John El Khoury

Incorporating Uncertainty into the Estimation of the Passing Sight Distance Requirements

Passing sight distance (PSD) is provided to ensure the safety of passing maneuvers on 2-lane, 2-way roads. Many random variables determine the minimum length required for a safe passing maneuver. Current PSD design practices replace these random variables by single-value means in the calculation process, disregarding their inherent variations, which results in a single-value PSD design criteria. The main aim of this paper is to derive a PSD distribution that accounts for the variations in the contributing random variables. Two models are devised, a Monte-Carlo simulation model used to obtain the PSD distribution and a closed form analytical estimation model used for verification purposes. The Monte-Carlo simulation model uses random sampling to select values of the contributing parameters from their corresponding distributions in each run. The analytical model accounts for each parameter variation by using their means and standard deviations in a closed form estimation method. The means and standard deviations of the PSD using both models are compared for verification purposes. Both models use the same PSD formulation. Analysis is conducted for a design speed of 50 mph. A PSD distribution is developed accordingly. Results of both models differ only by less than 2%. The obtained distribution is used to estimate the reliability index of the current PSD standards at a design speed of 50 mph.

Integrated Stochastic Approach for Risk and Service Estimation: Passing Sight Distance Application

The geometric design of highway elements is based on a set of standards that do not consider the risk levels associated with these designs. Safety elements including risk measures need to be identified and incorporated into the design process. The focus of this paper is a procedure that can be used by practitioners as a framework to conduct trade-off analyses between risk and service measures of specific design elements. The procedure builds on the randomness of parameters affecting the design attributes of any highway element. By accounting for the inherent variability of the determining parameters, random distributions of the design element can be derived. Then, using stochastic simulation, each of the design values can be tested to assess its risk measures. As a result, a risk index can then be attached to every design value in the random distribution. Finally, level of service (LOS) measures can be estimated and a trade-off analysis between LOS and safety could be conducted. The application focused on the design of the passing sight distance (PSD), which is an example of a highway element traditionally analyzed with no risk measures. Within the analysis, the risks and LOS measures associated with the use of the current PSD standards were assessed. The American Association of State Highways and Transportation Officials (AASHTO) Green Book values were shown to be conservative. The Manual on Uniform Traffic Control Devices (MUTCD) values fall within the acceptable risk and level of service (LOS) levels. Language: en

Assessing the effectiveness of probe vehicle acceleration measurements in estimating road roughness

In this article, we compare roadway roughness measured using a probe vehicle with roadway roughness calculated from the measured profile using an inertial profiler. Roughness is characterised by vehicle body vertical acceleration and probe vehicle roughness index (PVRI), which approximates the international roughness index (IRI) of a full car (rather than a quarter car). The reason the PVRI is used rather than the IRI is that acceleration measurements obtained from a probe vehicle represent the response of the full car rather than a quarter car. An important aspect of this article is that the same physical quantities are compared rather than obtaining a correlation between two different physical quantities. The results suggest that the roughness calculated from probe vehicle measurements is comparable with the roughness calculated from the measured profile; however, the investigation also revealed that data sampling frequency and quarter car parameters, specifically suspension damping and tyre stiffness, can have a significant effect on the measured PVRI.

Passive, Decentralized, and Fully Autonomous Intersection Access Control

Current research on autonomous intersection management makes a set of assumptions including active Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I) communications, and/or centralized control. While they enhance the efficiency of the solution, such assumptions have inherent security and privacy drawbacks and require high infrastructure costs. This paper sets to investigate an alternative solution to autonomous intersection management that is decentralized (no centralized controller) and passive (no vehicle communications). Our scheme permits autonomous vehicles approaching an intersection to make localized collision-free access decisions based purely on sensing and beacon information. Besides demonstrating the feasibility of a fully autonomous and decentralized approach, we show that our scheme operationally outperforms a standard actuated signal and all-way stop control. Our decentralized approach trades off optimality for low cost, and enhanced security, privacy, and practicality.

Integrating Data Collection Optimization into Pavement Management Systems

This paper describes a method for using location data to optimize the routing of pavement data collection vehicles. In much of the developed world, pavement testing is performed on a regular basis; the pavement testing data, in turn, serves as input to Pavement Management Systems. Currently, in the United States of America, state departments of transportation plan this data collection work by providing the list of roads that must be tested and then leave the routing of the vehicles to the equipment operators who typically execute the work in an ad hoc manner. This study presents the processes required to code the list of roads for testing, select appropriate hotels in the region of testing, and apply a Traveling Salesman Problem with Hotel Stops model to derive a route. Applying the processes to a case study shows significant cost savings associated with this method of roadway testing, as opposed to the current ad hoc methods.

A Practical Approach to Decentralized Intersection Access Control for Autonomous Vehicles

In a shift from the current research trend which is mostly geared towards centralizing access control of autonomous vehicles at intersection of the near future, the authors extend their previously presented intersection management model, which is fully decentralized. Even though it is the most efficient, central control requires fully automated connected vehicles, active vehicle-to-vehicle and vehicle-to-infrastructure communications, which introduces inherent security, privacy and feasibility issues. We simulate autonomous intelligent vehicles making local access decisions at isolated intersections, with only sensing and/or beacon information. The simulation proves to be collision-free. The extended management model is now able to account for various vehicle classes, all possible turns at the intersection and safe turning speeds. Compared to a standard signal controller, the proposed and improved model is again proven to be operationally more efficient.

Adaptive False Discovery Rate for Wavelet Denoising of Pavement Continuous Deflection Measurements

AbstractThe traffic speed deflectometer (TSD) is a device used to evaluate the pavement’s structural condition. Measurements obtained from the TSD are affected by noise, which can make it hard to interpret test results. The main objective of this paper is to develop a denoising methodology to use with TSD measurements and improve pavement structural evaluation. The denoising methodology comprises a computational algorithm to identify significant features in a high-dimensional vector of observations containing white Gaussian noise. The algorithm minimizes the classification error of features in the wavelet transform domain by adaptively selecting the level at which to control the false discovery rate. When tested in a simulation study, the results of the proposed algorithm compared favorably with other state-of-the-art methods. The proposed methodology was then successfully used with TSD measurements to identify possible weak joints in a jointed concrete pavement overlaid with an asphalt layer and to calcu...

Value of Dynamic Revenue-Maximizing Congestion Pricing in a Highly Congested Corridor

AbstractThis paper examines the value of utilizing dynamic, revenue-maximizing, congestion pricing on a privately operated tolled route, when the only alternative is a highly congested, public, free-access route. Three methods are specified by which revenue can be maximized—through the selection of a fixed percent of users to set the toll price for, through the selection of a fixed level of service on the toll road, and through the use of a nonlinear optimization model. These methods are tested on a case study involving a highly congested corridor. In simulation, the corridor’s flow rates are observed following the posting of a toll, the toll is updated, and the new flow observed until a subsequent round of revenue maximizing is applied to the new conditions. It was concluded that in a highly congested corridor a dynamic, revenue-maximizing toll can finance the construction of new capacity without degrading social welfare.