Simulation and evaluation of speed and lane-changing advisory of CAVS at work zones in heterogeneous traffic flow

Wu, Wenjing; Sun, Renchao; Ni, Anning; Liang, Zhikang; Jia, Hongfei

doi:10.1142/s021797922050201x

Cited by 16 publications

(8 citation statements)

References 22 publications

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“…Most of the studies however provide only theoretical foundations [22] or show the impact within a simulated environment [23][24][25][26][27][28]. The effects of connected, cooperative, and/or autonomous vehicles are discussed in literature [29][30][31][32]. The main control objective is the work zone throughput.…”

Section: State-of-artmentioning

confidence: 99%

Evaluation of a Mobile Highway Management System at Roadwork Zones

2022

IJE

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Road construction and maintenance activities cause traffic congestions and delays and present challenges for ensuring the safety of both motorists and road workers. While urban areas are well-equipped with traffic devices, in the case of highways our chances to collect traffic data and control traffic flows may be limited. Then the use of a temporary Highway Traffic Management System seems to be a suitable solution. Although the impacts of its deployment are addressed by many theoretical studies and demonstrated on traffic simulation models, there are not many references dealing with field tests. We provide results of the practical evaluation of the temporary Highway Management System installed and tested on the main highway in the Czech Republic during the road works period. Before-after analysis of collected traffic data was performed to prove the importance and positive impact of the proposed solution. We demonstrate an over 20% increase in the capacity of the roadwork zone and an almost 30 seconds decrease in average delay for one vehicle Highway administrators can use the results to justify investments into the temporary deployment of mobile traffic management systems.

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Section: State-of-artmentioning

confidence: 99%

Evaluation of a Mobile Highway Management System at Roadwork Zones

2022

IJE

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“…Automated vehicles (AVs) have attracted increasing interest in recent years. ey offer a huge potential to improve the operation and safety of transportation systems [12,13]. Studies on AVs' lane changing include two main aspects: lane-changing decision and lane-changing execution.…”

Section: Introductionmentioning

confidence: 99%

A Novel Dynamic Lane-Changing Trajectory Planning Model for Automated Vehicles Based on Reinforcement Learning

Luo

et al. 2022

Journal of Advanced Transportation

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Lane changing behavior has a significant impact on traffic efficiency and may lead to traffic delays or even accidents. It is important to plan a safe and efficient lane-changing trajectory that coordinates with the surrounding environment. Most conventional lane-changing models need to establish and solve constrained optimization models during the whole process, while reinforcement learning can just take the current state as input and directly output actions to vehicles. This study develops a lane-changing model using the deep deterministic policy gradient method, which can simultaneously control the lateral and longitudinal motions of the vehicle. To optimize its performance, a reward function is properly designed by combining safety, efficiency, gap, headway, and comfort features. To avoid collisions, a safety modification model is developed to check and correct acceleration at every time step. The driving trajectory data of 1169 lane-changing scenarios extracted from the Next Generation Simulation (NGSIM) dataset are used to train and test the model. The proposed model can quickly converge in training phase. Testing results show it can complete safe and efficient lane changing in different lane-changing scenarios with both shorter time headway and lane-changing duration than human drivers. Compared with the conventional dynamic lane-changing trajectory planning model, our model can reduce collision risk. It is also evaluated in automated and nonautomated mixed traffic in SUMO. Simulation results show that the proposed model also has a positive effect on the average speed of overall traffic flow.

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“…e results showed that the scheme could effectively reduce the average travel time and pollution emissions. Wu et al [32] established a two-lane lane-changing model and studied the control strategy at the freeway work area under the heterogeneous traffic flow. eir study disclosed that when the CAV penetration rate is high, the combination of the early lane-changing control strategy and the variable speed limits strategy is the optimal choice.…”

Section: Introductionmentioning

confidence: 99%

Overall Influence of Dedicated Lanes for Connected and Autonomous Vehicles on Freeway Heterogeneous Traffic Flow

Chen

Zhang

Wang

et al. 2022

Journal of Advanced Transportation

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With the development of autonomous driving and communication technology, the heterogeneous traffic flow by combining connected and autonomous vehicles (CAVs) and manually driven vehicles (MVs) will appear on the freeway in the near future. It is expected that CAVs can improve the freeway capacity and reduce vehicle exhaust emissions, but sharing the same road by CAVs and MVs will cause certain interference to CAVs. In order to reduce the negative influence of the heterogeneous traffic flow, setting up CAV dedicated lanes to separate CAVs from MVs to a certain extent is regarded as a reasonable solution. Based on the characteristics that MVs should be decelerated by a realistic amplitude and that the connected and autonomous vehicle can accurately predict the speed of its preceding and rear CAVs at the next time step, a heterogeneous traffic flow model was established. Based on this model, we studied the overall influence of different lane strategies on the operating efficiency of freeway traffic flow and vehicle exhaust emissions under different densities with different CAV penetration rates. The results show that setting up CAV dedicated lanes with low CAV penetration rates will have a negative impact on the freeway traffic flow. When the CAV penetration rate is 40%–60% and the density is not less than 30 veh/km/lane, setting up one CAV dedicated lane is the best choice. When the CAV penetration rate exceeds 60% and the density is not less than 40 veh/km/lane, setting up two CAV dedicated lanes is the best choice. The research finding will assist in understanding the overall influence of CAV dedicated lanes on freeway traffic flow and help determine the optimal number of CAV dedicated lanes under different traffic conditions.

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Simulation and evaluation of speed and lane-changing advisory of CAVS at work zones in heterogeneous traffic flow

Cited by 16 publications

References 22 publications

Evaluation of a Mobile Highway Management System at Roadwork Zones

Evaluation of a Mobile Highway Management System at Roadwork Zones

A Novel Dynamic Lane-Changing Trajectory Planning Model for Automated Vehicles Based on Reinforcement Learning

Overall Influence of Dedicated Lanes for Connected and Autonomous Vehicles on Freeway Heterogeneous Traffic Flow

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