Arash M. Roshandeh

New Methodology for Intersection Signal Timing Optimization to Simultaneously Minimize Vehicle and Pedestrian Delays

This study introduces a new methodology for signal timing optimization that is carried out by adjusting green splits of a.m. peak, p.m. peak, and rest of the day timing plans for each signalized intersection in the urban street network without changing the existing cycle length and signal coordination to minimize total vehicle and pedestrian delays per cycle. It contains a basic model that handles vehicle delays only and an enhanced model that simultaneously addresses vehicle and pedestrian delays using two different pedestrian delay estimation methods. Both models are incorporated into a high fidelity simulation-based regional travel demand forecasting model for detailed traffic assignments. A computational study is performed for methodology application using data on Chicago metropolitan area travel demand, traffic counts, geometric designs, and signal timing plans for major intersections in the Chicago central business district (CBD) area. A sensitivity analysis is conducted in the application of the enhanced model to examine the impacts of assigning different weights to vehicle and pedestrian delays on intersection vehicle travel time and delay reductions after signal timing optimization. The computational experiment reveals that after systemwide signal timing optimization, vehicle delays in the CBD area could reduce by 13% when considering only vehicle delays and by 5% when simultaneously considering vehicle and pedestrian delays.

Impacts of Signal-Related Characteristics on Crash Frequency at Urban Signalized Intersections

The effect of signals at urban intersections is critical in reducing death, injuries, and property loss. Unfortunately, the signal-related factors that can effectively reduce crash frequencies have not been adequately explored. This study investigates the impacts of signal-related, traffic, and highway geometric characteristics on crash frequency at urban signalized intersections. Seven-year crash data from 381 intersections in Illinois, United States of America, was used to estimate a random-parameters negative binomial model. The estimation results showed that a unit increase in the number of signal phases would increase crash frequency by 0.4. Additionally, the ratio of traffic volume on the major road to the traffic volume on the minor road was shown to unambiguously increase crash frequency. On the other hand, the number of approach lanes and the maximum green time of different approaches in a signal revealed an ambiguous effect, whereas increasing crash frequency on 76.33%, and 93.32% and decreasing it on the remaining 23.67%, and 6.68% of the signalized intersections, respectively. Although, this study is exploratory in nature, the results showed that ignoring these factors at urban signalized intersections would lead to the design of ineffective safety-related countermeasures, and the impacts could be underestimated by 5% to 25%.

Safety Impacts of Push-Button and Countdown Timer on Nonmotorized Traffic at Intersections

This paper applies the random parameters negative binominal model to investigate safety impacts of push-button and countdown timer on pedestrians and cyclists at urban intersections. To account for possible unobserved heterogeneity which could vary from one intersection to another, random parameters model is introduced. A simulation-based maximum likelihood method using Halton draws is applied to estimate the maximum likelihood of random parameters in the model. Dataset containing pedestrians’ and cyclists’ crash data of 1,001 intersections from Chicago is utilized to establish the statistical relationship between crash frequencies and potential impact factors. LIMDEP (Version 9.0) statistical package is utilized for modeling. The parameter estimation results indicate that existence of push-button and countdown timer could significantly reduce crash frequencies of pedestrians and cyclists at intersections. Increasing number of through traffic lanes, left turn lanes, and ratio of major direction AADT to minor direction AADT, tend to increase crash frequencies. Annual average daily left turn traffic has a negative impact on pedestrians’ safety, but its impact on cyclists’ crash frequency is statistically insignificant at 90% confidence level. The results of current study could provide important insights for nonmotorized traffic safety improvement projects in both planning and operational levels.

Heuristic Approach for Optimizing Emergency Medical Services in Road Safety within Large Urban Networks

Emergency medical service (EMS) providers participating in vehicle crash-induced incident management aim to offer as wide and efficient coverage as possible to meet the demand for incident responses effectively; however, the design and provision of efficient and cost-effective services are tough issues faced by emergency management authorities. This paper introduces a double standard model (DSM), along with a genetic algorithm (GA) for assigning EMS fleet from vehicle locations to intersection vehicle crash sites such that crash demand sites can be covered in accordance with two service coverage standards. Specifically, all demand sites are required to receive single coverage according to the secondary coverage standard and at least a portion (α) of demand sites need to maintain single coverage as per the primary coverage standard. The proposed model is applied for top 200 intersections in the City of Chicago selected using intersection crash records for 2004-2010 according to crash frequency-based and severity-based scenarios. The top 200 intersections are split into high and low severity sites for model application. Using the EMS vehicle fleet size currently maintained by the Chicago Fire Department as 15 basic life support (BLS) and 60 advanced life support (ALS) ambulances, almost 100% of double vehicle coverage can be achieved. Extended model application is conducted by keeping 15 BLS ambulances unchanged and reducing the 60 ALS ambulances by 50% to 30. Results show that nearly 90% of double coverage according to the primary standard can still be reached.

Risk-Based Two-Step Optimization Model for Highway Transportation Investment Decision-Making

A new methodology is introduced for project selection that explicitly addresses issues of achieving maximized overall project benefits by selecting a subcollection of candidate projects for possible implementation at a given budget level while controlling the total risk of the expected project benefits within an acceptable lower bound. The covariance value is utilized to denote the risk of the expected benefits of jointly implementing two projects, in which each project maintains a range of possible benefits and a probability distribution. The summation of all covariance values corresponding to all possible project implementation combinations represents the total risk of the expected benefits. The methodology contains two-step optimizations. First, the Markowitz mean-variance model is employed to establish the lower-bound risk of project benefits for a given budget level. Second, the conventionally accepted zero/one knapsack model for project selection is augmented to incorporate the lower-bound risk established from the first-step optimization as one additional chance constraint. In this way, the overall benefits of projects selected for implementation are maximized while controlling the total risk of the expected project benefits within a lower bound for a certain percentage of time. The proposed model is applied for a 6-year statewide interstate highway project selection and programming. Cross comparisons are made in the consistencies of project selection results generated from the basic knapsack model, proposed two-step enhanced knapsack model, and current state highway programming practice.

Optimal Decision Making of Interdependent Tollway Capital Investments Incorporating Risk and Uncertainty

A new methodology is proposed to address issues of networkwide effects of highway projects and interdependencies of jointly implementing multiple projects to support optimal investment decisions. Specifically, a multicommodity minimum cost network (MMCN) model is introduced to help obtain link-based traffic volumes, vehicle compositions, and speeds for a highway network that could be used for project benefit estimation using life cycle cost analysis approaches. A hypergraph knapsack model is formulated to identify the best subcollection of interdependent projects to achieve maximized overall benefits for a given budget level. A computational study is conducted using the proposed methodology for tollway capital investment decision making. It is revealed that the overall project benefits with risk and uncertainty considerations for facility construction and treatment costs, traffic forecasts, and the discount rate are significantly lower than the estimated project benefits without risk and uncertainty considerations. In addition, project interdependencies are found to exist for all joint project implementation scenarios. With the continuing growth of budget levels, the overall benefits of projects selected for implementation using the hypergraph knapsack could reach a maximum, beyond which no extra benefits could be obtained. The methodology may be adopted by state and local transportation agencies and metropolitan planning organizations to enhance investment decisions.

Trade-Off Analysis Approach for Multiobjective Transportation Investment Decision Making

AbstractTransportation planning is multidimensional, complex, and dynamic in nature. The decision-making process often involves multiple stakeholders with conflicting preferences. Effective decision outcomes can only be reached by explicitly addressing such conflicts. Over the last several decades, optimization techniques have been used for project-selection decisions to achieve maximized overall returns on investments. The existing methods for project selection capable of conducting trade-off analyses mainly focus on assessing trade-offs between project construction time, duration, and cost, as well as swapping between transportation agency costs and user costs. However, they have largely not addressed impacts on the overall economic returns by changing a few important decision factors such as differentiating relative importance of various transportation performance goals and measures, and different types of highway facilities, and further relaxing the budget constraints by management programs dealing wi...

Impact of HB‐1481 on Indiana’s Highway Revenue Generation, Asset Degradation, Modal Distribution, and Economic Development and Competitiveness

The Indiana House Enrolled Act 1481 (HEA-1481) requires that the Indiana Department of Transportation (INDOT) delivers the HEA-1481 study by December 31, 2014. This will precede the adoption of final rules for the issuance, fee structure, and enforcement of permits for overweight divisible loads; a fee structure of permits for loads on extra heavy duty highways; and a fee structure of permits for overweight loads. On December 26, 2013, INDOT adopted the Emergency Rules regarding these items, as required by HEA-1481, which became effective January 1, 2014. HEA-1481 requires INDOT to use the results of this impact study to inform the setting of the final rules. Three different fee structures were considered: Pre-HEA-1481 fee structures were in place prior to HEA-1481; Interim Policy fee structures that were in place between June 1, 2013 and December 31, 2013; and the Emergency Rules that took effect January 1, 2014 and superseded the above two fee structures. INDOT commissioned this study to evaluate the impacts of overweight divisible load permits on revenue, asset consumption, alternative transportation modes, and Indiana’s economic development and economic competitiveness relative to other Midwestern states. The results of the analysis indicate that overall, the overweight commodities divisible permit structure arising from HEA-1481 is not expected to dramatically change the consumption of Indianas pavement and bridge assets, but it will lead to a slight increase in the revenue collected per permit and a slight decrease in the gap between consumption and revenue. However, the gap between revenue and consumption is still significant: for the pre-HEA-1481 and the Emergency Rules periods, the consumption-revenue gaps were estimated as approximately

Geographic Information System Tool for Enhancing Administration of Overweight-Vehicle Permits

33 million and

Safety impacts of red light running photo enforcement at urban signalized intersections

30 million, respectively. From an operations standpoint of mobility and safety, it was estimated that HEA-1481 will have an ambiguous impact due to the twin but opposing effects of traffic impairment and trips reduction associated with overweight vehicles; the net effect depends on the prevailing characteristics of the traffic stream and extent of overweight loading. Also using the Federal Highway Administrations (FHWAs) Intermodal Transportation and Inventory Cost (ITIC) analysis tool, it was found that HEA-1481 will lead to little or no shift in the modal share across truck and rail, but a significant shift across the specific configurations of vehicles used in trucking operations. HEA-1481 is expected to increase the economic competitiveness of trucking operations in Indiana compared to the pre-HEA 1481 era, and in some cases, compared to other Midwestern states. Finally, HEA-1481 is expected to increase economic development at least in the long term by reducing the cost of transporting commodities by highways, an essential expenditure item of many major businesses in Indiana. Overall, HEA-1481 is expected to help protect the highway bridge and pavement infrastructure by providing incentives for less-damaging loading behavior, reduce the gap between revenue and consumption, increase the economic competitiveness of trucking operations relative to other states, and provide a more industry-friendly environment for increased economic development in the state of Indiana.