Managing transportation during highway reconstruction: A recommended process

Major highway reconstruction can cause significant disruptions to existing travel patterns and economic activity. Reducing these impacts on travelers, shippers, businesses and residents requires that innovative and effective transportation management actions be developed and implemented. This paper reports the major findings and recommendations of a research study on managing transportation during highway, reconstruction. The primary objectives of the study were

Habitual travel behaviour: Evidence from a six-week travel diary

This paper introduces different methods to measure similarity of travel behaviour addressing the question of how repetitious travel behaviour actually is. It compares empirical results of the different methods based on the data from a six-week travel diary. In general, the results show that the day-to-day behaviour is more variable if measured with trip-based methods instead of methods based on time budgets. Furthermore, it is confirmed that the similarity declines if the method captures more of the complexity of the travel pattern. It is also shown that travel behaviour is neither totally repetitious nor totally variable. Even for the whole observation period, it is demonstrated that two days always have some common elements. Additionally, it is found that the different methods yield the same pattern of variability for different types of day. Travel behaviour is clearly more stable on work days. Similar results for all methods are also obtained concerning the question of how long the minimum period of observation should be. All measures show that the period should not be less than two weeks if one aims at measuring variability.     

Correlation between automotive CO, HC, NO, and PM emission factors from on-road remote sensing: implications for inspection and maintenance programs

Carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NO) emission factors (EFs) are measured with a commercial vehicle emissions remote sensing system (VERSS) during a large-scale vehicle exhaust emissions study in Las Vegas. Particulate matter (PM) EFs are simultaneously measured for individual vehicles with a newly developed PM-VERSS based on ultraviolet backscatter light detection and ranging (Lidar). The effectiveness of CO and HC EFs as proxy for NO and PM EFs for spark-ignition vehicles is evaluated. Poor correlations were found between EFs for pollutants on an individual vehicle basis indicating that high EFs for one or more pollutants cannot be used as a predictor of high EFs for other pollutants. Stronger functional relationships became evident after averaging the EF data in bins based on rank-order of a single pollutant EF. Low overlap between the highest 10% emitters for CO, HC, NO, and PM was found. These results imply that for an effective reduction of the four pollutants, inspection and maintenance (I/M) programs, including clean screening, should measure all four pollutants individually. Fleet average CO and HC concentrations determined by gaseous VERSS were compared with fleet average CO and HC concentrations measured at low-idle and at high-idle during local I/M tests for spark-ignition vehicles. The fleet average CO concentrations measured by I/M tests at either idle were about half of those measured by remote sensing. The fleet average high-idle HC concentration measured by I/M tests was about half of that measured by VERSS while low-idle I/M and VERSS HC average concentrations were in better agreement. For a typical vehicle trip, most of the fuel is burned during non-idle conditions. I/M measurements collected during idling conditions may not be a good indicator of a vehicle’s potential to be a high emitter. VERSS measurements, when the vehicle is under a load, should more effectively identify high emitting vehicles that have a large contribution to the mobile emissions inventory.     

Exploring the impact of walk–bike infrastructure,safety perception,and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

This study estimates a random parameter (mixed) logit model for active transportation (walk and bicycle) choices for work trips in the New York City (using 2010–2011 Regional Household Travel Survey Data). We explored the effects of traffic safety, walk–bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk–bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Further, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists, will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The model would be an essential tool to estimate the impact of improving traffic safety and walk–bike infrastructure which will assist in investment decision making.     

Lagrangian flow in the California Undercurrent, an observation and model comparison

During the period 1992–1998, 38 isobaric RAFOS floats were deployed to sample the subsurface flow of the California Undercurrent. The deployments, released over the California continental slope west of San Francisco, have sampled robust year-round poleward subsurface flow associated with the Undercurrent most seasons and the combined inshore current and Undercurrent in winter. Two other types of flow have been seen: a region of weak flow with little net displacement just west of the California Undercurrent, and an active westward propagating eddy field. This eddy field appears to be the primary mechanism for moving floats from the Undercurrent into the ocean interior. The observations and statistics from the RAFOS floats are compared with Lagrangian estimates of particles tracked in a global high resolution ocean simulation in order to evaluate the fidelity of the model along an eastern boundary. The results show that the model reproduces the general character of the flow reasonably well, but underestimates both the mean and eddy energies by a substantial amount.     

Strategic alliances in container liner shipping

The economic crisis in the years between 2008 and 2010 has demonstrated the necessity for substantial adjustments on behalf of container lines. Capacities were shifted quickly to emerging and less affected markets allowing a faster recovery of globally organized companies. This paper illustrates the dynamics in the container shipping market. Alongside the main characteristics of the Top 20 ocean shipping companies, liner services are described. These services are classified by geographic coverage and vessel deployment. In addition, this paper provides a better understanding of the collaboration among service providers. Starting from a general framework of co-operative liner services, in-depth analyses of the global alliances in liner shipping are obtained. These formations - Grand Alliance, New World Alliance and CKYH Alliance - are compared with alternative forms of collaboration in the liner shipping industry. The analysis of alliance announcements which are related to operational and strategic changes indicates that the “global alliances” cannot be regarded as closed corporate-like entities. In effect, service agreements are not only negotiated with the focal members of the specific alliance. Instead, every service is arranged individually and under specific conditions. By understanding the dynamics within alliances, we are able to develop an assessment relating to the stability of collaborations. Ultimately, these insights direct us to several paths for future research.     

Automated Emergency Four-Wheel-Steered Vehicle Using Continuous Gain Equations

Advanced Vehicle Control Systems (AVCS), when realized, should substantially increase the convenience and safety of highway travel. Automated lateral control is an important step in the realization of AVCS. Much research has been concerned with lateral control during low-g maneuvers. However, before passengers' lives are in the hands of any automated laterally-controlled vehicle, the vehicle controller must be designed to respond to emergency situations where high-g maneuvers may be necessary.

This paper presents the development of a nonlinear-gain-optimized (NGO) controller for emergency automated lateral control of four wheel steered automobiles. Continuous gain equations (GE) are used to account for changes in the vehicle speed. The NGO controller uses a linear vehicle/tire model to define the state model. The response of a nonlinear vehicle/tire model is used to choose the performance index that optimizes the feedback gains for high-g emergency maneuvers at discrete speeds. Continuous gain equations are then derived as least-square approximations to each set of gains.

The performance of the four-wheel-steer continuous gain equations (4WS-GE) controller is compared to that of a two-wheel-steer continuous gain equations (2WS-GE) controller. Significant improvements in vehicle response are realized by using the 4WS-GE controller. The robustness of the controller's performance is examined with respect to changes in tire parameters and changes in vehicle mass.