交通运输系统工程与信息
交通運輸繫統工程與信息
교통운수계통공정여신식
JOURNAL OF COMMUNICATION AND TRANSPORTATION SYSTEMS ENGINEERING AND INFORMATION
2015年
1期
93-99
,共7页
张智勇%郝晓云%吴文斌%王东
張智勇%郝曉雲%吳文斌%王東
장지용%학효운%오문빈%왕동
交通工程%运行速度%互通立交%匝道%正交实验%预测模型
交通工程%運行速度%互通立交%匝道%正交實驗%預測模型
교통공정%운행속도%호통입교%잡도%정교실험%예측모형
traffic engineering%speed%interchange%ramp%orthogonal experiment%prediction model
匝道是互通立交的重要组成部分,基于运行速度的匝道设计理念是目前公路及互通立交一种新的设计思路。本文以互通立交匝道小型车辆的运行速度为主要研究目标,通过分析互通立交匝道运行速度的影响因素,制订正交实验方案,运用车载高精度GPS设备,采集了北京市4座互通式立交共14条匝道车辆连续运行速度数据。根据其中10条匝道的数据,按照车辆在互通立交匝道上的运行速度特性将匝道分为三段:减速段、匀速段、加速段,构建互通立交匝道各个分段运行速度与影响因素之间的预测模型,并使用另外4条匝道的实测数据对预测模型进行验证。结果表明,模型预测值的相对误差在5%以内,验证了模型的正确性。
匝道是互通立交的重要組成部分,基于運行速度的匝道設計理唸是目前公路及互通立交一種新的設計思路。本文以互通立交匝道小型車輛的運行速度為主要研究目標,通過分析互通立交匝道運行速度的影響因素,製訂正交實驗方案,運用車載高精度GPS設備,採集瞭北京市4座互通式立交共14條匝道車輛連續運行速度數據。根據其中10條匝道的數據,按照車輛在互通立交匝道上的運行速度特性將匝道分為三段:減速段、勻速段、加速段,構建互通立交匝道各箇分段運行速度與影響因素之間的預測模型,併使用另外4條匝道的實測數據對預測模型進行驗證。結果錶明,模型預測值的相對誤差在5%以內,驗證瞭模型的正確性。
잡도시호통입교적중요조성부분,기우운행속도적잡도설계이념시목전공로급호통입교일충신적설계사로。본문이호통입교잡도소형차량적운행속도위주요연구목표,통과분석호통입교잡도운행속도적영향인소,제정정교실험방안,운용차재고정도GPS설비,채집료북경시4좌호통식입교공14조잡도차량련속운행속도수거。근거기중10조잡도적수거,안조차량재호통입교잡도상적운행속도특성장잡도분위삼단:감속단、균속단、가속단,구건호통입교잡도각개분단운행속도여영향인소지간적예측모형,병사용령외4조잡도적실측수거대예측모형진행험증。결과표명,모형예측치적상대오차재5%이내,험증료모형적정학성。
Ramp is an important part of interchange, the ramp design idea based on the running speed is a new design idea of the highway and interchange. This paper is mainly focused on the interchange ramp running speed of the vehicle. Through the analysis of the influence factors of the interchange ramp running speed, the orthogonal experiment program is formulated, and then continuous running speed data of the vehicle on the four interchanges in Beijing is collected, in total of 14 ramps with the vehicle-mounted high precision GPS devices. According to 10 of these ramps’data, based on the running speed characteristics of the vehicle on the interchange ramp, the ramp is divided into three sections: deceleration section, uniform section, acceleration section. At last, the prediction model of each section between the interchange ramp running speed and the influence factors is established, and then the prediction model is verified through comparing the remaining four ramps’measured data. The results show that the relative error values of the prediction model are less than 5%, the accuracy of the model is validated.