Although car-following behavior is the core component of microscopic traffic simulation, intelligent transportation systems, and advanced driver assistance systems, the adequacy of the existing car-following models for Chinese drivers has not been investigated with real-world data yet. To address this gap, five representative car-following models were calibrated and evaluated for Shanghai drivers, using 2,100 urban-expressway car-following periods extracted from the 161,055 km of driving data collected in the Shanghai Naturalistic Driving Study (SH-NDS). The models were calibrated for each of the 42 subject drivers, and their capabilities of predicting the drivers' car-following behavior were evaluated.The results show that the intelligent driver model (IDM) has good transferability to model traffic situations not presented in calibration, and it performs best among the evaluated models. Compared to the Wiedemann 99 model used by VISSIM ® , the IDM is easier to calibrate and demonstrates a better and more stable performance. These advantages justify its suitability for microscopic traffic simulation tools in Shanghai and likely in other regions of China. Additionally, considerable behavioral differences among different drivers were found, which demonstrates a need for archetypes of a variety of drivers to build a traffic mix in simulation. By comparing calibrated and observed values of the IDM parameters, this study found that 1) interpretable calibrated model parameters are linked with corresponding observable parameters in real world, but they are not necessarily numerically equivalent; and 2) parameters that can be measured in reality also need to be calibrated if better trajectory reproducing capability are to be achieved.

No abstract

No abstract

A transportation network is a conglomeration of road-traffic-environment modules and features multicategories of interdependent factors. This mix makes the management of safety in traffic analysis zones (TAZs) explicitly challenging. This study investigated the association between crash frequencies and various types of trip productions and attractions in combination with the road characteristics of 1,349 TAZs of four counties in the state of Florida. Crash safety management of these TAZs is emphasized through prioritizing them by examining the effects of trip and roadway factors on the aggregated crash frequencies. Models were developed separately for total crashes, severe crashes (fatal and severe injury crashes), total crashes during peak hours, and pedestrian- and bicycle-related crashes on the basis of various groups of estimators. It was found that the total crash model and the peak-hour crash model were best estimated by total trip productions and total trip attractions. The severe crash model was best fit by trip-related variables only, and the pedestrian- and bicycle-related crash model was best fit by road-related variables only. The results from this study pave the way for better safety management and the incorporation of safety measures in travel and network planning.

Analysis of lane change is important for microsimulation and safety improvement, and can also provide reference for advanced driver assistance systems (ADAS) and connected and autonomous vehicles (CAVs). Yet little research has comprehensively explored lane changing, particularly in China, a site of current CAV testing. This study developed an automatic extraction algorithm to retrieve 5,339 lane change events from the Shanghai Naturalistic Driving Study, and used the data to examine the core lane change components: gap acceptance, duration, and impact on the following vehicle (FV). Multilevel mixed-effects linear models were employed to develop relationships between gap acceptance and duration and the influencing factors; impact was then assessed using speed change rate, brake timestamping, and time-to-collision (TTC). Key results showed that 1) gap acceptance varied by roadway type and motivation, and lead and lag gaps were significantly affected by environmental variables, vehicle type, and kinematic parameters; 2) duration varied from 0.7 s to 16.1 s, significantly affected by variables similar to gap acceptance, but notably, not by motivation; 3) as many as 1 in 5 Chinese FV drivers responded to lane changes with acceleration exceeding 10%; 4) nearly half of FVs braked when they perceived a vehicle's lane-change intention, and 90% braked before TTC reached 4.7 s; 5) in over 70% of lane changes, the minimum TTC occurred between the initiation and cross-lane points. In addition to advancing the international development of lane-change theory, one of this study's important applications is that CAVs can be designed to brake during a safer TTC phase.

No abstract

No abstract

No abstract