Investigating the Effect of Social and Cultural Factors on Drivers in Malaysia: A Naturalistic Driving Study

Road accidents are increasing every year in Malaysia, and it is always challenging to collect reliable pre-crash data in the transportation community. Existing studies relied on simulators, police crash reports, questionnaires, and surveys to study Malaysia’s drivers’ behavior. Researchers previously criticized such methods for being biased and unreliable. To fill in the literature gap, this study presents the first naturalistic driving study in Malaysia. Thirty drivers were recruited to drive an instrumented vehicle for 750 km while collecting continuous driving data. The data acquisition system consists of various sensors such as OBDII, lidar, ultrasonic sensors, IMU, and GPS. Irrelevant data were filtered, and experts helped identify safety criteria regarding multiple driving metrics such as maximum acceptable speed limits, safe accelerations, safe decelerations, acceptable distances to vehicles ahead, and safe steering behavior. These thresholds were used to investigate the influence of social and cultural factors on driving in Malaysia. The findings show statistically significant differences between drivers based on gender, age, and cultural background. There are also significant differences in the results for those who drove on weekends rather than weekdays. The study presents several recommendations to various public and governmental sectors to help prevent future accidents and improve traffic safety.

Analysis of Headway and Speed Based on Driver Characteristics and Work Zone Configurations Using Naturalistic Driving Study Data

The objective of this paper is to analyze headway and speed distribution based on driver characteristics and work zone (WZ) configurations by utilizing Naturalistic Driving Study (NDS) data. The NDS database provides a unique opportunity to study car-following behaviors for different driver types in various WZ configurations, which cannot be achieved from traditional field data collection. The complete NDS WZ trip data of 200 traversals and 103 individuals, including time-series data, forward-view videos, radar data, and driver characteristics, was collected at four WZ configurations, which encompasses nearly 1,100 vehicle miles traveled, 19 vehicle hours driven, and over 675,000 data points at 0.1 s intervals. First, the time headway selections were analyzed with driver characteristics such as the driver’s gender, age group, and risk perceptions to develop the headway selection table. Further, the speed profiles for different WZ configurations were established to explore the speed distribution and speed change. The best-fitted curves of time headway and speed distributions were estimated by the generalized additive model (GAM). The change point detection method was used to identify where significant changes in mean and variance of speeds occur. The results concluded that NDS data can be used to improve car-following models at WZs that have been implemented in current WZ planning and simulation tools by considering different headway distributions based on driver characteristics and their speed profiles while traversing the entire WZ.

Studying Battery Range and Range Anxiety for Electric Vehicles based on Real Travel Demands

Determination of appropriate battery ranges is critical for developing and utilizing electric cars, which remains an active research topic. In particular, the issues of range anxiety have not been well studied concerning the battery design. Towards these research gaps, this study firstly investigates the baseline battery ranges based on the actual travel data collected from a large-scale longitudinal naturalistic driving study in the Midwestern USA. The occurrences and severity levels of range anxiety are then studied given the baseline, which leads to an augmented optimization model to eliminate such issues. Results show that in the baseline model, 60% of drivers can replace their gas cars entirely with 400-mile battery ranges, and less than 40% can do so with 200-mile battery ranges. Even when all the travel needs are satisfied, the optimal battery ranges can still cause range anxiety issues for all the drivers. An additional 25 miles of battery range can help solve the problem based on the improved optimization results.

Driver Attention And The Built Environment Initial, Findings From A Naturalistic Driving Study

Maintaining driver attention is critical in multimodal urban spaces where risks to vulnerable users are not borne by the drivers that impose them. However, without an understanding of what it is within the built environment that elicits appropriate driver attention, it will be difficult to reduce the escalating tide of pedestrian fatalities we currently are experiencing. This study uses eye glance data from a naturalistic driving study tabulated for on-task vs. off-task driving and detailed tabulations of environmental variables to identify which features within the built environment have a significant impact on driver attention. An econometric utility model was generated that identified corridor pavement width, reduced drivewayspacing, and linearly aligned street trees as design features that have a positive impact on driver attention.One-way streets, undelineated parking or unstriped bicycle lanes reduce drivers need to attend. Recommendations for maintaining driver attention within urban spaces are included.