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.

Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems

Map-matching (MM) algorithms integrate positioning data from a Global Positioning System (or a number of other positioning sensors) with a spatial road map with the aim of identifying the road segment on which a user (or a vehicle) is travelling and the location on that segment. Amongst the family of MM algorithms consisting of geometric, topological, probabilistic and advanced, topological MM (tMM) algorithms are relatively simple, easy and quick, enabling them to be implemented in real-time. Therefore, a tMM algorithm is used in many navigation devices manufactured by industry. However, existing tMM algorithms have a number of limitations which affect their performance relative to advanced MM algorithms. This paper demonstrates that it is possible by addressing these issues to significantly improve the performance of a tMM algorithm. This paper describes the development of an enhanced weight-based tMM algorithm in which the weights are determined from real-world field data using an optimisation technique. Two new weights for turn-restriction at junctions and link connectivity are introduced to improve the performance of matching, especially at junctions. A new procedure is developed for the initial map-matching process. Two consistency checks are introduced to minimise mismatches. The enhanced map-matching algorithm was tested using field data from dense urban areas and suburban areas. The algorithm identified 96.8% and 95.93% of the links correctly for positioning data collected in urban areas of central London and Washington, DC, respectively. In case of suburban area, in the west of London, the algorithm succeeded with 96.71% correct link identification with a horizontal accuracy of 9.81 m (2σ). This is superior to most existing topological MM algorithms and has the potential to support the navigation modules of many Intelligent Transport System (ITS) services.     

Urban transportation modeling: The discussion continues

This article is a response to John Polak's article, entitled, A Comment on Supernak's Critique of Transport Modeling, published elsewhere in this issue of TRANSPORTATION. It offers necessary clarifications to the issues discussed in an earlier article in this journal (Supernak, 1983). It also responds to the philosophical issues discussed in Polak's article, such as the nature of transport phenomena, and the role, form and methodology of transport modeling.     

Assessing the representativeness of a smartphone-based household travel survey in Dar es Salaam,Tanzania

The household travel survey (HTS) finds itself in the midst of rapid technological change. Traditional methods are increasingly being sidelined by digital devices and computational power—for tracking movements, automatically detecting modes and activities, facilitating data collection, etc.. Smartphones have recently emerged as the latest technological enhancement. FMS is a smartphone-based prompted-recall HTS platform, consisting of an app for sensor data collection, a backend for data processing and inference, and a user interface for verification of inferences (e.g., modes, activities, times, etc.). FMS, has been deployed in several cities of the global north, including Singapore. This paper assesses the first use of FMS in a city of the global south, Dar es Salaam. FMS in Dar was implemented over a 1-month period, among 581 adults chosen from 300 randomly selected households. Individuals were provided phones with data plans and the FMS app preloaded. Verification of the collected data occurred every 3 days, via a phone interview. The experiment reveals various social and technical challenges. Models of individual likelihood to participate suggest little bias. Several socioeconomic and demographic characteristics apparently do influence, however, the number of days fully verified per individual. Similar apparent biases emerge when predicting the likelihood of a given day being verified. Some risk of non-random, non-response is, thus, evident.     

Back-Calculation of Ground Stress Field and Rockburst Analysis for Wunvfeng Tunnel北大核心CSCD

Studying the in-situ stress distribution at a tunnel site is very important to determine surrounding rock characteristics, the engineering design and the construction scheme. By using the multiple linear regression method based on the least square algorithm, the initial geostress field is analyzed and the corresponding regression coefficients are obtained. The ground stress obtained from the proposed back analysis is reasonable and can meet the demands of the engineering applications. From the rockburst risk level distribution diagram, it is speculated that the Wunvfeng tunnel is in the high filed stress area. Field monitoring should be strengthened and emergency plans should be made to cope with the rockburst risks during the construction process. © 2018, Editorial Office of "Modern Tunnelling Technology". All right reserved.     

Enhanced traffic information dissemination to facilitate toll road utilization: a nested logit model of a stated preference survey in Texas

This paper investigates the effects of the provision of traffic information on toll road usage based on a stated preference survey conducted in central Texas. Although many researchers have studied congestion pricing and traffic information dissemination extensively, most of them focused on the effects that these instruments individually produce on transportation system performance. Few studies have been conducted to elaborate on the impacts of traffic information dissemination on toll road utilization. In this study, 716 individuals completed a survey to measure representative public opinions and preferences for toll road usage in support of various traffic information dissemination classified by different modes, contents, and timeliness categories. A nested logit model was developed and estimated to identify the significant attributes of traffic information dissemination, traveler commuting patterns, routing behavior, and demographic characteristics, and analyze their impacts on toll road utilization. The results revealed that the travelers using dynamic message sign systems as their primary mode of receiving traffic information are more likely to choose toll roads. The potential toll road users also indicated their desire to obtain traffic information via internet. Information regarding accident locations, road hazard warnings, and congested roads is frequently sought by travelers. Furthermore, high-quality congested road information dissemination can significantly enhance travelers’ preferences of toll road usage. Specifically the study found that travelers anticipated an average travel time saving of about 11.3 min from better information; this is about 30 % of travelers’ average one-way commuting time. The mean value of the time savings was found to be about $11.82 per hour, close to ½ of the average Austin wage rate. The model specifications and result analyses provide in-depth insights in interpreting travelers’ behavioral tendencies of toll road utilization in support of traffic information. The results are also helpful to shape and develop future transportation toll system and transportation policy.     

Driver fatigue: a vision-based approach to automatic diagnosis

In this paper, we describe a system that locates and tracks the eyes of a driver. The purpose of such a system is to perform detection of driver fatigue. By mounting a small camera inside the car, we can monitor the face of the driver and look for eye movements which indicate that the driver is no longer in condition to drive. In such a case, a warning signal should be issued. This paper describes how to find and track the eyes. We also describe a method that can determine if the eyes are open or closed. The primary criterion for this system is that it must be highly non-intrusive. The system must also operate regardless of the texture and the color of the face. It must also be able to handle changing conditions such as changes in light, shadows, reflections, etc. Initial experimental results are very promising even when the driver moves his/her head in a way such that the camera does not have a frontal view of the driver’s face.     

Mathematical model for optimising the sequence for clearing snow from the manoeuvring area during winter operations

This article considers the optimisation of the sequence for clearing snow from stretches of the manoeuvring area of an airport. This issue involves the optimisation of limited resources to remove snow from taxiways and runways thereby leaving them in an acceptable condition for operating aircraft. The airfield is divided into subsets of significant stretches for the purpose of operations and target times are established during which these are open to aircraft traffic. The document contains several mathematical models each with different functions, such as the end time of the process, the sum of the end times of each stretch and gap between the estimated and the real end times. During this process, we introduce different operating restrictions on partial fulfilment of the operational targets as applied to zones of special interest, or relating to the operation of the snow‐clearing machines. The problem is solved by optimisation based on linear programming. The article gives the results of the computational tests carried out on five distinct models of the manoeuvring area, which cover increasingly complex situations and larger areas. The mathematical model is particularised for the case of the manoeuvring area of Adolfo Suarez Madrid—Barajas Airport. Copyright © 2016 John Wiley & Sons, Ltd.

Highlights
• Optimal sequence for clearing snow from the manoeuvring area of an airport.
• Contains optimising algorithms solved using CPLEX LP‐based tree search.
• Restrictions on partial fulfilment of operational targets applied to subsets of significant stretches, used for planning the operation of snow‐clearing machines.
• Model applied to the case of the manoeuvring area of Adolfo Suárez Madrid Barajas Airport.
• Conclusions are given on the results of the computational tests carried out. There are five models of the manoeuvring area which cover increasingly complex situations and larger areas.