Traffic and Transportation Studies, Volumes 1-2American Society of Civil Engineers, 2002 - Communication and traffic |
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Page 322
... node associated with each yard , though only super node D is illustrated here . Each supper node is connected to its associated yard nodes in each time period by supper links , le LP . The costs on these supper links represents the ...
... node associated with each yard , though only super node D is illustrated here . Each supper node is connected to its associated yard nodes in each time period by supper links , le LP . The costs on these supper links represents the ...
Page 324
... node ie ( I , D ) a number representing its supply / demand . If ¿ > 0 , node i is a supply node and it is origin of k ; if b < 0 , node i is destination of k and it is a demand node with a demand of -b ; and if b = 0 , node i is a ...
... node ie ( I , D ) a number representing its supply / demand . If ¿ > 0 , node i is a supply node and it is origin of k ; if b < 0 , node i is destination of k and it is a demand node with a demand of -b ; and if b = 0 , node i is a ...
Page 401
... nodes , which do not belong to N and which are not connected with any node of N by any arc a Є A. Let us mark in our network the set of parking nodes pe N. For each destination je D we introduce a set of directed arcs , which connect ...
... nodes , which do not belong to N and which are not connected with any node of N by any arc a Є A. Let us mark in our network the set of parking nodes pe N. For each destination je D we introduce a set of directed arcs , which connect ...
Contents
How Do We Make New Public Transport Systems More Successful? | 1 |
Study of Traffic Environment Awareness Among Elementary Schoolers in Japan | 9 |
Modeling Vehicle Age Distribution for Air Quality Analysis | 17 |
Copyright | |
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algorithm analysis arrival average behavior Beijing calculated carrying capacity China classification yards computing congestion constraints cost demand density departure depot destination distance distribution drivers dynamic emission environmental equation equilibrium estimated factors Figure forecasting freeway function fuzzy genetic algorithm headway high-speed household hypermarket increase interval km/h layer managed lanes method mode choice neural networks node non-work trips Northern Jiaotong University operation optimal order parameter pair paper path peak period planning pollution port problem public transport queue rail ramp meters ratio region removing coefficient road network route Royal Mile sample schedule Shenyang Shenzhen simulation SP data speed limits speed-raising passenger trains station survey Table Tianjin track traffic flow traffic volume Tramlink transit transportation system travel behavior truck urban urban rail transit users vanets variables vehicle warehousing yard zone