scholarly journals Prioritizing Safety or Traffic Flow? Qualitative Study on Highly Automated Vehicles’ Potential to Prevent Pedestrian Crashes with Two Different Ambitions

2020 ◽  
Vol 12 (8) ◽  
pp. 3206
Author(s):  
Roni Utriainen ◽  
Markus Pöllänen
Keyword(s):  
Qualitative Study ◽  
Traffic Flow ◽  
Pedestrian Safety ◽  
Automated Vehicles ◽  
Passenger Cars ◽  
High Expectations ◽  
Fatal Crashes ◽  
Pedestrian Crashes

Interaction between drivers and pedestrians enables pedestrians to cross the street without conflicts. When highly automated vehicles (HAVs) become prevalent, interaction will change. Although HAVs manage to identify pedestrians, they may not be able to assess pedestrians’ intentions. This study discusses two different ambitions: Prioritizing pedestrian safety and prioritizing efficient traffic flow; and how these two affect the possibilities to avoid fatal crashes between pedestrians and passenger cars. HAVs’ hypothetical possibilities to avoid different crash scenarios are evaluated based on 40 in-depth investigated fatal pedestrian crashes, which occurred with manually-driven cars in Finland in 2014–2016. When HAVs prioritize pedestrian safety, they decrease speed near pedestrians as a precaution which affects traffic flow due to frequent decelerations. When HAVs prioritize efficient traffic flow, they only decelerate, when pedestrians are in a collision course. The study shows that neither of these approaches can be applied in all traffic environments, and all of the studied crashes would not likely be avoidable with HAVs even when prioritizing pedestrian safety. The high expectations of HAVs’ safety benefits may not be realized, and in addition to safety and traffic flow, there are many other objectives in traffic which need to be considered.

scholarly journals On lane assignment of connected automated vehicles: strategies to improve traffic flow at diverge and weave bottlenecks

2021 ◽  
Vol 127 ◽  
pp. 103126
Author(s):  
Hari Hara Sharan Nagalur Subraveti ◽  
Anupam Srivastava ◽  
Soyoung Ahn ◽  
Victor L. Knoop ◽  
Bart van Arem
Keyword(s):  
Traffic Flow ◽  
Automated Vehicles ◽  
Connected Automated Vehicles

Cellular Automata–Based Modeling and Simulation of a Mixed Traffic Flow of Manual and Automated Vehicles

2017 ◽  
Vol 2622 (1) ◽  
pp. 105-116 ◽  
Author(s):  
Da Yang ◽  
Xiaoping Qiu ◽  
Lina Ma ◽  
Danhong Wu ◽  
Liling Zhu ◽  
...  
Keyword(s):  
Reaction Time ◽  
Traffic Flow ◽  
Road Traffic ◽  
Flow Characteristics ◽  
Lane Change ◽  
Mixed Traffic ◽  
Automated Vehicles ◽  
Obvious Effect ◽  
Mixed Traffic Flow ◽  
Automated Vehicle

In recent years, automated vehicles have been developing rapidly, and some automated vehicles have begun to drive on highways. The market share of automated vehicles is expected to increase and will greatly affect traffic flow characteristics. This paper focuses on the mixed traffic flow of manual and automated vehicles. The study improves the existing cellular automaton model to capture the differences between manual vehicles and automated vehicles. Computer simulations are employed to analyze the characteristic variations in the mixed traffic flow under different automated vehicle proportions, lane change probabilities, and reaction times. Several new conclusions are drawn in the paper. First, with the increment of the proportion of automated vehicles, freeway capacity increases; the capacity increment is more significant for single-lane traffic than for two-lane traffic. Second, for single-lane traffic flow, reducing the reaction time of the automated vehicle can significantly improve road traffic capacity—as much as doubling it—and reaction time reduction has no obvious effect on the capacity of the two-lane traffic. Third, with the proportion increment of automated vehicles, lane change frequency reduces significantly. Fourth, when the density is 15 < ρ < 55 vehicles/km, the addition of 20% automated vehicles to a traffic flow that consisted of only manual vehicles can decrease congestion by up to 16.7%.

scholarly journals Investigating Pedestrian Injury Crashes on Modern Roundabouts in Addis Ababa, Ethiopia

2015 ◽  
Vol 2512 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Getu Segni Tulu ◽  
M. Mazharul Haque ◽  
Simon Washington ◽  
Mark J. King
Keyword(s):  
Low Income ◽  
Goodness Of Fit ◽  
Negative Binomial ◽  
Addis Ababa ◽  
Random Effect ◽  
Pedestrian Safety ◽  
Fit Statistics ◽  
Traffic Characteristics ◽  
Multiple Observations ◽  
Pedestrian Crashes

Pedestrian crashes represent about 40% of total fatal crashes in low-income developing countries. Although many pedestrian crashes in these countries occur at unsignalized intersections such as roundabouts, studies focusing on this issue are limited. The objective of this study was to develop safety performance functions for pedestrian crashes at modern roundabouts to identify significant roadway geometric, traffic, and land use characteristics related to pedestrian safety. Detailed data, including various forms of exposure, geometric and traffic characteristics, and spatial factors such as proximity to schools and to drinking establishments were collected from a sample of 22 modern roundabouts in Addis Ababa, Ethiopia, representing about 56% of such roundabouts in Addis Ababa. To account for spatial correlation resulting from multiple observations at a roundabout, both the random effect Poisson (REP) and random effect negative binomial (RENB) regression models were estimated. Model goodness-of-fit statistics revealed a marginally superior fit of the REP model to the data compared with the RENB model. Pedestrian crossing volume and the product of traffic volumes along major and minor roads had significant and positive associations with pedestrian crashes at roundabouts. The presence of a public transport (bus or taxi) terminal beside a roundabout was associated with increased pedestrian crashes. Although the maximum gradient of an approach road was negatively associated with pedestrian safety, the provision of a raised median along an approach appeared to increase pedestrian safety at roundabouts. Remedial measures were identified for combating pedestrian safety problems at roundabouts in the context of a developing country.

Traffic Flow of Connected and Automated Vehicles: Challenges and Opportunities

2017 ◽  
pp. 235-245 ◽  
Author(s):  
Simeon Calvert ◽  
Hani Mahmassani ◽  
Jan-Niklas Meier ◽  
Pravin Varaiya ◽  
Samer Hamdar ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Automated Vehicles ◽  
Challenges And Opportunities

Insights from Integrated Geo-Location Data for Pedestrian Crashes, Demographics, and Land Uses

2020 ◽  
Vol 2674 (8) ◽  
pp. 720-731
Author(s):  
Rui Guo ◽  
Zhiqiang Wu ◽  
Yu Zhang ◽  
Pei-Sung Lin ◽  
Zhenyu Wang
Keyword(s):  
Low Income ◽  
Fast Food ◽  
Negative Binomial ◽  
Unobserved Heterogeneity ◽  
Pedestrian Safety ◽  
Marginal Effect ◽  
Land Uses ◽  
Crash Frequency ◽  
Location Data ◽  
Pedestrian Crashes

This study investigates the effects of demographics and land uses on pedestrian crash frequency by integrating the contextual geo-location data. To address the issue of heterogeneity, three negative binomial models (with fixed parameters, with observed heterogeneity, and with both observed and unobserved heterogeneities) were examined. The best fit with the data was obtained by explicitly incorporating the observed and unobserved heterogeneity into the model. This highlights the need to accommodate both observed heterogeneity across neighborhood characteristics and unobserved heterogeneity in pedestrian crash frequency modeling. The marginal effect results imply that some land-use types (e.g., discount department stores and fast-food restaurants) could be candidate locations for the education campaigns to improve pedestrian safety. The observed heterogeneity of the area indicator suggests that priority should be given to more populated low-income areas for pedestrian safety, but attention is also needed for the higher-income areas with larger densities of bus stops and hotels. Moreover, three normally distributed random parameters (proportion of older adults, proportion of lower-speed roads, and density of convenience stores in the area) were identified as having random effects on the probability of pedestrian crash occurrences. Finally, the identification of pedestrian crash hot zone provides practitioners with prioritized neighborhoods (e.g., a list of areas) for developing effective pedestrian safety countermeasures.

scholarly journals Improving E-Bike Safety on Urban Highways in China

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Linjun Lu ◽  
Chen Wang ◽  
Tao Wang
Keyword(s):  
Descriptive Analysis ◽  
Red Light ◽  
Drunk Driving ◽  
Educational Background ◽  
Passenger Cars ◽  
Red Light Running ◽  
Crash Data ◽  
Driving Behaviors ◽  
Fatal Crashes ◽  
Safety Countermeasures

This paper aims to examine characteristics of e-bike fatal crashes on urban highways in China. Crash data were retrieved from the three-year crash reports (2010–2012) of Taixing City. Descriptive analysis was conducted to examine characteristics of e-bike riders, drivers, and crashes. The important findings include the following: (1) most fatal crashes were related to e-bike riders’ aberrant driving behaviors, including driving in motorized lanes, red-light running, driving against the direction of traffic, inattentive driving, and drunk driving; (2) e-bike riders with lower educational background tended to perform illegal or inattentive driving behaviors in fatal crashes; (3) most drivers were not found to commit any faults and very few drivers were found to commit drunk driving offences; (4) most nighttime fatal crashes were related to absence of street lightings; (5) heavy good vehicles (HGVs) and small passenger cars were the two vehicle types that were mostly involved in the e-bike fatal crashes. This study provides useful information that can help traffic engineers better understand e-bike safety in China and develop safety countermeasures.

scholarly journals Will Automated Vehicles Negatively Impact Traffic Flow?

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
S. C. Calvert ◽  
W. J. Schakel ◽  
J. W. C. van Lint
Keyword(s):  
Traffic Flow ◽  
Gradual Transition ◽  
Mixed Traffic ◽  
Limited Data ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Low Level ◽  
Negative Effect ◽  
Vehicle Automation ◽  
Capacity Drop

With low-level vehicle automation already available, there is a necessity to estimate its effects on traffic flow, especially if these could be negative. A long gradual transition will occur from manual driving to automated driving, in which many yet unknown traffic flow dynamics will be present. These effects have the potential to increasingly aid or cripple current road networks. In this contribution, we investigate these effects using an empirically calibrated and validated simulation experiment, backed up with findings from literature. We found that low-level automated vehicles in mixed traffic will initially have a small negative effect on traffic flow and road capacities. The experiment further showed that any improvement in traffic flow will only be seen at penetration rates above 70%. Also, the capacity drop appeared to be slightly higher with the presence of low-level automated vehicles. The experiment further investigated the effect of bottleneck severity and truck shares on traffic flow. Improvements to current traffic models are recommended and should include a greater detail and understanding of driver-vehicle interaction, both in conventional and in mixed traffic flow. Further research into behavioural shifts in driving is also recommended due to limited data and knowledge of these dynamics.

Sign in / Sign up

Export Citation Format

Share Document