Urban Mobility & Equity Center

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The Urban Mobility & Equity Center (UMEC) focuses on research to improve urban mobility of people and goods in an environmentally sustainable and equitable manner. Based at Morgan State University, UMEC includes the University of Maryland and Virginia Polytechnic Institute and State University (Virginia Tech).

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    Fare Free Public Transportation: A full-scale, real-world experiment in Alexandria (VA)
    (2023-08) Cirillo, Cinzia; Tabrizi, Asal Mehdi; Rakha, Hesham; Du, Jianhe; Urban Mobility & Equity Center
    The Fare Free Public Transportation (FFPT) concept is a common part of the agenda among transit agencies and state and federal policy makers. The subject is particularly important in the post-pandemic period, as transit use is slowly recovering but has not yet reached pre-pandemic ridership and market share. FFPT has been implemented in Europe and to a certain degree in the USA; however, there are very few studies that have effectively collected data and evaluated the consequences with respect to its implementation. This study monitored a full-scale, real-world FFPT plan implemented in Alexandria, VA in the Fall of 2021, separating respondents into treatment and control groups. Descriptive statistics indicated minimal disparity between the treatment and control groups across most socio-demographic variables. Notably, residents of Alexandria exhibit a higher propensity to use buses compared to the control group, both prior to and post-policy implementation. Regarding awareness of the policy, a majority of respondents were uninformed, while the policy's impact is more pronounced among those who were aware. Around 32% of respondents increased their bus usage following FFPT implementation, with approximately 80% of this subset utilizing buses more frequently than before. This policy evaluation is relevant not only to Alexandria, but to many stakeholders across the country that are considering similar policies in other cities.
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    A Knowledge-Based Expert System for Pedestrian Safety Improvement at Intersections
    (2023-06-01) Chang, Gang-Len; Chan, Yam Ting; Cheng, Yao; Urban Mobility & Equity Center
    In response to the rising concerns about intersection safety across the United States, traffic administrators have developed various techniques to create more effective and targeted improvement projects. Among them, Knowledge-Based Expert Systems (KBESs) demonstrate the unique advantage of having low requirements for users' experience and efficient decision-making. Recognizing that existing KBESs often lack comprehensive analysis of the critical factors contributing to pedestrian-involved crashes and the capability to optimize countermeasure selection, this study proposes an enhanced KBES to assist the traffic community in efficiently generating a set of optimal cost-benefit countermeasures to address pedestrian safety risks at intersections. In the proposed KBES, the carefully designed knowledge acquisition process fills two knowledge bases: one containing well-evidenced cause-effect relationships between contributing factors and corresponding Safety Related Intersection Characteristics (SRICs), and the other storing various attributes of a comprehensive list of countermeasures. The first developed inference engine is capable of identifying the contributing factors at an intersection and innovatively quantifying the impact of each of them based on the user input of SRICs. The second inference engine optimizes the countermeasure selection to maximize the expected effectiveness in accurately targeting the impact of those contributing factors while accounting for both budget constraints and users' defined priorities among the countermeasures' attributes. The results of the performance evaluation indicate that the proposed KBES is effective in analyzing contributing factors and recommending countermeasures and can serve as an efficient tool for traffic engineers to develop safety improvement projects at intersections
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    E3: EVALUATING EQUITY IN EVACUATION: A PRACTICAL TOOL AND A CASE STUDY
    (2020-02) Cirillo, Cinzia; Nejad, Mohammad; Erdogan, Sevgi; Urban Mobility & Equity Center; USDOT University Transportation Centers Program
    Natural or man-made hazards that require evacuation put already vulnerable populations in a more precarious situation. When plans and decisions about evacuation are made, access to a private car is typically assumed, and differences in income levels across a community are rarely taken into account. The result is that carless members of a community can find themselves stranded. Low-income carless residents need alternative transportation means to reach shelters in case of an emergency. Thus, evacuation plans, decisions, and models need necessary information that identifies and locates these populations. In this study, data from the American Community Survey, U.S. Census, Internal Revenue Service, and the National Household Travel Survey are used to generate a synthetic population for Anne Arundel County, Maryland, using the copula concept. Geographic locations of low-income residents are identified within each subarea of the county (census tract) and their car ownership is estimated with a binomial logit model. The developed population synthesis method allows officials to have a more accurate account of populations for emergency planning and identify locations of shelters and triage points as well as planning carless transportation services.
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    Investigating the Impact of Distracted Driving among Different Socio-Demographic Groups
    (2019-12) Jeihani, Mansoureh; Ahangari, Samira; Hassan Pour, Arsalan; Khadem, Nashid; Banerjee, Snehanshu; Urban Mobility & Equity Center
    Previous studies examined the detrimental impact of distracted driving on safety; however, the effect of different types of distraction accompanied by different road classes has not been investigated. This study used a high-fidelity driving simulator and an eye-tracking system to examine the driving behavior of young participants while engaged in various in-vehicle distractions - no cell phone, handsfree call, hand-held call, voice commands text, text, taking on or off clothing, and eating or drinking - on different road classes: rural collector, freeway, urban arterial, and local road in a school zone; and with an out-of-vehicle billboard distraction. Some 92 participants drove a simulated network in the Baltimore Metropolitan Area with seven scenarios (one base scenario without any distraction and six different types of distractions). Participants also completed questionnaires documenting demographics and driving behavior before and after the driving simulator experience. The descriptive and statistical analysis of in-vehicle distractions revealed how they negatively impact safety: Participants exhibited greater fluctuations in speed, changed lanes significantly more times, and deviated from the center of the road when they were distracted while driving. The results indicated that drivers reduced their speed by up to 33% while distracted with hands free/voice command cell phone usage, which is inconsistent with the current cell phone usage policies in most states. The highest speed reduction happened on the local road when taking on/off clothing (50%), voice command texting (33%), and texting (29%). Visibility and gender significantly affected gaze fixation duration on billboards. Female participants had lower gaze fixation duration than their male counterparts on billboards, while males had less gaze fixation duration on the phone than female. The billboard with a lower cognitive load had less gaze fixation duration than the one with a higher cognitive load.
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    Innovative Methods for Delivering Fresh Foods to Underserved Populations
    (2019-12) Shin, Hyeon-Shic; Schonfeld, Paul; Lee, Young-Jae; Urban Mobility & Equity Center
    Limited access to fresh food sources--ones within reasonable distances with reliable, affordable transportation--has become a public health concern. The negative associations between a lack of fresh food consumption and health are well known. Because certain demographic groups are disproportionately affected by the absence of stores selling healthy and affordable food, equity issues result. Many inner-city residents are left in neighborhoods devoid of such stores, and every day they are forced to trade off increased costs against healthy food consumption and health. This study aimed to develop a cost-effective last-mile fresh food delivery system to households in food deserts, which could help improve fresh food accessibility. Six alternative delivery modes--conventional trucks, e-bikes, shared-ride transit, parcel lockers, pop-up stores, and independently contracted drivers--were identified and optimized by employing Traveling Salesman Problem. Then we compared the results with the system's total costs. Sensitive analyses were conducted in terms of the time of delivery, zone size, user's value of time waiting for goods, the optimal number of lockers, costs associated with combined deliveries at lockers as well as customer addresses, and a second delivery attempt. Building on optimized modes, GIS network analyses were performed for randomly selected household locations in parts of poverty-prone West Baltimore. Numerical results showed that deliveries by trucks are the most cost-effective alternative, while the third-party deliveries ranked second. The two most expensive alternatives were shared-ride service and e-bike deliveries, based on the estimated costs of providing them.
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    Optimized Development Of Urban Transportation Networks
    (2019-05-30) Schonfeld, Paul; Urban Mobility & Equity Center
    This report presents improved methods for planning and scheduling interrelated improvements in transportation networks. Due to the complexity of the relevant evaluation functions, which cannot be optimized with classical calculus techniques, the proposed methods rely on customized genetic algorithms for optimizing the selection, sequencing and scheduling of the interrelated alternatives. Three applications to urban transportation networks are presented in journal papers which are included in appendices. The papers demonstrate the applicability of the proposed methods to urban road networks, to intersections in urban road networks and to the development of urban rail transit networks.
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    Developing and Testing an ECO-Cooperative Adaptive Cruise Control System for Buses
    (2020-03-31) Rakha, Hesham; Chen, Hao; Jeihani, Mansoureh; Ahangari, Samira; Urban Mobility & Equity Center
    Studies over the past decade have shown that eco-driving systems which provide speed advisories to drivers/vehicles using data received via vehicle-to-infrastructure and vehicle-to-vehicle communications can help improve traffic mobility and reduce vehicle energy and emission levels. This study extends the Eco-Cooperative Adaptive Cruise Control (Eco-CACC) system previously developed for light duty vehicles to heavy duty vehicles (diesel and hybrid electric buses). First, the energy consumption models for diesel and hybrid buses are discussed and the field data collected by Blacksburg Transit are used to calibrate bus models. Thereafter, the bus Eco-CACC system is developed by incorporating the vehicle dynamic model and energy consumption model for buses. The developed Eco-CACC system has manual and automated modes to control buses. The manual Eco-CACC mode was tested by participants using driving simulators at Morgan State University under various scenarios that included different types of information. In addition, the automated bus Eco-CACC system was tested using the INTEGRATION microscopic simulation software to quantify the system-wide impacts of the proposed system under various traffic demand and vehicle types. The test results demonstrated that the proposed system could improve transit operations by reducing delay and helping transit agencies save on energy costs, resulting in an improved transit level of service, increased ridership, and improved traffic mobility.
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    Evaluating Equity Issues for Managed Lanes: Methods for Analysis and Empirical Results
    (2019-03) Cirillo, Cinzia; Bas Vicente, Javier; Urban Mobility & Equity Center
    Transportation planning decisions can have significant and diverse equity impacts (Litman, 2002). In particular, congestion and road pricing have raised equity concerns. Notably, the toll imposed on Managed Lanes on US highways affects drivers’ income. This is especially true for low-earning individuals, who devote a large portion of their available budget to transportation. Therefore, any policy or project assessment should take into consideration the so-called Income Effect. This concept refers to the fact that the impact of a change in driving cost – for instance, a toll increase – is not constant for all individuals but depends on their own income level. Unfortunately, the two measures most commonly used in project evaluation practice, Rule of a Half (RoH) and Log-sum (LS), rely on the assumption of absence of Income Effect. Since microeconomic theory does not support these grounds, not to account for income effect in policy evaluation may produce inaccurate results. Applying a policy for which the economic impact is not well-assessed may lead to severe equity issues. This project proposes a methodology that accounts for income effect in the appraisal of Managed Lanes and calculates the errors due to the use of approximated methods. In particular, the analysis is based on three pillars: i) the use of real data, ii) the use of more realistic assumptions about drivers’ behavior, considering different income levels and correlations between the alternatives, and iii) comparison of the LS and RoH and LS to the Compensating Variation (CV), the true benefit measure derived from microeconomic theory. These improvements provide a refined tool for the appraisal of the social, economic and equity aspects of transportation policy in the context of Managed Lanes. The tool will benefit private entities involved in road pricing projects, and transportation public agencies in need of ameliorating their evaluation of equity issues.
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    Dynamic (Time Dependent) Green Vehicle Routing Problem
    (2019-03-15) Haghani, Ali; Amoli, Golnush Masghati; Pternea, Moschoula; Department of Civil and Environmental Engineering, University of Maryland; University Transportation Centers Program
    This research summarizes recent studies on two versions of the Vehicle Routing Problem, i.e., the time-dependent vehicle routing problem (TD-VRP) and the green vehicle routing problem (G-VRP), for which a time-dependent version is also developed. A new formulation of TD-VRP is proposed that can deal with the time-dependent vehicle routing problem with dynamic demand information and provide the minimum cost routing plan. We also introduce a special case of G-VRP with a mixed fleet of heterogeneous electric and internal combustion engine commercial vehicles. Two different formulations are proposed to solve two different variants of the problem. A constructive heuristic is defined to generate initial feasible solution to the problem. The initial solution is further improved by deconstructing a large part of it and then, rebuilding it with the constructive heuristic. This algorithm is preferred over the local search algorithms as it provides better solutions due to the diversification effect embedded in it by deconstructing a large part of the solution. The results of the implementation of the proposed modes in a number of test problems and a large case study are also presented.
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    Sustainable Design of Concrete Bus Pads to Improve Mobility in Baltimore City
    (2019-03-02) Aslan, Kadir; Shokouhian, Mehdi; Civil Engineering; Urban Mobility & Equity Center
    Public transit, particularly buses in Baltimore City, plays a vital role in sustainable transportation in the United States as well as providing mobility to those without cars. Bus pads are usually constructed in the street, adjacent to a bus zone, to accommodate the weight of a bus. Bus pads are highly durable areas of the roadway surface at bus stops, usually made of concrete, addressing the common issue of asphalt distortion at bus stops. These concrete slabs bear the burden of the daily stream of buses better than asphalt. The major problem with the asphalt bus pads is shifting asphalt creating waves or ripples under buses’ weight, and when asphalt shifts, it cracks and can create potholes. Roadway pavements need to be strong enough to accommodate repetitive bus axle loads. Exact pavement designs will depend on site specific soil conditions. Areas where buses start, stop, and turn will be of particular concern for pavement design. Concrete pavement is desirable in these areas to avoid the failure problems that are experienced with asphalt. Concrete bus pads should be constructed based on the bus service frequency and type of transit vehicle used. However, if the concrete bus pad is not properly designed, it will encounter different problems with serviceability and strength of the slab. During a case study in Baltimore City that was used to collect preliminary data for the proposed research, it was observed that most of the concrete bus pads require more than regular routine maintenance due to surface cracks and local failure, resulting in major replacement costs for Baltimore City. Lack of appropriate load identification and definition of critical load scenarios for the appropriate design of the concrete bus pad were noted as shortcomings in addition to the design assumption of uniform distribution of soil pressure under the concrete slab, which was not the case noted in the field. This research carried out a field study and extracted two concrete strips in longitudinal and transverse axis from a bus pad in Baltimore. The concrete strips were tested at the Structures Laboratory of Morgan State University, under a four-point bending produced by two concentrated monotonic loads. The load and deflection were measured using precise instruments including LVDTs and load cells to investigate the concrete strips’ performances under the applied load until failure. All load cases and combinations were identified and determined based on possible loading scenarios. A numerical model was developed and soil-structure interaction was studied using the Winkler method. The maximum design forces and moments were extracted from the FE model, which considers the effect of moving loads on a two-way slab as well as the temperature. This research evaluated the load-bearing capacity of the current design of Baltimore bus pads and compared it to the tested strips as well as the required bending capacity of FE models. Results show that both design and construction of bus pads in Baltimore need to be modified. In conclusion, design and construction recommendations were proposed to enhance bus pads’ life span in Baltimore City to address the current issues and reduce maintenance costs.
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    Optimal Automated Demand Responsive Feeder Transit Operation and Its Impact
    (2018-09) Lee, Young-Jae; Nickkar, Amirezza; Urban Mobility & Equity Center; University Transportation Centers Program
    Although demand responsive feeder bus operation is possible with human-driven vehicles, it has not been very popular and mostly available as a special service because of the high operating costs due to the intensive labor costs as well as advanced real-time information technology and complicated operation. However, once automated vehicles become available, small-sized flexible door-to-door feeder bus operation will become more realistic, thanks to recent technological advances and business innovations by the transportation network companies (TNCs). So, preparing for the automated flexible feeder service is necessary to catch the rapid improvement of automated vehicle technology. Therefore, this research developed an algorithm for the optimal flexible feeder bus routing, which considers relocation of buses for multi-stations and multi-trains, using a simulated annealing (SA) algorithm for future automated vehicle operation. An example was developed and tested to demonstrate the developed algorithm. The algorithm successfully handled relocating the buses when the optimal bus routings were not feasible with the available buses at certain stations. Furthermore, the developed algorithm limited the maximum Degree of Circuity for each passenger while minimizing total cost, including total vehicle operating costs and total passenger in-vehicle travel time costs. Unlike fixed route mass transit, small vehicle demand responsive service uses flexible routing, which means lower unit operating costs not only decrease total operating costs and total costs but also can affect routing and impact network characteristics. In the second part of this research, optimal flexible demand responsive feeder transit networks were generated with various unit transit operating costs using the developed routing optimization algorithm. Then network characteristics of those feeder networks were examined and compared. The results showed that when unit operating costs decline, total operating costs and total costs obviously decline. Furthermore, when unit operating costs decline, the average passenger travel distance and total passenger travel costs decline while the ratio of total operating costs per unit operating costs increases. That means if unit operating costs decrease, the portion of passenger travel costs in total costs increases, and the optimization process tends to reduce passenger costs more while reducing total costs. Assuming that automation of the vehicles reduces the operating costs, it will reduce total operating costs, total costs and total passenger travel costs as well.