Solving the K-shortest paths problem in timetable-based public transportation systems

Finding the K-shortest paths in timetable-based public transportation systems is an important problem in practice. It has three typical variants: the K-earliest arrival problem (K-EAP), the K-shortest travel time problem (K-STTP), and the K-minimum number of transfers problem (K-MNTP). In this article we show that these problems can be solved efficiently by first modeling the timetable information with the time-expanded approach, then applying the Martins and Santos (MS) algorithm. Then we model the timetable information with the time-dependent approach and propose a modified version of the MS algorithm for solving the K-EAP. Experimental results on real-world data show that for K smaller than 100, which is enough for most applications, the execution times of the MS algorithm for the problems in the time-expanded model are less than 100 ms on a server with a 1.86-GHz central processing unit (CPU) and 4 GB of memory. For solving the K-EAP the modified MS algorithm in the time-dependent model is even more efficient (about three times faster for K ≤ 100) than the original algorithm in the time-expanded model. Our results imply the great potential of the MS algorithms in practical transportation service systems.     

A new approach to cross-sector cooperation in road safety through a comparison of policies in selected countries

Statistics from the databases of various countries and international organizations show that road accident rates and fatalities have fallen since the 1970s. With demographic changes taking place in many developed countries, however, accident and accident-risk patterns have changed in the last two decades. This study aims to introduce a new approach to cross-sector cooperation with the hope of making road safety more holistic and sustainable. The authors compare the road safety policies of three selected countries based on various categories, using a simple quantitative method. The results show some fragmentation within the policies, illustrating the need for a new road safety approach. The effort to reduce road traffic accidents by 50% by the year 2020 has also increased the pressure on stakeholders to meet this goal. This paper's contribution toward the 2020 goal lies in its recommendation of a new approach to road safety that will enlighten stakeholders on probable missing links in road safety.     

智能交通对城市交通效率改进的贡献——基于匹配和双重差分模型的估计

为了从众多复杂的影响因素中单独剥离出智能交通建设项目对城市交通的改善作用,定量评估智能交通对城市交通运行效率提升的贡献,在充分借鉴政策公共效应双重差分评估模型的基础上,引入了匹配算法,创新性地提出了双重差分与倾向得分匹配相结合的定量评价模型。在此基础上,系统分析了影响城市交通运行效率的主要因素,并利用格兰杰因果检验,筛选出城市道路网平均运行车速、地区生产总值、民用汽车拥有量、道路长度、常住人口等作为模型评估的变量指标。然后选择36 个城市,采集了其2008—2012 年的基础数据进行对照。研究提出的基于匹配和双重差分的模型具有较强的适用性和稳健性,可用于量化评估智能交通建设对交通运输效率的改善作用。模型实证分析测算结果显示：智能交通建设在提升城市交通运行效率方面发挥了明显作用,对城市交通平均运行速度提升的贡献约在9.2%左右。