考虑出行者行为的多重网络拥堵风险传播模型

城市道路交通拥堵风险传播过程受拥堵预警信息、出行者行为特性及居民出行流量分布等诸多因素影响.本文提出包括道路子网、信息子网和出行子网的多重网络模型,应用改进的UAU-SIR(Unaware-Aware-Unaware-Susceptible-Infective-Recovered)模型,探讨多重网络预警信息下的城市道路...     

纤维增强塑料(FRP)混凝土结构疲劳性能研究进展

FRP混凝土结构的疲劳性能是结构非常重要的一个性能,目前国内外对这方面的研究还较少,本文简要从FRP新建结构和FRP加固混凝土结构两方面介绍了国内外对FRP混凝土结构疲劳性能的研究进展,并对今后拟开展的研究工作提出了建议。     

基于有限元分析的城市客车扶手杆结构改进

基于国内城市客车扶手杆应用的现状,对顶置电池城市客车扶手结构进行了有限元分析,为扶手整体结构的强度、刚度设计提供理论依据。     

城市道路环境下自动驾驶车辆接管绩效分析（双语出版）

为了分析城市道路环境下高度自动驾驶中非驾驶相关任务和接管紧迫度对接管绩效的影响,基于驾驶模拟器设计了自动驾驶紧急接管场景并开展驾驶模拟试验,接管请求时间分别设定为3,4,5 s,非驾驶相关任务为读新闻、看视频、玩游戏,自动驾驶车速为50 km·h^-1,试验中共招募了49名被试（男性30名,女性19名）,被试的平均年龄为31.06岁（标准差为7.1岁）,驾驶人在自动驾驶阶段始终执行非驾驶相关任务,听到接管请求提示后需要接管车辆的控制权,并实施紧急避让操作。研究结果表明：在紧急接管情况下,接管紧迫度对合成加速度和最小TTC有影响,而对接管时间无影响,与5 s的接管请求时间条件相比,3,4 s的接管请求时间条件下的合成加速度明显增加,而最小TTC则随接管请求时间的减少而降低;非驾驶相关任务对接管时间和最小TTC有影响,而对合成加速度无影响,与无非驾驶相关任务相比,非驾驶相关任务会显著增加接管时间和降低最小TTC;碰撞几乎都发生在3 s和4 s的接管请求时间下,5 s的接管请求时间能够基本保证接管的安全性。     

基于LSTM网络的驾驶意图识别及车辆轨迹预测

自动驾驶汽车需具备预测周围车辆轨迹的能力,以便做出合理的决策规划,提高行驶安全性和乘坐舒适性。运用深度学习方法,设计了一种基于长短时记忆（LSTM）网络的驾驶意图识别及车辆轨迹预测模型,该模型由意图识别模块和轨迹输出模块组成。意图识别模块负责识别驾驶意图,其利用Softmax函数计算出驾驶意图分别为向左换道、直线行驶、向右换道的概率;轨迹输出模块由编码器-解码器结构和混合密度网络（MDN）层组成,其中的编码器将历史轨迹信息编码为上下文向量,解码器结合上下文向量和已识别的驾驶意图信息预测未来轨迹;引入MDN层的目的是利用概率分布来表示车辆未来位置,而非仅仅预测一条确定的轨迹,以提高预测结果的可靠性和模型的鲁棒性。此外,将被预测车辆及其周围车辆组成的整体视为研究对象,使模型能够理解车-车间的交互式行为,响应交通环境的变化,动态地预测车辆位置。使用基于真实路况信息的NGSIM（Next Generation SIMulation）数据集对模型进行训练、验证与测试。研究结果表明：与传统的基于模型的方法相比,基于LSTM网络的轨迹预测方法在预测长时域轨迹上具有明显的优势,考虑交互式信息的意图识别模块具备更高的预判性和准确率,且基于意图识别的轨迹预测能降低预测轨迹与真实轨迹间的均方根误差,显著提高轨迹预测精度。     

宜昌市夜明珠路总体方案研究

结合宜昌BRT(快速公交系统)建设对宜昌市夜明珠路进行改造,受众多因素控制,道路改造难度较高。介绍了工程建设条件及总体设计方案。总体方案结合路线两侧现状地形、控制因素等不同特点,将路线分为沿河线段和合流线段两个典型路段,并进行方案比选,综合各方面因素,得出了推荐方案。     

Understanding the impacts of a combination of service improvement strategies on bus running time and passenger’s perception

Transit agencies implement many strategies in order to provide an attractive transportation service. This article aims to evaluate the impacts of implementing a combination of strategies, designed to improve the bus transit service, on running time and passenger satisfaction. These strategies include using smart card fare collection, introducing limited-stop bus service, implementing reserved bus lanes, using articulated buses, and implementing transit signal priority (TSP). This study uses stop-level data collected from the Société de transport de Montréal (STM)’s automatic vehicle location (AVL) and automatic passenger count (APC) systems, in Montréal, Canada. The combination of these strategies has lead to a 10.5% decline in running time along the limited stop service compared to the regular service. The regular route running time has increased by 1% on average compared to the initial time period. The study also shows that riders are generally satisfied with the service improvements. They tend to overestimate the savings associated with the implementation of this combination of strategies by 3.5-6.0 min and by 2.5-4.1 min for both the regular route and the limited stop service, respectively. This study helps transit planners and policy makers to better understand the effects of implementing a combination of strategies to improve running time and passenger’s perception of these changes in service.     

Incorporating the extended theory of planned behavior in a school travel mode choice model: a case study of Shaoxing,China

Travel to and from school can have social, economic, and environmental implications for students and their parents. Therefore, understanding school travel mode choice behavior is essential to find policy-oriented approaches to optimizing school travel mode share. Recent research suggests that psychological factors of parents play a significant role in school travel mode choice behavior and the Multiple Indicators and Multiple Causes (MIMIC) model has been used to test the effect of psychological constructs on mode choice behavior. However, little research has used a systematic framework of behavioral theory to organize these psychological factors and investigate their internal relationships. This paper proposes an extended theory of planned behavior (ETPB) to delve into the psychological factors caused by the effects of adults’ cognition and behavioral habits and explores the factors’ relationship paradigm. A theoretical framework of travel mode choice behavior for students in China is constructed. We established the MIMIC model that accommodates latent variables from ETPB. We found that not all the psychological latent variables have significant effects on school travel mode choice behavior, but habit can play an essential role. The results provide theoretical support for demand policies for school travel.     

Daily activity and travel sequences of students,faculty and staff at a large Canadian university

This paper examines the activity engagement, sequencing and timing of activities for student, faculty and staff commuter groups at the largest university in the Maritime Provinces of Canada. The daily activity patterns of all university community groups are modeled using the classification and regression tree classifier algorithm. The data used for this study are derived from the Environmentally Aware Travel Diary Survey (EnACT) conducted in spring 2016 at Dalhousie University, Nova Scotia. Results show that there are significant differences in activity and travel behavior between university population segments and the general population in the region, and between campus groups. For example, students participate in more recreation activities compared to faculty and staff. They also take more trips to and from campus, and are more flexible in their scheduling of trips. The insights gained from this study will provide helpful information for promoting sustainability across university campuses, and for development of campus-based travel demand management strategies.     

Aggregating mobile object trajectories: cumulative time geographic density estimation for GPS data

We present new approaches that expand upon the time geographic density estimation (TGDE) framework previously employed to estimate potential path trees. In the past, TGDE metrics have identified possible locations an individual moving object may have passed between, given known origin and destination points. This paper utilizes a new form of TGDE to investigate taxicab GPS traces over a specified time horizon with position ‘gaps’. To this end, we propose a new extension to the TGDE framework, TGDE-C, which is used to determine the cumulative TGDE values for a group of GPS traces, at a given location. These metrics are applied to multiple taxis and allow for time of day analysis. Additionally, we combine these new extensions with existing TGDE metrics that allow us to determine how accessible individual or groups of vehicles are to urban opportunities.