The purpose of this research was to develop a decision support methodology to identify the optimal locations of a finite set of point detectors on a freeway corridor to minimize the error in travel time estimation. The developed methodology, consisting of floating vehicle-based global-positioning system data collection, and use of a heuristic search technique (genetic algorithm)–based search tool, was shown to be effective in determining preferred detector locations for the chosen objective. Case studies of freeway sections in two Virginia regions were conducted to demonstrate the utility of the developed methodology. The writers found that the placement of detectors for the development of accurate travel time estimates will vary by location on the basis of specific conditions. Arbitrary, evenly spaced detectors do not necessarily result in accurate travel time estimates. With carefully placed detectors that are well maintained, travel time estimates can be derived with an acceptable level of accuracy from point detection, under incident-free travel conditions.

This paper assesses various issues associated with the use of IntelliDrive probe vehicle data generated according to existing protocols. These evaluations are conducted using a virtual IntelliDrive probe vehicle data generator implemented within the Paramics microscopic traffic simulation model. Issues investigated included the ability to monitor queue conditions, the potential for data-sampling bias, effects of privacy rules on collected data, the ability to track vehicles over short distances, the magnitude of data latency induced by the protocols, and the ability to use probe vehicle data to estimate link travel times. The evaluations indicate various improvement needs: (1) generating snapshots at fixed intervals rather than at speed-based intervals, (2) promoting the use of short snapshot intervals, (3) allowing vehicles to include the snapshots they generate while stopped, (4) enabling vehicles to generate link exit snapshots, (5) allowing vehicles to keep uploading new snapshots generated while within range of a roadside communication unit, and (6) revising privacy protocols to ensure that adequate short vehicle tracks can be obtained. The impacts of current privacy rules on the ability to track vehicles over short distances are also outlined.

Over recent years it has been assumed that posted speed limits should consider an integrated set of requirements such as the built-in road environment and the presence and characteristics of its users. In the present paper a multinomial logit (MNL) discrete choice model for selecting speed limits is presented as an exploratory method for relating measurable roadside characteristics and speed limits over the full length of rural two-lane highways. The model was developed using as a case study 34 km of rural roads in the region of Coimbra (Portugal). The choice of four traffic safety experts was recorded for each 200 m segment, in both directions, permitting the estimation of the MNL. Only straight and nearly straight roadway segments were considered, and speed limitations resulting from restrictive geometric properties of the segments were disregarded in this study. The explanatory variables were collected to describe the built-up characteristics of the different segments of the road and its surrounding environment. The model adjusted well to the data; and an external data set was shown to be consistent with the expert judgment. Variables that were added to translate lateral roadside constraints were those with a higher significance in explaining the choice of lower limits. Comparing the model with the actual speed limits posted in situ, it was possible to conclude that there is a clear mismatch between these limits and the surrounding environment with a significant tendency for lower posted speed limits compared with the limits at which experts believe that it would be safe to drive.

This paper analyzes rail-track geometry degradation and uncertainty related to the phenomenon on the basis of the inspection of car records from recently upgraded sections of the Lisbon-Oporto line. Statistical analysis is performed distinguishing four groups of track sections based on the features of the infrastructure. For each group of track sections, lognormal distributions are fitted to track geometry degradation parameters. Moreover, important correlations between degradation parameters are explored, so that the assessment of the maintenance cycles of future upgraded lines can integrate them through simulation. Spatial linear correlations between degradation parameters are also explored, and some that may influence life-cycle maintenance, renewal, and unavailability costs are highlighted.

Magnetic levitation (maglev) has already captured the demanding eyes of worldwide transportation networks. However, there is hardly any report of practical algorithms for systematic calculations of loading on guideways of magnetically levitated trains. A proper model for guideway load distribution and accuracy of such model is the backbone for optimized guideway design. This research is in response to such a necessity. Parameters that are effective for the analysis and design of guideways, including its loading patterns and structural models, are investigated. Vehicle mechanical design and its loading capacity in addition to guideway geometry and properties of magnetic force elements are also used to develop the loading models. Correlation between magnetic forces and dynamics of the vehicle regarding its ride comfort on the straight and the curved routes are implemented. This facilitates evaluation of guideway structure in view of its mechanical strength and dynamic stability. The proposed models are evaluated in a case study by reviewing route design for the Mashhad-Tehran maglev system. It is concluded that the proposed analytical methods are accurate and ready made for practical purposes.

Separation of large obstacles from longitudinal road profiles using median filtering is presented. Detailed testing of this method confirms its ability to remove large obstacles without corrupting the random component of the road profile. At the same time, optimal length of the window as the ceiling of double the maximum obstacle length is estimated. For the specification of individual obstacles, six indicators are introduced, namely, obstacle length, maximum obstacle height, ratio of obstacle length to its maximum height, area of the obstacle profile, obstacle volume, and distance between two successive obstacles. About 23,400 records of road profiles gathered from the Long Term Pavement Performance (LTPP) program were processed from which 5,036 profiles displayed obstacles higher than 0.3 cm. A total number of 16,590 obstacles were detected. Statistical processing of all of these profiles to distinguish between asphalt concrete (AC) and portland cement concrete (CC) road surfaces and between bumps (B) and potholes (P) identified that 71% of all obstacles belong to the AC+P combination. In the appendix, correction factors (CF) are presented, allowing the elimination of bias attributable to preprocessing operations applied on LTPP profile records used for estimation of true obstacle dimensions.