Based on the pioneering work of Konishi et al., in consideration of the influence of drivers＇ steady desired speed ef/ect on the traffic flow, we develop a new coupled map car-following model in the real world. By us...Based on the pioneering work of Konishi et al., in consideration of the influence of drivers＇ steady desired speed ef/ect on the traffic flow, we develop a new coupled map car-following model in the real world. By use of the control theory, the stability condition of our model is derived. The validity of the present theoretical scheme is verified via numerical simulation, confirming the correctness of our theoretical analysis.展开更多
Through introducing a generalized optimal speed function to consider spatial position, slope grade and variable safe headway, the effect of slope in a single-lane highway on the traffic flow is investigated with the e...Through introducing a generalized optimal speed function to consider spatial position, slope grade and variable safe headway, the effect of slope in a single-lane highway on the traffic flow is investigated with the extended optimal speed model. The theoretical analysis and simulation results show that the flux of the whole road with the upgrade （or downgrade） increases linearly with density, saturates at a critical density, then maintains this saturated value in a certain density range and finally decreases with density. The value of saturated flux is equal to the maximum flux of the upgrade （or downgrade） without considering the slight influence of the driver＇s sensitivity. And the fundamental diagrams also depend on sensitivity, slope grade and slope length. The spatiotemporal pattern gives the segregation of different traffic phases caused by the rarefaction wave and the shock wave under a certain initial vehicle number. A comparison between the upgrade and the downgrade indicates that the value of saturated flux of the downgrade is larger than that of the upgrade under the same condition. This result is in accordance with the real traffic.展开更多
In this paper, a new traffic flow model called the forward-backward velocity difference (FBVD) model based on the full velocity difference model is proposed to investigate the backward-looking effect by applying a mod...In this paper, a new traffic flow model called the forward-backward velocity difference (FBVD) model based on the full velocity difference model is proposed to investigate the backward-looking effect by applying a modified backward optimal velocity using generalized backward maximum speed. The FBVD model belongs to the family of microscopic models that consider spatiotemporally continuous formulations. Neutral stability conditions of the discrete car-following model are derived using the linear stability theory. The stability analysis results prove that the modified backward optimal velocity has a significant positive effect in stabilizing the traffic flow. Through nonlinear analysis, a kink-antikink solution is derived from the modified Korteweg-de Vries equation of the FBVD model to explain traffic congestion of the model. The validity of this theoretical model is checked using numerical results, according to which traffic jams were found to have been significantly diminished by the introduction of the modified backward optimal velocity.展开更多
The SHRP2 Naturalistic Driving Study was used to evaluate the impact of various work zone and driver characteristics on back of queue safety critical events (crash, near-crash, or conflicts) The model included 43 SCE ...The SHRP2 Naturalistic Driving Study was used to evaluate the impact of various work zone and driver characteristics on back of queue safety critical events (crash, near-crash, or conflicts) The model included 43 SCE and 209 “normal” events which were used as controls. The traces included representing 209 unique drivers. A Mixed-Effects Logistic Regression model was developed with probability of a SCE as the response variable and driver and work zone characteristics as predictor variables. The final model indicated glances over 1 second away from the driving task and following closely increased risk of an SCE by 3.8 times and 2.9 times, respectively. Average speed was negatively correlated to crash risk. This is counterintuitive since in most cases, it is expected that higher speeds are related to back of queue crashes. However, most queues form under congested conditions. As a result, vehicles encountering a back of queue would be more likely to be traveling at lower speeds.展开更多
基金Project supported by the Major Consulting Project of Chinese Academy of Engineering(Grant No.2012-ZX-22)the National Natural Science Foundation of China(Grant No.71201178)+3 种基金the Natural Science Foundation of Chongqing City,China(Grant No.cstc2012jjB40002)the Research Fund for the Doctoral Program of Higher Education of China(Grant No.20120191110047)the Engineering Center Research Program of Chongqing City,China(Grant No.cstc2011pt-gc30005)the Key Technology R&D Project of Chongqing City,China(Grant Nos.cstc2011AB2052 and cstc2012gg-yyjsB30001)
文摘Based on the pioneering work of Konishi et al., in consideration of the influence of drivers＇ steady desired speed ef/ect on the traffic flow, we develop a new coupled map car-following model in the real world. By use of the control theory, the stability condition of our model is derived. The validity of the present theoretical scheme is verified via numerical simulation, confirming the correctness of our theoretical analysis.
基金Project supported by the National Basic Research Program of China (Grant No 2006CB705500)the National Natural Science Foundation of China (Grant Nos 10532060 and 10562001) the Shanghai Leading Academic Discipline Project, China (Grant No Y0103)
文摘Through introducing a generalized optimal speed function to consider spatial position, slope grade and variable safe headway, the effect of slope in a single-lane highway on the traffic flow is investigated with the extended optimal speed model. The theoretical analysis and simulation results show that the flux of the whole road with the upgrade （or downgrade） increases linearly with density, saturates at a critical density, then maintains this saturated value in a certain density range and finally decreases with density. The value of saturated flux is equal to the maximum flux of the upgrade （or downgrade） without considering the slight influence of the driver＇s sensitivity. And the fundamental diagrams also depend on sensitivity, slope grade and slope length. The spatiotemporal pattern gives the segregation of different traffic phases caused by the rarefaction wave and the shock wave under a certain initial vehicle number. A comparison between the upgrade and the downgrade indicates that the value of saturated flux of the downgrade is larger than that of the upgrade under the same condition. This result is in accordance with the real traffic.
文摘In this paper, a new traffic flow model called the forward-backward velocity difference (FBVD) model based on the full velocity difference model is proposed to investigate the backward-looking effect by applying a modified backward optimal velocity using generalized backward maximum speed. The FBVD model belongs to the family of microscopic models that consider spatiotemporally continuous formulations. Neutral stability conditions of the discrete car-following model are derived using the linear stability theory. The stability analysis results prove that the modified backward optimal velocity has a significant positive effect in stabilizing the traffic flow. Through nonlinear analysis, a kink-antikink solution is derived from the modified Korteweg-de Vries equation of the FBVD model to explain traffic congestion of the model. The validity of this theoretical model is checked using numerical results, according to which traffic jams were found to have been significantly diminished by the introduction of the modified backward optimal velocity.
文摘The SHRP2 Naturalistic Driving Study was used to evaluate the impact of various work zone and driver characteristics on back of queue safety critical events (crash, near-crash, or conflicts) The model included 43 SCE and 209 “normal” events which were used as controls. The traces included representing 209 unique drivers. A Mixed-Effects Logistic Regression model was developed with probability of a SCE as the response variable and driver and work zone characteristics as predictor variables. The final model indicated glances over 1 second away from the driving task and following closely increased risk of an SCE by 3.8 times and 2.9 times, respectively. Average speed was negatively correlated to crash risk. This is counterintuitive since in most cases, it is expected that higher speeds are related to back of queue crashes. However, most queues form under congested conditions. As a result, vehicles encountering a back of queue would be more likely to be traveling at lower speeds.
