A methodological framework for benchmarking smart transport cities

Besides responding to challenges of rapid urbanization and growing traffic congestion, the development of smart transport systems has attracted much attention in recent times. Many promising initiatives have emerged over the years. Despite these initiatives, there is still a lack of understanding about an appropriate definition of smart transport system. As such, it is challenging to identify the appropriate indicators of ‘smartness’. This paper proposes a comprehensive and practical framework to benchmark cities according to the smartness in their transportation systems. The proposed methodology was illustrated using a set of data collected from 26 cities across the world through web search and contacting relevant transport authorities and agencies. Results showed that London, Seattle and Sydney were among the world’s top smart transport cities. In particular, Seattle and Paris ranked high in smart private transport services while London and Singapore scored high on public transport services. London also appeared to be the smartest in terms of emergency transport services. The key value of the proposed innovative framework lies in a comparative analysis among cities, facilitating city-to-city learning.

Australian baby boomers switched to more environment friendly modes of transport during the global financial crisis

The global financial crisis (GFC) in 2008 rocked local, regional, and state economies throughout the world. Several intermediate outcomes of the GFC have been well documented in the literature including loss of jobs and reduced income. Relatively little research has, however, examined the impacts of the GFC on individual level travel behaviour change. To address this shortcoming, HABITAT panel data were employed to estimate a multinomial logit model to examine mode switching behaviour between 2007 (pre-GFC) and 2009 (post-GFC) of a baby boomers cohort in Brisbane, Australia—a city within a developed country that has been on many metrics the least affected by the GFC. In addition, a Poisson regression model was estimated to model the number of trips made by individuals in 2007, 2008, and 2009. The South East Queensland Travel Survey datasets were used to develop this model. Four linear regression models were estimated to assess the effects of the GFC on time allocated to travel during a day: one for each of the three travel modes including public transport, active transport, less environmentally friendly transport; and an overall travel time model irrespective of mode. The results reveal that individuals were more likely to switch to public transport who lost their job or whose income reduced between 2007 and 2009. Individuals also made significantly fewer trips in 2008 and 2009 compared to 2007. Individuals spent significantly less time using less environmentally friendly transport but more time using public transport in 2009. Baby boomers switched to more environmentally friendly travel modes during the GFC.

Associations between individual socioeconomic position, neighbourhood disadvantage, and transport mode: Baseline results from the HABITAT multilevel study

Background Understanding how different socioeconomic indicators are associated with transport modes provide insight into which interventions might contribute to reducing socioeconomic inequalities in health. The purpose of this study was to examine associations between neighbourhood-level socioeconomic disadvantage, individual-level socioeconomic position (SEP) and usual transport mode. Methods This investigation included 11,036 residents from 200 neighbourhoods in Brisbane, Australia. Respondents self-reported their usual transport mode (car or motorbike, public transport, walking or cycling). Indicators for individual-level SEP were education, occupation, and household income; and neighbourhood disadvantage was measured using a census-derived index. Data were analysed using multilevel multinomial logistic regression. High SEP respondents and residents of the most advantaged neighbourhoods who used a private motor vehicle as their usual form of transport was the reference category. Results Compared with driving a motor vehicle, the odds of using public transport were higher for white collar employees (OR1.68, 95%CrI 1.41-2.01), members of lower income households (OR 1.71 95%CrI 1.25-2.30), and residents of more disadvantaged neighbourhoods (OR 1.93, 95%CrI 1.46-2.54); and lower for respondents with a certificate-level education (OR 0.60, 95%CrI 0.49-0.74) and blue collar workers (OR 0.63, 95%CrI 0.50-0.81). The odds of walking for transport were higher for the least educated (OR 1.58, 95%CrI 1.18-2.11), those not in the labour force (OR 1.94, 95%CrI 1.38-2.72), members of lower income households (OR 2.10, 95%CrI 1.23-3.64), and residents of more disadvantaged neighbourhoods (OR 2.73, 95%CrI 1.46-5.24). The odds of cycling were lower among less educated groups (OR 0.31, 95% CrI 0.19-0.48). Conclusion The relationships between socioeconomic characteristics and transport modes are complex, and provide challenges for those attempting to encourage active forms of transportation. Further work is required exploring the individual- and neighbourhood-level mechanisms behind transport mode choice, and what factors might influence individuals from different socioeconomic backgrounds to change to more active transport modes.

Designing against boredom in automated driving

I draw on four years of experience in mobility and transport research. I was part of a research project with Siemens, for which we identified global trends in urban mobility and explored future business opportunities through scenario planning methods. Some of the proposed solutions for personal and public transport included driverless vehicles. In collaboration with BMW Design I explored the potential of new materials for automotive user interfaces...

Achieving sustainable transportation system for Indian cities - problems and issues

This article aims at identifying the research issues and challenges that need to be addressed to achieve sustainable transportation system for Indian cities. The same is achieved by understanding the current system and trends of urbanization, motorization and modal shares in India; and their impact on mobility and safety (the two basic goals of transportation) as well as environment. Further, the article explores the efforts by the central and state governments in India to address the sustainability issues, and the problems and issues over and above the present efforts to achieve sustainability. The article concludes by summarizing the research issues with respect to planning/modelling, non-motorized transport, public transport, driver behaviour and road safety and traffic management. It is expected that these research issues will provide potential directions for carrying out further research aimed at achieving sustainable transport system for Indian cities.

Natural gas as a sustainable transport fuel

Environmental concerns relating to gaseous emissions from transport have led to growth in the use of compressed natural gas vehicles worldwide with an estimated 13 million Natural Gas Vehicles (NGVs) currently in operation. Across Europe, many countries are replacing traditional diesel oil in captive fleets such as buses used for public transport and heavy and light goods vehicles used for freight and logistics with CNG vehicles. Initially this was to reduce localised air pollution in urban environments. However, with the need to reduce greenhouse gas emissions CNG is seen as a cleaner more energy efficient and environmental friendly alternative. This paper briefly examines the growth of NGVs in Europe and worldwide. Then a case study on CNG the introduction in Spain and Italy is presented. As part of the case study, policy interventions are examined. Finally, a statistical analysis of private and public refuelling stations in both countries is also provided. CNG can also be mixed with biogas. This study and the role of CNG is relevant because of the existing European Union Directive 2009/28/EC target, requiring that 10% of transport energy come from renewable sources, not alone biofuels such as biogas. CNG offers another alternative transport fuel.

Evidence reasoning for event inference in smart transport video surveillance

In this paper we present a new event recognition framework, based on the Dempster-Shafer theory of evidence, which combines the evidence from multiple atomic events detected by low-level computer vision analytics. The proposed framework employs evidential network modelling of composite events. This approach can effectively handle the uncertainty of the detected events, whilst inferring high-level events that have semantic meaning with high degrees of belief. Our scheme has been comprehensively evaluated against various scenarios that simulate passenger behaviour on public transport platforms such as buses and trains. The average accuracy rate of our method is 81% in comparison to 76% by a standard rule-based method.

Evidential event inference in transport video surveillance

This paper presents a new framework for multi-subject event inference in surveillance video, where measurements produced by low-level vision analytics usually are noisy, incomplete or incorrect. Our goal is to infer the composite events undertaken by each subject from noise observations. To achieve this, we consider the temporal characteristics of event relations and propose a method to correctly associate the detected events with individual subjects. The Dempster–Shafer (DS) theory of belief functions is used to infer events of interest from the results of our vision analytics and to measure conflicts occurring during the event association. Our system is evaluated against a number of videos that present passenger behaviours on a public transport platform namely buses at different levels of complexity. The experimental results demonstrate that by reasoning with spatio-temporal correlations, the proposed method achieves a satisfying performance when associating atomic events and recognising composite events involving multiple subjects in dynamic environments.

Realistic Traffic Scenarios Using a Census Methodology: Vila Real Case Study

This paper presents the first phase of the redevelopment of the Electric Vehicle Scenario Simulator (EVeSSi) tool. A new methodology to generate traffic demand scenarios for the Simulation of Urban MObility (SUMO) tool for urban traffic simulation is described. This methodology is based on a Portugal census database to generate a synthetic population for a given area under study. A realistic case study of a Portuguese city, Vila Real, is assessed. For this area the road network was created along with a synthetic population and public transport. The traffic results were obtained and an electric buses fleet was evaluated assuming that the actual fleet would be replaced in a near future. The energy requirements to charge the electric fleet overnight were estimated in order to evaluate the impacts that it would cause in the local electricity network.

Tráfico del demonio: vías y vidas de las motocicletas en Bogotá

En las últimas dos décadas el crecimiento de la ciudad ha generado una serie de problemas relacionados con la movilidad y el transporte para los bogotanos. La incapacidad de los distintos gobiernos distritales al proponer soluciones efectivas para mejorar dichas problemáticas, ha provocado que los ciudadanos busquen distintas alternativas para mejorar su movilización. El mercado y la ciudadanía encontraron en las motos una respuesta a los problemas del transporte en la ciudad, sin embargo, esta alternativa viene acompañada de una serie de efectos que por sí mismas repercuten y ahondan el problema de movilidad. Este trabajo pretende determinar las causas y consecuencias del uso de la moto en Bogotá como alternativa de movilización, ello a través de la mirada tanto de conductores de motocicletas como de los demás participantes de las vías y calles de la ciudad.

Psychological and situational influences on commuter-transport-mode choice

The relative importance and relationship between psychological and situational factors in predicting commuter-transport-mode choice was tested by four hypotheses. First, the influence of individuals’ values on commuter behavior is mediated by their corresponding beliefs about the environmental threat of cars (mediation hypothesis). Second, the influence of these beliefs on behavior is moderated by individual consideration of future consequences and control beliefs (moderation hypothesis). Third, cost, time, and access factors contribute to individuals’ commuter choice (situational hypothesis). Fourth, situational and psychological factors jointly influence proenvironmental behavior (interaction hypothesis). A sample of 205 Australian university students completed a survey to measure these relationships. Regression analyses indicated support for the mediation, situational, and interaction hypotheses. It was concluded that to achieve a transport-mode shift to public transport, public policy strategies should focus on individuals’ transport-related environmental beliefs (personal control and environmental effect of cars) and situations (access to public transport at reduced cost).

Are perceptions of the physical and social environment associated with mothers' walking for leisure and for transport? A longitudinal study

Objective
The role local neighbourhood environments play in influencing purpose-specific walking behaviors has not been well-explored in prospective studies. This study aimed to cross-sectionally and prospectively examine whether local physical and social environments were associated with mothers' walking for leisure and for transport.

Methods
In 2004, 357 mothers from Melbourne, Australia, provided information on their local physical and social neighbourhood environments, and in 2004 and 2006 reported weekly time spent walking for leisure and for transport. Environmental predictors of high levels of walking and increases in walking were examined using log binomial regression.

Results
Public transport accessibility and trusting many people in the neighbourhood were predictive of increases in walking for leisure, while connectivity, pedestrian crossings, a local traffic speed were predictive of increases in transport-related walking. Satisfaction with local facilities was associated with increasing both types of walking, and the social environment was important for maintaining high levels of both leisure- and transport-related walking.

Conclusion
The findings provide evidence of a longitudinal relationship between physical and social environments and walking behaviors amongst mothers. Enhancing satisfaction with local facilities and giving consideration to ‘walkability’, safety and public transport accessibility during environment planning processes may help mothers to increase walking.

Socioeconomic differences in outdoor food advertising at public transit stops across Melbourne suburbs.

To assess and compare the number and type of outdoor food advertisements at public transit stops within suburbs of varying levels of socioeconomic disadvantage.