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Dr. Feng Chen
College of Transportation Engineering, Tongji University, 1239 Siping Road, Shanghai, China

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0 Big Data
0 Human Factors
0 Reliability
0 Risk Assessment
0 Traffic Safety

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Traffic Safety
Finite Element Simulation
Big Data
Reliability
Risk Assessment
truck platooning
Pavement service life

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Journal article
Published: 08 July 2021 in Physica a
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The COVID-19 epidemic has had a major impact on people’s normal travel. Optimizing the control of the number of passengers boarding and deboarding the customized bus (CB) at CB stops can reduce the contact between passengers in the course of travel, which is meaningful for COVID-19 epidemic prevention and control. In this paper, a dynamic programming model based on nonlinear integer programming (NIP) is established to study the problem of boarding and alighting planning at various CB stops under the influence of COVID-19. Using Gurobi 9.1.1 solver, the optimal plan for passengers boarding and deboarding CB buses could be obtained. Besides, the mathematical model established in this paper can obtain the minimum value of the total number of contacts between passengers during travel under different CB numbers. It is found that the model solution results eventually form a Pareto frontier. When the number of CB buses increases, the total number of contacts between passengers will decrease This study has positive significance for ensuring the normal travel of passengers during the COVID-19 epidemic, and provides useful references for the studies about the planning of the customized bus.

ACS Style

Feng Chen; Haorong Peng; Wenlong Ding; Xiaoxiang Ma; Daizhong Tang; Yipeng Ye. Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19. Physica a 2021, 582, 126244 -126244.

AMA Style

Feng Chen, Haorong Peng, Wenlong Ding, Xiaoxiang Ma, Daizhong Tang, Yipeng Ye. Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19. Physica a. 2021; 582 ():126244-126244.

Chicago/Turabian Style

Feng Chen; Haorong Peng; Wenlong Ding; Xiaoxiang Ma; Daizhong Tang; Yipeng Ye. 2021. "Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19." Physica a 582, no. : 126244-126244.

Journal article
Published: 16 December 2020 in Transportation Research Part D: Transport and Environment
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Autonomous truck platoons are currently proposed to drive in an aligned form for saving fuel, which will cause repeated wheel loads and shorten pavements’ service life. Therefore, platoon’s form needs to be reconsidered. Several forms were proposed from the aspects of vehicle number, longitudinal interval and lateral offset. Their influence was evaluated based on the computational fluid dynamics simulations and finite element model. Parameters in the simulations were collected from laboratory tests. The average fuel-saving rate for a two-truck platoon is 3.8–8.9% when the longitudinal interval varies from 5L to 0.5L. The fuel-saving rate, however, grows at a decreasing rate with the increase in truck number. Besides, the lateral offset is found to be effective when organizing the two-truck platoon, and above 30% decrease in pavement fatigue damage and 8% fuel savings will be obtained concurrently. The findings help the policy makers to reconsider the management of platoons.

ACS Style

Mingtao Song; Feng Chen; Xiaoxiang Ma. Organization of autonomous truck platoon considering energy saving and pavement fatigue. Transportation Research Part D: Transport and Environment 2020, 90, 102667 .

AMA Style

Mingtao Song, Feng Chen, Xiaoxiang Ma. Organization of autonomous truck platoon considering energy saving and pavement fatigue. Transportation Research Part D: Transport and Environment. 2020; 90 ():102667.

Chicago/Turabian Style

Mingtao Song; Feng Chen; Xiaoxiang Ma. 2020. "Organization of autonomous truck platoon considering energy saving and pavement fatigue." Transportation Research Part D: Transport and Environment 90, no. : 102667.

Journal article
Published: 25 August 2020 in International Journal of Environmental Research and Public Health
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Walking is a sustainable mode of transport which has well established health and environmental benefits. Unfortunately, hundreds of thousands of pedestrians lose their lives each year over the world due to involvement in road traffic crashes, and mid-blocks witness a significant portion of pedestrian fatalities. This study examined the direct and indirect effects of various contributing factors on the pedestrian injury severity in vehicle–pedestrian crashes at mid-blocks. Data of vehicle–pedestrian crashes during 2002–2009 were extracted from the NASS-GES, with pre-crash behaviors and injury severity included. The SEM path analysis method was applied to uncover the inter-relationships between the pedestrian injury severity and various explanatory variables. Both the direct and indirect effects of these explanatory variables on the pedestrian injury severity were calculated based on the marginal effects in the multinomial and ordered logit models. The results indicate some variables including number of road lanes and the age of pedestrian have indirect impacts on the injury severity through influencing the pre-crash behaviors. Although most indirect effects are relatively small compared with the direct effects, the results in this study still provide some valuable information to improve the overall understanding of pedestrian injury severity at mid-blocks.

ACS Style

Haorong Peng; Xiaoxiang Ma; Feng Chen. Examining Injury Severity of Pedestrians in Vehicle–Pedestrian Crashes at Mid-Blocks Using Path Analysis. International Journal of Environmental Research and Public Health 2020, 17, 6170 .

AMA Style

Haorong Peng, Xiaoxiang Ma, Feng Chen. Examining Injury Severity of Pedestrians in Vehicle–Pedestrian Crashes at Mid-Blocks Using Path Analysis. International Journal of Environmental Research and Public Health. 2020; 17 (17):6170.

Chicago/Turabian Style

Haorong Peng; Xiaoxiang Ma; Feng Chen. 2020. "Examining Injury Severity of Pedestrians in Vehicle–Pedestrian Crashes at Mid-Blocks Using Path Analysis." International Journal of Environmental Research and Public Health 17, no. 17: 6170.

Journal article
Published: 16 June 2020 in Journal of Wind Engineering and Industrial Aerodynamics
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To study the effect of complex terrain on the wind characteristics of the glide paths at Hong Kong International Airport’s North Runway, wind tunnel testing was conducted in Tongji University’s TJ-3 boundary layer wind tunnel, and Cobra probes were used to measure the wind speed and wind direction at the North Runway glide paths. The effects of terrain on the wind characteristics, including turbulence intensity, turbulence integral scale, and mean headwind speed were analysed. The results show that the terrain fluctuations have a significant effect on the wind characteristics of the glide paths. The turbulence intensities in the cross-wind direction and the vertical direction increase with increasing turbulence intensity in the wind direction at the same altitude; the inflow may affect aircraft landing due to the decrease in headwind speed at glide path 25RA caused by the obstruction of certain terrain.

ACS Style

Feng Chen; Haorong Peng; Pak-Wai Chan; Xiaoqing Zeng. Wind tunnel testing of the effect of terrain on the wind characteristics of airport glide paths. Journal of Wind Engineering and Industrial Aerodynamics 2020, 203, 104253 .

AMA Style

Feng Chen, Haorong Peng, Pak-Wai Chan, Xiaoqing Zeng. Wind tunnel testing of the effect of terrain on the wind characteristics of airport glide paths. Journal of Wind Engineering and Industrial Aerodynamics. 2020; 203 ():104253.

Chicago/Turabian Style

Feng Chen; Haorong Peng; Pak-Wai Chan; Xiaoqing Zeng. 2020. "Wind tunnel testing of the effect of terrain on the wind characteristics of airport glide paths." Journal of Wind Engineering and Industrial Aerodynamics 203, no. : 104253.

Journal article
Published: 17 April 2020 in International Journal of Environmental Research and Public Health
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This study presents an empirical investigation of the impacts of real-time weather conditions on the freeway crash severity. A Bayesian spatial generalized ordered logit model was developed for modeling the crash severity using the hourly wind speed, air temperature, precipitation, visibility, and humidity, as well as other observed factors. A total of 1424 crash records from Kaiyang Freeway, China in 2014 and 2015 were collected for the investigation. The proposed model can simultaneously accommodate the ordered nature in severity levels and spatial correlation across adjacent crashes. Its strength is demonstrated by the existence of significant spatial correlation and its better model fit and more reasonable estimation results than the counterparts of a generalized ordered logit model. The estimation results show that an increase in the precipitation is associated with decreases in the probabilities of light and severe crashes, and an increase in the probability of medium crashes. Additionally, driver type, vehicle type, vehicle registered province, crash time, crash type, response time of emergency medical service, and horizontal curvature and vertical grade of the crash location, were also found to have significant effects on the crash severity. To alleviate the severity levels of crashes on rainy days, some engineering countermeasures are suggested, in addition to the implemented strategies.

ACS Style

Qiang Zeng; Wei Hao; Jaeyoung Lee; Feng Chen. Investigating the Impacts of Real-Time Weather Conditions on Freeway Crash Severity: A Bayesian Spatial Analysis. International Journal of Environmental Research and Public Health 2020, 17, 2768 .

AMA Style

Qiang Zeng, Wei Hao, Jaeyoung Lee, Feng Chen. Investigating the Impacts of Real-Time Weather Conditions on Freeway Crash Severity: A Bayesian Spatial Analysis. International Journal of Environmental Research and Public Health. 2020; 17 (8):2768.

Chicago/Turabian Style

Qiang Zeng; Wei Hao; Jaeyoung Lee; Feng Chen. 2020. "Investigating the Impacts of Real-Time Weather Conditions on Freeway Crash Severity: A Bayesian Spatial Analysis." International Journal of Environmental Research and Public Health 17, no. 8: 2768.

Journal article
Published: 27 February 2020 in Journal of Cleaner Production
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Construction and maintenance of road pavements are both expensive and environmentally unfriendly. The prolongation of pavement life can reduce material consumption and produce a cleaning effect. This study attempts to propose a lateral control scheme for autonomous vehicles that aims at maximizing pavement life. In the key unit of the scheme, the trajectory-oriented method and fatigue damage-oriented method were compared that would be applied to assign vehicle lateral positions. The simulation of a specific pavement structure had been conducted to calculate the fatigue damage growth with the lateral control scheme. The comparison among different methods revealed that fatigue damage-oriented method performs best. Using the fatigue damage-oriented method, fatigue damage growth decreased by 28% when trucks were 100% autonomous vehicles. Besides, the fatigue damage oriented method was found to be insensitive to the autonomous vehicle proportion higher than 20%. The example of dealing with two lanes situation suggests this scheme was also suitable for minimizing the fatigue difference caused by vehicle volume difference on two lanes.

ACS Style

Feng Chen; Mingtao Song; Xiaoxiang Ma. A lateral control scheme of autonomous vehicles considering pavement sustainability. Journal of Cleaner Production 2020, 256, 120669 .

AMA Style

Feng Chen, Mingtao Song, Xiaoxiang Ma. A lateral control scheme of autonomous vehicles considering pavement sustainability. Journal of Cleaner Production. 2020; 256 ():120669.

Chicago/Turabian Style

Feng Chen; Mingtao Song; Xiaoxiang Ma. 2020. "A lateral control scheme of autonomous vehicles considering pavement sustainability." Journal of Cleaner Production 256, no. : 120669.

Journal article
Published: 22 February 2020 in Tunnelling and Underground Space Technology
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In long tunnels where the driving environment is boring and monotonous, the speed perception of drivers is usually compromised. Although researchers have conducted a host of studies on driving safety in tunnels and found out that the sidewall environment was a significant factor that affected driver behavior inside tunnels, little is known regarding the mechanism of how the tunnel sidewall impacts the drivers, especially which regions of neural system are related to the impact of the sidewall. To fill this gap, the current study aims at examining the influence of the decorated tunnel sidewall on drivers’ brain activity using fMRI. To this end, an experiment was conducted where thirty-five subjects are recruited. The experiment was conducted using fMRI under two tunnel scenarios: empty sidewall and decorated sidewall. The video of the driving scene was taken in the real driving environment of a tunnel and presented by a projector outside the operating room. The results showed that the fusiform gyrus and precuneus were more activated in tunnels with the decorated sidewall than that with an empty sidewall. These regions are known to be responsible for visual recognition, visual processing and visual spatial functions. Therefore, it indicates that the presence of decorated sidewall provides drivers with a better spatial and speed perception and could help reduce accidents associated with speed judgment. The differences between driver groups were also explored and the finding revealed that the activation level of superior frontal gyrus is different between male and female drivers, which indicated that the same sidewall decoration has different effect between driver groups.

ACS Style

Peiyan Chen; Feng Chen; Lin Zhang; Xiaoxiang Ma; Xiaodong Pan. Examining the influence of decorated sidewaall in road tunnels using fMRI technology. Tunnelling and Underground Space Technology 2020, 99, 103362 .

AMA Style

Peiyan Chen, Feng Chen, Lin Zhang, Xiaoxiang Ma, Xiaodong Pan. Examining the influence of decorated sidewaall in road tunnels using fMRI technology. Tunnelling and Underground Space Technology. 2020; 99 ():103362.

Chicago/Turabian Style

Peiyan Chen; Feng Chen; Lin Zhang; Xiaoxiang Ma; Xiaodong Pan. 2020. "Examining the influence of decorated sidewaall in road tunnels using fMRI technology." Tunnelling and Underground Space Technology 99, no. : 103362.

Journal article
Published: 07 January 2020 in International Journal of Environmental Research and Public Health
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Social and economic burdens caused by truck-involved rear-end collisions are of great concern to public health and the environment. However, few efforts focused on identifying the difference of impacting factors on injury severity between car-strike-truck and truck-strike-car in rear-end collisions. In light of the above, this study focuses on illustrating the impact of variables associated with injury severity in truck-related rear-end crashes. To this end, truck involved rear-end crashes between 2006 and 2015 in the U.S. were obtained. Three random parameters ordered probit models were developed: two separate models for the car-strike-truck crashes and the truck-strike-car crashes, respectively, and one for the combined dataset. The likelihood ratio test was conducted to evaluate the significance of the difference between the models. The results show that there is a significant difference between car-strike-truck and truck-strike-car crashes in terms of contributing factors towards injury severity. In addition, indicators reflecting male, truck, starting or stopped in the road before a crash, and other vehicles stopped in lane show a mixed impact on injury severity. Corresponding implications were discussed according to the findings to reduce the possibility of severe injury in truck-involved rear-end collisions.

ACS Style

Xiaojun Shao; Xiaoxiang Ma; Feng Chen; Mingtao Song; Xiaodong Pan; Kesi You. A Random Parameters Ordered Probit Analysis of Injury Severity in Truck Involved Rear-End Collisions. International Journal of Environmental Research and Public Health 2020, 17, 395 .

AMA Style

Xiaojun Shao, Xiaoxiang Ma, Feng Chen, Mingtao Song, Xiaodong Pan, Kesi You. A Random Parameters Ordered Probit Analysis of Injury Severity in Truck Involved Rear-End Collisions. International Journal of Environmental Research and Public Health. 2020; 17 (2):395.

Chicago/Turabian Style

Xiaojun Shao; Xiaoxiang Ma; Feng Chen; Mingtao Song; Xiaodong Pan; Kesi You. 2020. "A Random Parameters Ordered Probit Analysis of Injury Severity in Truck Involved Rear-End Collisions." International Journal of Environmental Research and Public Health 17, no. 2: 395.

Review article
Published: 03 January 2020 in Journal of Advanced Transportation
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A truck platoon is a set of virtually linked trucks that travel in tandem with small intervehicle distances. Several studies have proved that traveling in platoons can significantly improve fuel economy due to the reduced aerodynamic drag. However, most literature only provides scattered pieces of information regarding fuel economy in truck platoons. Therefore, a literature survey is needed to understand what has been studied and what problems remain to be further addressed. This paper presents an overview of existing studies to illustrate the state of the art about fuel savings for truck platooning. Specifically, it summarized the methodologies, the contributing factors of fuel consumption, the coordination methods to improve the platooning rate, and the look-ahead control strategies to generate fuel-efficient speed profiles for each vehicle driving in a platoon over different road grades. After that, the autonomous truck platooning was introduced, and we raised and discussed a couple of outstanding questions to be addressed in future work.

ACS Style

Linlin Zhang; Feng Chen; Xiaoxiang Ma; Xiaodong Pan. Fuel Economy in Truck Platooning: A Literature Overview and Directions for Future Research. Journal of Advanced Transportation 2020, 2020, 1 -10.

AMA Style

Linlin Zhang, Feng Chen, Xiaoxiang Ma, Xiaodong Pan. Fuel Economy in Truck Platooning: A Literature Overview and Directions for Future Research. Journal of Advanced Transportation. 2020; 2020 ():1-10.

Chicago/Turabian Style

Linlin Zhang; Feng Chen; Xiaoxiang Ma; Xiaodong Pan. 2020. "Fuel Economy in Truck Platooning: A Literature Overview and Directions for Future Research." Journal of Advanced Transportation 2020, no. : 1-10.

Journal article
Published: 01 October 2019 in Building and Environment
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ACS Style

Feng Chen; Haorong Peng; Pak-Wai Chan; Xiaoqing Zeng. Low-level wind effects on the glide paths of the North Runway of HKIA: A wind tunnel study. Building and Environment 2019, 164, 1 .

AMA Style

Feng Chen, Haorong Peng, Pak-Wai Chan, Xiaoqing Zeng. Low-level wind effects on the glide paths of the North Runway of HKIA: A wind tunnel study. Building and Environment. 2019; 164 ():1.

Chicago/Turabian Style

Feng Chen; Haorong Peng; Pak-Wai Chan; Xiaoqing Zeng. 2019. "Low-level wind effects on the glide paths of the North Runway of HKIA: A wind tunnel study." Building and Environment 164, no. : 1.

Journal article
Published: 01 October 2019 in Tunnelling and Underground Space Technology
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ACS Style

Feng Chen; Haorong Peng; Xiaoxiang Ma; Jieyu Liang; Wei Hao; Xiaodong Pan. Examining the safety of trucks under crosswind at bridge-tunnel section: A driving simulator study. Tunnelling and Underground Space Technology 2019, 92, 1 .

AMA Style

Feng Chen, Haorong Peng, Xiaoxiang Ma, Jieyu Liang, Wei Hao, Xiaodong Pan. Examining the safety of trucks under crosswind at bridge-tunnel section: A driving simulator study. Tunnelling and Underground Space Technology. 2019; 92 ():1.

Chicago/Turabian Style

Feng Chen; Haorong Peng; Xiaoxiang Ma; Jieyu Liang; Wei Hao; Xiaodong Pan. 2019. "Examining the safety of trucks under crosswind at bridge-tunnel section: A driving simulator study." Tunnelling and Underground Space Technology 92, no. : 1.

Journal article
Published: 23 July 2019 in International Journal of Environmental Research and Public Health
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The existing studies on drivers’ injury severity include numerous statistical models that assess potential factors affecting the level of injury. These models should address specific concerns tailored to different crash characteristics. For rear-end crashes, potential correlation in injury severity may present between the two drivers involved in the same crash. Moreover, there may exist unobserved heterogeneity considering parameter effects, which may vary across both crashes and individuals. To address these concerns, a random parameters bivariate ordered probit model has been developed to examine factors affecting injury sustained by two drivers involved in the same rear-end crash between passenger cars. Taking both the within-crash correlation and unobserved heterogeneity into consideration, the proposed model outperforms the two separate ordered probit models with fixed parameters. The value of the correlation parameter demonstrates that there indeed exists significant correlation between two drivers’ injuries. Driver age, gender, vehicle, airbag or seat belt use, traffic flow, etc., are found to affect injury severity for both the two drivers. Some differences can also be found between the two drivers, such as the effect of light condition, crash season, crash position, etc. The approach utilized provides a possible use for dealing with similar injury severity analysis in future work.

ACS Style

Feng Chen; Mingtao Song; Xiaoxiang Ma. Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model. International Journal of Environmental Research and Public Health 2019, 16, 2632 .

AMA Style

Feng Chen, Mingtao Song, Xiaoxiang Ma. Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model. International Journal of Environmental Research and Public Health. 2019; 16 (14):2632.

Chicago/Turabian Style

Feng Chen; Mingtao Song; Xiaoxiang Ma. 2019. "Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model." International Journal of Environmental Research and Public Health 16, no. 14: 2632.

Conference paper
Published: 01 July 2019 in 2019 5th International Conference on Transportation Information and Safety (ICTIS)
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Improving pedestrian safety is one of the top priorities of different transportation agencies. However, vehicle-pedestrian crashes continue to claim a large toll on fatalities. According to NHSTA, the 5,987 pedestrian fatalities amount to 16 percent of all traffic fatalities in the U.S in 2016. While most of past studies focused on pedestrian crashes at intersections, only 18 percent of the total vehicle-pedestrian crashes happened at the intersections. The vehicle-pedestrian crashes at mid-block crossings were largely ignored. The objective of this study is to examine the contributing factors of pedestrians’ injury severities at mid-blocks and uncover the effects of pedestrians’ pre-crash behavior. To this end, crash records involving pedestrian at the mid-blocks were acquired from the General Estimates System. The pedestrians’ characteristics, their pre-crash behaviors, road geometrics, and crash characteristics were all processed together. A random parameter ordered probit model was developed to account for unobserved heterogeneities in the data. The results show that time of the crashes, crash characteristics, roadway features, and pedestrian characteristic are all significant in determining the injury severity levels of pedestrians. In addition, after accounting for these variables, pedestrians’ pre-crash behavior also plays a significant role in severity outcomes. The findings from this study bears policy potentials to help devise informed injury mitigation strategies at the mid-block crossings.

ACS Style

Zhidan Yang; Feng Chen; Xiaoxiang Ma; Bowen Dong. Injury Severity of Pedestrians at Mid-blocks: A Random Parameter Ordered Probit Approach. 2019 5th International Conference on Transportation Information and Safety (ICTIS) 2019, 735 -740.

AMA Style

Zhidan Yang, Feng Chen, Xiaoxiang Ma, Bowen Dong. Injury Severity of Pedestrians at Mid-blocks: A Random Parameter Ordered Probit Approach. 2019 5th International Conference on Transportation Information and Safety (ICTIS). 2019; ():735-740.

Chicago/Turabian Style

Zhidan Yang; Feng Chen; Xiaoxiang Ma; Bowen Dong. 2019. "Injury Severity of Pedestrians at Mid-blocks: A Random Parameter Ordered Probit Approach." 2019 5th International Conference on Transportation Information and Safety (ICTIS) , no. : 735-740.

Conference paper
Published: 01 July 2019 in 2019 5th International Conference on Transportation Information and Safety (ICTIS)
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With the continuous investment in the field of autonomous truck driving technology, fully autonomous self-driving trucks are set to become a reality soon. As a potential fuel-efficient driving mode of autonomous trucks, the truck platoon has been proposed and attracts great attention to vehicles connecting and control. However, simplified as an extreme long vehicle, autonomous truck platoon will undoubtedly affect the performance of traffic flow as it has an uncertain effect on the behavior of other vehicle drivers such as following and lane changing. Obviously, this effect deserves much attention. Besides, whether to set the special lane for platoons will become a notable issue considering traffic efficiency. To solve these problems, simulation of traffic flow will be the proper way. In this study, a three-lane cellular automaton (CA) model is proposed and the updated forwarding and lane changing rules are described in detail. Truck platoons contain two truck are considered. Based on the CA model, the influence of autonomous truck platoons on traffic flow such as lane changing frequency and average traffic speed is evaluated. Besides, the fundamental diagram of traffic flow is conducted. Compared to the existing cellular automaton models, the lane changing rules adopted in the proposed model differ according to driving scenarios and cell number varies in vehicle types in this study. As the results of numerical simulations show, to limit platoons on the special lane can higher the average speed of traffic flow and reduce the lane changing frequency. The existence of platoons improves the average traffic speed while setting special lane for platoons. However, when the traffic density grows up, this positive effect dissipates gradually.

ACS Style

Mingtao Song; Feng Chen; Xiaoxiang Ma. A Simulation of the Traffic Behavior with Autonomous Truck Platoons Based on Cellular Automaton. 2019 5th International Conference on Transportation Information and Safety (ICTIS) 2019, 416 -423.

AMA Style

Mingtao Song, Feng Chen, Xiaoxiang Ma. A Simulation of the Traffic Behavior with Autonomous Truck Platoons Based on Cellular Automaton. 2019 5th International Conference on Transportation Information and Safety (ICTIS). 2019; ():416-423.

Chicago/Turabian Style

Mingtao Song; Feng Chen; Xiaoxiang Ma. 2019. "A Simulation of the Traffic Behavior with Autonomous Truck Platoons Based on Cellular Automaton." 2019 5th International Conference on Transportation Information and Safety (ICTIS) , no. : 416-423.

Journal article
Published: 03 June 2019 in Transportation Research Part C: Emerging Technologies
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Vehicles are extremely vulnerable to single-vehicle accidents under some hazardous driving conditions (i.e. strong wind, icy or snowy road surface). An integrated framework is proposed to assess single-vehicle traffic safety performance of stochastic traffic flow under hazardous driving conditions. Different from most existing studies focusing on a single vehicle moving at a constant speed, for the first time, the proposed work evaluates individual vehicle safety performance based on the time-dependent simulation results of stochastic traffic flow, including instantaneous speeds and positions of each vehicle as a part of simulated traffic flow. Simultaneously, complex geometric and other environmental conditions of the highway system are also considered realistically, not only during the safety assessment process, but also in quantifying the wind loads applied on the vehicles. Finally, with the safety information of each individual vehicle, an overall safety performance index of the whole traffic flow on the highway system is further introduced, which serves as a potential traffic safety performance measure and resilience indicator of transportation infrastructure systems under various hazards. This study has potential applications to not only regular vehicles, but also advanced traffic management and control algorithms for connected and autonomous vehicles in hazardous driving environments.

ACS Style

Guangyang Hou; Suren Chen; Feng Chen. Framework of simulation-based vehicle safety performance assessment of highway system under hazardous driving conditions. Transportation Research Part C: Emerging Technologies 2019, 105, 23 -36.

AMA Style

Guangyang Hou, Suren Chen, Feng Chen. Framework of simulation-based vehicle safety performance assessment of highway system under hazardous driving conditions. Transportation Research Part C: Emerging Technologies. 2019; 105 ():23-36.

Chicago/Turabian Style

Guangyang Hou; Suren Chen; Feng Chen. 2019. "Framework of simulation-based vehicle safety performance assessment of highway system under hazardous driving conditions." Transportation Research Part C: Emerging Technologies 105, no. : 23-36.

Journal article
Published: 05 April 2019 in Transportation Research Part C: Emerging Technologies
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With ongoing massive investment in the field of autonomous vehicles, fully autonomous self-driving vehicles are set to become a reality soon. Despite the benefits in traffic safety and economy, the potential effects of autonomous vehicles, especially autonomous trucks, on transportation infrastructure remain to be determined. In this study, a finite element model was developed based on a typical flexible pavement structure. The effects of autonomous trucks’ lateral distribution within the lane with respect to rutting depth and fatigue damage were estimated by finite element analysis under certain environmental condition. Characteristics of the pavement structure and environmental condition have been collected and presented in this paper. Four possible lateral control modes on managing autonomous trucks’ lateral distribution were proposed, listed as zero-wander mode, uniform mode, double peak Gaussian mode, two-section uniform mode. Considering the difference between autonomous trucks and human-driven trucks, the ratio of autonomous trucks was also evaluated. Based on the simulation results, it has been confirmed that, if controlled appropriately, autonomous trucks could be highly beneficial to asphalt pavements for wider using of pavement. Conversely, if without appropriate lateral control, the effect of autonomous trucks on the typical flexible pavement life could be negative, owing to repeated single point load caused by lane centering and keeping. For example, the uniform mode, double peak Gaussian mode and two-section uniform mode all throw positive effect on the pavement. On the contrary, under the zero wander mode, the time when the rutting depth of the proposed pavement reaches 15 mm (defined as maintenance year) may advance by 1.56 years and fatigue damage at the bottom of asphalt layer increases by 146%. Compared with the normal situation nowadays, the two-section uniform distribution of autonomous trucks, the best performing control mode, delays the maintenance year by 2.3 years. From the aspect of fatigue, a much uniform distribution curve of fatigue within the lane can also be found under this mode. When all trucks’ lateral positions were in control, the two-section uniform mode could reduce the fatigue damage by up to 35% under repeated standard axle load on the flexible pavement. Finally, a framework of dealing with the lateral control was proposed as a reference for different conditions, such as asphalt pavement structures and materials.

ACS Style

Feng Chen; Mingtao Song; Xiaoxiang Ma; Xingyi Zhu. Assess the impacts of different autonomous trucks’ lateral control modes on asphalt pavement performance. Transportation Research Part C: Emerging Technologies 2019, 103, 17 -29.

AMA Style

Feng Chen, Mingtao Song, Xiaoxiang Ma, Xingyi Zhu. Assess the impacts of different autonomous trucks’ lateral control modes on asphalt pavement performance. Transportation Research Part C: Emerging Technologies. 2019; 103 ():17-29.

Chicago/Turabian Style

Feng Chen; Mingtao Song; Xiaoxiang Ma; Xingyi Zhu. 2019. "Assess the impacts of different autonomous trucks’ lateral control modes on asphalt pavement performance." Transportation Research Part C: Emerging Technologies 103, no. : 17-29.

Research article
Published: 29 August 2018 in Transportation Research Record: Journal of the Transportation Research Board
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Strong crosswind is one of the main factors that may cause traffic collisions. Because the wind velocity is influenced by the roadside environment and surrounding terrain, its distribution varies in both the temporal and spatial domains. Therefore, locations with a high probability of strong crosswind should be identified and safety measures should be implemented at these sites. However, geographical data of continuous winds along a highway cannot easily be obtained using existing technology. This prompted the development of a method for geo-location positioning and terrain analysis with elevation data in ArcGIS in combination with mobile mapping technology. The method was applied in a field test conducted on three different highways in China to identify places at which stronger crosswinds occur. The results showed that the proposed method can successfully obtain site-specific wind and crosswind velocity data. It was found that strong winds along the tested highways usually occur at a saddleback or at the border of a riverbank and river, whereas crosswinds are relatively stronger in sections connecting a bridge and tunnel, a bridgehead, or a cross-sea bridge. This information will be useful for future highway projects and traffic safety assessment.

ACS Style

Yatian Pu; Feng Chen; Peiyan Chen; Xiaodong Pan. Wind Data Collection and Analysis of Topographical Features along a Highway for Traffic Safety Assessment Based on Mobile Mapping Technology. Transportation Research Record: Journal of the Transportation Research Board 2018, 2672, 292 -301.

AMA Style

Yatian Pu, Feng Chen, Peiyan Chen, Xiaodong Pan. Wind Data Collection and Analysis of Topographical Features along a Highway for Traffic Safety Assessment Based on Mobile Mapping Technology. Transportation Research Record: Journal of the Transportation Research Board. 2018; 2672 (42):292-301.

Chicago/Turabian Style

Yatian Pu; Feng Chen; Peiyan Chen; Xiaodong Pan. 2018. "Wind Data Collection and Analysis of Topographical Features along a Highway for Traffic Safety Assessment Based on Mobile Mapping Technology." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 42: 292-301.

Research article
Published: 17 June 2018 in Transportation Research Record: Journal of the Transportation Research Board
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Non-motorized travel is considered as one of the most beneficial transportation modes. Compared with other road users, non-motorists as a whole account for about 13% of all fatal transportation-related accidents, and from 2002 to 2009 nearly 30% of those fatalities occur at mid-blocks. In addition, there are few reported studies that investigated the impact of non-motorists’ pre-crash behavior on injury severities. To examine the risk factors of non-motorist injury severity at mid-blocks, 8-year crash-related data from the General Estimates System were explored, based on the mixed logit model. The data contain various information including time characteristics, crash features, environmental conditions, roadway attributes, non-motorists’ characteristics, and their pre-crash behaviors. The results show that five factors tend to have mixed effects on injury severities, including the speed limit between 30 and 55 mph, night time indicator, right-side collision, and hit-and-run action on the incapacitating injury, as well as no action of motorists on the non-incapacitating injury. Moreover, heavy and light truck, dark not lighted indicator, and age over 65 are found to increase the likelihood of fatal injury, while age below 25 decreases the likelihood of fatality. Other indicators including roadway alignment, number of lanes, and so forth also affected injury severity. After controlling for these factors, non-motorists’ pre-crash behaviors such as darting or running into the road, activities in the roadway, and improper passing are found to have a significant impact on severity outcomes.

ACS Style

Bowen Dong; Xiaoxiang Ma; Feng Chen. Analyzing the Injury Severity Sustained by Non-Motorists at Mid-Blocks considering Non-Motorists’ Pre-Crash Behavior. Transportation Research Record: Journal of the Transportation Research Board 2018, 2672, 138 -148.

AMA Style

Bowen Dong, Xiaoxiang Ma, Feng Chen. Analyzing the Injury Severity Sustained by Non-Motorists at Mid-Blocks considering Non-Motorists’ Pre-Crash Behavior. Transportation Research Record: Journal of the Transportation Research Board. 2018; 2672 (38):138-148.

Chicago/Turabian Style

Bowen Dong; Xiaoxiang Ma; Feng Chen. 2018. "Analyzing the Injury Severity Sustained by Non-Motorists at Mid-Blocks considering Non-Motorists’ Pre-Crash Behavior." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 38: 138-148.

Journal article
Published: 01 June 2018 in Journal of Safety Research
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Driving environment, including road surface conditions and traffic states, often changes over time and influences crash probability considerably. It becomes stretched for traditional crash frequency models developed in large temporal scales to capture the time-varying characteristics of these factors, which may cause substantial loss of critical driving environmental information on crash prediction. Crash prediction models with refined temporal data (hourly records) are developed to characterize the time-varying nature of these contributing factors. Unbalanced panel data mixed logit models are developed to analyze hourly crash likelihood of highway segments. The refined temporal driving environmental data, including road surface and traffic condition, obtained from the Road Weather Information System (RWIS), are incorporated into the models. Model estimation results indicate that the traffic speed, traffic volume, curvature and chemically wet road surface indicator are better modeled as random parameters. The estimation results of the mixed logit models based on unbalanced panel data show that there are a number of factors related to crash likelihood on I-25. Specifically, weekend indicator, November indicator, low speed limit and long remaining service life of rutting indicator are found to increase crash likelihood, while 5-am indicator and Number of merging ramps per lane per mile are found to decrease crash likelihood. The study underscores and confirms the unique and significant impacts on crash imposed by the real-time weather, road surface and traffic conditions. With the unbalanced panel data structure, the rich information from real-time driving environmental big data can be well incorporated.

ACS Style

Feng Chen; Suren Chen; Xiaoxiang Ma. Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data. Journal of Safety Research 2018, 65, 153 -159.

AMA Style

Feng Chen, Suren Chen, Xiaoxiang Ma. Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data. Journal of Safety Research. 2018; 65 ():153-159.

Chicago/Turabian Style

Feng Chen; Suren Chen; Xiaoxiang Ma. 2018. "Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data." Journal of Safety Research 65, no. : 153-159.

Journal article
Published: 01 February 2018 in Journal of Transportation Engineering, Part A: Systems
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Crash rate data are mainly analyzed using the Tobit model. However, there are three major limitations associated with the Tobit model when it is applied to crash data: (1) the assumption that zeros are originated from the data generating process, (2) the presumption of a normal distribution of the latent response variable, and (3) the Tobit proportionality assumption. Moreover, unobserved heterogeneities are usually present, which lead to biased results in crash analyses. To address these limitations, the marginalized two-part model with random parameter specification is proposed as an alternative to the Tobit model. For comparison purposes, four models are developed: (1) Tobit model, (2) fixed parameter marginalized two-part (FPMTP) model, (3) uncorrelated random parameter marginalized two-part (URPMTP) model, and (4) correlated random parameter marginalized two-part (CRPMTP) model. The proposed methodology is demonstrated by investigating daily crash rates on a major freeway in Colorado. Model estimation results show that marginalized two-part models outperform the Tobit model, exhibiting good potential for future adoption when studying crash rates. Among the three two-part models, CRPMTP outperforms the other two, indicating that the correlated random parameter model can better capture the unobserved heterogeneities. Furthermore, the time-varying variables, including traffic and weather variables, are also found to play a significant role in crash occurrence.

ACS Style

Xiaoxiang Ma; Suren Chen; Feng Chen. Correlated Random Parameter Marginalized Two-Part Model: Application to Refined-Scale Longitudinal Crash Rates Data. Journal of Transportation Engineering, Part A: Systems 2018, 144, 04017071 .

AMA Style

Xiaoxiang Ma, Suren Chen, Feng Chen. Correlated Random Parameter Marginalized Two-Part Model: Application to Refined-Scale Longitudinal Crash Rates Data. Journal of Transportation Engineering, Part A: Systems. 2018; 144 (2):04017071.

Chicago/Turabian Style

Xiaoxiang Ma; Suren Chen; Feng Chen. 2018. "Correlated Random Parameter Marginalized Two-Part Model: Application to Refined-Scale Longitudinal Crash Rates Data." Journal of Transportation Engineering, Part A: Systems 144, no. 2: 04017071.