城市居民出行调查数据处理系统设计

城市居民出行调查所得到的交通数据非常庞大，必须通过计算机来进行快速处理和存储。探讨了利用Visual Basic程序设计语言和Access数据库建立城市居民出行调查数据处理系统的软件设计，主要针对系统各大模块关键技术问题，探讨了各模块功能的实现。     

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在简要分析信息熵原理的基础上提出：相对于OD期望线，信息熵可以从定量的角度更加直观地表征同一城市不同时期居民出行空间分布的变化情况。对广州市不同时期的居民出行空间分布进行实例分析后得出结论：1984年至1998年居民出行空间分布均衡程度提高主要与城市内部功能完善有关；1998年至2005年居民出行空间分布均衡程度缓慢下降主要与城市地域规模的扩大以及城市形态的变化有关。     

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针对商业网点的交通方式构成特性,首先分析了影响交通方式选择的因素,在北京市商业网点的调查数据基础上,利用人工神经网络强大的非线性映射能力和泛化功能,建立了公交出行比例预测的神经网络模型,并定量的分析了影响因素值的改变对公交比例的影响,预测了在不同策略下商业网点公交出行比例的变化情况。     

城市居民出行方式距离曲线的研究与应用

利用城市居民出行调查的数据建立居民出行方式距离曲线,研究城市居民出行的规律,一方面能够了解城市内在因素时市民出行决策的影响,另一方面,将建立的居民出行方式距离曲线用于交通方式划分,可以弥补常用交通方式划分方法的不足。     

Metropolitan sprawl measurement and its impacts on commuting trips and road emissions

This study measures urban form as indicators of metropolitan sprawl and explores its impact on commuting trips and NO_x and CO₂ emissions from road traffic in all metropolitan statistical areas (MSAs) and four groups’ MSAs separated by population in the continental United States. Encompassing all MSAs, the study adds the accessibility factor to four existing factors: density, land use mix, centeredness, and street connectivity. The study establishes multivariate regression models between urban form, commuting trips, and emissions from road traffic while controlling for socioeconomic conditions. The study shows that urban form index and five urban form factors have a statistically significant association with commuting trips, NO_x and CO₂ emissions from road traffic. In four MSA groups as determined by MSA population size, higher values of urban form factors (i.e., lower sprawl) are statistically associated with more walking commuters. On the other hand, higher values of urban form factors are associated with fewer commuting vehicles per household in large MSAs with the moderate effect, a lower average commuting drive time in medium and small MSAs, and more commuters using public transportation in medium and large MSAs. This study provides an urban form index covering all metropolitan areas in the continental United States by adding another urban form factor, and the findings show that urban form factors have different effects on mode choices, drive time, and emission from road traffic depending on the MSA population size.     

Applying behavioural theories to studying the influence of climate change on young people’s future travel intentions

Transport policy in the UK is seeking to promote the development of low carbon transport technology and to encourage people to choose to use low carbon travel options. This paper draws on existing behavioural theories to study young people’s travel behaviour intentions and the influence on these from their knowledge of, and willingness to act on, climate change. The study involved a series of focus groups with young people aged 11-18 years, where attitudes to transport modes, attitudes towards climate change and travel behaviour intentions were discussed. Knowledge and values are established as the key determinants of young people’s attitudes and behaviour intentions towards transport in the context of climate change. More specifically it is established that young people’s values emphasise speed and freedom and that it is important to young people that the mode of transport they choose is reflective of the image they want to portray.