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类型 基础研究 预答辩日期 2018-03-04
开始(开题)日期 2014-12-03 论文结束日期 2017-10-17
地点 东南大学九龙湖校区交通学院大楼331 论文选题来源 非立项    论文字数 13 (万字)
题目 大型车辆对多车道高速公路交通运行影响研究
主题词 多车道高速公路,大型车辆,驾驶行为,元胞自动机模型,屏障效应
摘要 我国高速公路交通中大型车辆的比例平均可达到25%。随着大型车辆大型化、重载化的发展及混入率的不断提高,大型车辆对高速公路交通运行的影响逐渐加剧。多车道高速公路作为区域公路交通的主动脉,规模逐年增长,在高速公路网中的比例已达到18%以上。多车道高速公路由于基础设施的改变及车道管理的加入,大型车辆在运行中产生的影响较双向四车道高速公路发生了一定的变化。研究大型车辆对多车道高速公路交通运行的影响,可以发现大型车辆对其他车辆驾驶行为的干扰作用、大型车辆对多车道高速公路交通运行状态参数的影响规律,为交通管理者制定交通管理策略提供理论依据与技术支撑,对提高多车道高速公路交通安全与运行效率,降低大型车辆的不利影响具有重要的现实意义。 论文首先分析了多车道高速公路的交通特性。阐述了多车道高速公路相对双向四车道高速公路的运行特性变化,包括道路设施特性、交通管理特性、交通环境特性以及车辆行为特性等方面。对多车道高速公路交通流特征进行了研究,分析多车道高速公路在有无车道管理下交通量、速度、车头时距的变化特征,发现了大型车辆在多车道高速公路中的运行特征及受车道管理策略影响的变化。这些分析为后续的大型车辆对交通流影响的研究提供了基础。 分析了大型车辆对驾驶员影响的基本特征并建立了大型车辆对驾驶员影响的量化分析方法。对SP调查获得的数据进行统计分析,发现了大型车辆对驾驶员影响的基本特征,包括影响的普遍性、影响的范围、产生的原因、影响的效果及程度。建立了大型车辆对驾驶员影响的量化分析方法,包括构建了大型车辆影响与个人属性因素及驾驶环境因素的二项Logistic模型以及基于模糊逻辑的大型车辆对驾驶员影响的量化计算模型。前者可以筛选出对大型车辆影响有显著作用的因素并用于分析大型车辆对驾驶员影响的作用机理,后者可以根据不同的个人属性及驾驶环境定量计算出驾驶员在行驶中感受到的大型车辆影响值。这些分析为后续车辆驾驶行为模型的构建提供了思路。 建立了基于跟车对组合的元胞自动机跟驰模型的构建方法。运用Kruskal–Wallis检验、Mann–Whitney U检验及t检验等数理统计方法从车头时距、车头间距、车辆速度、车辆加速度等方面验证了不同跟车对组合跟驰行为的差异性。以四类跟车对组合为建模对象进行跟驰建模,建模中结合方差分析及效应量确定了各跟车对组合的主要影响因素,构建了驾驶行为、防碰撞及随机慢化规则。运用误差检验等方法对构建的模型进行了效果评价,并与已有的元胞自动机跟驰模型进行比较验证模型的有效性。结果表明基于跟车对组合的元胞自动机跟驰模型考虑了小型车辆与大型车辆跟驰行为的差别及大型车辆对其他车辆跟驰行为的影响,具有更好的仿真效果。 建立了考虑车型差异性的元胞自动机换道模型的构建方法。基于车辆在换道中的空间位置关系提取出有效的车辆换道数据,通过统计分析发现了小型车辆和大型车辆的换道特征差异并确定了大型车辆对车辆换道选择的影响作用。分别以小型车辆和大型车辆为建模对象进行换道建模,建模中基于不同车型的换道特征差异性,建立了小型车辆和大型车辆的换道决策和换道实施规则,并加入大型车辆对换道选择的影响。对构建的模型进行效果评价,并与已有的元胞自动机换道模型进行比较验证模型的有效性。结果表明考虑车型差异性的元胞自动机换道模型由于包含了小型车辆与大型车辆在换道决策与实施中的差别以及大型车辆对换道概率的影响,改善了对车辆换道的模拟效果。 综合所构建的元胞自动机跟驰模型与换道模型,对多车道高速公路进行仿真模拟,分析了大型车辆对多车道高速公路基本路段与入口匝道区段交通流特征的影响规律。基本路段的研究包括大型车辆比例、跟车对组合、大型车辆最大速度、大型车辆长度、大型车辆影响强度、车道管理策略对多车道高速公路流量、速度、拥挤率、换道率及稳定性等交通流状态参数的影响规律。入口匝道区段的研究包括大型车辆比例对多车道高速公路入口匝道系统、主路交通、入口匝道交通的影响规律,着重研究了大型车辆屏障效应,发现不同因素对大型车辆屏障效应的影响效果,确定了大型车辆屏障效应的出现条件。最后根据分析结果提出了一些关于大型车辆影响的改善对策。
英文题目 RESEARCH ON THE IMPACT OF HEAVY VEHICLES ON THE TRAFFIC OPERATION OF MULTI-LANE FREEWAYS
英文主题词 multi-lane freeway,heavy vehicle,driving behavior,cellular automata model,barrier effect
英文摘要 The average percentage of heavy vehicles on freeways in China can reach 25%. With the development of large-scale and heavy-duty vehicles and the increase in heavy vehicles, the impact of heavy vehicles on freeways will become more and more serious. Multi-lane freeways are the regional arterial highways and already account for more than 18% in the freeway network. Because of the change in road infrastructure and the lane management, the impact of heavy vehicles on multi-lane freeways is changed compared with two-way four-lane freeways. This research can analyze the car-truck interaction and find out the impact of heavy vehicles on multi-lane freeway traffic state parameters, which can be used to provide the theoretical basis and technical support for traffic manager to make traffic management strategy. It is of great significance to reduce the negative effect of heavy vehicles and improve the traffic safety and operation efficiency of multi-lane freeways. The traffic characteristics of multi-lane freeways are analyzed. The operating feature of multi-lane freeways is identified compared with two-way four-lane freeways from the road facility, traffic management, traffic environment and vehicle behavior. Combining with the actual survey data, the difference of traffic volume, velocity and headway on multi-lane freeways under normal conditions and lane management is analyzed. Through the analysis, the operating feature of heavy vehicles on the multi-lane freeway and the influence of lane management on truck operation are found. These analyses provide the basis for the subsequent studies of the impact of heavy vehicles on traffic flow. The basic characteristics of the impact of heavy vehicles on drivers are analyzed and a quantitative analysis method of the impact of heavy vehicles on drivers is put forward. The data obtained from SP survey is analyzed statistically to find out the basic characteristics of the impact of heavy vehicles on drivers, including universality, influence range, cause, influence degree and influence effect. The quantitative analysis method of the impact of heavy vehicles on drivers is constructed, which includes the binary logistic model between the truck impact and personal attributes and the driving environment and the quantitative calculation model for the impact of heavy vehicles on drivers based on the fuzzy logic. The binary logistic model can be used to screen out the significant factors and analyze the mechanism of the truck impact on drivers. The quantitative calculation model can be used to calculate the value of the impact of trucks under different environments. These analyses provide the idea for the construction of the simulation model for driver’s behavior. The method of constructing the cellular automata model of car-following based on the vehicle combination is proposed. The car-following behavior difference among different vehicle combinations is verified from time headway, space headway, velocity and acceleration by Kruskal–Wallis test, Mann–Whitney U test, t-test, etc. Four vehicle combinations are set as the objects in the modelling. Main factors of each vehicle combination are screened out by variance analysis and effect size and the driving behavior rule, anti-collision rule and randomization rule are then built. The model validation is implemented by error test and the proposed model is compared with some existed cellular automata model to verify the effectiveness. The results show that the proposed model can consider the behavior difference between cars and heavy vehicles and the impact of heavy vehicles on the car-following behavior of other vehicles. It has a better simulation effect. The method of constructing the cellular automata model of lane change considering the difference of the vehicle type is proposed. The data which obtained based on the spatial location of vehicles during the lane change is used to find out the difference between car drivers and heavy vehicle drivers in lane-changing decision and lane-changing execution. In addition, the effect of heavy vehicles on the lane-changing choice is obtained. In the modeling process, cars and heavy vehicles are set as the objects, respectively. Based on the differences in lane change characteristics between different vehicle types, the lane-changing decision rule and lane-changing execution rule of cars and heavy vehicles are built. Also, the impact of heavy vehicles on the lane-changing probability is added. The model validation is implemented by error test and the proposed model is compared with some existed cellular automata model to verify the effectiveness. Because considering the differences in the lane change of cars and heavy vehicles and the impact of heavy vehicles on the lane-changing probability, the accuracy is improved. Combining the proposed car-following model and lane-changing model, it is used to simulate the operation of the multi-lane freeway to analyze the impact of heavy vehicles on the basic segment and the on-ramp segment of the mluti-lane freeway. For the basic segment, heavy vehicle percentage, vehicle combination, maximum speed of heavy vehicle, heavy vehicle length, impact strength of heavy vehicle and lane management are variable to obtain traffic volume, velocity, congestion rate, lane-changing rate and stability of the multi-lane freeway in different scenarios. For the on-ramp segment, the impact of heavy vehicles on the on-ramp system, the main road traffic and the on-ramp traffic is analyzed, respectively. The barrier effect of heavy vehicles is studied in this part. The influence of different factors on the barrier effect of heavy vehicles are analyzed and the occurrence condition of the barrier effect of heavy vehicles is determined. Finally, some measures for improving the impact of heavy vehicles are put forward based on the analysis.
学术讨论
主办单位时间地点报告人报告主题
东南大学交通学院 2017.1.9 东南大学交通学院3楼会议室 惠先宝 江苏省“十三五”综合交通运输体系发展规划
东南大学交通学院 2016.9.7 东南大学交通学院2楼会议室 金凌 江苏智慧交通发展现状与展望
东南大学交通学院 2014.11.10 东南大学交通学院327室 过秀成 “十三五”综合运输体系规划若干问题的思考
东南大学交通学院 2013.3.27 东南大学交通学院3楼会议室 王印海 Sensing Traffic Management
东南大学交通学院 2016.3.7 东南大学交通学院327室 孔德文 大型车辆影响及交通仿真研究
North Carolina State University 2015.4.10 North Carolina State University 孔德文 Summary of Truck Operation and Influence
东南大学交通学院 2014.9.15 东南大学交通学院327室 孔德文 Aimsun交通仿真软件介绍及实践操作
东南大学交通学院 2013.11.16 东南大学交通学院327室 孔德文 高速公路扩建施工区交通组织与车辆汇入控制
     
学术会议
会议名称时间地点本人报告本人报告题目
第六届国际绿色智能交通系统与安全学术会议 2015.7.2 北方工业大学 Analysis of Vehicle Headway Distribution on Multi-lane Freeway Considering Car-truck Interaction
第十三届COTA国际交通科技年会 2013.8.15 深圳大学 Research on Dynamic Merge Control at Freeway Expanding Reconstruction Section
Transportation Research Board 2017.1.10 华盛顿 Evaluating Operational Effects of Bus Lane with Intermittent Priority under Connected Vehicle Environments
     
代表作
论文名称
The influence of heavy vehicles on traffic dynamics around on-ramp system: Cellular automata approac
Analyzing the impact of trucks on traffic flow based on an improved cellular automaton model
Analysis of vehicle headway distribution on multi-lane freeway considering car-truck interaction
Analysis of Late Merge Control at Freeway On-Ramp Based on Microscopic Simulation
 
答辩委员会组成信息
姓名职称导师类别工作单位是否主席备注
刘志远 正高 教授 博导 东南大学交通学院 主任委员
马健霄 正高 教授 博导 南京林业大学汽车与交通工程学院
钱振东 正高 教授 博导 东南大学交通学院
邓卫 正高 教授 博导 东南大学交通学院
王昊 正高 教授 博导 东南大学交通学院
邓润飞 正高 研究员级高级工程师 其他 中设设计集团
      
答辩秘书信息
姓名职称工作单位备注
王卫 其他 讲师 东南大学交通学院