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Dr. Camille Kamga
Department of Civil Engineering, The City College of New York, New York, NY 10031, USA

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0 Traffic Incident Management
0 Transportation Safety
0 intelligent transportation systems
0 Urban Sustainability
0 Transportation policy and planning

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Review
Published: 27 March 2021 in Transport Policy
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This paper presents a review of social distancing measures deployed by transit agencies in the United States and Canada during the COVID-19 pandemic and discusses how specific operators across the two countries have implemented changes. Challenges and impacts on their operations are also provided. Social distancing is one of the community mitigation measures traditionally implemented during influenza pandemics and the novel coronavirus pandemic. Research has shown that social distancing is effective in containing the spread of disease. This is applicable to the current situation with the novel coronavirus, given the lack of effective vaccines and treatments in the United States and Canada in the first eight months of the pandemic. Moreover, social distancing is particularly useful in settings where community transmission is substantial. Directives for social distancing were issued in several states and public transit operators were charged with how to provide for physical distance of six feet between passengers on their property including physical infrastructure such as station buildings and rolling infrastructure (rolling stock) including trains, subway cars and buses. Operational changes were also required due to physical distancing, e.g. adding train cars to provide for opportunities to physically distance on the train. Examples of some measures discussed in this research includes taping off every other seat on buses, increasing the total length of trains by adding cars, separating bus drivers from passengers with plastic sheeting, rear door boarding, etc. This research also analyzes long-term impacts for transit operators and challenges to encourage passengers to return to public transit after lockdown requirements ordered by government officials are lifted. A section on the policies that are being explored by government to continue to sustain public transportation is also included.

ACS Style

Camille Kamga; Penny Eickemeyer. Slowing the spread of COVID-19: Review of “Social distancing” interventions deployed by public transit in the United States and Canada. Transport Policy 2021, 106, 25 -36.

AMA Style

Camille Kamga, Penny Eickemeyer. Slowing the spread of COVID-19: Review of “Social distancing” interventions deployed by public transit in the United States and Canada. Transport Policy. 2021; 106 ():25-36.

Chicago/Turabian Style

Camille Kamga; Penny Eickemeyer. 2021. "Slowing the spread of COVID-19: Review of “Social distancing” interventions deployed by public transit in the United States and Canada." Transport Policy 106, no. : 25-36.

Journal article
Published: 01 February 2019 in Journal of Transportation Engineering, Part A: Systems
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This paper investigates the randomness in incident-induced capacity reductions and discusses the further impacts on delay calculation and modeling. For this purpose, incident and traffic count data sets from four important freeways in California, i.e., I-80, I-280, I-580, and, I-880, dating from February 1 to June 20, 2017, are utilized to analyze the incident capacity reductions. Accordingly, the capacity reduction distributions are identified and compared with the findings from the literature. In addition, the impact of variation in capacity reduction on incident delay is derived analytically for a deterministic queuing model. Through further analysis of the data, it is shown that capacity reduction values vary with respect to traffic conditions (e.g., volume). Accordingly, it is discussed that capacity reduction tables that do not incorporate traffic flow conditions and variance may provide incorrect estimations of delay. Considering the widely used capacity reduction tables for delay calculation, a regression tree approach is utilized to provide similar tables that provide traffic-dependent capacity reduction and variance for practitioner use.

ACS Style

Amirmasoud Almotahari; M. Anil Yazici; Sandeep Mudigonda; Camille Kamga. Analysis of Incident-Induced Capacity Reductions for Improved Delay Estimation. Journal of Transportation Engineering, Part A: Systems 2019, 145, 04018083 .

AMA Style

Amirmasoud Almotahari, M. Anil Yazici, Sandeep Mudigonda, Camille Kamga. Analysis of Incident-Induced Capacity Reductions for Improved Delay Estimation. Journal of Transportation Engineering, Part A: Systems. 2019; 145 (2):04018083.

Chicago/Turabian Style

Amirmasoud Almotahari; M. Anil Yazici; Sandeep Mudigonda; Camille Kamga. 2019. "Analysis of Incident-Induced Capacity Reductions for Improved Delay Estimation." Journal of Transportation Engineering, Part A: Systems 145, no. 2: 04018083.

Journal article
Published: 01 March 2018 in Journal of Computing in Civil Engineering
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In urban transportation systems, the traffic signal is the main component in controlling traffic congestion. Using actuated traffic control as one of the traffic-controlling systems can cause fewer delays for transportation users, specifically when it comes to an isolated intersection. Although actuated signal control has many benefits, the prediction of cycle length is cumbersome because it varies from time to time. The value of signal cycle length in actuated control depends on many parameters. In this research, the authors attempted to understand whether any dependence existed between the current value of the cycle length and its previous values. To capture the dependence among cycle length data, time series analysis was applied over the data, which were obtained from the simulated fully actuated signal. The behavior of the signal’s cycle length under different levels of demand was analyzed, and, based on sample autocorrelation functions (ACFs), a well-known family of time series called autoregressive integrated moving average (ARIMA) was chosen for model fitting and prediction. The results revealed that there is a statistically significant dependence between two consecutive cycle lengths, and this dependence becomes more pronounced as the demand increases. Further, to improve the fit and prediction accuracy of cycle length for signals with more than two critical phases, a linear regression component using skipping indicators has been added to the ARIMA model. Finally, simulation-based cycle length prediction using the proposed model performs reasonably well under different simulation scenarios, and it achieves a smaller mean squared prediction error (MSPE) as compared to more traditional averaging prediction models.

ACS Style

Bahman Moghimi; Abolfazl Safikhani; Camille Kamga; Wei Hao. Cycle-Length Prediction in Actuated Traffic-Signal Control Using ARIMA Model. Journal of Computing in Civil Engineering 2018, 32, 04017083 .

AMA Style

Bahman Moghimi, Abolfazl Safikhani, Camille Kamga, Wei Hao. Cycle-Length Prediction in Actuated Traffic-Signal Control Using ARIMA Model. Journal of Computing in Civil Engineering. 2018; 32 (2):04017083.

Chicago/Turabian Style

Bahman Moghimi; Abolfazl Safikhani; Camille Kamga; Wei Hao. 2018. "Cycle-Length Prediction in Actuated Traffic-Signal Control Using ARIMA Model." Journal of Computing in Civil Engineering 32, no. 2: 04017083.

Preprint
Published: 06 December 2017
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The demand for e-hailing services is growing rapidly, especially in large cities. Uber is the first and popular e-hailing company in the United Stated and New York City. A comparison of the demand for yellow-cabs and Uber in NYC in 2014 and 2015 shows that the demand for Uber has increased. However, this demand may not be distributed uniformly either spatially or temporally. Using spatio-temporal time series models can help us to better understand the demand for e-hailing services and to predict it more accurately. This paper analyzes the prediction performance of one temporal model (vector autoregressive (VAR)) and two spatio-temporal models (Spatial-temporal autoregressive (STAR); least absolute shrinkage and selection operator applied on STAR (LASSO-STAR)) and for different scenarios (based on the number of time and space lags), and applied to both rush hours and non-rush hours periods. The results show the need of considering spatial models for taxi demand.

ACS Style

Sabiheh Sadat Faghih; Abolfazl Safikhani; Bahman Moghimi; Camille Kamga. Predicting Short-Term Uber Demand Using Spatio-Temporal Modeling: A New York City Case Study. 2017, 1 .

AMA Style

Sabiheh Sadat Faghih, Abolfazl Safikhani, Bahman Moghimi, Camille Kamga. Predicting Short-Term Uber Demand Using Spatio-Temporal Modeling: A New York City Case Study. . 2017; ():1.

Chicago/Turabian Style

Sabiheh Sadat Faghih; Abolfazl Safikhani; Bahman Moghimi; Camille Kamga. 2017. "Predicting Short-Term Uber Demand Using Spatio-Temporal Modeling: A New York City Case Study." , no. : 1.

Preprint
Published: 28 November 2017
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A highly dynamic urban space in a metropolis such as New York City, the spatio-temporal variation in demand for transportation, particularly taxis, is impacted by various factors such as commuting, weather, road work and closures, disruption in transit services, etc. To understand the user demand for taxis through space and time, a generalized spatio-temporal autoregressive (STAR) model is proposed in this study. In order to deal with the high dimensionality of the model, LASSO-type penalized methods are proposed to tackle the parameter estimation. The forecasting performance of the proposed models is measured using the out-of-sample mean squared prediction error (MSPE), and it is found that the proposed models outperform other alternative models such as vector autoregressive (VAR) models. The proposed modeling framework has an easily interpretable parameter structure and practical to be applied by taxi operators. Efficiency of the proposed model also helps in model estimation in real-time applications.

ACS Style

Abolfazl Safikhani; Camille Kamga; Sandeep Mudigonda; Sabiheh Sadat Faghih; Bahman Moghimi. Spatio-temporal Modeling of Yellow Taxi Demands in New York City Using Generalized STAR Models. 2017, 1 .

AMA Style

Abolfazl Safikhani, Camille Kamga, Sandeep Mudigonda, Sabiheh Sadat Faghih, Bahman Moghimi. Spatio-temporal Modeling of Yellow Taxi Demands in New York City Using Generalized STAR Models. . 2017; ():1.

Chicago/Turabian Style

Abolfazl Safikhani; Camille Kamga; Sandeep Mudigonda; Sabiheh Sadat Faghih; Bahman Moghimi. 2017. "Spatio-temporal Modeling of Yellow Taxi Demands in New York City Using Generalized STAR Models." , no. : 1.

Journal article
Published: 01 September 2017 in Research in Transportation Business & Management
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ACS Style

Alison Conway; Jialei Cheng; Camille Kamga; Dan Wan. Cargo cycles for local delivery in New York City: Performance and impacts. Research in Transportation Business & Management 2017, 24, 90 -100.

AMA Style

Alison Conway, Jialei Cheng, Camille Kamga, Dan Wan. Cargo cycles for local delivery in New York City: Performance and impacts. Research in Transportation Business & Management. 2017; 24 ():90-100.

Chicago/Turabian Style

Alison Conway; Jialei Cheng; Camille Kamga; Dan Wan. 2017. "Cargo cycles for local delivery in New York City: Performance and impacts." Research in Transportation Business & Management 24, no. : 90-100.

Journal article
Published: 01 November 2016 in Transportation Research Part F: Traffic Psychology and Behaviour
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Although trucks only account for approximately 4% of all the vehicles based on the Federal Railway Administration (FRA) database, about 25% involved truck accidents happen at highway-rail grade crossings. This study applied an ordered probit model to explore the determinants of injury severity of truck drivers at highway-rail grade crossing in the United States. Given the importance of trucking to the economics of a country and the safety concerns posed by the trucks (as a result of their large size and weight making them difficult to control, maneuver, and stop), a comprehensive research on truck accidents is critical. Based on data analysis results, the strong effects of driver-, environmental-, weather- characteristics on the injury severities in truck accidents happened at highway-rail grade crossings are found. The findings reveal that better speed control for trucks will significantly reduce driver injury severity in accidents occurring at highway-rail grade crossings. In addition, several truck driver behavior characteristics (such as driving under influence of fatigue during peak hour) were found to be statistically significant predictors of high-level injury severity. Thus, education and enforcement targeted to truck drivers could facilitate safety improvements. Moreover, environmental factor (such as area type and roadway pavement) is found to be statistically significant. Truck drivers are more likely to have severe injury in open space area with low traffic volume compared with other areas. The bad weather and visibility condition is found to increase the probability of truck drivers’ high level injury severity.

ACS Style

Wei Hao; Camille Kamga; Xianfeng Yang; Jiaqi Ma; Ellen Thorson; Ming Zhong; Chaozhong Wu. Driver injury severity study for truck involved accidents at highway-rail grade crossings in the United States. Transportation Research Part F: Traffic Psychology and Behaviour 2016, 43, 379 -386.

AMA Style

Wei Hao, Camille Kamga, Xianfeng Yang, Jiaqi Ma, Ellen Thorson, Ming Zhong, Chaozhong Wu. Driver injury severity study for truck involved accidents at highway-rail grade crossings in the United States. Transportation Research Part F: Traffic Psychology and Behaviour. 2016; 43 ():379-386.

Chicago/Turabian Style

Wei Hao; Camille Kamga; Xianfeng Yang; Jiaqi Ma; Ellen Thorson; Ming Zhong; Chaozhong Wu. 2016. "Driver injury severity study for truck involved accidents at highway-rail grade crossings in the United States." Transportation Research Part F: Traffic Psychology and Behaviour 43, no. : 379-386.

Journal article
Published: 01 July 2016 in Transport Policy
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The Bus Rapid Transit (BRT) system in New York City (NYC), called Select Bus Service (SBS), is a “light” BRT system with some but not all BRT features. Focusing on it, this study aims to contribute to a better understanding of riders' perceptions of BRT service implemented with limited space and capital funding. A total of 1700 SBS riders on four routes were interviewed using the survey methodology developed in this study. Statistical analysis and regression modeling were used to analyze rider socio-demographics, investigate the relationship between rider satisfaction levels, and the key factors driving them. The results show that, while most of them are transit dependent, new SBS riders are mainly attracted by better service and accessibility. Riders on different routes were found to have different socio-demographics. The statistical tests of satisfaction means provide further insight into the disparity in service evaluation between/among groups of riders (e.g. gender, experience, weather, route, trip purpose). Service frequency, speed, and on-time performance were found to have a positive influence on rider satisfaction across all routes. Variables related to off-board ticket machines and travel information are more valued than others. The effects of external factors vary according to characteristics of the routes and rider groups. This study suggests potential applications of the results for future planning and improvement to increase rider satisfaction and thereby retain and increase ridership.

ACS Style

Dan Wan; Camille Kamga; Jun Liu; Aaron Sugiura; Eric B. Beaton. Rider perception of a “light” Bus Rapid Transit system - The New York City Select Bus Service. Transport Policy 2016, 49, 41 -55.

AMA Style

Dan Wan, Camille Kamga, Jun Liu, Aaron Sugiura, Eric B. Beaton. Rider perception of a “light” Bus Rapid Transit system - The New York City Select Bus Service. Transport Policy. 2016; 49 ():41-55.

Chicago/Turabian Style

Dan Wan; Camille Kamga; Jun Liu; Aaron Sugiura; Eric B. Beaton. 2016. "Rider perception of a “light” Bus Rapid Transit system - The New York City Select Bus Service." Transport Policy 49, no. : 41-55.

Comparative study
Published: 22 September 2015 in International Journal of Injury Control and Safety Promotion
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Based on the Federal Railway Administration (FRA) database, there were 25,945 highway–rail crossing accidents in the United States between 2002 and 2011. With an extensive research, analysis results showed that there were substantial differences between rural and urban areas at highway–rail grade crossings. However, there is no published study specific on driver's injury severity at highway–rail grade crossings classified by area types. Using an ordered probit modelling approach, the study explores the determinants of driver-injury severity at rural highway–rail grade crossings compared with urban highway–rail grade crossings. The analysis found that motor vehicle driver's injury level at rural highway–rail grade crossing is extremely higher than urban area. Compared to collisions at urban area, collisions happened at rural area tend to result in more severe injuries. These crashes were more prevalent if vehicle drivers are driving at a high speed or the oncoming trains are high-speed. Moreover, highway–rail grade crossing accidents were more likely to occur at rural area without pavement and lighting.

ACS Style

Wei Hao; Camille Kamga. Difference in rural and urban driver-injury severities in highway–rail grade crossing accidents. International Journal of Injury Control and Safety Promotion 2015, 24, 174 -182.

AMA Style

Wei Hao, Camille Kamga. Difference in rural and urban driver-injury severities in highway–rail grade crossing accidents. International Journal of Injury Control and Safety Promotion. 2015; 24 (2):174-182.

Chicago/Turabian Style

Wei Hao; Camille Kamga. 2015. "Difference in rural and urban driver-injury severities in highway–rail grade crossing accidents." International Journal of Injury Control and Safety Promotion 24, no. 2: 174-182.

Journal article
Published: 01 November 2014 in Waste Management
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Truck-based collection of municipal solid waste imposes significant negative externalities on cities and constrains the efficiency of separate collection of recyclables and organics and of unit-price-based waste-reduction systems. In recent decades, hundreds of municipal-scale pneumatic collection systems have been installed in Europe and Asia. Relatively few prior studies have compared the economic or environmental impacts of these systems to those of truck collection. A critical factor to consider when making this comparison is the extent to which the findings reflect the specific geographic, demographic, and operational characteristics of the systems considered. This paper is based on three case studies that consider the specific characteristics of three locations, comparing pneumatic systems with conventional collection on the basis of actual waste tonnages, composition, sources, collection routes, truck trips, and facility locations. In one case, alternative upgrades to an existing pneumatic system are compared to a potential truck-collection operation. In the other cases, existing truck operations are compared to proposed pneumatic systems which, to reduce capital costs, would be installed without new trenching or tunneling through the use of existing linear infrastructure. For the two proposed retrofit pneumatic systems, up to 48,000 truck kilometers travelled would be avoided and energy use would be reduced by up to 60% at an incremental cost of up to $400,000 USD per year over the total operating-plus-capital cost of conventional collection. In the location where a greenfield pneumatic system is already in operation, truck collection would be both less expensive and more energy-efficient than pneumatic collection. The results demonstrate that local geographic, demographic, and operational conditions play a decisive role in determining whether pneumatic collection will reduce energy requirements, produce more or fewer greenhouse gas emissions, and cost more or less over the long-term. These findings point to the local factors that will determine the relative economic and environmental costs and benefits in specific situations.

ACS Style

Benjamin Miller; Juliette Spertus; Camille Kamga. Costs and benefits of pneumatic collection in three specific New York City cases. Waste Management 2014, 34, 1957 -1966.

AMA Style

Benjamin Miller, Juliette Spertus, Camille Kamga. Costs and benefits of pneumatic collection in three specific New York City cases. Waste Management. 2014; 34 (11):1957-1966.

Chicago/Turabian Style

Benjamin Miller; Juliette Spertus; Camille Kamga. 2014. "Costs and benefits of pneumatic collection in three specific New York City cases." Waste Management 34, no. 11: 1957-1966.

Journal article
Published: 01 January 2014 in Flux
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This paper compares the economic and environmental impacts of truck collection of household waste with those of the pneumatic tube system employed by one New York City neighborhood, Roosevelt Island (RI), since 1975. Although all homes are connected to the pneumatic system, businesses and institutions are not, meaning that trucks still collect three-quarters of the Island’s waste. In order to assess the potential benefits of employing pneumatic tube systems in other New York neighborhoods, the paper discusses the findings of a 2013 feasibility study which analyzed potential upgrades and extensions to the network. The study confirmed the context-specific nature of collection impacts and found that on Roosevelt Island trucks are more energy-efficient than the pneumatic system. However, the pneumatic scenarios tested would reduce truck miles by up to 70%, and could lead to a system based on 90% electricity While direct operating costs are slightly lower for the tube-based scenarios, when debt service on the initial capital expenditures is included, pneumatic systems are 40 to 90% more expensive. The study did not calculate the local impacts of increased heavy-truck traffic, but it suggests that the relative cost of pneumatic collection may be offset by the public benefit of reductions in these local impacts as well as improved collection of recyclable materials.

ACS Style

Juliette Spertus; Benjamin Miller; Camille Kamga; Lisa Douglass; Brian Ross. Tubes vs. Trucks: A Comparative Analysis of the Impacts of Alternative Waste-Collection Methods with Specific Reference to Roosevelt Island in New York City. Flux 2014, N° 95, 6 .

AMA Style

Juliette Spertus, Benjamin Miller, Camille Kamga, Lisa Douglass, Brian Ross. Tubes vs. Trucks: A Comparative Analysis of the Impacts of Alternative Waste-Collection Methods with Specific Reference to Roosevelt Island in New York City. Flux. 2014; N° 95 (1):6.

Chicago/Turabian Style

Juliette Spertus; Benjamin Miller; Camille Kamga; Lisa Douglass; Brian Ross. 2014. "Tubes vs. Trucks: A Comparative Analysis of the Impacts of Alternative Waste-Collection Methods with Specific Reference to Roosevelt Island in New York City." Flux N° 95, no. 1: 6.