995 resultados para Business districts.


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verso: Things reached a fever pitch in 1915 as the Wolverine Paved Way was nearing completion. A brick road from Detroit to Lansing would be finished and the town's main street would finally be paved. In this photograph autos had started from Lansing and picked up others in all the small towns on the way to Howell for the big celebration. As you can see, they didn't worry about parking. They stopped their cars in the street and left them. Before Prohibition, Howell was known as the fun city of Southern Michigan, and there is said to have been 13 bars in the main four blocks of town. All the travelling men made it a point to stay over in Howell whenever possible. It was said that you could not fall down on the main street of town without falling into the doorway of a bar. This probably explains the empty cars after a long dusty trip. Notice, too, that about half the cars are still right hand drive.

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Prepared for the Downtown Kalamazoo Planning Committee.

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In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.

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In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.

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Also covers part of central business district adjacent to canal.

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The paper extends research into the importance of freight transport partnerships by considering the role of Business Improvement Districts (BIDs) in supporting sustainable urban freight initiatives. A review of the freight transport-related work that has been carried out in BIDs in central London is included. A detailed case study of a freight project in the Baker Street Quarter (BSQ) Partnership provides insight into work carried out in the multi-tenanted office and hotel sectors. The findings of this research in terms of freight transport and logistics activity patterns at the businesses studied together with the potential freight transport solutions identified are discussed.