结了新加坡的公共交通发展经验。首先介绍了新加坡对小汽车和公共交通发展采取的＂推、拉策略＂,以及新加坡公共交通的发展历程。在此基础上,对新加坡公共交通发展的成功经验进行了归纳和总结,包括管理机制、公共交通设施建设、公共交通运营系统、政策法规等方面的内容。结合我国城市交通发展的现状和特点,对城市公共交通的发展提出了措施和建议。     

公路工程招标工作中存在的问题及应对技巧

文章介绍了我国公路工程招标的主要形式,就公路工程招标工作中存在的一些问题,提出了解决建议和应对技巧,为提高与改进公路项目招标工作提供参考.     

公共自行车近期文献综述

提供公共自行车服务的城市数量快速发展,从20世纪90年代末屈指可数发展到如今超过800个。通过综述近期公共自行车文献,总结公共自行车研究领域的若干议题。便捷性是出行者使用公共自行车的主要动机。省钱是促使低收入群体使用的原因,与停放站间距离是预测会员数量的重要指标。在一些国家,只有不到半数会员每月使用率少于一次。男性使用率高于女性,但性别失衡情况并未如私人自行车那样显著(至少在自行车使用率低的国家)。年会员最普遍的出行目的是通勤。与私人自行车使用者相比,公共自行车使用者不常佩戴头盔,但在法律强制佩戴头盔的国家,其使用水平则受到影响。公共自行车使用者相比私人自行车使用者不易受伤。未来发展方向包括电动自行车集成、GPS全球定位系统、无停放站系统和改进的公共交通一体化。指出应开展更多研究量化公共自行车在出行方式选择、尾气排放、拥堵和健康方面的影响。     

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。     

小汽车限行政策实践评述与反思

为解决小汽车保有量增加过快引发的交通相关问题,国内外许多城市开始实施限行政策.本文梳理总结了国内外城市限行政策的演化进程,发现尽管限行政策对缓解交通拥堵和改善空气污染有一定的作用,但不同城市的限行措施和限行效果也各有差异,出行者的一些规避限行的行为可能会对限行政策的实施效果产生一定的影响.     

治国方略与人性假设

中西不同的人性论预设,导致了不同的治国方略和制度路径.人性善或经验主义人性恶假设是人治和专制治理的理论基础;理性主义人性恶假设是法治的理论基础.人性善强调了道德自律的可能性,但缺乏预警机制,理性主义人性恶的不足在于过分强调人性中的阴暗,忽略了人的主动性.人性善或经验主义人性恶假设是人治和专制治理的理论基础;理性主义人性恶假设是法治的理论基础.人性善强调了道德自律的可能性,但缺乏预警机制,理性主义人性恶的不足在于过分强调人性中的阴暗,忽略了人的主动性.理想的治理结构应该是德治与法治的统一,其理论基础是理性与非理性,善与恶相统一的人性论假设.理想的治理结构应该是德治与法治的统一,其理论基础是理性与非理性,善与恶相统一的人性论假设.     

北京市政公交一卡通使用现状及改进策略研究

本文分析了北京市政公交一卡通使用过程中的优越性和存在的问题;介绍了上海、香港使用一卡通的成功之处;结合北京市的市情和交通现状,针对北京市公交一卡通存在的问题,提出了培养市民刷卡文化、完善管理制度、强化售后服务、优化公交站台和线路设置、实现一卡互通、异地互联互通等建议.     

公共交通客运枢纽设计评价方法

公交客运枢纽是城市一体化交通系统的关键环节,目前国内在枢纽的设计和建设方面还存在诸多不足,科学合理地对枢纽设计方案进行评价显得尤为重要.本文从分析公交客运枢纽的设计原则和流程入手,讨论了公交客运枢纽设计方案的综合评价指标体系的确立,以及相关指标的量化,最后讨论采用灰色关联度的方法对方案进行评价.