Making do: The effects of a mass transit strike on travel behavior

A brief transit strike in early December 1976 disrupted bus services to the city of Pittsburgh and surrounding Allegheny County. That strike provided an opportunity for testing a variety of approaches to increase ride-sharing and to reduce traffic congestion, and for examining the effect of the strike on traffic congestion and on individual travel behavior. Even though over 60% of the commuters to the CBD use transit, the effects of the strike were relatively mild. There was some increase in traffic flow into the CBD and some spreading of the peak period. The largest proportion of the transit commuters who made trips to the CBD during the strike were dropped off by a non-commuter, increasing highway traffic. The most severe impact was felt by those transit commuters who had no cars in the household; 25% of these commuters (only 3% of the total CBD commuters) stayed home from work on the first day of the strike. Most attempts to mitigate the impact of the strike had little effect, largely because most commuters were able to manage adequately during the short strike. The anticipated parking problem, on which much of the contingency planning was focused, did not emerge, largely because of the use of carpooling and drop-off mode by many of the transit users.     

Bush-based sensitivity analysis for approximating subnetwork diversion

Subnetwork analysis is often used in traffic assignment problems to reduce the size of the network being analyzed, with a corresponding decrease in computation time. This is particularly important in network design, second-best pricing, or other bilevel problems in which many equilibrium runs must be solved as a subproblem to a master optimization program. A fixed trip table based on an equilibrium path flow solution is often used, but this ignores important attraction and diversion effects as drivers (globally) change routes in response to (local) subnetwork changes. This paper presents an approach for replacing a regional network with a smaller one, containing all of the subnetwork, and zones. Artificial arcs are created to represent “all paths” between each origin and subnetwork boundary node, under the assumption that the set of equilibrium routes does not change. The primary contribution of the paper is a procedure for estimating a cost function on these artificial arcs, using derivatives of the equilibrium travel times between the end nodes to create a Taylor series. A bush-based representation allows rapid calculation of these derivatives. Two methods for calculating these derivatives are presented, one based on network transformations and resembling techniques used in the analysis of resistive circuits, and another based on iterated solution of a nested set of linear equations. These methods are applied to two networks, one small and artificial, and the other a regional network representing the Austin, Texas metropolitan area. These demonstrations show substantial improvement in accuracy as compared to using a fixed table, and demonstrate the efficiency of the proposed approach.     

The determinants of long distance travel in Great Britain

This study analyses of the determinants of long distance travel in Great Britain using data from the 1995-2006 National Travel Surveys (NTSs). The main objective is to determine the effects of socio-economic, demographic and geographic factors on long distance travel. The estimated models express the distance travelled for long distance journeys as a function of income, gender, age, employment status, household characteristics, area of residence, size of municipality, type of residence and length of time living in the area. A time trend is also included to capture common changes in long distance travel over time not included in the explanatory variables. Separate models are estimated for total travel, travel by each of four modes (car, rail, coach and air), travel by five purposes (business, commuting, leisure, holiday and visiting friends and relatives (VFRs)) and two journey lengths (<150 miles and 150+ miles one way), as well as the 35 mode-purpose-distance combinations.The results show that long distance travel is strongly related to income: air is most income-elastic, followed by rail, car and finally coach. This is the case for most journey purposes and distance bands. Notable is the substantial difference in income elasticities for rail for business/commuting as opposed to holiday/leisure/VFR. In addition, the income elasticity for coach travel is very low, and zero for the majority of purpose-distance bands, suggesting coach travel to be an inferior mode in comparison to car, rail and air. Regarding journey distance, we find that longer distance journeys are more income elastic than shorter journeys.For total long distance travel, the study indicates that women travel less than men, the elderly less than younger people, the employed and students more than others, those in one adult households more than those in larger households and those in households with children less than those without. Long distance travel is also lowest for individuals living in London and greatest for those in the South West, and increases as the size of the municipality declines.     

Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand

Network pricing serves as an instrument for congestion management, however, agencies and planners often encounter problems of estimating appropriate toll prices. Tolls are commonly estimated for a single-point deterministic travel demand, which may lead to imperfect policy decisions due to inherent uncertainties in future travel demand. Previous research has addressed the issue of demand uncertainty in the pricing context, but the elastic nature of demand along with its uncertainty has not been explicitly considered. Similarly, interactions between elasticity and uncertainty of demand have not been characterized. This study addresses these gaps and proposes a framework to estimate nearest optimal first-best tolls under long-term stochasticity in elastic demand. We show first that the optimal tolls under the deterministic-elastic and stochastic-elastic demand cases coincide when cost and demand functions are linear, and the set of equilibrium paths is constant. These assumptions are restrictive, so three larger networks are considered numerically, and the subsequent pricing decisions are assessed. The results of the numerical experiments suggest that in many cases, optimal pricing decisions under the combined stochastic-elastic demand scenario resemble those when demand is known exactly. The applications in this study thus suggest that inclusion of demand elasticity offsets the need of considering future demand uncertainties for first-best congestion pricing frameworks.     

Strategic intent: Guiding port authorities to their new world?

Following the financial tsunami many organisations are facing greater risks to their sustainability. Strategic collaborations in logistics networks, of which ports are a significant node, reduce risks for all organisations in the network, increase an organisation's ability to access efficiencies such as economies of scale and create opportunities for learning. The knowledge learnt from collaborators is enhanced by managing the key relationships and forming a strategic intent to learn for mutual benefit. Mutual benefits may include market information or innovation. As Awad and Ghaziri (2004, p. 17) comment ‘Beyond efficiency and productivity, the real benefit of collaboration is innovation.’ The more central the port authority is in this network, the greater are the opportunities for learning. Three key factors are critical for port authorities to integrate knowledge from networks; firstly, there are levels of common knowledge that enable effective communication, including concepts, behavioural norms, language and experience. Secondly integrative efficiency requires organisational routines which foster knowledge sharing through frequent, coordinated activities that are repetitive. Thirdly efficient structures within the port authority help maintain effective and efficient communication to minimise the knowledge loss on integration. Strategising provides opportunities for port authorities to steer the critical path between maintaining their current sources of competitive advantage and developing future resilience through innovation opportunities provided by learning from their trading networks. Port authorities, by developing skills in reading the collective mind and interpreting information available in trading networks, can foster resilience into the future. Given the current risky prognosis for the short-medium term following the financial tsunami, instigating strategies that may lessen those risks may be an option for port authorities.     

Employability skills of maritime business graduates: industry perspectives

The maritime industry underpins international business and world trade. As to be expected, business management is critical for the maritime industry, requiring highly trained individuals and teams to lead the development, implementation and control of sound contemporary management practices. Maritime business degrees are developed by universities to meet such demand by providing graduates with sufficient skills for the onshore business-related roles. This empirical study conducted in Australia, USA and Canada, investigates current and future industry employability skills for maritime business graduates through focus groups, individual interviews and an online survey with senior managers in maritime organisations. This study found the important employability skills for maritime business graduates which include communication, problem solving, adaptability, self-management, team work, and digital literacy and technology. Demand for digital literacy and technology knowledge and skills have increased due to the maritime industry having a trend of moving towards digitalisation and automation. However, the survey findings revealed that a skills focus for maritime business graduates will not be the technology itself but the use and management of technology. In relation to future skills/knowledge required from maritime business degree graduates in 10 years’ time, communication and adaptability are recognised as being the most important. Employers expect that maritime business graduates should be able to adopt new technology and be competent in communication, and be more adaptable given the highly dynamic nature of the maritime industry. Moreover, they require graduates to be equipped with a higher level of computer skills, have a strong work ethic and multilingual skills.     

The impact of dry port operations on container seaports competitiveness

The concepts of intermodal logistics and distribution networks have made integration of the inland freight distribution system essential for an efficient container seaport system. Inland components, such as dry ports, which exist within the seaport system, have become important in shaping the performance and competitive strategies of container seaports. Owing to the importance of interdependence between dry ports and container seaports, this paper aims to investigate the impact of dry port operations on container seaport competitiveness. It conducted an empirical study in Malaysia through 120 online surveys to key stakeholders of dry ports, including freight forwarders, shippers, seaports, rail operator, shipping lines, and haulers. The data collected were analysed using exploratory factor analysis (EFA). The results from EFA show that Malaysian dry port operations have impacts on seaport competitiveness. These include enhancing seaport performance, increasing service variations for seaports, improving seaport-hinterland proximity, increasing seaport trade volume, and enhancing seaport capacity.     

Policy challenges of increasing automation in driving

The convergence of information and communication technologies (ICT) with automotive technologies has already resulted in automation features in road vehicles and this trend is expected to continue in the future owing to consumer demand, dropping costs of components, and improved reliability. While the automation features that have taken place so far are mainly in the form of information and driver warning technologies (classified as level I pre-2010), future developments in the medium term (level II 2010–2025) are expected to exhibit connected cognitive vehicle features and encompass increasing degree of automation in the form of advanced driver assistance systems. Although autonomous vehicles have been developed for research purposes and are being tested in controlled driving missions, the autonomous driving case is only a long term (level III 2025 +) scenario. This paper contributes knowledge on technological forecasts regarding automation, policy challenges for each level of technology development and application context, and the essential instrument of cost-effectiveness for policy analysis which enables policy decisions on the automation systems to be assessed in a consistent and balanced manner. The cost of a system per vehicle is viewed against its effectiveness in meeting policy objectives of improving safety, efficiency, mobility, convenience and reducing environmental effects. Example applications are provided that illustrate the contribution of the methodology in providing information for supporting policy decisions. Given the uncertainties in system costs as well as effectiveness, the tool for assessing policies for future generation features probabilistic and utility-theoretic analysis capability. The policy issues defined and the assessment framework enable the resolution of policy challenges while allowing worthy innovative automation in driving to enhance future road transportation.     

新能源汽车消费者购买意愿调查

<正>虽然政府频频出台新能源利好政策,希望刺激消费者购买欲望,但研究显示,仅靠政策单方面刺激很难完成到2020年累计销售500万辆新能源车的目标,需要地方政府、汽车OEM和电网公司共同致力于推动新能源汽车的成功发展,解决充电等难题,从根本上消除消费者的顾虑。"中国消费者对新能源汽车(NEV)的兴趣及购买意愿仍不足以实现中国政府新能源汽车销量的目标。"中国是全球最大的汽车市场,而汽车业如火如荼的发展也同时造成了大城市的严重交通拥堵和空气污染。随着城镇化进程的不断推进(城镇人口有望从2014年