Locating rental stations and bikeways in a public bike system

To determine the spatial distribution of rental stations and bikeways in a public bike system, this paper proposes a facility location and network design model. The model is developed as a multi-objective programing problem that considers four objectives (minimizing cyclist risk, maximizing cyclist comfort, minimizing adverse impacts on traffic and maximizing service coverage) and multiple constraints (monetary budget, network connectivity, station spacing, bikeway types, station number and value ranges of decision variables). The ε-constraint method solves the programing problem for the public bike system in Daan District, Taipei City, Taiwan. The nine non-dominated alternatives generated are all markedly better than existing locations of rental stations and bikeways. Scenario analysis results indicate that increasing the construction budget for bikeways significantly improves cyclist safety and comfort whilst increasing the adverse impact on traffic. Planners can use this model to develop public bike systems that spatially integrate rental stations and bikeway networks.     

云南省民航客运发展预测

民航运输是云南省在进行综合交通运输建设的重点之一,也是该省在未来十四五(2021-2025年)和十五五(2026-2030年)规划期间的研究热点。本文以云南省为研究范围,以省内民航客运为研究对象,选取省内主要的社会经济因素为影响因子,运用主成分分析法(PCA)、反向传播神经网络算法(BP神经网络算法)和回归分析法,构建了省内民航客运的预测模型,得出省内各主要机场在十四五末和十五五末的预计旅客吞吐量,对省政府在进行机场改扩建上有一定的指导意义。     

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.     

Integrating mesoscopic dynamic traffic assignment with agent-based travel behavior models for cumulative land development impact analysis

A number of approaches have been developed to evaluate the impact of land development on transportation infrastructure. While traditional approaches are either limited to static modeling of traffic performance or lack a strong travel behavior foundation, today’s advanced computational technology makes it feasible to model an individual traveler’s response to land development. This study integrates dynamic traffic assignment (DTA) with a positive agent-based microsimulation travel behavior model for cumulative land development impact studies. The integrated model not only enhances the behavioral implementation of DTA, but also captures traffic dynamics. It provides an advanced yet practical approach to understanding the impact of a single or series of land development projects on an individual driver’s behavior, as well as the aggregated impacts on the demand pattern and time-dependent traffic conditions. A simulation-based optimization (SBO) approach is proposed for the calibration of the modeling system. The SBO calibration approach enhances the transferability of this integrated model to other study areas. Using a case study that focuses on the cumulative land development impact along a congested corridor in Maryland, various regional and local travel behavior changes are discussed to show the capability of this tool for behavior side estimations and the corresponding traffic impacts.     

综合交通线网规划方案合理性评价内涵探讨

文章从合理性的一般哲学解释出发,论证出综合交通线网规划方案合理性存在的必然性,然后分别从多方式合理分工、各交通线路分阶段整体推进、交通线网投资实施总体控制、交通网络构建符合OD分布规律、以及线网规划目标考虑资源消耗限制等方面,深入分析合理的综合交通体系应具备的特征,并由此推荐系列评价指标集,从而为综合交通线网规划方案合理性评价提供理论依据。     

The impact of major road developments on the spheres of urban influence of Japanese cities

This study aims to measure the impact of major road developments on the spheres of urban influence of Japanese cities.First, the sphere of urban influence is defined by application of an individual behavior model. The model explains the number of trips to representative cities in regions from the residential place of each individual using the following factors; the attractiveness of cities, the travel time to cities and the individual's free time. Development of major roads shortens the travel time, and this causes the change in the sphere of urban influence. The model we propose has the structure to explain this phenomenon.Second, this method is applied to all of Japan where expressways are now being rapidly constructed and, how they change spheres of urban influence is explained. In the application, as a measure of attractiveness of cities, population, commercial and industrial activity, etc. are considered. From these points of view, the impacts of construction of expressways in Japan are estimated.     

广西路网工程路线设计方法

文章结合广西路网工程建设背景、路网工程建设程序、路线设计步骤,介绍了以公路运行安全、新征用土地数量、工程造价、地形地物、方便施工等为原则控制路线的设计方法,同时针对当前路网工程路线设计中存在的主要问题,提出了相关的处理措施。     

大洪山生态文化旅游区空间发展模式研究

文章针对近域旅游区主导旅游资源相似和相异并存的特点,提出旅游区＂整合-竞合＂发展模式（3C模式）,并以大洪山生态文化旅游区组织与规划为例,提出基于游客行为的旅游线路组织模式及相应的旅游公路网布局结构与交通设计理念。     

Prioritizing road extension projects with interdependent benefits under time constraint

Since transportation projects are costly and resources are limited, prioritizing or sequencing the projects is imperative. This study was inspired by a client who asked: “I have tens of approved road extension projects, but my financial resources are limited. I cannot construct all the projects simultaneously, so can you help me prioritize my projects?” To address this question, the benefits and costs of all the possible scenarios must be known. However, the impacts (or benefit) of road extension projects are highly interdependent, and in sizable cases cannot be specified thoroughly. We demonstrate that the problem is analogous to the Traveling Salesman Problem (TSP). Dynamic change in travel demand during construction is another aspect of the complexity of the problem. The literature is yet to provide efficient methods for large cases. To this end, we developed a heuristic methodology in which the variation of travel demand during the construction period is considered. We introduce a geometrical objective function for which a solution-finding policy based on “gradient maximization” is developed. To address the projects’ interdependency, a special neural network (NN) model was devised. We developed a search engine hybridized of Ant Colony and Genetic Algorithm to seek a solution to the TSP-like problem on the NN based on gradient maximization. The algorithm was calibrated and applied to real data from the city of Winnipeg, Canada, as well as two cases based on Sioux-Falls. The results were reliable and identification of the optimum solution was achievable within acceptable computational time.     

Gantry crane operations to transfer containers between trains: A simulation study of a Spanish terminal

Freight transfer operations are critical in combined transport networks. In this paper a simulation model and modelling approach to the transfer of cargo between trains at rail terminals is presented. The model is used to study the Port-Bou terminal, the main intermodal terminal at the Spanish-French frontier. Four different gantry crane operation modes to interchange containers between trains are evaluated. These operation rules are tested in several scenarios to examine the critical factors of the system and the best operation rule for each situation. Latest generation software is used to develop the model that incorporates modular programming and enhanced graphic systems for output representation. It allows a dynamic display of the simulated system and, likewise, the possibility of developing modules that can be reused in other studies. The research shows how simulation can be a useful planning tool in the rail transportation context.