Abstrato

Research of two-factor optimization model of a multi-lane freeway traffic rules

Aimin Yang, Shujuan Yuan, Yingna Zhao, Qingpeng Ding, Longge Yan

Under circumstances of left-driving rule, from both internal and external causes, to consider the difference of driving on the left or right, and we found that the person of driving at left side is slower by 0.5s than that of the right side, and therefore affect the safe distance between vehicles thus further affecting the safety factor and traffic flow. Then in combination with the two-factor optimizationmodel based on performance problems of a multi-lane freeway traffic rules to calculate the optimal solution when driving at left side, that is an average speed of vehicles in the second lane should be maintained as v  80km/h , the second lane speed limit is 85 km/h, theminimumspeed limit is 75 km/h, themaximumspeed limit for the first lane is 95 km/h, theminimumspeed limit is 85 km/h, and we use actual data to verify the conclusion. Intelligent systemresponse time is negligible, we obtained that the response time can be reduced therefore to shorten safe distance between vehicles. Then according to two-factor optimization model based on performance problems of amulti-lane freeway traffic rules, and the optimal speed for the second lane should be 94km/h, and the second laneminimumspeed limit is 84 km/h; highest speed limit of first lane is 104km/h, the lowest speed limit of first lane is 94 km/h. Finally, the traffic properties under this case are analyzed; we found the impact on traffic performance from intelligent system can be improved by 11%