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Dr. Sara Moridpour
Senior Lecturer

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Research Keywords & Expertise

0 Traffic Simulation
0 Transport Modelling
0 Urban Planning Resilience Sustainable environments City Regeneration
0 Traffic Safety
0 Transport Infrastructure Maintenance

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Traffic Safety

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Journal article
Published: 23 April 2021 in Sustainability
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The elderly population is increasing rapidly. Understanding travel behaviour for this group of commuters (in terms of the trip purpose and travel time) is necessary for future transport planning. Many researchers are working on travel’s spatial and temporal analysis to provide operational decision making and transport network planning. This research study’s primary purpose is to identify the influence of trip duration (using public transport), time of the day (usage of public transport), and public transport (PT) accessibility over public transport mode preference by elderly (over 65 years of age) commuters. The methodology of this study is divided into two parts as spatial analysis and temporal analysis. The research identified the dependency of trip duration, time of the day, geographical areas, and PT access over transport mode preference of elderly. The temporal study shows that transport mode preference can vary depending on trip purposes. However, for specific trip durations and times of the day, the elderly sometimes choose PT as a mobility mode. For instance, on shopping trips between 10:00 and 11:00 a.m., the elderly have a greater possibility of choosing public transport over private vehicles. Moreover, the results show the public transport mode preference based on different times of the day and trip purposes. Urban and transport planner can use the results to modify/plan public transport schedule, which can be easily accessible by the elderly population.

ACS Style

Kaniz Fatima; Sara Moridpour; Tayebeh Saghapour. Spatial and Temporal Distribution of Elderly Public Transport Mode Preference. Sustainability 2021, 13, 4752 .

AMA Style

Kaniz Fatima, Sara Moridpour, Tayebeh Saghapour. Spatial and Temporal Distribution of Elderly Public Transport Mode Preference. Sustainability. 2021; 13 (9):4752.

Chicago/Turabian Style

Kaniz Fatima; Sara Moridpour; Tayebeh Saghapour. 2021. "Spatial and Temporal Distribution of Elderly Public Transport Mode Preference." Sustainability 13, no. 9: 4752.

Editorial
Published: 14 March 2021 in Journal of Advanced Transportation
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Transport infrastructure is the lifeline of modern economy and significantly contributes to economic growth and our well-being. Transport infrastructure is not just about moving people and goods, but it is also an essential part of the continued economic growth and social development of countries. Our transport infrastructure is also increasingly complex and subject to a range of hazards or failures. A sustainable and resilient transport infrastructure provides access to jobs and other services with minimum environmental impacts and is able to withstand disruption and absorb disturbance by adapting to changing conditions, including climate change. This special issue aims at identifying and discussing a range of challenges that are faced in delivering safe, sustainable, and smart transport infrastructure as well as introducing innovative approaches to resolve these problems and challenges. We hope that this special issue would attract a major attention of the peers. 25 papers were submitted to this special issue, 8 of which were accepted for publication. As the guest editors of this special issue, we would like to summarize the 8 accepted papers as follows.

ACS Style

Sara Moridpour; Xiaobo Qu; Nirajan Shiwakoti; Samiul Hasan. Sustainable and Resilient Transport Infrastructure. Journal of Advanced Transportation 2021, 2021, 1 -2.

AMA Style

Sara Moridpour, Xiaobo Qu, Nirajan Shiwakoti, Samiul Hasan. Sustainable and Resilient Transport Infrastructure. Journal of Advanced Transportation. 2021; 2021 ():1-2.

Chicago/Turabian Style

Sara Moridpour; Xiaobo Qu; Nirajan Shiwakoti; Samiul Hasan. 2021. "Sustainable and Resilient Transport Infrastructure." Journal of Advanced Transportation 2021, no. : 1-2.

Review
Published: 29 January 2021 in Journal of Advanced Transportation
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In recent years, traffic congestion prediction has led to a growing research area, especially of machine learning of artificial intelligence (AI). With the introduction of big data by stationary sensors or probe vehicle data and the development of new AI models in the last few decades, this research area has expanded extensively. Traffic congestion prediction, especially short-term traffic congestion prediction is made by evaluating different traffic parameters. Most of the researches focus on historical data in forecasting traffic congestion. However, a few articles made real-time traffic congestion prediction. This paper systematically summarises the existing research conducted by applying the various methodologies of AI, notably different machine learning models. The paper accumulates the models under respective branches of AI, and the strength and weaknesses of the models are summarised.

ACS Style

Mahmuda Akhtar; Sara Moridpour. A Review of Traffic Congestion Prediction Using Artificial Intelligence. Journal of Advanced Transportation 2021, 2021, 1 -18.

AMA Style

Mahmuda Akhtar, Sara Moridpour. A Review of Traffic Congestion Prediction Using Artificial Intelligence. Journal of Advanced Transportation. 2021; 2021 ():1-18.

Chicago/Turabian Style

Mahmuda Akhtar; Sara Moridpour. 2021. "A Review of Traffic Congestion Prediction Using Artificial Intelligence." Journal of Advanced Transportation 2021, no. : 1-18.

Review
Published: 07 September 2020 in Sustainability
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The number of elderly people as a proportion of the world’s population is growing significantly. Special attention to the accessibility and mobility requirements of this group is needed. The contribution of this paper is a review of travel patterns, mode preferences, infrastructure solutions, accessibility indices, mode choice models and datasets as they relate to elderly mobility. Key findings highlight the role of residential location characteristics in shaping elderly travel patterns, helping to explain why research on elderly travel has largely relied on case studies to date. The review also summarizes a range of indices that have been developed to measure public transport and walking accessibility among the elderly, including distance and time-based methods. Future research should consider the dominance of private transport in facilitating elderly mobility and its implications for cities experiencing an aging population.

ACS Style

Kaniz Fatima; Sara Moridpour; Chris De Gruyter; Tayebeh Saghapour. Elderly Sustainable Mobility: Scientific Paper Review. Sustainability 2020, 12, 7319 .

AMA Style

Kaniz Fatima, Sara Moridpour, Chris De Gruyter, Tayebeh Saghapour. Elderly Sustainable Mobility: Scientific Paper Review. Sustainability. 2020; 12 (18):7319.

Chicago/Turabian Style

Kaniz Fatima; Sara Moridpour; Chris De Gruyter; Tayebeh Saghapour. 2020. "Elderly Sustainable Mobility: Scientific Paper Review." Sustainability 12, no. 18: 7319.

Review
Published: 04 August 2020 in Journal of Traffic and Transportation Engineering (English Edition)
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The rising number of vehicles on roadways expedites the urge to increase efforts in implementing monitoring systems that look after road pavement conditions. This rising in number of vehicles on roadways also cause more damages and distresses on road pavement. Road pavement conditions should be accurately evaluated to identify the severity of pavement damages and types of pavement distress. Therefore, monitoring systems are considered a significant step of maintenance processes. Paved roads and unpaved roads require regular maintenance to provide for and preserve users’ usability, accessibility, and safety. Transport agents and researches would spend a lot of time and money in inspecting some sections of the roadway surface; that inspection would then be followed by results recording and data analysis to diagnose the type of treatment required. These monitoring systems have been developed using various methods that include smart technologies and prepared equipment. Many related studies evaluate road pavement degradation and distress, while others focus on identifying the best maintenance monitoring approach in terms of time and cost. This paper set out to explore different monitoring techniques used to evaluate road pavement surface condition. Also, this study introduces dynamic and static monitoring systems used in both paved and unpaved roads to identify the severity of pavement degradations and types of pavement distress on road surfaces and also this study explains the used equipment in the previous monitoring studies.

ACS Style

Amir Shtayat; Sara Moridpour; Berthold Best; Avinash Shroff; Divyajeetsinh Raol. A review of monitoring systems of pavement condition in paved and unpaved roads. Journal of Traffic and Transportation Engineering (English Edition) 2020, 7, 629 -638.

AMA Style

Amir Shtayat, Sara Moridpour, Berthold Best, Avinash Shroff, Divyajeetsinh Raol. A review of monitoring systems of pavement condition in paved and unpaved roads. Journal of Traffic and Transportation Engineering (English Edition). 2020; 7 (5):629-638.

Chicago/Turabian Style

Amir Shtayat; Sara Moridpour; Berthold Best; Avinash Shroff; Divyajeetsinh Raol. 2020. "A review of monitoring systems of pavement condition in paved and unpaved roads." Journal of Traffic and Transportation Engineering (English Edition) 7, no. 5: 629-638.

Journal article
Published: 20 May 2020 in Sustainability
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Professional drivers play a key role in urban road network safety. It is therefore important to employ safer drivers, also find the problem, and train the existing ones. However, a direct driving test may not be very useful solely because of drivers’ consciousness. This study introduces a latent predictor to expect driving behaviors, by finding the relation between taxi drivers’ psychological characteristics and their driving behaviors. A self-report questionnaire was collected from 245 taxi drivers by which their demographic characteristics, psychological characteristics, and driving behaviors were obtained. The psychological characteristics include instrumental attitude, subjective norm, sensation seeking, aggressive mode, conscientiousness, life satisfaction, premeditation, urgency, and selfishness. Driving behaviors questionnaire (DBQ) provides information regarding drivers’ violations, aggressive violations, errors, and lapses. The standard linear regression model is used to determine the relationship between driving behavior and psychological characteristics of drivers. The findings show that social anxiety and selfishness are the best predictors of the violations; aggressive mode is a significant predictor of the aggressive violations; urgency has a perfect impact on the errors; and finally, life satisfaction, sensation seeking, conscientiousness, age, and urgency are the best predictors of the lapses.

ACS Style

Kayvan Aghabayk; Leila Mashhadizade; Sara Moridpour. Need Safer Taxi Drivers? Use Psychological Characteristics to Find or Train! Sustainability 2020, 12, 4206 .

AMA Style

Kayvan Aghabayk, Leila Mashhadizade, Sara Moridpour. Need Safer Taxi Drivers? Use Psychological Characteristics to Find or Train! Sustainability. 2020; 12 (10):4206.

Chicago/Turabian Style

Kayvan Aghabayk; Leila Mashhadizade; Sara Moridpour. 2020. "Need Safer Taxi Drivers? Use Psychological Characteristics to Find or Train!" Sustainability 12, no. 10: 4206.

Corrigendum
Published: 30 September 2019 in Journal of Advanced Transportation
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ACS Style

Tayebeh Saghapour; Sara Moridpour; Russell Thompson. Corrigendum to “Modeling Access to Public Transport in Urban Areas”. Journal of Advanced Transportation 2019, 2019, 1 -1.

AMA Style

Tayebeh Saghapour, Sara Moridpour, Russell Thompson. Corrigendum to “Modeling Access to Public Transport in Urban Areas”. Journal of Advanced Transportation. 2019; 2019 ():1-1.

Chicago/Turabian Style

Tayebeh Saghapour; Sara Moridpour; Russell Thompson. 2019. "Corrigendum to “Modeling Access to Public Transport in Urban Areas”." Journal of Advanced Transportation 2019, no. : 1-1.

Editorial
Published: 05 August 2018 in Journal of Advanced Transportation
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ACS Style

Sara Moridpour; Edward Chin-Shin Chung; Taha Rashidi. Optimization Concepts in Traffic and Transportation Science. Journal of Advanced Transportation 2018, 2018, 1 -2.

AMA Style

Sara Moridpour, Edward Chin-Shin Chung, Taha Rashidi. Optimization Concepts in Traffic and Transportation Science. Journal of Advanced Transportation. 2018; 2018 ():1-2.

Chicago/Turabian Style

Sara Moridpour; Edward Chin-Shin Chung; Taha Rashidi. 2018. "Optimization Concepts in Traffic and Transportation Science." Journal of Advanced Transportation 2018, no. : 1-2.

Research article
Published: 24 May 2018 in Journal of Advanced Transportation
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Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work. With the restrictions on financial support, the rail transport authorities are in pursuit of improved modern methods, which can provide a precise prediction of rail maintenance timeframe. The expectation from such a method is to develop models to minimise the human error that is strongly related to manual prediction. Such models will help rail transport authorities in understanding how the track degradation occurs at different conditions (e.g., rail type, rail profile) over time. They need a well-structured technique to identify the precise time when rail tracks fail to minimise the maintenance cost/time. The rail track characteristics that have been collected over the years will be used in developing a degradation prediction model for rail tracks. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use the data in prediction model development. An accurate model can play a key role in the estimation of the long-term behaviour of rail tracks. Accurate models can increase the efficiency of maintenance activities and decrease the cost of maintenance in long-term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curves and straight sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model. The results from the developed model show that it is capable of predicting the gauge values with R2 of 0.6 and 0.78 for curves and straights, respectively.

ACS Style

Mostafa Karimpour; Lalith Hitihamillage; Najwa ElKhoury; Sara Moridpour; Reyhaneh Hesami. Fuzzy Approach in Rail Track Degradation Prediction. Journal of Advanced Transportation 2018, 2018, 1 -7.

AMA Style

Mostafa Karimpour, Lalith Hitihamillage, Najwa ElKhoury, Sara Moridpour, Reyhaneh Hesami. Fuzzy Approach in Rail Track Degradation Prediction. Journal of Advanced Transportation. 2018; 2018 ():1-7.

Chicago/Turabian Style

Mostafa Karimpour; Lalith Hitihamillage; Najwa ElKhoury; Sara Moridpour; Reyhaneh Hesami. 2018. "Fuzzy Approach in Rail Track Degradation Prediction." Journal of Advanced Transportation 2018, no. : 1-7.

Research article
Published: 06 May 2018 in Journal of Advanced Transportation
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Tram is classified as a light rail mode of transportation. Tram tracks experience high acceleration and deceleration forces of locomotives and wagons within their service life and also share their route with other vehicles. This results in higher rates of degradation in tram tracks compared to the degradation rate in heavy rail tracks. In this research, gauge deviation is employed as a representative of track geometry irregularities for the predication of the tram track degradation. Data sets used in this research were sourced from Melbourne’s tram system. For model development, the data of approximately 250 km of tram tracks are used. Two different models including a regression model and an Artificial Neural Networks (ANN) model have been applied for predicting tram track gauge deviation. According to the results, the performances of the regression models are similar to the ANN models. The determination coefficients of the developed models are above 0.7.

ACS Style

Amir Falamarzi; Sara Moridpour; Majid Nazem; Reyhaneh Hesami. Rail Degradation Prediction Models for Tram System: Melbourne Case Study. Journal of Advanced Transportation 2018, 2018, 1 -8.

AMA Style

Amir Falamarzi, Sara Moridpour, Majid Nazem, Reyhaneh Hesami. Rail Degradation Prediction Models for Tram System: Melbourne Case Study. Journal of Advanced Transportation. 2018; 2018 ():1-8.

Chicago/Turabian Style

Amir Falamarzi; Sara Moridpour; Majid Nazem; Reyhaneh Hesami. 2018. "Rail Degradation Prediction Models for Tram System: Melbourne Case Study." Journal of Advanced Transportation 2018, no. : 1-8.

Review
Published: 28 February 2018 in The Open Transportation Journal
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In the past few decades, the railway infrastructure has been widely expanded in urban and rural areas, making it the most complex matrix of rail transport networks. Safe and comfortable travel on railways has always been a common goal for transportation engineers and researchers, and requires railways in excellent condition and well-organized maintenance practices. Degradation of rail tracks is a main concern for railway organizations as it affects the railway’s behaviour and its parameters, such as track geometry, speed, traffic and loads. Therefore, the prediction of the degradation of rail tracks is very important in order to optimise maintenance needs, reduce maintenance and operational costs of railways, and improve rail track conditions.This paper provides a comprehensive review of rail degradation prediction models, their parameters, and the strengths and weaknesses of each model. A comprehensive discussion of existing research and a comparison of different models of degradation of rail tracks is also provided. Finally, this review presents concluding remarks on the limitations of existing studies and provides recommendations for further research and appraisal practices.

ACS Style

Najwa ElKhoury; Lalith Hitihamillage; Sara Moridpour; Dilan Robert. Degradation Prediction of Rail Tracks: A Review of the Existing Literature. The Open Transportation Journal 2018, 12, 88 -104.

AMA Style

Najwa ElKhoury, Lalith Hitihamillage, Sara Moridpour, Dilan Robert. Degradation Prediction of Rail Tracks: A Review of the Existing Literature. The Open Transportation Journal. 2018; 12 (1):88-104.

Chicago/Turabian Style

Najwa ElKhoury; Lalith Hitihamillage; Sara Moridpour; Dilan Robert. 2018. "Degradation Prediction of Rail Tracks: A Review of the Existing Literature." The Open Transportation Journal 12, no. 1: 88-104.

Article
Published: 21 November 2016 in Journal of Advanced Transportation
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ACS Style

Tayebeh Saghapour; Sara Moridpour; Russell G. Thompson. Retracted: Modeling access to public transport in urban areas. Journal of Advanced Transportation 2016, 50, 1785 -1801.

AMA Style

Tayebeh Saghapour, Sara Moridpour, Russell G. Thompson. Retracted: Modeling access to public transport in urban areas. Journal of Advanced Transportation. 2016; 50 (8):1785-1801.

Chicago/Turabian Style

Tayebeh Saghapour; Sara Moridpour; Russell G. Thompson. 2016. "Retracted: Modeling access to public transport in urban areas." Journal of Advanced Transportation 50, no. 8: 1785-1801.

Journal article
Published: 12 September 2014 in Journal of Advanced Transportation
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This work examines the impact of heavy vehicle movements on measured traffic characteristics in detail. Although the number of heavy vehicles within the traffic stream is only a small percentage, their impact is prominent. Heavy vehicles impose physical and psychological effects on surrounding traffic flow because of their length and size (physical) and acceleration/deceleration (operational) characteristics. The objective of this work is to investigate the differences in traffic characteristics in the vicinity of heavy vehicles and passenger cars. The analysis focuses on heavy traffic conditions (level of service E) using a trajectory data of highway I‐80 in California. The results show that larger front and rear space gaps exist for heavy vehicles compared with passenger cars. This may be because of the limitations in manoeuvrability of heavy vehicles and the safety concerns of the rear vehicle drivers, respectively. In addition, heavy vehicle drivers mainly keep a constant speed and do not change their speed frequently. This work also examines the impact of heavy vehicles on their surrounding traffic in terms of average travel time and number of lane changing manoeuvres using Advanced Interactive Microscopic Simulator for Urban and Non‐Urban Networks (AIMSUN) microscopic traffic simulation package. According to the results, the average travel time increases when proportion of heavy vehicles rises in each lane. To reflect the impact of heavy vehicles on average travel time, a term related to heavy vehicle percentage is introduced into two different travel time equations, Bureau of Public Roads and Akçelik's travel time equations. The results show that using an exclusive term for heavy vehicles can better estimate the travel times for more than 10%. Finally, number of passenger car lane changing manoeuvres per lane will be more frequent when more heavy vehicles exist in that lane. The influence of heavy vehicles on the number of passenger car lane changing is intensified in higher traffic densities and higher percentage of heavy vehicles. Large numbers of lane changing manoeuvres can increase the number of traffic accidents and potentially reduce traffic safety. The results show an increase of 5% in the likelihood of accidents, when percentage of heavy vehicles increases to 30% of total traffic. Copyright © 2014 John Wiley & Sons, Ltd.

ACS Style

Sara Moridpour; Ehsan Mazloumi; Mahmoud Mesbah. Impact of heavy vehicles on surrounding traffic characteristics. Journal of Advanced Transportation 2014, 49, 535 -552.

AMA Style

Sara Moridpour, Ehsan Mazloumi, Mahmoud Mesbah. Impact of heavy vehicles on surrounding traffic characteristics. Journal of Advanced Transportation. 2014; 49 (4):535-552.

Chicago/Turabian Style

Sara Moridpour; Ehsan Mazloumi; Mahmoud Mesbah. 2014. "Impact of heavy vehicles on surrounding traffic characteristics." Journal of Advanced Transportation 49, no. 4: 535-552.

Journal article
Published: 01 February 2012 in Journal of Transportation Engineering
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Heavy vehicles can considerably affect traffic flow particularly during heavy-traffic conditions. Large numbers of heavy-vehicle lane-changing maneuvers can contribute to increase the number of traffic accidents and hence to reduce the freeway safety. The increase in the number of heavy vehicles on freeways has been the motivation to establish strategies to reduce the interaction between heavy vehicles and passenger cars. Previous studies have examined different lane-restriction strategies for heavy vehicles using microscopic traffic-simulation packages. Those packages mostly use a general lane-changing model to estimate the lane-changing behavior of heavy-vehicle and passenger-car drivers. The general lane-changing models ignore the fundamental differences in the lane-changing behavior of passenger cars and heavy vehicles. However, an exclusive lane-changing model for heavy vehicles can increase the accuracy of simulation models. The application of such a model can result in a more reliable evaluation of lane restriction strategies. In this paper, different lane restriction strategies are defined for heavy vehicles. For each strategy, the macroscopic and microscopic traffic measurements of two freeway sections in California are analyzed, using the VISSIM default lane-changing model and an exclusive heavy- vehicle lane-changing model. The results show that the VISSIM default model unrealistically overestimates the observed number of heavy-vehicle lane-changing maneuvers and potentially overestimates the number of traffic accidents. Using the exclusive lane-changing model for heavy vehicles enhances the accuracy of the VISSIM traffic simulation model in microscopically estimating the lane-changing maneuvers of heavy vehicles.

ACS Style

Sara Moridpour; Ehsan Mazloumi; Majid Sarvi; Geoff Rose. Enhanced Evaluation of Heavy Vehicle Lane Restriction Strategies in Microscopic Traffic Simulation. Journal of Transportation Engineering 2012, 138, 236 -242.

AMA Style

Sara Moridpour, Ehsan Mazloumi, Majid Sarvi, Geoff Rose. Enhanced Evaluation of Heavy Vehicle Lane Restriction Strategies in Microscopic Traffic Simulation. Journal of Transportation Engineering. 2012; 138 (2):236-242.

Chicago/Turabian Style

Sara Moridpour; Ehsan Mazloumi; Majid Sarvi; Geoff Rose. 2012. "Enhanced Evaluation of Heavy Vehicle Lane Restriction Strategies in Microscopic Traffic Simulation." Journal of Transportation Engineering 138, no. 2: 236-242.

Journal article
Published: 01 November 2010 in Journal of Transportation Engineering
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Lane changing maneuvers could have a substantial influence on traffic flow characteristics as a result of their interfering effect on surrounding vehicles. The interference effect of lane changing is more pronounced when heavy vehicles change lanes compared to when passenger cars undertake the same maneuver. This is due to the physical effects that the heavy vehicles impose on surrounding traffic. This paper investigates and compares the traffic flow characteristics which influence the lane changing behavior of heavy vehicle and passenger car drivers on freeways under heavy traffic conditions. A trajectory data set comprising 28 heavy vehicle and 28 passenger car lane changing maneuvers is analyzed in this study. The results suggest a substantial difference exists between the traffic characteristics influencing the lane changing behavior of heavy vehicle and passenger car drivers. Heavy vehicles’ speed changes little during a lane changing maneuver. Heavy vehicle drivers mainly move into the slower lanes to prevent obstructing the fast moving vehicles which approach from the rear. However, passenger car drivers increase their speed according to the speeds of the lead and lag vehicles in the target lane. They more commonly move into the faster lanes to gain speed advantages.

ACS Style

Sara Moridpour; Geoff Rose; Majid Sarvi. Effect of Surrounding Traffic Characteristics on Lane Changing Behavior. Journal of Transportation Engineering 2010, 136, 973 -985.

AMA Style

Sara Moridpour, Geoff Rose, Majid Sarvi. Effect of Surrounding Traffic Characteristics on Lane Changing Behavior. Journal of Transportation Engineering. 2010; 136 (11):973-985.

Chicago/Turabian Style

Sara Moridpour; Geoff Rose; Majid Sarvi. 2010. "Effect of Surrounding Traffic Characteristics on Lane Changing Behavior." Journal of Transportation Engineering 136, no. 11: 973-985.

Journal article
Published: 01 July 2010 in Transportation Letters
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ACS Style

Sara Moridpour; Majid Sarvi; Geoff Rose. Lane changing models: a critical review. Transportation Letters 2010, 2, 1 .

AMA Style

Sara Moridpour, Majid Sarvi, Geoff Rose. Lane changing models: a critical review. Transportation Letters. 2010; 2 (3):1.

Chicago/Turabian Style

Sara Moridpour; Majid Sarvi; Geoff Rose. 2010. "Lane changing models: a critical review." Transportation Letters 2, no. 3: 1.

Journal article
Published: 01 March 2010 in Journal of Urban Planning and Development
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ACS Style

Ehsan Mazloumi; Sara Moridpour; Hassan Mohsenian. Delay Function for Signalized Intersections in Traffic Assignment Models. Journal of Urban Planning and Development 2010, 136, 67 -74.

AMA Style

Ehsan Mazloumi, Sara Moridpour, Hassan Mohsenian. Delay Function for Signalized Intersections in Traffic Assignment Models. Journal of Urban Planning and Development. 2010; 136 (1):67-74.

Chicago/Turabian Style

Ehsan Mazloumi; Sara Moridpour; Hassan Mohsenian. 2010. "Delay Function for Signalized Intersections in Traffic Assignment Models." Journal of Urban Planning and Development 136, no. 1: 67-74.