Effective Transportation Planning Research Articles

Using Spatial Modeling for Identifying Determinants Influencing Crash Estimate: Case Study of Hamedan, Iran

Road crashes are a major cause of fatalities worldwide, posing significant challenges for road-safety experts in selecting appropriate crash-frequency estimation models. This study introduces localized safety performance functions (C-SPFs), which explore the spatial variation of crash frequency and the spatial correlation between dependent variables. The exploratory spatial regression method is employed to identify optimal spatial associations. The study further predicts crashes using geographically weighted Poisson regression (GWPR) and generalized Poisson regression. Results indicate that C-SPFs offer greater accuracy than do models calibrated solely on annual average daily traffic. Moreover, the proposed model is especially relevant for jurisdictions facing higher heavy-vehicle traffic and frequent crashes. The development of C-SPFs and the use of GWPR provide valuable tools for policymakers and road-safety experts in enhancing crash-frequency estimation accuracy. Implementing these techniques can aid in prioritizing safety measures and countermeasures, especially in regions with significant heavy-vehicle traffic and crash occurrences. Additionally, the integration of spatial-analysis techniques and localized models can lead to more effective transportation planning and targeted road-safety interventions, ultimately contributing to reducing the burden of road crashes on a global scale.

Automated Traffic Surveillance Using Existing Cameras on Transit Buses.

Millions of commuters face congestion as a part of their daily routines. Mitigating traffic congestion requires effective transportation planning, design, and management. Accurate traffic data are needed for informed decision making. As such, operating agencies deploy fixed-location and often temporary detectors on public roads to count passing vehicles. This traffic flow measurement is key to estimating demand throughout the network. However, fixed-location detectors are spatially sparse and do not cover the entirety of the road network, and temporary detectors are temporally sparse, providing often only a few days of measurements every few years. Against this backdrop, previous studies proposed that public transit bus fleets could be used as surveillance agents if additional sensors were installed, and the viability and accuracy of this methodology was established by manually processing video imagery recorded by cameras mounted on transit buses. In this paper, we propose to operationalize this traffic surveillance methodology for practical applications, leveraging the perception and localization sensors already deployed on these vehicles. We present an automatic, vision-based vehicle counting method applied to the video imagery recorded by cameras mounted on transit buses. First, a state-of-the-art 2D deep learning model detects objects frame by frame. Then, detected objects are tracked with the commonly used SORT method. The proposed counting logic converts tracking results to vehicle counts and real-world bird's-eye-view trajectories. Using multiple hours of real-world video imagery obtained from in-service transit buses, we demonstrate that the proposed system can detect and track vehicles, distinguish parked vehicles from traffic participants, and count vehicles bidirectionally. Through an exhaustive ablation study and analysis under various weather conditions, it is shown that the proposed method can achieve high-accuracy vehicle counts.

A composite index for assessing accessibility in urban areas: A case study in Central Athens, Greece

Effective transportation planning necessitates the consideration of all road network users and their needs. Towards this goal, the integration of accessibility in planning and the development of tools that enable the assessment and measurement of accessibility within urban areas becomes essential. This study aims to contribute to the accessibility assessment process of urban areas by developing two accessibility indices: the infrastructure and the opportunity accessibility index, which use an infrastructure-based and distance-based approach, respectively. Four types of users and their needs are considered: pedestrians, People with Disabilities (PWD), cyclists and public transport users. Data for modeling the accessibility indices are collected by: 1) an infrastructure audit, 2) a user survey, and 3) geographic information systems. The proposed method is applied in a district in central Athens, Greece, which is characterized by high population density and high level of activities. The Infrastructure Accessibility Index (IAI) measures accessibility for sidewalks, crosswalks, bikeways and public transport stops. The IAI results indicate moderate accessibility levels for pedestrians and PWD, for sidewalks and crosswalks. The Opportunity Accessibility Index (OAI) measures the share of different types of users that reach different opportunities within a time threshold. The accepted time threshold per user type is estimated based on the survey responds, for seven different opportunities: green spaces, recreational spaces, education buildings, health buildings, public service building, commercial uses and public transport stops. Compared to the IAI, the majority of users reach different opportunities within the estimated time threshold. The study concludes with recommendations to improve accessibility levels at local level.

Investigating and Weighing the Importance of Transport Mode Choice Factors: Dry-Cargo Shipping. A Case of Malawi

Understanding the transport mode choice factors that are important to the commodity shippers is one of the important key aspects to consider when aiming for efficient and effective transport planning. Over the years, several studies have been conducted in other countries trying to establish the factors that influence commodity shippers’ decisions when choosing transport modes. While these factors have been unearthed, little is known about how these factors are prioritized in shipping decisions. This study therefore aimed to investigate the factors that influence transport mode choices and also examine how shippers weigh and rank these factors with regard to their importance. A descriptive research design within quantitative methodology was employed. Using a simple random sampling technique, 84 participants were recruited for this study. The findings of the study revealed that shipment travel time, transport cost, transport mode availability, and transport service reliability have an influence on how shippers choose a transport mode for their shipments. The study further revealed that transportation cost was the ranking transport modal choice factor among the factors. It was therefore recommended that the government should consider revitalising low-cost rail transportation to make it more efficient and responsive to shippers’ demands.

Estimation of the origin-destination matrix from national road traffic data in Central Java Province using the least squares method

Central Java Province has experienced increased movement due to economic, social, and cultural developments. This increased activity has caused transportation problems, highlighting the need for effective transportation planning. A commonly used method for transportation planning is the four-step technique. Therefore, this study aimed to estimate the origin-destination (O-D) matrix for Central Java Province in 2022 and 2040. The traffic count method was utilized for calculating the O-D matrix in 2022, while the gravity method was employed for 2040. The results showed that the total movement for 2022 was 50,295 PCU/hour, while the projected amount for 2040 was 139,674 PCU/hour. In 2022, the action was primarily dominated by internal-internal trips, which account for 75% or 37,528 PCU/hour. In conclusion, the proposed approach has good validity, as indicated by a coefficient of determination (R2) of 0.677.

Identifying High-accuracy Regions in Traffic Camera Images to Enhance the Estimation of Road Traffic Metrics: A Quadtree-based Method

The growing number of real-time camera feeds in urban areas has made it possible to provide high-quality traffic data for effective transportation planning, operations, and management. However, deriving reliable traffic metrics from these camera feeds has been a challenge because of the limitations of current vehicle detection techniques, as well as the various camera conditions, such as height and resolution. In this work, a quadtree-based algorithm is developed to continuously partition the image extent until only regions with high detection accuracy remain. These regions are referred to as high-accuracy identification regions (HAIRs) in this paper. We demonstrate how the use of HAIRs can improve the accuracy of traffic density estimates using images from traffic cameras at different heights and resolutions in Central Ohio. Our experiments show that the proposed algorithm can be used to derive robust HAIRs in which vehicle detection accuracy is 41% higher than that in the original image extent. The use of HAIRs also significantly improves the traffic density estimation with an overall decrease of 49% in root mean squared error.

Machine learning approach for spatial modeling of ridesourcing demand

Accurately forecasting ridesourcing demand is important for effective transportation planning and policy-making. With the rise of Artificial Intelligence (AI), researchers have started to utilize machine learning models to forecast travel demand, which, in many cases, can produce higher prediction accuracy than statistical models. However, most existing machine-learning studies used a global model to predict the demand and ignored the influence of spatial heterogeneity (i.e., the spatial variations in the impacts of explanatory variables). Spatial heterogeneity can drive the parameter estimations varying over space; failing to consider the spatial variations may limit the model's prediction performance. To account for spatial heterogeneity, this study proposes a Clustering-aided Ensemble Method (CEM) to forecast the zone-to-zone (census-tract-to-census-tract) travel demand for ridesourcing services. Specifically, we develop an interactive clustering approach (powered by human-in-the-loop AI) to split the origin-destination pairs into different clusters and ensemble the cluster-specific machine learning models for prediction. We implement and test the proposed methodology by using the ridesourcing-trip data in Chicago. The results show that, with a more transparent and flexible model structure, the CEM significantly improves the prediction accuracy than the benchmark models (i.e., global machine-learning and statistical models directly trained on all observations). This study offers transportation researchers and practitioners a new methodology of travel demand forecasting, especially for new travel modes like ridesourcing and micromobility.

Mode choice, substitution patterns and environmental impacts of shared and personal micro-mobility

Shared micro-mobility services are rapidly expanding yet little is known about travel behaviour. Understanding mode choice, in particular, is quintessential for incorporating micro-mobility into transport simulations in order to enable effective transport planning. We contribute by collecting a large dataset with matching GPS tracks, booking data and survey data for more than 500 travellers, and by estimating a first choice model between eight transport modes, including shared e-scooters, shared e-bikes, personal e-scooters and personal e-bikes. We find that trip distance, precipitation and access distance are fundamental to micro-mobility mode choice. Substitution patterns reveal that personal e-scooters and e-bikes emit less CO2 than the transport modes they replace, while shared e-scooters and e-bikes emit more CO2 than the transport modes they replace. Our results enable researchers and planners to test the effectiveness of policy interventions through transport simulations. Service providers can use our findings on access distances to optimize vehicle repositioning.

Utilizing an inter-professional online advisory board: A case study to inform innovation in community-engaged, transportation equity research and planning

This case study describes implementation of an innovative, online, inter-professional advisory board in the context of transportation equity research. The board was comprised of 14 professionals from social work, transportation planning, and engineering. The board advised the research team on research methods such as sample recruitment strategies and data collection, as well as interpreting the results at the conclusion of the study and forming policy implications. The case study underscores the importance of: 1) ensuring broad, inter-professional membership; 2) utility of online meeting formats for reducing participation barriers and promoting more diverse participation; 3) designing active strategies to promote board members’ interaction and networking during meetings; and 4) continually orientating members to the board’s contribution to the research. Efforts to utilize participatory research methods in transportation equity research may lead to more effective transportation planning and more equitable transportation services.

Examining freight performance of third-party logistics providers within the automotive industry in India: an environmental sustainability perspective

The purpose of this study is to examine relationships between measures of sustainable freight transport performance (in the context of mid-sized third-party auto components’ logistics players) with the associated externalities and firms’ intrinsic characteristics when information exchange occurs between logistics firms and the auto manufacturer. Employing a survey-based research methodology, appropriate data were collected for a number of third-party logistics players, thus yielding a total of 708 responses from the operational managers of these firms. The research construct was validated through a rigorous procedure involving measurement and structural equation model. From a theoretical perspective, the results of this study provide evidences supporting systemic relationships between internal enablers of the logistics firms and externalities in the backdrop of environmental sustainability. Major findings indicate that transportation planning and distribution network and, commodity considerations backed by top management support can further environmental performance. Further, we also find evidence that effective transport planning and distribution network design used in conjunction with commodity considerations can be a source of sustainable supply chain performance. By bridging the literature pertaining to environmental sustainability, information exchange, and pertinent external/internal nuances of logistics firms, this study reveals novel findings that can help logistics players streamline operations focused at achieving environmental sustainability performance.

Software modeling application for verification of transportation planning engineering hypotheses

The organization of traffic is a complex of engineering and organizational arrangements aimed at maximizing the use of traffic flows opportunities represented by the road geometric parameters and condition. The article deals with an example of using software modeling for creating a digital twin of a complex intersection in Saratov in order to verify the engineering hypotheses concerning the effective transportation planning. The current traffic situation in the PTV VISSIM program is simulated. The transportation planning engineering hypothesis proposed and simulated the solution options of changing the working traffic light duration at the intersection for verifying and widening the carriageway by adding a lane. The analysis of two models options allowed determining the most effective transportation planning measure in a given transport hub of the city with a high level of traffic delays, which is actually the duration change of the working traffic light at the intersection. The software modeling application is confirmed for creating a digital twin complex intersection in Saratov.

The Cultures of Decision-Making: A qualitative study of urban transport projects in Alexandria, Egypt

This paper seeks to advance the practical insights from applying a polyrational approach on researching transport policy. Transport planning in Egypt is examined by applying cultural theory to ascertain different stakeholders’ rationality in the decision-making process. A ‘Stakeholder Driven Decision-making Model’ (SDDM) is put forward as a more robust and nuanced approach to examine transport planning decisions in developing countries. A cultural perspective of understanding actors’ values and rationality is very much needed in this field; as transport planners and traffic engineers, especially in developing countries, have adopted a highly technocratic approach to address urban transport problems and implement unrealistic policy. The proliferating car dependency culture in Alexandria is a typical example of the failure of such technical studies, which highlights the research gap in transport governance studies that neglect policy processes and outcomes. Transport studies tend to miss the critical socio-cultural and political aspects of decision-making and often resulted in failure during the early phases of implementation. Through applying SDDM, this paper shows a way forward to examine urban transport decisions, with a qualitative approach, for more effective transport planning and effective policy formulation.

Evaluation of Risk Factor for Children During Drop-off and Pick-up Time around the Primary School in Thailand

Background:Traffic accidents, hazardous behaviors, and caretakers’ opinions have a strong effect on students’ safety during the drop-off and pick-up period. The present research about student drop-off and pick-up behaviors and spatial analysis will be helpful for better understanding school traffic incidents and related risk factors.Objective:To examine the risk factors associated with school drop-off and pick-up in three dimensions: 1) risk zones, 2) risk behaviors, and 3) risk periods.Method:A mixed method approach was employed using 4 sets of data, consisting of 1) the statistics of accidents occurring around primary schools, 2) the student drop-off and pick-up behaviors, 3) the opinions toward risk zones and risk periods, and 4) the data obtained from the survey and interview. The spatial analysis was conducted using kernel density estimation technique. The statistical data analysis was carried out to analyze and compare the questionnaire responses given by the teachers and parents from the primary schools with the highest accident rate in 5 regions of Thailand.Results:Pedestrian crossing points in front of the school gates and blind spots behind the school buildings were considered the risk zones. In the morning, the parents usually dropped the students off at the pavements in front of the school gate. Some of them walked the students to the classrooms. After school, the parents parked their cars and then walked to wait for the students at the meeting points scattered inside or outside the school. The opinions of the teachers and parents regarding the risk periods were found to be significantly different (p< 0.01), which affected the way the teachers and parents looked out for the students’ safety in the morning and after school period.Conclusion:The areas around pedestrian crossing points and school gates require effective transport planning in order to specifically prevent and monitor hazardous incidents. A scattering of drop-off and pick-up points are risk behaviors. Therefore, each school should clearly set up safe drop-off and pick-up points and pay close attention to the safety of students both in the morning and after school. Creating safety for students should start with improving the school environment in order to reduce anxiety and facilitate behavior change.

Exploring transportation planning issues during the preparations for EXPO 2012 Yeosu Korea

Korea is hosting a World Expo in 2012. The Expo can provide a good opportunity for the city to construct new inter-regional transportation facilities so as to improve the physical, economic and social structure of the host city. The purpose of this paper is to suggest the transportation planning tasks that should be completed in order to provide effective transportation planning guidance and support, and ensure that the required new transportation facilities, services and supportive transportation demand management policies will be in place to ensure a successful Expo. The discussion focuses on four issues: 1) the low carbon green growth policy initiatives of the government in the planning and operation of the Expo, 2) the governance system that will oversee the planning and operation of the Expo, 3) progress in building the required transportation infrastructure and designing the effective traffic and transit operational systems, and 4) preparations for the Expo by the local community. The success of the Expo will depend on in part providing environmentally-friendly transportation services for the mobility and accessibility of visitors. The paper discusses how the Korean low carbon green growth policy can be translated into pragmatic transportation measures used in the Expo by limiting automobile access to the Expo site, while ensuring that competitive public transportation systems and services are available to visitors, including upgraded passenger rail, express, inter-city, and shuttle bus services, as well as a well designed, on site non-motorized transportation system based on walking and cycling.

The Role of Indicators, Targets and Monitoring in Decision-Support for Transport

Indicators can be seen as crucial to the transport planning processes as they can be used for decision-support in all aspects of policy development and assessment from option generation, through policy testing and appraisal to monitoring and feedback. Indicators are however, also seen by many practitioners as artificially focussing transport policy on what can be counted and on which indicators can most easily be improved. This paper presents the findings of a four year study into the use of indicators in the UK. In response to requests from local government practitioners, the research developed advice on how to develop a coherent indicator framework. The framework was tested through application in four case studies. The implications of the application of the framework are described in the paper and the degree to which the main criticisms of indicators can be overcome assessed. Many of the criticisms levelled at indicators such as their role in the distortion of decision-making processes arise not because indicators inevitably lead to significant conflicts but because of poor internal planning processes or unnecessary external constraints. The evidence presented in this paper suggests that, developed properly, an indicator framework is an essential part of an effective transport planning process for internal management and decision support and for external communication. Advice is provided on the conditions necessary for the development of an effective framework.

Innovative Coordination between States, Metropolitan Planning Organizations, and Tribes in Transportation Planning

Innovative consultation practices between tribes, states, and metropolitan planning organizations (MPOs) within the transportation planning process are highlighted. The FHWA Office of Planning sponsored the development of six case studies that highlight a range of practices implemented by tribal and nontribal governments to advance tribal consultation in statewide and metropolitan transportation planning. These case studies demonstrate that effective tribal consultation results from the identification of common goals and the establishment of ongoing coordination procedures. Researchers obtained input from tribal, federal, state, and local representatives in the six cases; examined current practices and the outcomes of these approaches; and developed lessons learned. Three overarching themes emerged from the case studies: participation and support from tribes, FHWA, FTA, states, and MPOs; funding and resources; and safety issues. As the foundation for effective transportation planning, participation must involve all parties. This process requires commitment and involvement by leadership, communication, and personal meetings and interviews; networking and consortia development, involvement, and representation on appropriate boards and committees; and the critical role that individuals often play in building relationships. Funding and resources also are highlighted. Innovative funding and partnership practices are crucial, as are the resources and technical assistance that states and MPOs provide. Finally, the case studies illustrate the ability to address safety issues through transportation, corridor, and crash-reporting studies and the completion of highway improvements.

TOWARDS A MICROSCOPIC SIMULATION MODEL FOR TRAFFIC MANAGEMENT: A COMPUTER-BASED APPROACH

Traffic congestion is increasing world-wide as a result of increased motorization, urbanization, population growth and changes in population density. Congestion reduces utilization of the transportation infrastructure and increases travel time, air pollution and fuel consumption. Automatic and adaptive control can play a significant corrective role for managing transportation systems in today's highly congested traffic networks. This paper presents the microscopic simulation model development of a major highly congested traffic network of Nicosia, Cyprus. Based on the validated simulation model various traffic control strategies involving the use of intelligent transportation systems will be tested prior to their implementation. Finally, this paper demonstrates a wider spectrum of understanding on the principles of traffic flow theory and how a traffic flow simulation model is developed and utilized for effective transportation planning.

Assessing communicative rationality as a transportation planning paradigm

Communicative rationality offers a new paradigm for transportation planning. Drawing on the literature and lessons from transportation planning practice, this paper describes the characteristics of a “communicative” form of transportation planning and compares them with conventional practices. A communicative rationality paradigm would place language and discourse at the core of transportation planning. The paper argues that it would lead to greater attention to desired transportation ends (goals), better integration of means and ends, new forms of participation and learning, and enhanced deliberative capacity. The paper explains the implications of this paradigm for the role of the transportation planner, the purpose of planning, the planning process, communicative practices, problem framing, and the nature of planning analysis. The paper concludes with an assessment of communicative rationality's ability to promote more effective transportation planning. It seeks to create a dialogue that will support the investigation of new transportation planning processes.

Incentives and Rates of Return for Travel Surveys

In recent years, lower rates of return for household-based travel surveys have become a reality. It may be difficult to collect enough data for effective transportation planning. Various incentive methods have been used to induce survey recipients to participate fully. Incentive methods will be described (along with other factors affecting rates of return), and their apparent effect on rates of return discussed. It appears that monetary incentives sent with survey materials are most effective in increasing return rates; nonmonetary incentives offered with survey packets are somewhat less effective. The data are inconclusive regarding monetary and nonmonetary incentives offered as a reward upon completion of surveys.

Incentives and Rates of Return for Travel Sur veys

In recent years, lower rates of return for household-based travel surveys have become a reality. It may be difficult to collect enough data for effective transportation planning. Various incentive methods have been used to induce survey recipients to participate fully. Incentive methods will be described (along with other factors affecting rates of return), and their apparent effect on rates of return discussed. It appears that monetary incentives sent with survey materials are most effective in increasing return rates; nonmonetary incentives offered with survey packets are somewhat less effective. The data are inconclusive regarding monetary and nonmonetary incentives offered as a reward upon completion of surveys.