Resilience assessment and optimization method of city road network in the post-earthquake emergency period

The post-earthquake emergency period,which is a sensitive time segment just after an event,mainly focuses on saving life and restoring social order.To improve the seismic resilience of city road networks,a resilience evaluation method used in the post-earthquake emergency period is proposed.The road seismic damage index of a city road network can consider the influence of roads,bridges and buildings along the roads,etc.on road capacity after an earthquake.A function index for a city road network is developed,which reflects the connectivity,redundancy,traffic demand and traffic function of the network.An optimization model for improving the road repair order in the post-earthquake emergency period is also developed according to the resilience evaluation,to enable decision support for city emergency management and achieve the best seismic resilience of the city road network.The optimization model is applied to a city road network and the results illustrate the feasibility of the resilience evaluation and optimization method for a city road network in the post-earthquake emergency period.

Lazy loading algorithm for traffic assignment of road networks under fixed charge condition

The measures of path charge are important considerations in traffic assignment of road networks. Factors, such as travel time, fixed charge and traffic congestion which affect road users＇ choices of trip paths, are analyzed. Travelers usually decide their trip paths based on their personal habits, preferences and the information at hand. By considering both deterministic and stochastic factors which affect the value of time （VOT） during the process of path choosing, a variational inequality model is proposed to describe the problem of traffic assignment. A lazy loading algorithm for traffic assignment is designed to solve the proposed model, and the calculation steps are given. Numerical experiment results show that compared with the all-or-nothing assignment, the proposed model and the algorithm can provide more optimal traffic assignments for road networks. The results of this study can be used to optimize traffic planning and management.

Short-Term Traffic Flow Prediction Based on Road Network Topology

Accurate short-term traffic flow prediction plays a crucial role in intelligent transportation system (ITS), because it can assist both traffic authorities and individual travelers make better decisions. Previous researches mostly focus on shallow traffic prediction models, which performances were unsatisfying since short-term traffic flow exhibits the characteristics of high nonlinearity, complexity and chaos. Taking the spatial and temporal correlations into consideration, a new traffic flow prediction method is proposed with the basis on the road network topology and gated recurrent unit (GRU). This method can help researchers without professional traffic knowledge extracting generic traffic flow features effectively and efficiently. Experiments are conducted by using real traffic flow data collected from the Caltrans Performance Measurement System (PEMS) database in San Diego and Oakland from June 15, 2017 to September 27, 2017. The results demonstrate that our method outperforms other traditional approaches in terms of mean absolute percentage error (MAPE), symmetric mean absolute percentage error (SMAPE) and root mean square error (RMSE).

A Novel Network Screening Methodology for Rural Low-Volume Roads

Low-volume roads (LVRs) are an integral part of the rural transportation network providing access to remote rural areas and facilitating the movement of goods from farms to markets. These roads pose unique challenges for highway agencies including those related to safety management on the highway network. Specifically, traditional network screening methods using crash history can be effective in screening rural highways with higher traffic volumes and more frequent crashes. However, these traditional methods are often ineffective in screening LVR networks due to low traffic volumes and the sporadic nature of crash occurrence. Further, many of the LVRs are owned and operated by local agencies that may lack access to detailed crash, traffic and roadway data and the technical expertise within their staff. Therefore, there is a need for more efficient and practical network screening approaches to facilitate safety management programs on these roads. This study proposes one such approach which utilizes a heuristic scoring scheme in assessing the level of risk/safety for the purpose of network screening. The proposed scheme is developed based on the principles of US Highway Safety Manual (HSM) analysis procedures for rural highways and the fundamentals in safety science. The primary application of the proposed scheme is for ranking sites in network screening applications or for comparing multiple improvement alternatives at a specific site. The proposed approach does not require access to detailed databases, technical expertise, or exact information, making it an invaluable tool for small agencies and local governments (e.g. counties, townships, tribal governments, etc.).

Traffic Signals Control with Adaptive Fuzzy Controller in Urban Road Network

An adaptive fuzzy logic controller (AFC) is presented for the signal control of the urban traffic network. The AFC is composed of the signal control system-oriented control level and the signal controller-oriented fuzzy rules regulation level. The control level decides the signal timings in an intersection with a fuzzy logic controller. The regulation level optimizes the fuzzy rules by the Adaptive Rule Module in AFC according to both the system performance index in current control period and the traffic flows in the last one. Consequently the system performances are improved. A weight coefficient controller (WCC) is also developed to describe the interactions of traffic flow among the adjacent intersections. So the AFC combined with the WCC can be applied in a road network for signal timings. Simulations of the AFC on a real traffic scenario have been conducted. Simulation results indicate that the adaptive controller for traffic control shows better performance than the actuated one.

Optimization Strategy of Road Traffic System in Urban Renewal Area

At present,problems such as insufficient road infrastructure and supporting facilities,and limited parking spaces are increasingly prevalent,and there are large conflicts of interest in the process of urban renewal.Therefore,it is crucial to improve the quality of the road network.This paper presents an analysis on the current situation of the road traffic system in a completed area outside the Third Ring Road in Xindu District,Chengdu,and provides corresponding road traffic optimization strategies,with aims of solving the existing road traffic problems,improve road service levels,and promote the overall development of the area and improve the quality of urban space.

Research on the Application of Wireless Network in Collecting Road Traffic Information

Due to the characteristics of variability and dispersion in traffic information, to get the reliable real-time traffic information has been a bottleneck in the development of intelligent transportation systems. However, with the development of wireless network technology and mobile Internet, the mobile phones are rapidly developed and more popular, so it is possible to get road traffic information by locating the mobile phones in vehicles. The system structure for the road traffic information collection is designed based on wireless network and mobile phones in vehicles, and the vehicle recognition and its information computation methods are given and discussed. Also the simulation is done for vehicle recognition and computation based on fuzzy cluster analysis method and the results are obtained and analyzed.

Traffic organization during urban road constructions

This research presented a bi-level programming approach to optimize the schedule of ur- ban road construction activities based on a hypothetical transport network, with an objective of mini- mizing the overall traffic delays. A heuristic algorithm was utilized to identify a set of road construction schedules, while PARAMICS was adopted to estimate the total travel time in the network under each road construction scenario. To test the performance of proposed heuristics-simulation methodology, a numerical test was implemented. The overall results suggested that the proposed methodol- ogy could quickly find the optimum solution with good convergence.

Perspective of Adaptive CN System for Forecasting Congestion of Road Traffic Flow

Basing upon the Weber-Fechner Law with respect to the stimulus (distance-headway) to the vehicle driver and the driver’s sensation (speed), the characteristic speed Vβ is defined, which is the critical vehicles flow speed just before going to congestion in road traffic flow. From the information of real time measurement of traffic flow speed (V) and time-headway (T) at the specific positions along the road, the value of Vβ is calculated and used for forecasting the flow. Discussed is how to use each Vβ to forecast the congestion. The CN system devoted to the management of road traffic flow is proposed. The idea may contribute not only to easing the traffic flow but also to optimizing it to get high efficient traffic flow.

Dynamic evaluation of traffic flows on city roads

This paper presents an analysis of the random fluctuations, deferred conduction effect and periodicity of road traffic based on the basic features of road networks. It also discusses the limitations of road network evaluation theories based on road "V/C". In addition, it proposes a set of theoretical and technical methods for the real-time evaluation of traffic flows for entire road networks, and for solving key technical issues, such as real-time data collection and processing in areas with no blind zones, the spatial-temporal dynamic analysis of road network traffic, and the calibration of key performance index thresholds. It also provides new technical tools for the strategic transportation planning and real-time diagnosis of road traffic. The new tools and methodology presented in this paper are validated using a case study in Beijing.

Cars as a Diffuse Network of Road-Environment Monitoring Nodes

The present paper aims to describe the conceptual idea to use cars as sensors to measure and acquire data related road environment. The parameters are collected using only standard equipment commonly installed and operative on commercial cars. Real sensors and car sub-systems (e.g. thermometers, accelerometers, ABS, ESP, and GPS) together with other “implicit” sensors (e.g. fog lights, windscreen wipers) acquire and contain information. They are shared inside an in-vehicle communication network using mainly the standard CAN bus and can be collected by a simple central node. This node can also be available on the market without too expensive costs thanks to some companies which business is devoted to car fleet monitoring. All the collected data are then geolocalized using a standard GPS receiver and sent to a remote elaboration unit, exploiting mobile network technologies such as GPRS or UMTS. A large number of cars, connected together in a diffuse Wireless Sensor Network, allow the elaboration unit to realize some info-layers put at the disposal of a car driver. Traffic, state of the road and other information about the weather can be received by car drivers using an ad hoc developed mobile application for smartphone which can give punctual information related to a specific route, previously set on the mobile phone navigator. The description of some experimental activities is presented, some technical points will be addressed and some examples of applications of the network of cars “as sensors” will be given.

Characterizing Peak-Time Traffic Jam Incidents in Kampala Using Exploratory Data Analysis

Traffic congestion is associated with increased environmental pollutions, as well as reduced socio-economic productivity due to significant delays in travel times. The consequences are worse in least developed countries where motorized road transport networks are often inefficiently managed in addition to being largely underdeveloped. Recent research on traffic congestion has mostly focused on infrastructural aspects of road networks, with little or no emphasis at all on motorists’ on-the-road behavior (MB). The current study thus aimed to bridge this knowledge gap by characterizing traffic jam incidents (TJI) observed over a period of 80 days in Uganda’s Capital City, Kampala. MB as well as road network infrastructural factors such as road blockage (RB), were captured for each of the observed TJI. A total of 483 peak-time TJI were recorded, and exploratory data analysis (EDA) subsequently performed on the TJI dataset. EDA involved Hierarchical clustering analysis (HCA) and K-means clustering of the TJI dataset, as well as a detailed descriptive statistical analysis of both the entire dataset and the emerging TJI clusters. A highlight finding of this study is that 48.2% of the observed TJIs were as a result of on-the-road motorist behavior. Furthermore, the intervention of traffic police officers in a bid to regulate traffic flow was equally responsible for 25.9% of the TJIs observed in this study. Overall, these results indicate that whereas road infrastructural improvement is warranted in order to improve traffic flow, introducing interventions to address inappropriate on-the-road motorists’ behavior could alone improve traffic flow in Kampala, by over 48%. Additionally, in-order to effectively regulate traffic flow in Kampala and other least developed cities with similar traffic congestion management practices, motorists’ on-the-road behavior ought to be factored into any data-driven mechanisms deployed to regulate traffic flow and thus potentially significantly curbing traffic congestion.

基于SA-Apriori的道路事故风险评估研究

道路事故风险评估是提高道路安全水平的有效方式。为实现在道路网络特征视角下的道路事故风险评估,融合线段分析与频繁集算法,提出SA-Apriori的特征提取算法,进而构建SA-Apriori道路事故风险评估模型,以重庆市大渡口区作为分析对象,建立以道路网络特征变量为指标的道路事故风险等级划分体系,评估其道路事故风险水平,结合商业点位分布情况对该评估方法的有效性进行验证。并针对大渡口区道路事故风险情况,提出道路事故风险的管理对策与建议。结果表明:该道路事故风险评估方法具有较高的可靠性,可为基于路网特征的道路事故风险评估提供参考。

基于ICAE算法的城市群高速公路网布局优化研究

为提升城市群高速公路网通达程度和可达性水平,建立了体现城市群特征的优化模型,并改进了帝国竞争算法,以哈长城市群为案例,探究布局优化效果。采用高速公路出行时间确定城市群可达性等级,通过考虑可达性、距离等参数建立优化模型;引入进化算子改进算法,构建进化帝国竞争算法;根据哈长城市群特征确定约束条件并求解,利用求解节点和周边道路网确定优化方案。研究表明:改进的算法收敛精度提高16.4%,时间缩短42.4%,共求解出6个节点,规划新建高速公路6条,改建高速公路14条,优化后的城市群高速公路2 h交通圈覆盖范围达到65.3%,14个县域交通圈等级上升,优化方案扩大了城市群2 h交通圈范围。

暴雨内涝下城市路网抗涝韧性评估

极端降雨给城市路网的正常运行带来了极大挑战,为了评估在应对极端降雨时路网的抗涝韧性,本文采用场景模拟方法分析暴雨内涝灾害对路网的影响;以道路水深是否超过水深阈值为标准,判断道路的连通性,构建以节点强度和不同水深下道路速度的衰减函数为计算指标的综合评价框架;基于降雨—积水过程下道路系统的性能变化曲线和4R特征理论,分析4种暴雨重现期下路网的抗涝韧性;提出通过改造易涝交通枢纽提高路网抗涝韧性的提升策略。结果表明:降雨对路网服务性能的影响要大于对路网结构性能的影响,路网的抗涝韧性随着降雨重现期的增大而减小,道路的淹没程度与道路等级和降雨强度两个方面有关;易涝交通枢纽对路网抗涝韧性有较大影响,降雨重现期越小,影响越大。在实施提升策略后,可以显著提升路网的鲁棒性和快速性,增强路网的抗涝韧性。

分形视角下城市非规则道路网近百年演化过程研究

城市道路网在不同时期具有独特的网络结构,然而在近百年历程中如何演变,其过程并不清晰。研究以城市非规则道路网为例,通过历史资料整理提取了南京市鼓楼片区1900年来4个时期道路网,运用分形理论量化表达道路网覆盖均匀度和发育复杂度。结果表明:鼓楼片区非规则路网是由贯通性主干路牵引形成的;其路网相对稀疏,依然有更新和改进的空间;路网覆盖度和连通度近年来趋于平缓,城市应重视干道的功能拓展和“大院制”支路的打通。通过文献史料分析,解释了不同阶段规划思想、社会变革等因素对道路网演变起到的作用,认为历史古城道路网的更新保护应重视起牵引作用的骨架干道,同时重视非机动车和行人的需求,提升其可达性。

基于双层规划模型的“才”字形交叉口禁流向交通组织方法研究

为解决城市多路交叉口车流复杂导致的交通拥堵和交通安全问题,针对多路交叉口中的“才”字形交叉口,明确其特点,对交叉口部分交通流向禁行的必要性进行分析。基于双层规划构建交叉口禁流向交通组织模型,以局部路网中车均行驶时间最小为目标,判别交叉口各流向车流是否禁行,并确定禁流向后交通组织方案,减少交叉口内车流及冲突点数量。以哈尔滨市学府路—西大直街交叉口为例,比较禁流向交通组织方案和单向交通组织方案,发现此交叉口禁流向交通组织更优,冲突点个数减少52%,路网车均行驶时间下降0.98%。考虑交通量变化分析禁流向交通组织模型的适用性,发现OD量变化超过26%时模型适用性较差,潮汐现象明显的交叉口,应设置单向交通组织。

不确定环境下收费与信息对路径选择行为影响的实验研究

在不确定环境下考虑信息发布与拥挤收费两种措施,基于交通网络均衡,推导了两路径简单路网的最优收费模型,并推广至一般路网。基于两路径路网设计逐日路径选择行为实验,分析了两种措施对路径选择行为的影响。结果表明:完美信息与收费的实施均能减少流量波动,单独实施收费的效果最佳,但只有两种措施相结合时,路网流量趋于用户均衡的趋势最稳定;完美信息会增加路径切换行为,而收费可有效抑制大幅的路径切换;无收费时路径切换往往会造成出行成本增加,而收费时则相反;收费与信息结合时的出行时间比两种措施单独实施时小。

基于知识图谱的公路气象灾害研究

为更好掌握现有公路气象灾害研究的知识结构及发展进程,收集中国知网(CNKI)核心集1992—2022年和Web of Science核心集2000—2022年收录的1840篇论文,基于CiteSpace软件,从文献分布、共现网络、聚类分析、关键词突现等方面进行分析。结果表明:1)随着学科不断发展,公路气象灾害领域论文年发文量总体呈增长趋势;2)公路气象灾害研究具有多学科交叉性质,研究学者来自交通、气象及地质学等相关研究机构及院校;3)国内外研究热点主要有气象灾害对交通基础设施的破坏、气象灾害对交通运行及安全的影响、气象灾害模拟及风险评估、路网监测及交通管控措施等;4)公路边坡灾害及恶劣天气对公路正常运行的影响在多时期引起国内外学者的广泛关注;5)随着研究的不断深入,公路抗灾韧性、智慧交通管控及全寿命公路气象灾害评估等方向近几年引起研究学者关注。

考虑抵达时间成本的道路交通事故风险评估方法

道路交通事故频发,给生命财产造成重大损失,给社会生活带来重大影响。现有针对道路交通事故风险的研究未建立有效的道路网络模型,难以准确描述交通事故风险在道路上的传播特点,评估准确度不高。基于此,提出了一种基于抵达时间成本的网络地理加权回归方法,并利用某县级市2018—2020年的道路、交通违法、交通事故、城市POI等数据开展实验,结果表明,基于抵达时间成本的网络地理加权回归方法融合了交通事故风险在道路上的传播性质,显著降低了评估误差,能够有效评估道路交通事故风险及其影响因素;市中心区域道路交通事故高风险区域主要集中在车流量较大的道路交会处与部分交通设施尚不完备的道路;各类交通违法数量、城市POI对道路交通事故风险的影响程度不同,且具有很强的空间异质性。