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Generation and provision of personal travel advices to optimize traffic flows.

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Last Updated: 2-2015

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This study explores the effectiveness of the provision of personal departure time advices to commuters  to  optimally  distribute  travel  demand  in  order  to  avoid  or  alleviate  arising  congestion. By making use of an application on people’s smartphone individual aspects can be included in the optimal distributing of the travel demand and a ‘tailor‐made’ departure advice can be provided in order to balance travel demand. Departure and arrival patterns can intelligently be controlled and coordinated in order to decrease peak demands and limit the exceedance of the infrastructure’s capacity.

Firstly,  a  methodology  will  be  proposed  to  generate  optimal  departure  time  advices  while  commuter’s individual characteristics, preferences and constraints are taken into account. The optimization problem to find an optimal travel demand distribution is approached with an equilibrium‐seeking method which is based on an iterative algorithmic procedure. By using this  method  in  combination  with  an  agent  based  transportation  model,  which  allows  the  personalizing of agents, individual aspects can be included.

Secondly, by making use of a case study, this research describes quantitatively the effect of the provision of the generated departure advices on resulting traffic flows, within the context of business park ‘de Liesbosch’ located in Nieuwegein in the Netherlands. The business park currently suffers several negative effects of excessive loads on the infrastructure caused by the morning and evening commute. These effects decrease the accessibility of the business park and therefore negatively affect the area’s sustainability.

In  this  study  travel  demand  forecasts  are  combined  with  scenario  analysis  concerning  the  effect of crucial uncertainties like the number of commuters making use of the application and receiving personal departure advices. By using a microscopic transportation simulation model the effectiveness is analysed. Furthermore it is explored whether the effectiveness of the provision of personal departure advices can be increased when it is applied as part of an integral traffic management policy.

It can be concluded that the generation and provision of optimal departure time advices to commuters  by  integrating  data  can  be  an  effective  measure  to  alleviate  congestion  and  improve accessibility. The results can even be improved by applying it in combination with other traffic management measures like coordinated working hours and traffic actuated signal control.

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