Current Issue : April - June Volume : 2018 Issue Number : 2 Articles : 5 Articles
Plug-in Electric Vehicles (PEVs) are considered one solution to reducing GHG emissions from private transport. Additionally,\nPEV adopters often have free access to public charging facilities. Through a pattern analysis, this study identifies five distinct\nclusters of daily PEV charging profiles observed at the public charging stations. Empirically observed patterns indicate a significant\namount of operational inefficiency, where 54% of the total parking duration PEVs do not consume electricity, preventing other\nusers from charging. This study identifies the opportunity cost in terms of GHG emissions savings if gasoline vehicles are replaced\nwith potential PEV adopters. The time spent in parking without charging by current PEV users can be used by these potential PEV\nusers to charge their PEVs and replace the use of gasoline.Theresults suggest that reducing inefficient station use leads to significant\nreductions in emissions. Overall, there is significant variability in outcomes depending on the specific cluster membership....
Road traffic accidents are believed to be associated with not only road geometric feature and traffic characteristic, but also weather\ncondition. To address these safety issues, it is of paramount importance to understand how these factors affect the occurrences of\nthe crashes. Existing studies have suggested that the mechanisms of single-vehicle (SV) accidents and multivehicle (MV) accidents\ncan be very different. Few studies were conducted to examine the difference of SV and MV accident probability by addressing\nunobserved heterogeneity at the same time. To investigate the different contributing factors on SV and MV, a mixed logit model\nis employed using disaggregated data with the response variable categorized as no accidents, SV accidents, andMV accidents. The\nresults indicate that, in addition to speed gap, length of segment, and wet road surfaces which are significant for both SV and\nMV accidents, most of other variables are significant only for MV accidents. Traffic, road, and surface characteristics are main\ninfluence factors of SV and MV accident possibility. Hourly traffic volume, inside shoulder width, and wet road surface are found\nto produce statistically significant random parameters. Their effects on the possibility of SV andMV accident vary across different\nroad segments....
A fuzzy increment controller is designed aimed at the vibration system of automobile active suspension with seven degrees of\nfreedom (DOF). For decreasing vibration, an active control force is acquired by created Proportion-Integration-Differentiation\n(PID) controller.The controller�s parameters are adjusted by a fuzzy increment controller with self-modifying parameters functions,\nwhich adopts the deviation and its rate of change of the body�s vertical vibration velocity and the desired value in the position of the\nfront and rear suspension as the input variables based on 49 fuzzy control rules. Adopting Simulink, the fuzzy increment controller\nis validated under different road excitation, such as thewhite noise inputwith four-wheel correlation in time-domain, the sinusoidal\ninput, and the pulse input of C-grade road surface. The simulation results show that the proposed controller can reduce obviously\nthe vehicle vibration compared to other independent control types in performance indexes, such as, the root mean square value of\nthe body�s vertical vibration acceleration, pitching, and rolling angular acceleration....
Amultidepot VRP is solved in the context of total urban traffic equilibrium.Under the total traffic equilibrium, themultidepot VRP\nis changed to GDAP (the problem of Grouping Customers + Estimating OD Traffic + Assigning traffic) and bilevel programming\nis used to model the problem, where the upper model determines the customers that each truck visits and adds the trucks� trips\nto the initial OD (Origin/Destination) trips, and the lower model assigns the OD trips to road network. Feedback between upper\nmodel and lower model is iterated through OD trips; thus total traffic equilibrium can be simulated....
This study proposes a new vehicle type recognition method that combines global and local features via a two-stage classification.\nTo extract the continuous and complete global feature, an improved Canny edge detection algorithm with smooth filtering and\nnon-maxima suppression abilities is proposed. To extract the local feature fromfour partitioned key patches, a set of Gabor wavelet\nkernels with five scales and eight orientations is introduced. Different from the single-stage classification, where all features are\nincorporated into one classifier simultaneously, the proposed two-stage classification strategy leverages two types of features and\nclassifiers. In the first stage, the preliminary recognition of large vehicle or small vehicle is conducted based on the global feature\nvia a ...
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