Estimating the robustness of questionnaire results: lessons from a mixed-mode survey of expectations for tele-working and road-based business travel

The robustness of questionnaire results to various forms of bias are explored in the context of a dual-mode (web and hardcopy) survey of employers’ anticipations of levels of employee commuting and business travel activity under a range of future ICT scenarios. The questionnaire incorporated several innovative features which, together with the dual-mode format, allowed an unusually wide range of analyses. For example: the robustness of respondents’ opinions was tested by examining the effect of incorporating alternative versions of a briefing text, one being very positive and one very negative, about the role of ICT; instrument bias was identified via detailed comparison of the results from the two versions of the questionnaire; and the impact of exogenous factors which are often ignored or taken as constant was assessed via special supplementary questions. Analysis showed that the robustness of opinions and expectations varied and was influenced by respondent characteristics, and that results from the two versions of the questionnaire differed significantly. It is concluded that opinions and expectations are less robust, and questionnaire results are more subject to bias and myopic interpretation, than is generally recognised and that web-based surveys seem particularly vulnerable to sampling bias. Methods are suggested for measuring robustness, for reducing bias and for validating and contextualising results. The use of contrasting briefing texts is recommended as a means of establishing the robustness of opinions and expectations while supplementary questions are recommended for validating and contextualising SP and SE exercises.

Comparative analysis of household car,motorcycle and bicycle ownership between Osaka metropolitan area,Japan and Kuala Lumpur,Malaysia

The interactions among different types of vehicle ownership including car, motorcycle and bicycle are examined by developing simultaneous vehicle ownership models in this study. Large scale person trip survey data for Osaka metropolitan area, Japan and Kuala Lumpur, Malaysia are used for empirical analysis. The results suggest that population density at residential area significantly and negatively affects car ownership for both areas, and that the effects are larger for Osaka metropolitan area than for Kuala Lumpur. Also, bicycle ownership becomes higher at higher population density area for Osaka area, while higher at lower population density area for Kuala Lumpur, which represents the different usage patterns of bicycle between the two areas.

Time taken for residents to adopt a new public transport service: examining heterogeneity through duration modelling

When a new public transport service is introduced it would be valuable for public authorities, financing organisations and transport operators to know how long it will take for people to start to use the service and what factors influence this. This paper presents results from research analysing the time taken for residents living close to a new guided bus service to start to use (or adopt) the service. Data was obtained from a sample of residents on whether they used the new service and the number of weeks after the service was introduced before they first used it. Duration modelling has been used to analyse how the likelihood of starting to use the new service changes over time (after the introduction of the service) and to examine what factors influence this. It is found that residents who have not used the new service are increasingly unlikely to use it as time passes. Those residents gaining greater accessibility benefits from the new service are found to be quicker to use the service, although the size of this effect is modest compared to that of other between-resident differences. Allowance for the possibility that there existed a proportion of the sample that would never use the new service was tested using a split population model (SPD) model. The SPD model indicates that 36% of residents will never use the new service and is informative in differentiating factors that influence whether Route 20 is used and when it is used.

Second best toll and capacity optimisation in networks: solution algorithm and policy implications

This paper looks at the first and second best jointly optimal toll and road capacity investment problems from both policy and technical oriented perspectives. On the technical side, the paper investigates the applicability of the constraint cutting algorithm for solving the second best problem under elastic demand which is formulated as a bilevel programming problem. The approach is shown to perform well despite several problems encountered by our previous work in Shepherd and Sumalee (Netw. Spat. Econ., 4(2): 161–179, 2004). The paper then applies the algorithm to a small sized network to investigate the policy implications of the first and second best cases. This policy analysis demonstrates that the joint first best structure is to invest in the most direct routes while reducing capacities elsewhere. Whilst unrealistic this acts as a useful benchmark. The results also show that certain second best policies can achieve a high proportion of the first best benefits while in general generating a revenue surplus. We also show that unless costs of capacity are known to be low then second best tolls will be affected and so should be analysed in conjunction with investments in the network.

Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.

Regulation of the informal transport sector in Rio de Janeiro,Brazil: welfare impacts and policy analysis

In Brazil, the explosion of informal transport activity during the past decade has had profound effects on formal public transport systems and is a source of great controversy in the urban transportation sector. A variety of policies have been proposed to manage the growth of the sector. This study seeks to understand how proposed policies will impact the users of these systems. A corridor in Rio de Janeiro with substantial informal activity was used as a case study. Measures of welfare changes in a discrete choice framework were used to estimate proposed policies’ impacts on users. Eleven candidate policies were evaluated, ranging from the eradication of the informal modes and investment in formal modes, to the legalization of the informal modes. Benefits were compared with costs and the distribution of benefits across income classes was explored. Net benefits from some policies were found to be substantial. Legalizing the informal sector was found to benefit users slightly but further investments in the sector are probably inefficient. Users benefited most from improvements in formal mass transit modes, at roughly 100–200 dollars per commuter per year. Finally, policies to foster a competitive environment for the delivery of both informal and formal services were shown to benefit users about 100 dollars per commuter per year. Together, the regulation of the informal sector and investments in the formal sector serve to reinforce the movement towards competitive concessions for services and help reduce the impacts of cartelization and costly in-road competition.

考虑多目标的城市停车换乘选址优化模型及算法

停车换乘选址问题是城市交通网络设计研究的重点领域,已有研究的优化目标多集中在系统总费用方面,而对交通可持续发展方面考虑不足。为此,提出综合考虑多方面目标的停车换乘设施选址优化模型及其求解算法。首先,基于超网络理论,提出多方式城市交通系统的超网络模型并定义O-D (Origin-destination)间的超路径、有效超路径及子路径,结合出行者出行过程及交通网络拥挤特征,给出超路径费用的数学表达;其次,基于多方式交通网络随机均衡配流结果,构建交通总阻抗、污染物排放量以及交通系统公平性等系统优化指标的计算模型,并建立用以描述停车换乘设施选址问题的多目标优化模型;进而,以多目标系统优化模型为上层问题,以超网络下满足Logit分配的多方式交通网络配流模型为下层问题,构建描述城市多方式交通系统停车换乘设施选址问题的双层规划模型,并基于模型特征,结合“记录-搜索”思想设计非支配排序遗传算法进行求解;最后,基于Sioux Falls网络设计算例。研究结果表明：算法能够在有限的步骤内搜索到90%以上的Pareto最优解;平均而言,停车换乘措施使得交通总阻抗减小了0.31%,污染物排放量减少了7.32%...     

信号交叉口行车风险场建立及车辆通行行为优化

随着汽车逐步向智能化、网联化发展,智能网联车辆逐步进入实际应用阶段。进行智能网联车辆的通行行为优化,对提升驾驶安全性和行车效率,避免事故发生和交通拥堵至关重要。车辆在通过交叉口时将受到很多环境及运动因素的影响,而现有的通行优化模型难以准确表达各类因素共同作用下的行驶环境。为此,基于风险场理论建立由环境场和运动场组成的信号交叉口行车风险场,表征信号交叉口中每点的实时行车风险程度,从而引导车辆驶向风险值低点,并提供下一步长的位移及速度指引,实现车辆的动态轨迹优化及速度控制。典型场景下的仿真结果表明：在优化模型的控制下单车的信号交叉口通行效率明显提升,其中直行方向车辆单车平均通行效率提升最高,平均提升6.35%,通过对交叉口面积内所有车辆进行通行行为优化,交叉口通行效率提升了9.3%,这表明所建模型可以准确表达交叉口行车环境并优化车辆通行行为。研究结论可应用于自动驾驶车辆的交叉口通行控制,并为网联环境下的行车环境表达和安全驾驶控制提供模型基础。