Tunnels on freeways,as one of the critical bottlenecks,frequently cause severe congestion and passenger delay.To solve the tunnel bottleneck problem,most of the existing research can be divided into two types.One is t...Tunnels on freeways,as one of the critical bottlenecks,frequently cause severe congestion and passenger delay.To solve the tunnel bottleneck problem,most of the existing research can be divided into two types.One is to adopt variable speed limits(VSLs)to regulate a predetermined speed for vehicles to get through a bottleneck smoothly.The other is to adopt high-occupancy vehicle(HOV)lane management.In HOV lane management strategies,all traffic is divided into HOVs and low-occupancy vehicles(LOVs).HOVs are vehicles with a driver and one or more passengers.LOVs are vehicles with only a driver.This kind of research can grant priority to HOVs by providing a dedicated HOV lane.However,the existing research cannot both mitigate congestion and maximize passenger-oriented benefits.To address the research gap,this paper leverages connected and automated vehicle(CAV)technologies on intelligent freeways and develops a tunnel bottleneck management strategy with a dynamic HOV lane(DHL).The strategy bears the following features:1)enables tunnel bottleneck management at a microscopic level;2)maximizes passenger-oriented benefits;3)grants priority to HOVs even when the HOV lane is open to LOVs;4)allocates right-of-way segments for HOVs and LOVs in real time;and 5)performs well in a mixed-traffic environment.The proposed strategy is evaluated through comparison against the non-control baseline and a VSL strategy.Sensitivity analysis is conducted under different congestion levels and penetration rates.The results demonstrate that the proposed strategy outperforms in terms of passenger-oriented delay reduction and HOVs’priority level improvement.展开更多
Traffic accident severity prediction is essential for dynamic traffic safety management.To explore the factors influencing the severity of traffic accidents on mountain freeways and to predict the severity of traffic ...Traffic accident severity prediction is essential for dynamic traffic safety management.To explore the factors influencing the severity of traffic accidents on mountain freeways and to predict the severity of traffic accidents,four models based on machine learning algorithms are constructed using support vector machine(SVM),decision tree classifier(DTC),Ada_SVM and Ada_DTC.In addition,random forest(RF)is used to calculate the importance degree of variables and the accident severity influences with high importance levels form the RF dataset.The results show that rainfall intensity,collision type,number of vehicles involved in the accident and toad section type are important variables influencing accident severity.The RF feature selection method improves the classification performance of four machine leaming algorithms,resulting in a 9.3%,5.5%,7.2% and 3.6% improvement in prediction accuracy for SVM,DTC,Ada_SVM and Ada_DTC,respectively.The combination of the Ada_SVM integrated algorithm and RF feature selection method has the best prediction performance,and it achieves 78.9% and 88.4% prediction precision and accuracy,respectively.展开更多
This study evaluates the Dynamic Message Signs (DMSs) use to dissipate incident information on the freeways in Las Vegas, Nevada. It focuses on the DMSs message timing, extent, and content, from the operators’ and dr...This study evaluates the Dynamic Message Signs (DMSs) use to dissipate incident information on the freeways in Las Vegas, Nevada. It focuses on the DMSs message timing, extent, and content, from the operators’ and drivers’ perspectives, considering the variability in drivers’ freeway experience. Two-week incidents data with fifty-nine incidents, DMS log data, and responses from a survey questionnaire were used. The descriptive analysis of the incidents revealed that about 54% of the incidents had their information posted on the DMSs;however, information of only 18.6% of the incidents was posted on time. The posted information covered the incident type (54.2%), location (49.2%), and lane blockage (45.8%), while the expected delay or the time the incident has lasted are rarely posted. Further, the standard DMSs are the most preferred sources of traffic information on the freeway compared to the travel time only DMSs, and the graphical map boards. The logistic regression applied to the survey responses revealed that regular freeway users are less likely to take an alternative route when they run into congestion, given no other </span><span style="font-family:Verdana;">information is available. Conversely, when given accurate information</span><span style="font-family:Verdana;"> through DMSs, regular freeway users are about 2.9 times more likely to detour. Furthermore, regular freeway users perceive that the DMSs show clear information about the incident location. Upon improving the DMSs usage, 73% of respondents suggested that the information be provided earlier, and 54% requested improvements on congestion duration and length information. These findings can be used by the DMSs operators in Nevada and worldwide to improve freeway operations.展开更多
Effective transportation systems lead to the efficient movement of goods and people, which significantly contribute to the quality of life in every society. In the heart of every economic and social development, there...Effective transportation systems lead to the efficient movement of goods and people, which significantly contribute to the quality of life in every society. In the heart of every economic and social development, there is always a transportation system. Mathematically the problem of modeling vehicle traffic flow can be solved at two main observation scales: The microscopic and the macroscopic levels. In the microscopic level, every vehicle is considered individually, and therefore, for every vehicle, we have an equation that is usually an ordinary differential equation (ODE). At a macroscopic level, we use from the dynamics models, where we have a system of partial differential equation, which involves variables such as density, speed, and flow rate of traffic stream with respect to time and space. Therefore, considering above content, this study has tried to compare solution of equation of macroscopic flow considering linear form (speed-density) and applying boundary condition that resulting to form solved is non-linear one-order partial differential equation (sharpy method) with non-linear assuming (speed and density) and consequently homographic nonlinear relation (speed-density). The recent case clearly gives more significant speeds than linear case of speed and density that can be a good scientific basis. In terms of safety for accidents and traffic signal, just as a reminder, but it is resulted of the reality that generally solutions of partial differential equations can have different forms. Therefore, the solution of partial differential equation (macroscopic flow) can have different answers and solutions so that all of these solutions apply in PDE (equation of macroscopic flow). Thus, under this condition, we can have solution of linear equation similar to greenberg or greenshield & android that are explained in logarithm and exponential function, but this article is based mostly on nonlinear solution of macroscopic equation, provided that existing nonlinear relationship between speed and density (homogra展开更多
This study develops crash rate prediction models based on the premise that crash frequencies observed from adjacent paired non-weaving and weaving freeway segments are spatially correlated and therefore requires a sim...This study develops crash rate prediction models based on the premise that crash frequencies observed from adjacent paired non-weaving and weaving freeway segments are spatially correlated and therefore requires a simultaneous equation modeling approach. Simultaneous equation models for paired freeway non-weaving segments and weaving segments along with combined three freeway segments upstream and downstream were developed to investigate the relationship of crash rate with freeway characteristics. The endogenous variables have significant coefficients which indicate that unobserved variables exist on these contiguous segments, resulting in different crash rates. AADT is a variable that can show the interaction between the traffic and crashes on these contiguous segments. The results corroborate such an interaction. By comparing the simultaneous equation model and the multiple linear regression model, it is shown that more model parameters in the simultaneous models are significant than those from linear regression model. This demonstrates the existence of the correlation between the interchange and between-interchange segments. It is crucial that some variables like segment length can be identified significant in the simultaneous model, which provides a way to quantify the safety impact of freeway development.展开更多
Suitable speed limit is important for providing safety for road users. Lower-than-required posted speed limits could cause the majority of drivers non-compliant and higher-than-required posted speed limits may also in...Suitable speed limit is important for providing safety for road users. Lower-than-required posted speed limits could cause the majority of drivers non-compliant and higher-than-required posted speed limits may also increase the number of crashes with related severities. The speed limit raised in Kansas from 70 mph to 75 mph on a number of freeway segments in 2011. The goal of this study is to assess the safety impacts of the freeway sections influenced by speed limit increase. Three years before and three years after speed limit increase was considered and three methods were used: 1-Empirical Bayes (EB), 2-before-and-after with comparison group, and 3-cross-sectional study. The Crash Modification Factors (CMFs) were estimated and showed 16 percent increase for total crashes according to EB method. Further, the before-and-after with comparison group method showed 27 percent increase in total crashes and 35 percent increase on fatal and injury crashes. The cross- sectional method also presented 25 percent increase on total crashes and 62 percent increase on fatal and injury crashes. It was seen that these increases were statistically significant.展开更多
基金supported by the National Key R&D Pro-gram of China(Grant No.2022YFF0604905)the National Natural Science Foundation of China(Grant No.52072264)+2 种基金the Zhengzhou Major Science and Technology Project(Grant No.2021KJZX0060-9)the Shanghai Automotive Industry Science and Technology De-velopment Foundation(Grant No.2213)the Tongji Zhongte Chair Professor Foundation(Grant No.000000375-2018082).
文摘Tunnels on freeways,as one of the critical bottlenecks,frequently cause severe congestion and passenger delay.To solve the tunnel bottleneck problem,most of the existing research can be divided into two types.One is to adopt variable speed limits(VSLs)to regulate a predetermined speed for vehicles to get through a bottleneck smoothly.The other is to adopt high-occupancy vehicle(HOV)lane management.In HOV lane management strategies,all traffic is divided into HOVs and low-occupancy vehicles(LOVs).HOVs are vehicles with a driver and one or more passengers.LOVs are vehicles with only a driver.This kind of research can grant priority to HOVs by providing a dedicated HOV lane.However,the existing research cannot both mitigate congestion and maximize passenger-oriented benefits.To address the research gap,this paper leverages connected and automated vehicle(CAV)technologies on intelligent freeways and develops a tunnel bottleneck management strategy with a dynamic HOV lane(DHL).The strategy bears the following features:1)enables tunnel bottleneck management at a microscopic level;2)maximizes passenger-oriented benefits;3)grants priority to HOVs even when the HOV lane is open to LOVs;4)allocates right-of-way segments for HOVs and LOVs in real time;and 5)performs well in a mixed-traffic environment.The proposed strategy is evaluated through comparison against the non-control baseline and a VSL strategy.Sensitivity analysis is conducted under different congestion levels and penetration rates.The results demonstrate that the proposed strategy outperforms in terms of passenger-oriented delay reduction and HOVs’priority level improvement.
基金supported by the Science and Technology Innovation programme of the Department of Transportation,Yunnan Province,China(Grants No.2019303 and[2020]75)the general programme of key science and technology in transportation,the Ministry of Transport,China(Grants No.2018-MS4-102 and 2021-TG-005)the research fund of the Nanjing Joint Institute for Atmospheric Sciences(Grant No.BJG202101).
文摘Traffic accident severity prediction is essential for dynamic traffic safety management.To explore the factors influencing the severity of traffic accidents on mountain freeways and to predict the severity of traffic accidents,four models based on machine learning algorithms are constructed using support vector machine(SVM),decision tree classifier(DTC),Ada_SVM and Ada_DTC.In addition,random forest(RF)is used to calculate the importance degree of variables and the accident severity influences with high importance levels form the RF dataset.The results show that rainfall intensity,collision type,number of vehicles involved in the accident and toad section type are important variables influencing accident severity.The RF feature selection method improves the classification performance of four machine leaming algorithms,resulting in a 9.3%,5.5%,7.2% and 3.6% improvement in prediction accuracy for SVM,DTC,Ada_SVM and Ada_DTC,respectively.The combination of the Ada_SVM integrated algorithm and RF feature selection method has the best prediction performance,and it achieves 78.9% and 88.4% prediction precision and accuracy,respectively.
文摘This study evaluates the Dynamic Message Signs (DMSs) use to dissipate incident information on the freeways in Las Vegas, Nevada. It focuses on the DMSs message timing, extent, and content, from the operators’ and drivers’ perspectives, considering the variability in drivers’ freeway experience. Two-week incidents data with fifty-nine incidents, DMS log data, and responses from a survey questionnaire were used. The descriptive analysis of the incidents revealed that about 54% of the incidents had their information posted on the DMSs;however, information of only 18.6% of the incidents was posted on time. The posted information covered the incident type (54.2%), location (49.2%), and lane blockage (45.8%), while the expected delay or the time the incident has lasted are rarely posted. Further, the standard DMSs are the most preferred sources of traffic information on the freeway compared to the travel time only DMSs, and the graphical map boards. The logistic regression applied to the survey responses revealed that regular freeway users are less likely to take an alternative route when they run into congestion, given no other </span><span style="font-family:Verdana;">information is available. Conversely, when given accurate information</span><span style="font-family:Verdana;"> through DMSs, regular freeway users are about 2.9 times more likely to detour. Furthermore, regular freeway users perceive that the DMSs show clear information about the incident location. Upon improving the DMSs usage, 73% of respondents suggested that the information be provided earlier, and 54% requested improvements on congestion duration and length information. These findings can be used by the DMSs operators in Nevada and worldwide to improve freeway operations.
文摘Effective transportation systems lead to the efficient movement of goods and people, which significantly contribute to the quality of life in every society. In the heart of every economic and social development, there is always a transportation system. Mathematically the problem of modeling vehicle traffic flow can be solved at two main observation scales: The microscopic and the macroscopic levels. In the microscopic level, every vehicle is considered individually, and therefore, for every vehicle, we have an equation that is usually an ordinary differential equation (ODE). At a macroscopic level, we use from the dynamics models, where we have a system of partial differential equation, which involves variables such as density, speed, and flow rate of traffic stream with respect to time and space. Therefore, considering above content, this study has tried to compare solution of equation of macroscopic flow considering linear form (speed-density) and applying boundary condition that resulting to form solved is non-linear one-order partial differential equation (sharpy method) with non-linear assuming (speed and density) and consequently homographic nonlinear relation (speed-density). The recent case clearly gives more significant speeds than linear case of speed and density that can be a good scientific basis. In terms of safety for accidents and traffic signal, just as a reminder, but it is resulted of the reality that generally solutions of partial differential equations can have different forms. Therefore, the solution of partial differential equation (macroscopic flow) can have different answers and solutions so that all of these solutions apply in PDE (equation of macroscopic flow). Thus, under this condition, we can have solution of linear equation similar to greenberg or greenshield & android that are explained in logarithm and exponential function, but this article is based mostly on nonlinear solution of macroscopic equation, provided that existing nonlinear relationship between speed and density (homogra
文摘This study develops crash rate prediction models based on the premise that crash frequencies observed from adjacent paired non-weaving and weaving freeway segments are spatially correlated and therefore requires a simultaneous equation modeling approach. Simultaneous equation models for paired freeway non-weaving segments and weaving segments along with combined three freeway segments upstream and downstream were developed to investigate the relationship of crash rate with freeway characteristics. The endogenous variables have significant coefficients which indicate that unobserved variables exist on these contiguous segments, resulting in different crash rates. AADT is a variable that can show the interaction between the traffic and crashes on these contiguous segments. The results corroborate such an interaction. By comparing the simultaneous equation model and the multiple linear regression model, it is shown that more model parameters in the simultaneous models are significant than those from linear regression model. This demonstrates the existence of the correlation between the interchange and between-interchange segments. It is crucial that some variables like segment length can be identified significant in the simultaneous model, which provides a way to quantify the safety impact of freeway development.
文摘Suitable speed limit is important for providing safety for road users. Lower-than-required posted speed limits could cause the majority of drivers non-compliant and higher-than-required posted speed limits may also increase the number of crashes with related severities. The speed limit raised in Kansas from 70 mph to 75 mph on a number of freeway segments in 2011. The goal of this study is to assess the safety impacts of the freeway sections influenced by speed limit increase. Three years before and three years after speed limit increase was considered and three methods were used: 1-Empirical Bayes (EB), 2-before-and-after with comparison group, and 3-cross-sectional study. The Crash Modification Factors (CMFs) were estimated and showed 16 percent increase for total crashes according to EB method. Further, the before-and-after with comparison group method showed 27 percent increase in total crashes and 35 percent increase on fatal and injury crashes. The cross- sectional method also presented 25 percent increase on total crashes and 62 percent increase on fatal and injury crashes. It was seen that these increases were statistically significant.
