M. N. Murshed, Imelda Barrett, P. E., and Randy B. Machemehl, P. E., “Predicting Priorities for Installing Over-height Vehicle Detection/Warning Systems for Bridges,” TRB 95th Annual Meeting Compendium of Papers, 2016. Publisher's VersionAbstract
Although collisions of over-height vehicles or vehicles carrying over-height loads with a bridge 3 superstructure may be considered a rare event, occurrences of such events are not uncommon. 4 When such an event takes place, the damage sustained by the bridge superstructure may be 5 substantial- sometimes even leading to total collapse of the bridge. Out of the available solutions 6 to this problem the most promising and attractive one involves the installation of over-height 7 vehicle detection and warning systems, however, such systems have diverse installation costs, 8 effectiveness and longevity. Moreover, yearly budget constraints limit the number of such 9 installations and there is no guideline as to which bridges should be equipped with such devices. 10 In this study a relatively simple but effective method is developed using only two basic items of 11 information about the bridge (minimum vertical under-clearance) and total number of traffic 12 lanes under the bridge to produce a priority ranking based upon the likelihood of the bridge being 13 hit by an over-height truck. Bridge collision datasets were obtained from three state DOTs- New 14 York, Missouri and Texas and these were used to develop the predictive procedure.
M. Motamed and Machemehl, R., “

Detecting Peak-hour Freeway Incident Using Machine Learning

,” Presented in 94th Annual Meeting of the Transportation Research Board. 2015. Publisher's VersionAbstract
The purpose of this study is to evaluate application of a type of supervised machine learning model called support vector machine (SVM) to freeway automatic incident detection. Many automatic incident detection algorithms are focused on identifying changes in traffic patterns but do not adequately investigate similarities in patterns observed under incident-free conditions. The most challenging part of real-time incident detection is recognition of traffic pattern changes when incidents happen during rush hour stop-and-go conditions. Incident detection can be described as a pattern classification problem and SVMs have pattern learning algorithms that have been successfully applied to incident detection. Previous evaluation studies have been based on either simulation data or the I-880 database. The possible issue with these is that non-incident traffic patterns may be biased by actual incident data. This study uses field traffic pattern data to overcome the problem of incident detection during peak hour. Data collected by the Dallas traffic control center including upstream and downstream speed and volume and typical upstream speed profiles. All parameters were used as base model input and different scenarios were defined, in terms of SVM kernel functions (the sigmoid and RBF) and different parameters combination. Cross-validation has been applied to increase classification accuracy. Based on this evaluation, the proposed SVM model provides reliable results.
M. Khan and Machemehl, R., “

A Truck Trip Generation Model for Williamson County, Texas: Survey Analysis

,” Presented in 94th Annual Meeting of the Transportation Research Board. 2015.Abstract
This paper uses ordered-response model and linear regression model structures to evaluate the demographic and land-use factors that affect truck trip generation at a regional level. The data used for this paper were collected from the business establishments located in Williamson County, Texas through a mailout-mailback survey conducted in year 2014. The paper presents the empirical results and discusses the policy implications of these results for urban planning. Model results show that industry type, size and the location of business establishments affect their truck trip generation behavior. Business establishments with larger number of employees are more likely to attract more truck traffic, whereas, businesses owning their trucks are more likely to produce more truck traffic. Businesses located in areas with higher land-values tend to generate less truck traffic whereas businesses located in industrial land-use types are likely to generate more truck traffic. 
File khan_mubassira_trb_truck_trip_generation_2015.04.14_for_web.docx
M. Motamed and Machemehl, R., “

Real-Time Freeway Incident Detection,Report No. SWUTC/13/600451-00083-1

,” Southwest University Transportation Center, 2014. Publisher's VersionAbstract
The US Department of Transportation (US-DOT) estimates that over half of all congestion events are caused by highway incidents rather than by rush-hour traffic in big cities. Real-time incident detection on freeways is an important part of any modern traffic control center operation because it offers an opportunity to maximize road system performance. An effective incident detection and management operation cannot prevent incidents, however, it can diminish the impacts of non-recurring congestion problems. The main purpose of real-time incident detection is to reduce delay and the number of secondary accidents, and to improve safety and travel information during unusual traffic conditions. The purpose of this project is to evaluate two recently developed automatic incident detection algorithms. The majority of automatic incident detection algorithms are focused on identifying traffic incident patterns but may not adequately investigate possible similarities in patterns observed under incident-free conditions. When traffic demand exceeds road capacity, the traffic speed decreases significantly and the traffic enters a highly unstable regime often referred to as “stop-and-go” conditions. The most challenging part of real-time incident detection is recognition of traffic pattern changes when incidents happen during stop-and-go conditions. This work describes a case study evaluation of two recently evolved incident detection methods using data from the Dallas, TX traffic control center. 
W. Fan, Machemehl, R., Gemar, M., and Brown, L., “A Stochastic Dynamic Programming Approach for the Equipment Replacement Optimization under Uncertainty,” Journal of Transportation Systems Engineering and Information Technology, vol. 14, no. 3, pp. 76-84, 2014. Publisher's VersionAbstract
In this paper, a stochastic dynamic programming (SDP) based optimization model is formulated for the equipment replacement optimization (ERO) problem that can explicitly account for the uncertainty in vehicle utilization. The Bellman approach is developed and implemented to solving the ERO SDP problem. Particular attention is paid to the SDP state-space growth and special scenario reduction techniques are developed to resolve the “curse of dimensionality” issue that is inherent to the dynamic programming method to ensure that the computer memory and solution computational time required will not increase exponentially with the increase in time horizon. SDP software computer implementation techniques, functionalities and the Graphical User Interfaces (GUI) are discussed. The developed SDP-based ERO software is tested and validated using the current Texas Department of Transportation (TxDOT) vehicle fleet data. Comprehensive numerical results, such as statistical analyses, the software computational time and solution quality, are described and substantial cost-savings have been estimated by using this ERO software. Finally, future research directions are also suggested. 
PDF icon fan_wei_gemar_brown_stochastic_dynamic_programming_2014_elsevier.pdf
M. Khan, Machemehl, R., and Zhang, Z., “

The Impact of Land-Use Variables on Free-floating Carsharing Vehicle Rental Choice and Parking Duration

,” Presented at the 2014 Workshops on Big Data and Urban Informatics at the University of Illinois, Chicago. 2014. Publisher's VersionAbstract
Carsharing is an innovative transportation mobility solution which offers the benefits of a personal vehicle without the burden of ownership. Free-floating carsharing service is a relatively new concept and is gaining popularity because it offers additional flexibility allowing one-way auto rental and charging users usage by minute. Traditionally, carsharing services require returning the rented vehicle to the same location where rented with a minimum rental duration. Since free-floating service is a very new addition in the overall transportation system, the empirical research is still very limited. This study focuses on identifying the impact of land-use variables on free-floating carsharing vehicle rental choice and parking duration of Car2Go services in Austin, Texas on a typical weekday between 9:00 AM to 12:00 PM. Two different methodological approaches, namely a logistic regression model approach and a duration model technique, are used for this purpose. The results of this study indicate that land-use level demographic variables, the carsharing parking policy, and numbers of transit stops effect the usage of free-floating carsharing vehicles.
M. Khan and Machemehl, R., “An Injury Severity Study of Bicycle-Motor Vehicle Crashes,” Presented in 93rd Annual Meeting of the Transportation Research Board. 2014.Abstract
This paper examines bicyclist injury severity in bicycle-motor vehicle crashes using the 2012 Texas Department of Transportation (TxDOT) Crash Records Information System (CRIS). Three different modeling frameworks are used: a binary logit, an ordered logit, and a multinomial logit model framework. All bike-motor crashes that involved a single motor vehicle and a single bicyclist are included. Three data sub-sets are examined to identify bike-motor crash risk factors and injury severity levels. These include all bike-motor vehicle crash data, only intersection related crashes and only non-intersection related crashes. Model results indicate that the common factors that affect all crashes include bicyclist and motor vehicle driver demographic characteristics, land use characteristics of the crash location, motor vehicle body type, and roadway speed limit. Motor vehicle driver age (age < 35 years), alcohol intoxication, and bicyclist age (age > 60 years) have larger effects on the bicyclist injury severity for intersection related crashes. Roadway speed (speed > 50 mph), road geometry (horizontal curve), and time of day have greater effects on bicyclist injury severity for non-intersection related crashes. Results of this study can help educate road users, improve traffic regulations, and also suggest roadway safety feature designs to enhance safety.
L. Wang, Kolahdoozan, S., Seedah, D. P. K., Leite, F., and Machemehl, R. B., “Risk Management Process for Very Short Duration Work Zone Operations”. Transportation Research Board, Washington, D.C., 2013.
L. Wang, Kolahdoozan, S., Seedah, D., Leite, F., and Machemehl, R. B., “Worker Safety in Very Short Duration Work Zone Operations: State of Practice and Risk Management Process,” 2013.Abstract
Very short duration maintenance operations (VSDOs) last for 15 minutes or less and usually involve operations such as removing an object from the roadway (either on the pavement or adjacent shoulder) or pothole patching. These activities have the potential to interrupt traffic flow and can pose a safety risk for both workers and drivers. Specific guidance for VSDOs is undocumented and workers tend to use their own judgment in making critical time sensitive decisions. Identifying risk factors in VSDOs helps maintenance workers better judge the immediate conditions and make more informed decisions on whether to conduct an operation as a VSDO or not. This study sought to define a VSDO and identify typical VSDOs. In addition, this study identified risk factors that maintenance workers may face during VSDOs. Moreover, this study prepared a list of technologies and methods for minimizing risk to workers in VSDOs. This study also presented a risk management process that enables maintenance workers to identify work zone hazards for VSDOs and improve their judgment about work zone conditions and hazards. Multiple scenarios illustrating the risks were presented, and related safety recommendations were also discussed.
M. Khan and Machemehl, R., “Evaluation of Potential Impacts of Alternative Vehicle Fuels on TxDOT Funding,” Center for Transportation Research, University of Texas at Austin, 2013. Publisher's VersionAbstract
This study presents an evaluation of the potential impacts on TxDOT revenues of substituting liquefied natural gas (LNG), compressed natural gas (CNG), and liquefied petroleum gas (LPG) for traditional diesel or gasoline vehicle fuels in Texas. Time series analyses are conducted for LNG, CNG, and LPG to estimate a model to forecast diesel and gasoline consumption for years 2012 to 2025. Taking into account the federal and state fuel taxes, the revenue generated from traditional fuel consumption is compared to three alternative fuel substitution scenarios. Overall, if the Federal and State excise tax rates remain at current levels the analysis suggests that substitution of LNG and LPG for traditional fuels will generate more revenue for the forecast years. However, substitution of CNG for gasoline consumption will reduce revenue if the Federal and State excise tax rates remain the same for the forecast years. 
PDF icon 0-6581-ct-task18.pdf
M. Motamed and Machemehl, R., “Traveler Path Choice during Freeway Closure,” 54th Annual Transportation Research Forum, TRF 2013. Annapolis, MD, 2013.Abstract
Construction activities and numbers of related work zones on urban freeways have grown significantly. The most problematic work zones occur on roads that are already fully loaded with traffic. The impact of work zones on mobility and safety makes success of the traffic control plan vital. Full freeway closures are sometimes implemented to expedite project completion and thereby reduce the cumulative impact of construction on travelers. Traffic diversion strategy is one way to improve the management of traffic and reduce user costs. An effective diversion plan makes drivers become aware of likely work zone delays and available alternate routes increasing the chances that they will choose alternate routes. Construction on the SH-71/IH-35 interchange required complete closure of all IH-35 main lanes. IH-35 is an important business corridor, conveniently connecting four large Texas cities, as well as, facilitating trade between Mexico and the United States. A parallel route, the SH-130 toll road, was made free to travelers during those closures. The purpose of this paper is to investigate driver route switching behavior during IH-35 closure and explore options for relieving delays on IH-35 during future closures. The Austin highway network was analyzed. However, usage of SH-130 was less than anticipated, and there was significant traffic queuing on IH-35 at the work zone. Analysis was based on integrating data from all available sources. In order to compare conditions of a non-closure weekend to the closure weekend, five recent months were considered.
Y. Yu and Machemehl, R. B., “Real Time Circulator Route Design Based on Destinations of Commuter Rail Passengers Using an Adaptive Tabu Search Algorithm,” Transportation Research Record, 2013.Abstract
Commuter rail systems, operating on unused or under-used railroad rights-of-way, are being introduced into many urban transportation systems. Since locations of available rail rights-of-way were typically chosen long ago to serve the needs of rail freight customers, the majority of commuter rail users do not live or work within walking distance of potential commuter rail stations. Minimizing access time to rail stations and final destinations is crucial if commuter rail is to be a viable option for commuters. This paper focuses on real time optimization of the Commuter Rail Circulator Route Network Design Problem (CRCNDP) supposing that real-time demand data can be obtained partially through users’ smart phone app. The route configuration of the circulator system – where to stop and the route among the stops – is determined on a real-time basis by employing adaptive Tabu Search to quickly solve a Mixed Integer Programming problem with an objective to minimize total cost incurred to both transit users and transit operators. Numerical experiments are executed and methodologies are proposed to find the threshold for the minimum fraction of travelers that would need to report their destinations via smart phone to guarantee the practical value of optimization based on real-time collected demand against a base case defined as the average performance of all possible routes.
J. Loskorn, Mills, A. F., Brady, J. F., Duthie, J. C., and Machemehl, R. B., “Effects of Bicycle Boxes on Bicyclist and Motorist Behavior at Intersections in Austin, Texas,” Journal of Transportation Engineering, 2013.Abstract
Provision of bicycle facilities at intersections is often inadequate and can lead to unsafe interactions between motorists and bicyclists. The bicycle box is a tool intended to improve the predictability of bicyclist stopping position at an intersection by allowing bicyclists utilizing a bicycle lane to position themselves in front of motorists during a red phase. The bicycle box in this application is meant to reduce the possibility of a right-hook collision, where a right turning motorist collides with a through moving bicyclist departing the intersection. The primary goal of this study was to determine what effect, if any, bicycle boxes have on bicyclist and motorist behavior. In 2009, 950 bicyclists were observed at two sites in three phases: existing conditions, after bicycle box markings were installed, and after a green colored pavement marking was added to the bicycle box and approaching bicycle lane. The predictability of bicyclists’ behavior improved based on the increased percentage of bicyclists who used the bicycle lane to approach the intersection, departed the intersection before motorists, and stopped in front of the motor vehicle queue. While only 20% to 26% of bicyclists stopped in the bicycle box area after installation of the bicycle box markings, over 90% of bicyclists stopped in front of motorists and were therefore more visible to motorists. The addition of the green pavement markings led to significant improvements in bicyclist behavior, but at a considerably higher material cost. Motorist encroachment on the bicycle box was common at both sites as well as illegal right turns on red at one site. No bicycle-motorist collisions were observed during any stage of the study. Read More:
W. Fan, Gemar, M. D., and Machemehl, R. B., “Equipment Replacement Decision Making: Challenges and Opportunities”. 2013.Abstract
This paper uses a genetic algorithm to systematically examine the underlying characteristics of the optimal bus transit route network design problem BTRNDP with variable transit demand. A multiobjective nonlinear mixed integer model is formulated for the BTRNDP. The proposed solution framework consists of three main components: an initial candidate route set generation procedure ICRSGP that generates all feasible routes incorporating practical bus transit industry guidelines; and a network analysis procedure NAP that decides transit demand matrix, assigns transit trips, determines service frequencies, and computes performance measures; and a genetic algorithm procedure GAP that combines these two parts, guides the candidate solution generation process, and selects an optimal set of routes from the huge solution space. A C++ program code is developed to implement the proposed solution methodology for the BTRNDP with variable transit demand. An example network is successfully tested as a pilot study. Sensitivity analyses are performed. Comprehensive characteristics underlying the BTRNDP, including the effect of route set size, the effect of demand aggregation, and the redesign of the existing transit network issue, are also presented.
C. L. Melson, Boyles, S. D., and Machemehl, R. B., “Modeling the Traffic Impacts of Transit Facilities Using Dynamic Traffic Assignment,” TRB Annual Meeting. Transportation Research Board, Washington, D.C., 2013.Abstract
This paper demonstrates the capabilities and benefits of using dynamic traffic assignment (DTA) to analyze traffic impacts caused by transit services. The City of Austin’s proposed urban rail system is used as a case study. The urban rail connects the CBD, the University of Texas at Austin campus, and other large traffic generators. The majority of the rail system shares right-of-way with traffic. However, several segments have completely dedicated guideway. Previous analyses have focused either on microsimulation (which is limited in spatial area and does not consider route choice changes) or regional planning (which typically lacks detailed inputs and does not directly model transit impedances in the traffic assignment process). DTA provides a connection between these two methods: it can model route choice behavior using realistic inputs at a fine time scale across a large spatial area. Five scenarios with varying mode split percentages were modeled. At low ridership levels, corridors with major geometric modifications experienced more congestion. This caused travel pattern changes, increasing the volume on nearby parallel corridors.
J. Duthie, Machemehl, R. B., and Mills, A. F., “Entry-Lane Capacity Analysis of Roundabouts in Texas Using VISSIM, SIDRA, and the Highway Capacity Manual”. 2012.Abstract
K. Kortum and Machemehl, R. B., “Free-floating Carsharing Systems: Innovations in Membership Prediction, Mode Share, and Vehicle Allocation Optimization Methodologies”. Southwest Region University Transportation Center, Center for Transportation Research, University of Texas at Austin, 2012. Publisher's VersionAbstract
Free-floating carsharing systems are among the newest types of carsharing programs. They allow one-way rentals and have no set “homes” or docks for the carsharing vehicles; instead, users are permitted to drive the vehicles anywhere within the operating zone and leave the vehicle in a legal parking space. Compared to traditional carsharing operations, free-floating carsharing allows much greater spontaneity and flexibility for the user. However, it leads to additional operational challenges for the program. This report provides methodologies for some of these challenges facing both free-floating and traditional carsharing programs. First, it analyzes cities with carsharing to determine what characteristics increase the likelihood of the city supporting a successful carsharing program; high overall population, small household sizes, high transit use, and high levels of government employment all make the city a likely carsharing contender. Second, in terms of membership prediction, several modeling alternatives exist. All of the options find that the operating area is of key importance, with other factors (including household size, household densities, and proportion of the population between ages 20 and 39) of varying importance depending on the modeling technique. Third, carsharing trip frequencies and mode share are of value to both carsharing and metropolitan planning organizations, and this report provides innovative techniques to determine the number of trips taken and the share of total travel completed with carsharing (both free-floating and traditional). Fourth and finally, an original methodology for optimizing the vehicle allocation issue for free-floating carsharing organizations is provided. The methodology takes a user input for the total number of vehicles and returns the allocations across multiple demand periods that will maximize revenue, taking into account the cost of reallocating vehicles between demand periods. Keywords: Carsharing; Cars2Go; Binary Logit Metropolitan Modeling; Mode Share Modeling
A. R. Haire, “A methodology for incorporating fuel price impacts into short-term transit ridership forecasts,” 2012.Abstract
W. (D. ) Fan, Machemehl, R. B., and Gemar, M. D., “Optimization of Equipment Replacement,” Transportation Research Record: Journal of the Transportation Research Board, vol. 2292, pp. 160–170, 2012.Abstract
K. R. Persad, Machemehl, R., Weatherby, C., Stockton, W., Nash, P., and Cleveland, T., “Seven TxDOT Strategic Research Briefs for FY 2011”. 2012.Abstract